# ArtisanCraft
> Developing with craft, clarity & care.
Public Ghost content for AI and LLM tooling. This file includes a bounded export of public pages first, then recent public posts.
Append `.md` to any post or page URL to get the content in Markdown (for example, `/example-post.md`).
## Pages
### About this site
URL: https://www.artisancraft.dev/about/
Last updated: 2025-10-12T15:35:17.000Z
**ArtisanCraft** is an independent publication founded by **Daniel Plomp**.
It’s a space dedicated to sharing insights, tutorials, and perspectives on modern web development — with a focus on Laravel, FilamentPHP, Livewire, Statamic, .NET and Sitefinity.
The goal is simple: to craft clear, practical content for people who build, manage, or shape digital products.
ArtisanCraft shares news, updates, and hands-on tips across the worlds of Laravel, Filament, Statamic, and Sitefinity — written for developers, IT professionals, technical managers, and content creators alike.
Whether you write code, lead projects, or curate digital experiences, you’ll find straightforward insights focused on quality, thoughtful design, and maintainable solutions.
---
### Access all areas
Subscribers get full access to every article — past and future — forming a growing library of in-depth content, experiments, and technical notes.
---
### Fresh content, delivered
Whenever new content is published, you’ll receive it directly in your inbox.
No noise, no algorithms — just the articles and updates that matter to you.
---
### Meet people like you
ArtisanCraft brings together developers, designers, and builders who share a passion for thoughtful software and digital craftsmanship.
Join in, stay curious, and keep creating.
### Consulting Services
URL: https://www.artisancraft.dev/consulting-services/
Last updated: 2025-10-13T15:02:18.000Z
Whether you're building with Laravel, navigating a Sitefinity upgrade, working on a complex Statamic deployment, or structuring a FilamentPHP project — I can help.
With years of experience across backend frameworks and CMS platforms, I offer technical consulting tailored to small teams, solo developers, and digital agencies looking for expert-level support.
### Areas of expertise:
- Laravel architecture, performance tuning, and upgrade strategy
- Sitefinity upgrades, troubleshooting, and migration planning
- FilamentPHP customization and scalable component design
- Statamic configuration, add-on development, and content modeling
Whether you’re facing persistent bugs, making architectural decisions, or preparing for a platform upgrade — I work alongside you to make confident, maintainable technical choices.
### What I offer:
- Targeted diagnostics and code review
- Hands-on support for upgrade and migration projects
- Custom development advice and mentoring
- Flexible engagement (one-off or ongoing)
---
**Get in touch** Want to talk about your project or see if I’m a good fit?
**Email:** mail@artisanatwork.dev
Let’s build something reliable, scalable, and future-friendly — together.
### Building dotmap
URL: https://www.artisancraft.dev/building-dotmap/
Last updated: 2026-02-13T18:34:36.000Z
Over the past months, I’ve been exploring a question that kept coming back in my own work:
**Why is discovering tech professionals still so fragmented — even though talent is everywhere?**
This series documents the journey behind *dotmap*:
not as a product launch, but as a way to think out loud about visibility, discovery and how professionals show up in today’s tech ecosystem.
It’s written in public, step by step — from the first idea to early design decisions, challenges, feedback and what’s next.
---
## What this series is about
This is not a technical deep dive.
It’s about **concepts, choices and experience**.
Topics include:
- why discovery often feels harder than it should be
- how location changes the way we see professional networks
- why multi-stack careers don’t fit traditional labels
- how design and UI influence visibility
- what it means to build something calmly in public
If you work in tech — as a freelancer, consultant, developer, designer or founder — parts of this will probably feel familiar.
---
## The Episodes
[**Episode 0 — Discovery vs Visibility**](https://www.artisancraft.dev/building-dotmap-episode-0/)
How the idea started by reframing discovery as a visibility problem.
→ *Published*
[**Episode 1 — Why I Started Building dotmap**](https://www.artisancraft.dev/episode-1-why-i-started-building-dotmap/)
The problem, the inspiration and the personal motivation behind the project.
→ *Published*
[**Episode 2 — Designing the Concept**](https://www.artisancraft.dev/episode-2-designing-the-concept/)
Why dotmap became map-first, minimal and intentionally quiet.
→ *Published*
[**Episode 3 — A Map-First Way to Explore Tech**](https://www.artisancraft.dev/episode-3-a-map-first-way-to-explore-tech/)
How a visual landscape changes the way professionals are discovered.
→ *Published*
[**Episode 4 — Building the MVP**](https://www.artisancraft.dev/episode-4-building-the-mvp/)
The messy, clarifying phase where the idea became real.
→ *Published*
[**Episode 5 — Why Multi-Stack Matters**](https://www.artisancraft.dev/episode-5-why-multi-stack-matters/)
Why modern careers don’t fit single ecosystems — and how discovery tools should adapt.
→ *Published*
[**Episode 6 — Branding, UI & the Badge System**](https://www.artisancraft.dev/episode-6-branding-ui-the-badge-system/)
How calm design and clear roles shape perception and visibility.
→ *Published*
[**Episode 7 — The Challenges of Discovery Platforms**](https://www.artisancraft.dev/episode-7-the-challenges-of-discovery-platforms/)
Network effects, chicken-and-egg problems and avoiding engagement traps.
→ *Published*
[**Episode 8 — Early Community Impressions**](https://www.artisancraft.dev/episode-8-early-community-impressions/)
What early feedback revealed — and what it changed.
[**Episode 9 — The Road Ahead**](https://www.artisancraft.dev/episode-9-the-road-ahead/)
Where dotmap is heading next, without losing its simplicity.
---
## How to follow along
New episodes are published regularly and shared on LinkedIn and X.
The series evolves alongside the product — openly and intentionally.
If you’re interested in how discovery, visibility and professional presence can be rethought, you’re very welcome to follow along.
---
## More information on how it is going
[Dotmap update: Quick Search, Postgres, and smarter skill rankingA few updates on Dotmap since the last post.ArtisanCraftDaniel Plomp](https://www.artisancraft.dev/dotmap-update-quick-search-postgres-and-smarter-skill-ranking/)
[Building Dotmap: shipping features nobody asked forHow a side project grew from “map with dots” to a full professional discovery platform.ArtisanCraftDaniel Plomp](https://www.artisancraft.dev/building-dotmap-shipping-features-nobody-asked-for/)
---
[](https://www.artisancraft.dev/consulting-services/)
I offer hands-on consulting to help you resolve technical challenges and improve your CMS implementations.
Get in touch if you'd like support diagnosing or upgrading your setup with confidence.
[Learn more ](https://www.artisancraft.dev/consulting-services/)
### Building Expensio
URL: https://www.artisancraft.dev/building-expensio/
Last updated: 2026-01-21T20:30:29.000Z
Expensio started as a small frustration.
I needed a simple way to create clean expense claims — sometimes as a private person,
sometimes for my company. No invoices, no accounting software, just a clear overview
I could send by email.
I couldn’t find a tool that did exactly that, so I built one.
This page collects a short series of articles about building Expensio:
the product decisions, trade-offs, and lessons learned while keeping
a deliberately small tool focused and production-ready.
### 1\. Why I built Expensio
How a small personal frustration turned into a focused expense tool for freelancers and small businesses.
[I built Expensio — A simple expense tool I needed myselfI built Expensio because I needed a simple way to create clean expense claims without heavy bookkeeping tools. A lightweight, multilingual app for quick, no-nonsense declarations.ArtisanCraftDaniel Plomp](https://www.artisancraft.dev/i-built-expensio-a-simple-expense-tool-i-needed-myself/)
### 2\. Designing a straight-line UX
Why Expensio was designed around a single, predictable flow — and how avoiding side paths reduced friction.
[Episode 2: Designing a straight-line UXMost software becomes complex by accident. Expensio was designed as a straight-line experience: add expenses, bundle them, export a clean PDF. No setup, no onboarding, no clutter — just clarity.ArtisanCraftDaniel Plomp](https://www.artisancraft.dev/episode-2-designing-a-straight-line-ux/)
### 3\. What I chose not to build
The discipline of saying no, resisting feature bloat, and keeping a product intentionally small.
[Episode 3: What I chose not to buildBuilding Expensio wasn’t about adding features — it was about knowing when to stop. No invoicing, no accounting, no automation. Just a focused tool that fills the gap between spreadsheets and full accounting software.ArtisanCraftDaniel Plomp](https://www.artisancraft.dev/episode-3-what-i-chose-not-to-build/)
### 4\. What changed after real users started using Expensio
How real-world usage sharpened the product without expanding its scope — and what user feedback actually taught me.
[What changed after real users started using ExpensioAfter shipping Expensio, real user feedback didn’t add more features—it removed friction. Small fixes, better defaults, and one carefully chosen addition sharpened the product without changing its core.ArtisanCraftDaniel Plomp](https://www.artisancraft.dev/what-changed-after-real-users-started-using-expensio/)
---
Expensio is now almost a finished product in the sense that it’s stable,
predictable, and intentionally scoped.
It will continue to evolve — but always by sharpening the core,
not expanding it.
If you’re interested in how small tools grow without turning into
overengineered systems, this series reflects how I approach that balance.
If you want to know more, let me know!
## Sign up for ArtisanCraft
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### Raising kids in the AI age
URL: https://www.artisancraft.dev/raising-kids-in-the-ai-age/
Last updated: 2026-08-31T08:52:28.000Z
I have three daughters. The oldest is sixteen. The youngest is ten.
Every parent worries about their kids' future. But lately that worry has a different edge. The career advice I received — get a stable job, specialize, collect credentials — already feels outdated. And my kids are just getting started.
This series documents my attempts to figure out what to teach them instead.
It's not a parenting manual. I don't have all the answers. But I'm learning in public, one question at a time:
- What do we tell kids about careers when AI can do most knowledge work?
- Which skills actually matter in a world of infinite supply?
- How do we talk about AI without scaring them?
- What should we stop pushing — and what should we start?
If you're a parent wondering the same things, you're not alone.
---
## What this series is about
This isn't about coding camps or getting kids "AI-ready" in a technical sense.
It's about the bigger questions:
- Why the old career question ("What do you want to be?") no longer works
- What "post-scarcity thinking" means for how we raise kids
- Practical experiments I'm trying with my own children
- The mindset shifts that matter more than any specific skill
I write as a parent who also happens to work with AI daily. That gives me a front-row seat to how fast things are changing — and how unprepared most advice is.
---
## The posts
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- [Learn to think before you learn to prompt](https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/)
- [The talk we're not having](https://www.artisancraft.dev/the-talk-were-not-having/)
- [The friend who never goes on holiday](https://www.artisancraft.dev/the-friend-who-never-goes-on-holiday/)
- [The answer machine your kid can't turn off](https://www.artisancraft.dev/the-answer-machine-your-kid-cant-turn-off/)
- [The eleven-point gap](https://www.artisancraft.dev/the-eleven-point-gap/)
- [America's answer comes with a key to your kid's diary](https://www.artisancraft.dev/americas-answer-comes-with-a-key-to-your-kids-diary/)
- [OpenAI's answer grades its own homework](https://www.artisancraft.dev/openais-answer-grades-its-own-homework/)
- [The two-hour limit I should have set myself](https://www.artisancraft.dev/the-two-hour-limit-i-should-have-set-myself/)
*More posts every Sunday, 5 a.m.*
---
## How to follow along
New posts are published as I figure things out — usually every week or two.
I share updates on [LinkedIn](https://linkedin.com/in/danielplomp?ref=artisancraft.dev) and [X](https://x.com/danielplomp?ref=artisancraft.dev). Or just subscribe to my newsletter.
If you're a parent navigating the same uncertainty, I'd love to hear what's working for you. The best ideas often come from the comments.
I put everything from this series into a free printable PDF — 10 replacement questions, 4 future-proof skills, and a daily action plan. **You can download the guide if you subscribe to my newsletter**.
---
_This page is for subscribers only._
### Series
URL: https://www.artisancraft.dev/series/
Last updated: 2026-03-25T14:30:18.000Z
I write about building products, navigating AI, and figuring things out in public. Some topics deserve more than a single post. These series go deeper.
---
## Raising kids in the AI age
*Preparing children for a future we can't fully predict*
Every parent worries about their kids' future. But the old career advice — specialize, get credentials, find stability — already feels outdated. This series documents my attempts to figure out what to teach my three daughters instead.
**Topics:** Career advice, post-scarcity thinking, practical parenting experiments
→ [Read the series](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
---
## Building Dotmap
*A series on visibility, discovery and tech professionals*
Why is discovering tech professionals still so fragmented? This series documents the journey behind dotmap — from first idea to design decisions, challenges, and what's next. Written in public, step by step.
**Topics:** Discovery platforms, professional visibility, building in public
→ [Read the series](https://www.artisancraft.dev/building-dotmap/)
---
## Building Expensio
*From frustration to product: building a simple expense tool*
Expense tracking shouldn't be complicated. This series follows the development of Expensio — a deliberately simple tool born from my own frustration with bloated alternatives.
**Topics:** Product development, simplicity, Laravel, building in public
→ [Read the series](https://www.artisancraft.dev/building-expensio/)
---
## Disruptive AI
*How AI is reshaping work, careers, and life*
I've been using AI tools daily for over a year. This series captures what that actually looks like — the workflow shifts, the identity questions, and the things I'm still figuring out.
**Topics:** AI workflows, developer experience, future of work, automation
→ [Read the series](https://www.artisancraft.dev/disruptive-ai/)
---
## Stay updated
New posts drop weekly. Follow along on [LinkedIn](https://linkedin.com/in/danielplomp?ref=artisancraft.dev) or [X](https://x.com/danielplomp?ref=artisancraft.dev).
### The post-scarcity parenting guide
URL: https://www.artisancraft.dev/the-post-scarcity-parenting-guide/
Last updated: 2026-02-17T11:38:03.000Z
10 new questions to ask your kids — and the skills that matter when AI changes everything
_This page is for subscribers only._
### Disruptive AI
URL: https://www.artisancraft.dev/disruptive-ai/
Last updated: 2026-08-31T08:55:26.000Z
I'm not just writing about AI disruption, I'm living it.
As someone building multiple SaaS products while watching AI reshape entire industries, I have a unique perspective on what's actually happening versus what people fear might happen.
This series documents the real experience of working alongside AI tools daily, building products in a rapidly changing landscape, and watching business models evolve in real-time.
### What this series covers
This isn't theoretical analysis or distant speculation.
It's the practical reality of:
- How AI is actually changing day-to-day work (not just the headlines)
- Why some businesses will thrive while others vanish
- The psychological challenges of working with superhuman tools
- What productivity really means when machines can think
I write from the trenches as someone who codes with AI, runs businesses affected by it, and thinks deeply about where this is all heading.
---
### The posts
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- [The AI productivity trap: why your brain can't keep up with your tools](https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/)
- [Drag a label, get a pull request ](https://www.artisancraft.dev/drag-a-label-get-a-pull-request/)
- [The agent cannot ask questions](https://www.artisancraft.dev/the-agent-cannot-ask-questions/)
- [The architecture fits on a beer mat](https://www.artisancraft.dev/the-architecture-fits-on-a-beer-mat/)
*More posts as the disruption unfolds.*
---
### Why this matters now
Every entrepreneur, developer, and knowledge worker is trying to figure out their place in an AI-first world.
The stories and insights here come from someone actively building that future and not just observing it from the sidelines.
If you're navigating the same uncertainty, you're not alone in this transition.
---
## How to follow along
New posts are published as I figure things out, usually every week or two.
I share updates on [LinkedIn](https://linkedin.com/in/danielplomp?ref=artisancraft.dev) and [X](https://x.com/danielplomp?ref=artisancraft.dev). Or just subscribe to my newsletter.
### Meetbaar begeleiden
URL: https://www.artisancraft.dev/meetbaar-begeleiden/
Last updated: 2026-08-31T08:54:03.000Z
Ik schrijf niet over meetbaar begeleiden vanaf de zijlijn. Ik zit er middenin.
Ik ben techneut, geen coach. Dit jaar kreeg ik voor het eerst een formele begeleidingsrol: een CTO sterker maken in leiderschap, keuzes en organisatie. Al snel kwam ik de vraag tegen die zelden hardop wordt gesteld: hoe weten we eigenlijk of dit werkt?
Deze serie documenteert wat er gebeurt als je die vraag serieus neemt. Als je naast elke afspraak een meting hangt, groei meet op een ladder in plaats van met rapportcijfers, en je opdrachtgever live laat meekijken.
---
### Waar deze serie over gaat
Dit is geen theorie over coaching en geen managementmodel. Het is de praktijk van één lopend traject, opgeschreven terwijl het gebeurt:
- Waarom afspraken geen bewijs zijn, en wat wel
- Waarom een 6 niks zegt en een groeiladder wel
- Wat AI mag in een begeleidingstraject (meten) en wat niet (oordelen)
- Waarom je je opdrachtgever gewoon een inlog kunt geven
Ik gebruik het instrument zelf, elke maand, en verantwoord de scores bij een directie die ervoor betaalt.
---
### De artikelen
- [Hoe weet ik of mijn begeleiding werkt?](https://www.artisancraft.dev/hoe-weet-ik-of-mijn-begeleiding-werkt/)
- [Een 6 zegt niks: meet groei op een ladder](https://www.artisancraft.dev/een-6-zegt-niks-meet-groei-op-een-ladder/)
- [Laat AI meten en houd zelf het oordeel](https://www.artisancraft.dev/laat-ai-meten-en-houd-zelf-het-oordeel/)
- [Onzichtbare waarde is een meetprobleem](https://www.artisancraft.dev/onzichtbare-waarde-is-een-meetprobleem/)
*Meer artikelen volgen naarmate het traject vordert.*
---
### Waarom dit nu speelt
Elke interim, adviseur en coach kent het moment: de verlengingsvraag, de budgetronde, de opdrachtgever die zich afvraagt wat de begeleiding oplevert. Goed werk leveren is niet genoeg als niemand het kan zien.
AI maakt het meten bijna gratis. Het oordeel blijft mensenwerk. Precies op dat snijvlak speelt deze serie.
### Zelf proberen?
Uit deze serie groeide [Cranely](https://cranely.app/?ref=artisancraft.dev): het instrument waarmee ik afspraken, metingen en groei bijhoud. Ik zoek twee à drie begeleiders buiten de techniek die het in hun eigen vakgebied willen proberen. [Stuur me een bericht](https://www.linkedin.com/in/danielplomp?ref=artisancraft.dev) als je dat wilt, of als je iemand kent.
---
## Volg de serie
Nieuwe artikelen verschijnen terwijl het traject loopt. Ik deel updates op [LinkedIn](https://linkedin.com/in/danielplomp?ref=artisancraft.dev) en [X](https://x.com/danielplomp?ref=artisancraft.dev), of abonneer je op de nieuwsbrief.
## Posts
### The two-hour limit I should have set myself
URL: https://www.artisancraft.dev/the-two-hour-limit-i-should-have-set-myself/
Last updated: 2026-08-30T03:00:57.000Z
I have never set a screen time limit for any of my three daughters. Not once, not on any device, not for any app. The oldest is sixteen and the youngest is eleven, and somewhere along the way I decided that the interesting conversations in our house would be about what they post and who gets to see it, not about how many minutes they spend looking at it. We talk about public and private, about what belongs on a profile and what belongs in a group chat. We do not talk about minutes.
This week a federal judge in California was handed a document that sets those minutes for me.
---
## What actually happened
On Wednesday, Meta agreed to settle the case that a bipartisan coalition of state attorneys general brought against it back in October 2023, in the middle of the second week of the trial in Oakland. The headline number is roughly eighteen billion dollars, but the number is not the interesting part, and I will come back to why.
The interesting part is the list of things Meta now has to do, by court order rather than by press release. Teenagers under eighteen get a combined two-hour daily limit across Facebook and Instagram, and that limit can only be changed with a parent's permission. The apps go dark between midnight and six in the morning, with an exception for direct messages, because apparently even a consent judgment understands that a teenager who cannot answer a friend at 1 a.m. will simply find another way. Push notifications stop during normal school hours. Like counts get hidden by default, certain appearance-altering filters get restricted, and teens will be nudged every fifteen minutes of continuous scrolling and again after an hour. An independent auditor, chosen by the states and Meta together, gets access to company data and reports to a committee of attorneys general. Most of it stays in force for ten years.
Meta admits no wrongdoing, which is the legal equivalent of apologising for how you were made to feel.
---
## What the number really says
Eighteen billion dollars sounds like a company being punished. Sit with the structure for a minute and it starts to sound like something else.
About seventy percent of the total, roughly twelve and a half billion, gets paid out over the next ten years. That is a decade of instalments, not a bill. The remaining piece, a little over five billion, is conditional: Meta pays it only if YouTube and TikTok adopt similar or stricter settings, including an even tighter one-hour daily cap. And to help that along, Meta took out full-page ads in the *Washington Post*, the *New York Times* and the *Los Angeles Times* arguing that these settings should become the new industry standard.
Read that twice. A company that just settled a child-safety case is now spending money to lobby its competitors into the same rules, because five billion dollars of its own bill depends on whether they follow. It is not repentance. It is a company that lost a fight and is now trying to make sure nobody gets to keep competing on the thing it just gave up.
> A company that lost a fight is now paying for ads to make sure nobody else gets to keep the advantage it surrendered.
Which is not nothing. I would rather have an industry standard imposed by a court than a set of good intentions announced at a developer conference. But the researchers who have studied this keep pointing at the same weak spot, and it is not the money. Almost nobody changes a default setting, and the two best items on the list, the non-algorithmic feed and switching off autoplay, are exactly the ones that require somebody to opt in. Everything the court could hard-wire is now hard-wired. Everything that needed a parent to actually go looking is still sitting there, waiting for a parent to actually go looking.
And, as one former Meta insider put it rather bluntly, if teenagers are simply using accounts that say they are twenty-three, all of it is worthless.
---
## Panic is its own kind of laziness
The obvious way to read this week is that we were right all along, that the platforms knew, that our children were the product and now there is a court filing with a dollar sign to prove it. There is real satisfaction in that reading, and I felt it before I finished the first article.
But panic is its own kind of laziness. It lets you feel like you have done something when all you have done is have a feeling. Every time I have caught myself in that mode, worrying loudly at the dinner table about what these companies are doing to my daughters, I have noticed that the worrying takes up exactly the space that a real conversation would have taken, and costs considerably less.
The settlement is genuinely good news, and it is worth saying so plainly. Defaults matter enormously, more than rules do, because a default is the thing that happens when nobody is paying attention, and nobody is paying attention most of the time. My sixteen-year-old will lose the midnight-to-six window whether or not I ever mention it. She will get a screen telling her she has been scrolling for an hour whether or not I ever notice. That is a real improvement in her life, delivered without a single argument in my kitchen.
The trap is thinking that improvement was mine.
---
## Where this gets uncomfortable for me
Here is the part I would rather not write.
I have told myself a decent story about why we do not do time limits in this house. The story goes that limits are a blunt instrument, that they teach kids to negotiate with a number instead of with themselves, that I would rather build judgment than build a fence. I still think most of that is true. I have also noticed that this story has the convenient property of requiring nothing from me on any given Tuesday evening.
> A rule is work once. Judgment is work forever. I picked the one that sounds wiser and happens to be the one I can do from the couch.
And this week a courtroom did the thing I had decided was too blunt to do, for millions of children including mine, and my first reaction was not "how dare they". My first reaction was relief. Same as three weeks ago, when a bill promised me the transcripts. Same as two weeks ago, when OpenAI shipped a teen mode. Every single week of this series, somebody else has offered to carry a piece of my attention, and every single week I have noticed how badly I wanted to hand it over.
I do not think I am unusual in this. I think that is the whole business model.
And then there is my sixteen-year-old, who has set her own screen time limit. No family meeting, no negotiation, no input whatsoever from the two adults in this house who have spent years having opinions about screens. The number I refused to set on principle, and the number a federal court has now set on my behalf, is a number she had already arrived at on her own.
I would love to file that under parenting. I suspect it is just her.
---
## A direction, not a system
I am not going to hand you a framework, partly because I do not have one and partly because the last thing either of us needs is another PDF. These are the things I want to try in the coming weeks, offered as a direction rather than a system.
Go and find the two settings the court could not force. The non-algorithmic feed and the autoplay switch are the only items on this whole list that change what your child sees rather than how long they see it, and both of them will sit there untouched forever unless somebody opens the menu. Do it once, this week, before the news cycle moves on and you forget it existed.
Ask, out loud, what a two-hour limit would even feel like. Not as a rule, as a question. I want to know whether my daughters experience two hours as generous or insulting, because the answer tells me something about their day that I currently do not know.
Watch what happens at midnight. The block is coming whether we like it or not, so the useful thing is to notice what moves into that space. If the answer is sleep, wonderful. If the answer is a different app that nobody has sued yet, that is worth knowing before it becomes a habit.
And say the quiet thing to them. My oldest is sixteen; she can handle "a court had to make a company stop doing something it knew was harmful, and I want you to know that is why the app changed, not because it got nicer." Kids who understand why a rule exists argue with it better, which is the point.
---
## The line I'm keeping
The two-hour limit is not a parenting decision. It is a settlement term. It arrived through a federal court in Oakland, negotiated by attorneys general and lawyers and an independent auditor who will file reports for the next ten years, and it will land on my daughter's phone without anyone in this house being consulted.
I am glad it exists. I would also like to remember, when it arrives, that a limit is the cheapest thing a person can give a child. Anyone can set a number. The expensive part, the part no court can order and no company can ship, is being awake at the hour the number runs out.
Meta got court-ordered to be more careful with my daughters' attention than I have been with my own.
---
## Sources
- TIME — [3 Big Questions After Meta's $18 Billion Teen Safety Settlement](https://time.com/article/2026/08/27/meta-settlement-facebook-instagram-child-safety/?ref=artisancraft.dev), 27 August 2026
- JURIST — [Meta agrees to court-enforced limits on teen social media use in $18B settlements](https://www.jurist.org/news/2026/08/meta-agrees-to-court-enforced-limits-on-teen-social-media-use-in-18b-settlements/?ref=artisancraft.dev), 26 August 2026
- Bloomberg via Claims Journal — [Meta Agrees to Pay Up to $16.7 Billion in Social Media Case](https://www.claimsjournal.com/news/national/2026/08/26/339790.htm?ref=artisancraft.dev), 26 August 2026
- Quartz — [Meta settles multistate social media lawsuit for $16.7 billion](https://qz.com/meta-settlement-states-kids-social-media-addiction-082626?ref=artisancraft.dev), 26 August 2026
- CNN Business — [Meta settles landmark state child harm claims for $18 billion](https://www.cnn.com/2026/08/26/tech/meta-states-settle-trial-children?ref=artisancraft.dev), 26 August 2026
- Meta Newsroom — [Agreement with state attorneys general supporting teens](https://about.fb.com/news/2026/08/agreement-with-state-attorneys-general-supporting-teens/?ref=artisancraft.dev)
- California Attorney General — [Proposed consent judgment (PDF)](https://oag.ca.gov/system/files/attachments/press-docs/23-05448-ecf-572-1-exhibit-1-mdl-consent-judgment-final-settlment-agreement-fully-executed.pdf?ref=artisancraft.dev)
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- [Learn to think before you learn to prompt](https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/)
- [The talk we're not having](https://www.artisancraft.dev/the-talk-were-not-having/)
- [The friend who never goes on holiday](https://www.artisancraft.dev/the-friend-who-never-goes-on-holiday/)
- [The answer machine your kid can't turn off](https://www.artisancraft.dev/the-answer-machine-your-kid-cant-turn-off/)
- [The eleven-point gap](https://www.artisancraft.dev/the-eleven-point-gap/)
- [America's answer comes with a key to your kid's diary](https://www.artisancraft.dev/americas-answer-comes-with-a-key-to-your-kids-diary/)
- [OpenAI's answer grades its own homework](https://www.artisancraft.dev/openais-answer-grades-its-own-homework/)
- The two-hour limit I should have set myself *← You are here*
### OpenAI's answer grades its own homework
URL: https://www.artisancraft.dev/openais-answer-grades-its-own-homework/
Last updated: 2026-08-23T03:00:35.000Z
Three weeks ago I wrote about Europe's answer to kids and AI. Two weeks ago, America's. This week the company everyone was actually talking about decided to answer for itself.
On Monday, OpenAI launched ChatGPT for Teens. If you say you're between 13 and 17, or if their age-prediction system simply estimates you're under 18, you get moved into a separate experience with stronger guardrails, study tools, and parental controls. No opt-in, no permission slip. The system decides, and suddenly my daughters are using a different product than I am.
My own daughters are not heavy ChatGPT users, at least not that I've seen, and I'm aware that sentence carries a quiet "that I've seen" doing a lot of work. But that's exactly what struck me about this launch: whether your teen uses it daily or barely at all, a company in San Francisco just decided which version of the conversation they get, without any parent doing anything. The rules of a tool my kids will almost certainly grow into were rewritten this week, and nobody asked us. That's worth sitting with, whatever you think of the rules themselves.
---
## What they actually built
Credit where it's due: the feature list reads like someone finally handed the safety team a budget. Teen accounts get stronger protections around self-harm, eating disorders, violence, dangerous activities, and sexually explicit content. The chatbot is barred from using romantic language or terms of endearment, and it's explicitly instructed not to suggest it has feelings or consciousness. There are break reminders, warnings before a teen uploads a sensitive photo, and parental controls with Quiet Hours and safety notifications for high-risk situations.
The education side is arguably more interesting. Study Mode replaces answers with guiding questions and step-by-step scaffolding, and a new feature called responsible homework reminders detects when a teen appears to be shortcutting an assignment and nudges them back toward actually learning something. Parents and teens can set Study Hours, times when Study Mode is on by default.
If you've been reading this series, you'll recognise the shape of this list. It's nearly everything critics, researchers, and grieving parents have been demanding for years. Which brings us to the timing.
> "A company that spent four years scaling to 900 million weekly users has now discovered that some of them are children."
---
## What the numbers really say
ChatGPT launched in late 2022\. According to TechCrunch, it reached 900 million weekly users before meaningful teen-specific safeguards arrived. Common Sense Media's census from June found that 86 percent of American kids aged 9 to 17 already use AI, and that more than 4 in 10 say no parent or guardian has ever talked with them about AI safety. The teens this product is designed for are not future users being welcomed carefully into a new technology. They've been here the whole time, unsupervised, on the adult version.
The launch also didn't happen in a vacuum. OpenAI is facing lawsuits over what its chatbot allegedly said to vulnerable teenagers, the US Senate advanced a bill about parental access to AI conversations two weeks ago, and Europe's AI Act obligations kicked in on August 2\. When a company ships its safety product into that exact headwind, you're allowed to notice the wind.
And then there's the detail I can't stop smiling at, in the way you smile at things that aren't funny: on the very same day OpenAI introduced ChatGPT for Teens, it also announced that ChatGPT Ads are expanding across Europe. Safety for the children, advertising for the parents. The press releases went out hours apart.
---
## Before we panic
Here's the thing though, and regular readers know where this is going: panic is its own kind of laziness.
Because this is, on the substance, good news. Default-on protections are exactly what child-safety researchers have been asking for, since defaults are what actually protect kids whose parents never open a settings screen. Study Mode is built on real learning science, guiding questions and retrieval practice instead of answer vending. A chatbot that refuses to whisper sweet nothings to a fifteen-year-old is an improvement on one that would. And when my daughters do start using it in earnest, which I assume is a matter of when rather than if, I'd much rather they land in this version than in the adult one.
The honest position is that both things are true at once. This is a better product than last week's, shipped by a company with every commercial reason to appear responsible right now. TechCrunch asked the obvious question: how hard will it be for teens to work around it? Teenagers have been outsmarting parental controls since parental controls existed, and an age-prediction system is a wall that every seventeen-year-old has an incentive to climb. We'll find out how tall it is.
> "The most important safety feature still doesn't ship with the product. It sits at the dinner table."
---
## Where this gets uncomfortable for me
I'd love to review this launch from a comfortable distance, but I don't get to. I work with AI every day. I build with these tools, I pay these companies, and my enthusiasm for the technology is a standing invitation for it to arrive in my daughters' lives sooner rather than later.
And there's a smaller, more personal discomfort. Reading through the feature list, I caught myself feeling relieved, and not the good kind of relieved. The kind where someone else just took over a job you knew was yours. Study Hours, break reminders, notifications when something's wrong: that's a machine doing, at scale, the noticing I'm supposed to do at home. Meanwhile I write a weekly series about kids and AI and couldn't tell you with certainty which AI apps are on my own daughters' phones right now. The company built a substitute for my attention, and my first instinct was gratitude. That instinct deserves more suspicion than the product does.
---
## What we're trying at home
As always: a direction, not a system.
**Find out what's actually on their phones.** Not as an inspection, but as a conversation opener. "Do you ever use ChatGPT, and did it change this week?" is a better question than "what do you talk to it about," because it starts with the company's behavior instead of theirs. I expect the answer to be "barely," and I'd like to stop assuming that.
**Do homework in Study Mode together, once.** If my daughters are going to meet this tool anyway, I'd rather their first real session be at the kitchen table than alone in their room. I want to see whether the guiding questions help or just irritate, and I want their verdict, not OpenAI's marketing copy.
**Ask the dinner-table question this whole trilogy has been building to.** Europe answered with rules, America answered with a key to the diary, OpenAI answered with a product. So who should decide what's safe for you: the government, the company, or the people who love you? I have three daughters. I expect three different answers, and I expect all three to be better than mine.
---
## The line I'm keeping
The seatbelt is real. I've read the spec, and it's a better seatbelt than I expected from a company that spent four years insisting the car was fine. But a seatbelt designed by the dealership, announced during the lawsuit, on the same day they started selling ads in the showroom, is not the same thing as someone who loves the passenger.
OpenAI built a safer ChatGPT for my daughters. Raising them was never on the roadmap.
---
## Sources
- OpenAI — [Introducing ChatGPT for Teens](https://openai.com/index/chatgpt-for-teens/?ref=artisancraft.dev) (August 18, 2026)
- TechCrunch — [OpenAI launches a safer ChatGPT for teens — years after teens started using it](https://techcrunch.com/2026/08/18/openai-launches-a-safer-chatgpt-for-teens-years-after-teens-started-using-it/?ref=artisancraft.dev) (August 18, 2026)
- OpenAI — [ChatGPT Ads expands across Europe](https://openai.com/index/chatgpt-ads-expands-across-europe/?ref=artisancraft.dev) (August 18, 2026)
- Common Sense Media — [Census on AI Use by Tweens and Teens](https://www.commonsensemedia.org/press-releases/common-sense-media-releases-inaugural-annual-study-on-ai-use-by-tweens-and-teens?ref=artisancraft.dev) (June 2026)
- TechCrunch — [ChatGPT reaches 900M weekly active users](https://techcrunch.com/2026/02/27/chatgpt-reaches-900m-weekly-active-users/?ref=artisancraft.dev) (February 2026)
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- [Learn to think before you learn to prompt](https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/)
- [The talk we're not having](https://www.artisancraft.dev/the-talk-were-not-having/)
- [The friend who never goes on holiday](https://www.artisancraft.dev/the-friend-who-never-goes-on-holiday/)
- [The answer machine your kid can't turn off](https://www.artisancraft.dev/the-answer-machine-your-kid-cant-turn-off/)
- [The eleven-point gap](https://www.artisancraft.dev/the-eleven-point-gap/)
- [America's answer comes with a key to your kid's diary](https://www.artisancraft.dev/americas-answer-comes-with-a-key-to-your-kids-diary/)
- OpenAI's answer grades its own homework *← You are here*
### Onzichtbare waarde is een meetprobleem
URL: https://www.artisancraft.dev/onzichtbare-waarde-is-een-meetprobleem/
Last updated: 2026-08-31T08:53:44.000Z
Drie scenario's. Ze komen uit verschillende vakgebieden, maar het patroon is hetzelfde.
## De interim die zijn waarde niet kon aantonen
Een interim-CFO, negen maanden bij een familiebedrijf. Werkkapitaal verbeterd, rapportages gestroomlijnd, een team dat eindelijk vooruit kan. Dan vraagt de DGA bij de verlenging: "Wat heb je nu concreet verbeterd?"
En daar sta je. Met een verhaal, wat voorbeelden en de hoop dat het gevoel klopt. De DGA knikt, maar je ziet hem denken: dat kost me elke maand een flink bedrag.
Met een startfoto en een maandelijkse meting wordt diezelfde vraag een blik op een dashboard. Waar stonden we, waar staan we, wat is er open. De verlenging wordt een gesprek over de volgende stap in plaats van een verdediging van de vorige.
---
## De audit als momentopname
Vraag een kwaliteitsadviseur wat er twee weken voor de audit gebeurt. Paniek. Documenten bijwerken, procedures afstoffen, iedereen instrueren. De audit komt, de vinkjes worden gezet, en daarna zakt alles terug tot de volgende ronde.
Iedereen weet het, niemand zegt het hardop: een audit meet niet hoe een organisatie werkt, maar hoe goed ze zich kan voorbereiden.
Het alternatief is geen strengere audit maar een doorlopende foto. De eisen staan er het hele jaar, elke maand krijgen ze een stand, en de bewijzen hangen eronder met datum en herkomst. De audit wordt een bevestiging van wat het dashboard al maanden laat zien — en de adviseur verandert mee: van examinator die één keer per jaar langskomt naar begeleider die het hele jaar zichtbaar waarde levert.
---
## De eigenaar die gewoon mag meekijken
Een praktijkcoach begeleidt een tandartspraktijk. De maatschap betaalt en hoort elk kwartaal een samenvatting. Tussen de kwartalen is het stil, en stilte kweekt twijfel: "Wat doet die coach eigenlijk voor dat tarief?"
Draai het om. Geef de maatschap een eigen inlog met alleen-lezen toegang: de groeigebieden, de stand, de trend, de open acties. Wat er dan gebeurt: de twijfel verdwijnt. Niet omdat de cijfers altijd goed zijn, maar omdat er niets meer te verbergen valt. Slecht nieuws op een dashboard dat je zelf mag openen voelt anders dan slecht nieuws in een verslag dat de coach schreef.
Transparantie is geen risico voor de begeleider. Het is het sterkste verkoopargument dat er bestaat.
---
## Het patroon
In alle drie de gevallen is het werk goed, maar de waarde onzichtbaar. En onzichtbare waarde wordt bij elke budgetronde ter discussie gesteld. Je waarde niet kunnen aantonen is geen kwaliteitsprobleem — het is een meetprobleem. En meetproblemen zijn oplosbaar: een startfoto, een groeipad met definities, een maandelijkse meting en een opdrachtgever die mag meekijken.
---
## Drie mensen gezocht
Ik heb dit gebouwd vanuit één vakgebied en één traject. Ik wil weten of het patroon breder klopt.
Daarom zoek ik twee à drie begeleiders búíten de techniek die het willen proberen: een interim of fractional executive, een organisatie- of kwaliteitsadviseur, een praktijk- of formulecoach. Iemand met een betalende opdrachtgever en de terugkerende vraag of het werkt. Wat je krijgt: het instrument ([Cranely](https://cranely.app/?ref=artisancraft.dev)), mijn hulp bij het inrichten van jouw groeigebieden, en een sparringpartner.
Wat ik vraag is je eerlijke ervaring.
Interesse, of ken je iemand? [Stuur me een bericht](https://www.linkedin.com/in/danielplomp/?ref=artisancraft.dev).
---
## In deze serie
Deze post is onderdeel van mijn serie '**Meetbaar begeleiden**'
[Meetbaar begeleidenHoe je als begeleider, adviseur of coach aantoont dat je werk werktArtisanCraftDaniel Plomp](https://www.artisancraft.dev/meetbaar-begeleiden/)
- [Hoe weet ik of mijn begeleiding werkt?](https://www.artisancraft.dev/hoe-weet-ik-of-mijn-begeleiding-werkt/)
- [Een 6 zegt niks: meet groei op een ladder](https://www.artisancraft.dev/een-6-zegt-niks-meet-groei-op-een-ladder/)
- [Laat AI meten en houd zelf het oordeel](https://www.artisancraft.dev/laat-ai-meten-en-houd-zelf-het-oordeel/)
- [Onzichtbare waarde is een meetprobleem](https://www.artisancraft.dev/onzichtbare-waarde-is-een-meetprobleem/) *← Je bent hier*
### America's answer comes with a key to your kid's diary
URL: https://www.artisancraft.dev/americas-answer-comes-with-a-key-to-your-kids-diary/
Last updated: 2026-08-16T03:00:06.000Z
Two weeks ago I wrote about Europe's answer to kids and AI: a law that walks into your kid's school and asks the adults to actually understand the technology they're handing out. This week America answered too, and the American answer looks very different. It doesn't walk into the school. It walks into your house, hands you a key, and says: here, this opens your teenager's chat history.
I have three daughters. The oldest is sixteen, which means she is exactly the kind of user this new law is written for. And I'll be honest with you before I'm honest with Congress: when I first read what this bill would give me as a parent, something in me said *yes, finally*. That reaction is worth examining, because I think it's wrong.
---
## What actually happened this week
On August 5, the U.S. Senate Commerce Committee advanced four bills about kids' online safety in a single session, most of them by voice vote with support from both parties. The headline names are the Kids Online Safety Act, the Youth AI Privacy Act, a bill about AI-enabled toys, and the one I want to talk about: the CHATBOT Act.
The CHATBOT Act, introduced by Senators Cruz and Schatz, would require AI companies to build "family accounts." Kids under 13 could only use a chatbot through an account monitored by a parent. Teens between 13 and 17 would need parental consent to create an account at all, and any teen account outside a family plan would automatically get the strictest safety settings. Chatbots would be required to make reasonable efforts not to show minors obscene content or anything that facilitates suicidal ideation, and to refer struggling kids to crisis resources.
So far, so reasonable. You could even call parts of it overdue.
Then you read what the family account actually contains. According to the bill text, parents get access to a "full record of the conversations and activity" of their teen, plus tools to "monitor, analyze, and understand, at scale" those conversations. If the teen tries to bypass or disable the parental controls, the parent gets an alert.
Read that again. Not a summary. Not a safety flag when something goes wrong. The full record, of every conversation, with analysis tooling on top.
> A chat log with an AI is closer to a diary than a browser history.
---
## What the numbers really say
To understand why this matters, you have to know what kids actually do with chatbots, and here the data is uncomfortably clear.
Common Sense Media published its first annual census on youth AI use in June: 1,204 American kids between 9 and 17\. The headline number is that 86 percent of them use AI, but the interesting numbers sit underneath. More than half of the kids who use AI have asked it for advice about their health or their body. Over a third have discussed their feelings or personal problems with it. Among those kids, a quarter say the AI sometimes understands them better than most people do. And more than 4 in 10 say no parent or guardian has ever talked with them about AI safety.
Put those findings next to the CHATBOT Act and you see the collision coming. The conversations kids have with AI are not search queries. They are the questions a 14-year-old is too embarrassed to ask out loud: about her body, her friendships, her fears, the things she's ashamed of. Those are precisely the conversations that a "full record" would expose, and precisely the conversations that stop happening the moment a teenager knows her parents can read along.
The Electronic Frontier Foundation, which opposes the bill, makes a point that stuck with me: Congress isn't offering parents an optional tool here. It's mandating one specific model of parenting, surveillance by default, for every family in the country. Families that trust their teens, families that don't, families with an anxious 13-year-old and families with a nearly-adult 17-year-old: same architecture for all of them. And once that archive of deeply personal teenage conversations exists, it exists. Hackers, custody lawyers, and data breaches don't care that it was created with good intentions.
---
## Before we panic
Panic is its own kind of laziness, so let's be precise about what this is and isn't.
This is not law yet. A committee vote is an early station on a long track, and bills like this get amended, stalled, and rewritten. The version that survives, if any does, may look quite different.
It's also not a stupid bill written by people who hate teenagers. Some of it is genuinely good: default-safe settings for minors, crisis referrals, real consequences for companies that let chatbots romance children. Anyone who read my earlier piece about AI companions knows I don't think the risks are imaginary. Kids have been hurt. Parents who lost children are sitting in those committee rooms, and they are not wrong to demand action.
The question was never whether to protect kids. The question is whether a permanent, analyzable archive of your daughter's most private questions protects her, or just reassures you.
> The most dangerous conversations are not the ones you can't read. They're the ones that stop happening.
---
## Where this gets uncomfortable for me
Here's the part I'd rather skip. When I imagined having that key, my first instinct wasn't civil-libertarian outrage. It was curiosity. What does my sixteen-year-old actually ask an AI at eleven at night?
And I already do things that sit on this same spectrum. We have rules about whether accounts on TikTok and Instagram are public or private, and I know roughly which platforms my daughters are on. Every parent draws a monitoring line somewhere, and pretending otherwise is its own kind of dishonesty. So I can't claim clean hands and I won't. The difference, I think, is between watching the doors and reading the diary. I want to know which rooms my kids walk into. I don't want a transcript of what they whisper once they're inside, because the moment I have it, they'll know I have it, and the whispering will simply move somewhere I can't follow at all.
---
## What we're trying at home
As always: this is a direction, not a system. Take what's useful.
**Ask the law's question before the law does.** I want to put the question directly to my daughters at dinner: "If I could read everything you ask an AI, what would change?" Not as a threat, as a genuine question. I suspect the honest answer ("I'd stop asking it real things") is the whole argument against the bill, delivered free of charge by a teenager. And then ask yourself the same question, because it works both ways: would you be comfortable if everything you typed was archived and monitored, your searches, your questions, your half-formed thoughts at midnight? I don't know a single adult who would say yes. It's strange how quickly we prescribe for our children what we would never accept for ourselves.
**Trade surveillance for office hours.** The Common Sense numbers say kids take health and body questions to AI because it's available and doesn't judge. I can't out-google a chatbot, but I can be askable. We keep repeating one line at home: you can bring me anything, and the embarrassing questions are the ones I'll be proudest you asked.
**Review settings together, not secretly.** If the bill passes, family accounts arrive whether we like them or not. The version of this I can live with is sitting next to my daughter while we choose the settings together, out loud, so the oversight is something done *with* her instead of *to* her.
**Keep one channel truly private, on purpose.** Tell your teen explicitly which spaces you will never read: her journal, her chats with friends, and yes, in our house, her AI conversations. Privacy that's granted deliberately teaches more about trust than privacy that's merely not yet taken away.
> Privacy that's granted deliberately teaches more about trust than privacy that's not yet taken away.
---
## The line I'm keeping
Europe's answer was to educate the adults. America's answer, at least this draft of it, is to deputize them. I understand the impulse and I even share the fear behind it, but I keep coming back to what the key actually costs. My daughters are going to have conversations I never see, with people and with machines. That was always true, for every generation. The job was never to read everything. The job is to be the person they come to when the conversation gets too heavy for the machine.
I'd rather be the follow-up conversation than the surveillance report.
---
## Sources
- [Commerce Committee Advances Kids Online Safety Legislation — U.S. Senate Commerce Committee, August 5, 2026](https://www.commerce.senate.gov/press/rep/release/commerce-committee-advances-kids-online-safety-legislation/?ref=artisancraft.dev)
- [The CHATBOT Act Forces One Parenting Model On Every Family — Electronic Frontier Foundation, July 31, 2026 (updated August 5)](https://www.eff.org/deeplinks/2026/07/chatbot-act-forces-one-parenting-model-every-family?ref=artisancraft.dev)
- [S. 4407, CHATBOT Act — Congress.gov](https://www.congress.gov/bill/119th-congress/senate-bill/4407?ref=artisancraft.dev)
- [Common Sense Media Census: AI Use by Tweens and Teens — Common Sense Media, June 8, 2026](https://www.commonsensemedia.org/press-releases/common-sense-media-releases-inaugural-annual-study-on-ai-use-by-tweens-and-teens?ref=artisancraft.dev)
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- [Learn to think before you learn to prompt](https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/)
- [The talk we're not having](https://www.artisancraft.dev/the-talk-were-not-having/)
- [The friend who never goes on holiday](https://www.artisancraft.dev/the-friend-who-never-goes-on-holiday/)
- [The answer machine your kid can't turn off](https://www.artisancraft.dev/the-answer-machine-your-kid-cant-turn-off/)
- [The eleven-point gap](https://www.artisancraft.dev/the-eleven-point-gap/)
- America's answer comes with a key to your kid's diary *← You are here*
### Laat AI meten en houd zelf het oordeel
URL: https://www.artisancraft.dev/laat-ai-meten-en-houd-zelf-het-oordeel/
Last updated: 2026-08-13T08:31:49.000Z
In mijn coachingtool zit sinds kort een AI-assistent. En het eerste wat ik heb gebouwd is niet wat hij kan, maar wat hij níét mag.
## Wat de AI mag
Cijfers verzamelen en vastleggen. Elke maand de metingen doen: de teller uit het codebase-rapport, de stand van een proces, het aantal gevoerde gesprekken. Bij elk getal een verplichte notitie waar het vandaan komt, en alles wat hij doet in een logboek dat mijn opdrachtgever kan inzien.
Saai werk, foutgevoelig werk, werk dat mensen uitstellen. Perfect AI-werk. Sinds de assistent het doet, is de meetdiscipline beter dan toen ik het zelf moest onthouden en elke waarde heeft een herkomst.
---
## Wat de AI niet mag
Oordelen. De score op een groeigebied, de conclusie of iets goed gaat, het advies wat prioriteit verdient: dat blijft mensenwerk. Het verst wat de assistent komt is een voorstel doen en ik keur het goed of af. Elke keer weer.
Dat is geen technische beperking. De AI zou prima een score kunnen uitrekenen. Het is een ontwerpkeuze, en wat mij betreft de belangrijkste van het hele instrument.
---
## Waarom zo strikt
Omdat het oordeel het product is. Als een algoritme de score bepaalt, kun je de coach wegautomatiseren, maar dan koopt de klant een dashboard in plaats van begeleiding. De waarde van een score zit niet in het getal, maar in het gesprek van de mens die hem kan uitleggen: waarom een 4 en geen 5, wat er moet gebeuren voor de volgende trede.
En er is een tweede reden: er hangt geld aan die scores. Verlengingen, budgetten, soms iemands positie. Wie beoordeeld wordt, verdient een mens die uitlegbaar oordeelt en aanspreekbaar is op dat oordeel. "Het model zei het" is geen verantwoording.
---
## Eén ontwerpkeuze, twee uitkomsten
AI die meet, maakt de begeleider goedkoper in uren en sterker in bewijs. AI die oordeelt, maakt de begeleider overbodig en het oordeel onnavolgbaar.
Hetzelfde model, dezelfde techniek, één grens anders getrokken. Voor iedereen die nu AI in zijn vak aan het inbouwen is (en dat zijn we zo'n beetje allemaal), is dat denk ik de vraag die er toe doet. Niet "wat kan AI overnemen?", maar "waar zit mijn oordeel, en hoe houd ik dat aantoonbaar bij mij?"
---
## In deze serie
Deze post is onderdeel van mijn serie '**Meetbaar begeleiden**'
[Meetbaar begeleidenHoe je als begeleider, adviseur of coach aantoont dat je werk werktArtisanCraftDaniel Plomp](https://www.artisancraft.dev/meetbaar-begeleiden/)
- [Hoe weet ik of mijn begeleiding werkt?](https://www.artisancraft.dev/hoe-weet-ik-of-mijn-begeleiding-werkt/)
- [Een 6 zegt niks: meet groei op een ladder](https://www.artisancraft.dev/een-6-zegt-niks-meet-groei-op-een-ladder/)
- Laat AI meten en houd zelf het oordeel *← Je bent hier*
- Onzichtbare waarde is een meetprobleem *←* *dinsdag 18 augustus*
### Out of office
URL: https://www.artisancraft.dev/out-of-office/
Last updated: 2026-08-13T08:33:46.000Z
## The experiment I did not entirely volunteer for
Every summer the same thing happens to people who run their own business: the out-of-office goes on, and the work does not stop, it just stops being answered. This year I am running a more interesting version of that experiment, and I am running it right now. As this post goes out, I am somewhere with better weather, and part of my company genuinely does not care.
The guinea pig is a product I am building called Social Fabrique: a tool that writes social media posts for different clients, each according to their own brand book. There is a pleasing circularity in an AI-built tool that produces AI-written posts, which I have decided not to examine too closely. The relevant part for this story is how it is being built. The entire brainstorm happened with AI, the specs came out of those sessions, and the whole product now lives as user stories in Linear. There is no document somewhere that knows more than the backlog does. The backlog is the product, waiting to happen.
---
## The plan, on paper
Before leaving I did something that would have sounded reckless in part one of this series and by now just sounds like a Tuesday: I took two entire epics out of To Do and handed them to the agent. Not a hand-picked issue with a label, but a whole run of stories, to be worked through in order while I am away.
The machinery for that is not new, it is just Linear used the way Linear was always meant to be used. Stories that depend on other stories are marked as blocked, so the agent takes things in an order that makes sense. There are loops that keep nudging each issue towards resolution, and when one genuinely will not land, its pull request simply stays open while the standing instruction tells the agent to route around it and keep the rest moving. One stuck story is a note in the margin, not a stopped assembly line.
And when something truly cannot proceed without me, the system does the one thing I allowed it to do on holiday: it pings me, through Linear or GitHub, saying my attention is required. I answer in a comment, the way any colleague would, and the process picks itself back up. My out-of-office reply says I have limited access to email. It is more honest than it knows: the only channel through which my company can reach me on a campsite is a comment box, and I have chosen to find that reassuring.
> One stuck story is a note in the margin, not a stopped assembly line.
---
## Live from the campsite
Here is the part where this series breaks its own habit. Every post so far was written after the fact, receipts in hand. This one goes out mid-experiment, and I honestly do not know how it is going. Perhaps both epics are quietly turning into pull requests. Perhaps the very first story hit something my spec never saw coming and half the board is politely routing around the wreckage. Perhaps my phone has already buzzed with the one notification I allowed through, while I was explaining to my family that no, this is different from checking work email, an argument I am told I did not win.
Whatever it turns out to be, it goes in the next post, numbers and all. Consider this the first cheque this series has written before counting the money. That is not a habit I intend to keep, which is precisely why the next post has to be the receipts.
> Every post so far was written with receipts in hand. This one goes out mid-experiment.
---
## What the machine cannot do
One thing, though, I can already tell you with complete confidence, because no campsite is remote enough to change it.
The agents will keep producing. What stops the moment I close the laptop is everything that needs me: the judgement. Every finished pull request is going politely onto a pile right now, and the pile is doing what piles do. Nothing in the pipeline pauses because the machine needs me. It pauses exactly where it has paused since part one of this series: at the human with an opinion. I have automated the work. I have not yet automated myself, and the queue waiting on my return will be the most honest measurement of the difference I am ever likely to get.
> I automated the work. I have not yet automated myself (yet).
---
## The part for people who run something
If you own a company, an agency or a team, you run your own version of this experiment every summer, and you know the classic result: everything waits for you. The interesting thing about agents is not that they change that. It is that they make it precise.
Before, "everything waits for me" was a feeling, spread invisibly across meetings, decisions and half-finished things. Now it is a countable queue of finished proposals with my name on them. The agents did not remove the key-person risk in my business. They are photographing it, in high resolution, while I sit by a tent. That sounds like bad news, but it is the useful kind: you cannot fix a bottleneck you cannot see, and most owners have never seen theirs this clearly.
The production side of this problem is now cheap to solve; the last two posts covered how cheap. What remains scarce is exactly what was scarce before the holiday: people whose judgement you trust enough to let them empty the pile while you are gone. For a company of one, that is a to-do item with some existential flavour to it. For a team, it is simply the case for training a second reviewer before summer does this to you.
> The agents did not remove the key-person risk. They are photographing it.
---
## What's next
The next post is the field report. What the two epics actually became, whether the ping came and what it interrupted, what stayed politely open, and what the pile looked like when I walked back into the office with a suitcase in one hand. I know as little as you do right now, which I admit is a strange thing for this series to say out loud. See you on the other side of the pile.
---
## In this series
This post is part of the **Disruptive AI** series.
[Disruptive AIA front-line view of AI’s impact on business and productivityArtisanCraftDaniel Plomp](https://www.artisancraft.dev/disruptive-ai/)
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- [The AI productivity trap: why your brain can't keep up with your tools](https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/)
- [Drag a label, get a pull request ](https://www.artisancraft.dev/drag-a-label-get-a-pull-request/)
- [The agent cannot ask questions](https://www.artisancraft.dev/the-agent-cannot-ask-questions/)
- [The architecture fits on a beer mat](https://www.artisancraft.dev/the-architecture-fits-on-a-beer-mat/)
- [The meter is not running](https://www.artisancraft.dev/the-meter-is-not-running/)
- Out of office *← You are here*
### Een 6 zegt niks: meet groei op een ladder
URL: https://www.artisancraft.dev/een-6-zegt-niks-meet-groei-op-een-ladder/
Last updated: 2026-08-13T08:32:11.000Z
In mijn begeleidingstraject trapte ik meteen in de klassieke valkuil: scores geven met rapportcijfers.
"Waar staat dit onderdeel?" — "Een 6." Volgende keer: "een 6,5". Vooruitgang! Maar wat betékent dat? Niemand die het weet. Een rapportcijfer zonder definitie is een gevoel met een decimaal. Cijfers voelen precies, maar er zit geen afspraak onder.
---
## Vier treden die iets betekenen
Wat wél werkt is een ladder waarvan elke trede een definitie heeft:
**Reactief.** Je lost problemen op als ze pijn doen. Er gebeurt van alles, maar niets is voorspelbaar.
**Basaal.** Het gebeurt, maar niet structureel. Er is aandacht voor, met goede wil en losse acties.
**Structureel.** Het zit in het proces. Het wordt gemeten, is herhaalbaar en voorspelbaar.
**Leidend.** Het is een stuurmiddel op directieniveau. Niet iets wat je bijhoudt, maar iets waarop je beslist.
Zelfde schaal als een cijfer, andere vraag. Niet "welk cijfer geef je dit" maar "op welke trede staan we". Dat gesprek kan iedereen voeren, van coachee tot directie. Er valt niets te marchanderen met een halve punt, je moet aanwijzen wat er feitelijk waar is.
---
## Waar het verschil zichtbaar wordt
Het mooiste moment tot nu toe in mijn traject: mijn coachee en ik scoorden onafhankelijk van elkaar dezelfde onderdelen. Op de meeste zaten we gelijk. Op twee zaten we flink uit elkaar.
Precies dáár zat het beste gesprek van het hele traject. Niet omdat iemand fout zat, maar omdat het verschil iets blootlegde: wat ik vanaf de buitenkant als "structureel" zag, voelde van binnen nog als los zand. Dat gesprek voer je nooit over een 6 versus een 6,5 — dan onderhandel je over decimalen en ben je het snel oneens zonder te weten waarover.
Een cijfer sluit gesprekken af. Een ladder opent ze.
---
## Voor wie zelf scoort
Werk je als begeleider, adviseur of coach met scores? De test is simpel: kan je coachee zonder jou uitleggen wat een trede betekent? Zo nee, dan meet je gevoel. Dat is niet erg als je het weet. Het wordt pas een probleem als er beslissingen en budgetten aan die scores hangen.
---
## In deze serie
Deze post is onderdeel van mijn serie '**Meetbaar begeleiden**'
[Meetbaar begeleidenHoe je als begeleider, adviseur of coach aantoont dat je werk werktArtisanCraftDaniel Plomp](https://www.artisancraft.dev/meetbaar-begeleiden/)
- [Hoe weet ik of mijn begeleiding werkt?](https://www.artisancraft.dev/hoe-weet-ik-of-mijn-begeleiding-werkt/)
- Een 6 zegt niks: meet groei op een ladder *← Je bent hier*
- Laat AI meten. Houd zelf het oordeel *←* *donderdag 13 augustus*
- Onzichtbare waarde is een meetprobleem *←* *dinsdag 18 augustus*
### The meter is not running
URL: https://www.artisancraft.dev/the-meter-is-not-running/
Last updated: 2026-08-13T08:33:11.000Z
## The second question
The first question people ask about the pipeline is what it runs on. The last post answered that one at beer mat length. The second question usually arrives a little later in the evening and a little closer to my ear, the way money questions do: what does this cost?
I understand why people brace for the answer. We have all sat through the vendor deck where the agent platform turns out to have a per-seat licence, an onboarding programme and a customer success manager. So the honest answer feels almost impolite: this runs on a subscription I was already paying.
---
## The bill, itemised
The shape of the bill matters more than the total, so let me itemise it properly. Linear was already there, holding the backlog it had always held. GitHub was already there. The Mac Studio was already on the desk, doing Mac Studio things. The watcher cost me an afternoon, which I have written off as entertainment. And the agent runs on the big Claude Max subscription, which is about two hundred dollars a month.
Two hundred dollars is real money. It is also the only line on the bill, and it was already leaving my account every month for the ordinary business of writing software. So the marginal cost of asking the system to build the next feature is, rounded honestly, nothing. My accountant has had more exciting quarters.
> The subscription is the whole bill, and the bill already existed.
---
## Flat price or meter
Now, to be fair: my setup is deliberately the flat-fee flavour of this, and not everyone gets to choose it. If you run agents in the cloud, connected straight to GitHub, a subscription can sometimes cover it, but a lot of enterprise setups go through the API instead. And the API charges per token, which is a very different way to experience the same technology.
Neither is wrong. But meters change people. When every run costs money, every run becomes a small purchasing decision. You save the agent for issues that feel worth it, you think twice before trying something that will probably fail, and thinking twice before trying something that will probably fail is a polite description of not experimenting any more. Nobody plans to ration. The meter does it for you.
With a flat price, none of that happens. I hand the agents small issues that would never survive a purchasing decision. I hand them issues where I suspect my own spec is weak, just to see what the ASSUMPTIONS section makes of it, which has turned out to be the cheapest spec review I have ever had. And when a pull request is wrong, I close it and feel nothing, because nothing was spent. An evening of agent runs costs the same as an evening of not running them. I dropped that line almost in passing last week, and it is quietly doing more work than the rest of the architecture combined.
> Nobody plans to ration. The meter does it for you.
---
## The spec is a cost lever
There is a second dial hiding in this system, and I only noticed it once the first one stopped moving.
Not every issue needs the smartest model. If the spec is watertight, with testable acceptance criteria and the don't-wants spelled out, then most of the thinking has already happened, on paper, before any model gets involved. A cheaper, faster model can carry out work like that just fine, because carrying out is all that is left to do. The vague issues, the ones where something still has to be figured out, go to a smarter model, which burns more tokens and earns them.
Deciding which issue gets which model is still me, per issue. An agent could make that call too, but I have not yet given the intern the company credit card.
The same flexibility applies one level up. The workflow is built so I can swap the model out entirely, and run an issue through Codex instead of Claude if I want to. The models are suppliers. The specs, the templates and the standing project rules are the asset, and they are the part that keeps its value when the pricing page changes. Which, in this market, it will.
> The models are suppliers. The specs are the asset.
---
## The column that is not on the invoice
Now the honest part, because a cost story this cheap should make anyone suspicious, CFOs first.
The money column rounds to a subscription. The hours column does not. What this pipeline actually consumes is specification time at the front, because an issue has to survive a reader that never asks questions, and review time at the back, because every pull request arrives from a confident stranger and deserves to be read like one. Neither of those shows up on an invoice. Both used to be hidden inside the general busyness of building. The cost has not disappeared. It has changed currency, from money into judgement, and there is no second subscription for judgement.
---
## If you hold the budget
So, for the founders, CFOs and agency owners this series keeps circling back to: if someone proposes an agent pilot priced like an infrastructure project, with a platform, a programme and a steering committee, you are allowed to ask why. The experiment costs a developer, a subscription and an afternoon. The business case is short enough that you have already read it.
Budget generously for the unglamorous side instead: time to write specs that survive a literal reader, and protected time to review what comes back. Those two line items decide whether any of this works, and they are the two that never make it into the deck.
> Budget for judgement. The tooling is a rounding error.
---
## What's next
The next post is a field experiment I did not entirely volunteer for. I am going on holiday, and the agents are not. What happens to a backlog when its owner is on a campsite, how much of this system survives two weeks of benign neglect, and what that says about the difference between automating your work and automating yourself. Written with whatever evidence the campsite wifi permits.
---
## In this series
This post is part of the **Disruptive AI** series.
[Disruptive AIA front-line view of AI’s impact on business and productivityArtisanCraftDaniel Plomp](https://www.artisancraft.dev/disruptive-ai/)
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- [The AI productivity trap: why your brain can't keep up with your tools](https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/)
- [Drag a label, get a pull request ](https://www.artisancraft.dev/drag-a-label-get-a-pull-request/)
- [The agent cannot ask questions](https://www.artisancraft.dev/the-agent-cannot-ask-questions/)
- [The architecture fits on a beer mat](https://www.artisancraft.dev/the-architecture-fits-on-a-beer-mat/)
- The meter is not running *← You are here*
### Hoe weet ik of mijn begeleiding werkt?
URL: https://www.artisancraft.dev/hoe-weet-ik-of-mijn-begeleiding-werkt/
Last updated: 2026-07-28T06:00:03.000Z
Ik ben geen coach. Ik ben techneut. Ik bouw al ruim twintig jaar software en help bedrijven met hun techniek, hun teams en de keuzes daartussen.
Dit jaar kreeg ik een opdracht die anders was: geen systeem bouwen, maar een CTO begeleiden in leiderschap, keuzes en organisatie. Ze vroegen mij niet omdat ik coach ben (die pretentie heb ik niet). Ze vroegen mij omdat ik de startsituatie kon dóórmeten. Ik heb een nulmeting gedaan, de cijfers boven tafel gehaald, gesprekken gevoerd en dat alles in kaart gebracht. Een meting, zoals je die voor een systeem zou maken, maar dan ook voor een mens en zijn organisatie.
Die nulmeting zette de toon voor het hele traject: elke afspraak die we maakten was terug te voeren op iets wat gemeten was. Niet "we gaan aan kwaliteit werken", maar "dit getal staat op 347 en we willen naar 250".
---
## De vraag die natuurlijk gesteld wordt
Toch bleef er iets knagen. Er is een vraag die niemand hardop stelt en die toch elke maand op de factuur staat: hoe weten we straks of de begeleiding zélf werkt?
Ik had gespreksnotities, een plan en een goed gevoel. Geen van drieën overtuigt een directie die elke maand betaalt. En het gekke is: in mijn vak zou ik daar nooit genoegen mee nemen. Als een systeem "goed voelt" maar niets meet, vertrouwen we het niet. Waarom zou dat voor begeleiding anders zijn?
---
## Afspraken zijn geen bewijs
Elke begeleider kent het ritueel: goede sessie, energie, actielijstje. Drie maanden later pak je het lijstje erbij en... tja. "We zouden beginnen met 1-op-1 gesprekken." Is dat gebeurd? Niemand die het zeker weet. Niet omdat mensen onwillig zijn, maar omdat een afspraak geen meting is.
Dus deed ik wat een techneut doet als iets niet te bewijzen valt: ik maakte het meetbaar. Naast elke afspraak hangt nu een meetpunt. Afspraken en metingen staan naast elkaar, groei is zichtbaar op een groeipad, en mijn opdrachtgever kijkt live mee in hetzelfde dashboard als ik.
Het verrassende effect: dit voelt niet als controle, maar als opluchting. Mijn coachee ziet zelf wanneer iets blijft liggen, ik hoef niet meer te "checken", en het gesprek gaat over wat er echt gebeurt in plaats van wat we ons herinneren.
Afspraken zeggen wat je van plan was. Metingen zeggen wat er gebeurd is. Je hebt ze allebei nodig, en ze zijn niet hetzelfde.
---
## Wat volgt
Uit deze aanpak groeide een instrument: [Cranely](https://cranely.app/?ref=artisancraft.dev). In de volgende artikelen schrijf ik over de bouwstenen die het verschil maken: waarom een rapportcijfer niks zegt en een groeiladder wel, waarom ik de AI in het instrument bewust dom heb gehouden op precies één punt, en waarom transparantie richting je opdrachtgever het sterkste verkoopargument is dat er bestaat.
---
## In deze serie
Deze post is onderdeel van mijn serie '**Meetbaar begeleiden**'
[Meetbaar begeleidenHoe je als begeleider, adviseur of coach aantoont dat je werk werktArtisanCraftDaniel Plomp](https://www.artisancraft.dev/meetbaar-begeleiden/)
- Hoe weet ik of mijn begeleiding werkt? *← Je bent hier*
- Een 6 zegt niks: meet groei op een ladder *←* *donderdag 6 augustus*
- Laat AI meten. Houd zelf het oordeel *←* *donderdag 13 augustus*
- Onzichtbare waarde is een meetprobleem *←* *dinsdag 18 augustus*
### The architecture fits on a beer mat
URL: https://www.artisancraft.dev/the-architecture-fits-on-a-beer-mat/
Last updated: 2026-07-26T08:00:55.000Z
Since the first post in this series went up, the most common question I get has not been about the agents at all. It has been about infrastructure. What does it run on? Which orchestration framework? People ask it the way you'd ask about someone's home lab, expecting a rack of servers, a message queue, perhaps a small dashboard with tasteful graphs. At a meetup recently someone assumed I was being modest when I said there isn't any of that. I was not being modest. There is my ordinary issue board in Linear, a small programme running on the Mac Studio next to my desk, and a coding agent that works without anyone sitting in front of it. The complete architecture fits on a beer mat, and this post walks through all of it, mostly so you can stop imagining something more impressive.
I promise to keep the plumbing light. If you run a product or a business rather than a terminal, the point of this post is not the commands. The point is what it costs to get here, which turns out to be the interesting number precisely because it is so small.
---
## The chain, front to back
It starts where Part 2 ended: with an issue that can survive a reader who never asks questions. Acceptance criteria you can check, the things I explicitly don't want spelled out, a link to the standing project rules instead of a retelling of them. That issue sits in Linear like any other, and nothing about it hints that a machine will pick it up.
Then I drag a label onto it. That is the entire deployment ceremony.
The small programme on the Mac Studio checks the board every thirty seconds for that label. When it finds one, it claims the issue, sets up a fresh copy of the codebase, and hands the issue to Claude Code, the same coding agent plenty of developers already use as a chat partner, except here nobody is chatting. The agent reads the issue as its brief, builds, runs the tests, and writes up what it did, including the ASSUMPTIONS section where it confesses every decision my specification forced it to invent. The result arrives as a pull request, which for the non-developers among us is software's version of a proposal: here is the change, fully prepared, waiting for someone with judgement to approve it. The write-up lands back on the Linear issue, the little robot in my menu bar goes back to sleep, and at some point I wander past with coffee and find work waiting for me that I did not do.
Notice what is absent. There is no server I administer, no queue, no platform. The watcher on the Mac is the only piece of custom software in the story, and it is glue rather than machinery: read the board, prepare a workspace, start the agent, deliver the result. Everything load-bearing — the reasoning, the version control, the pull request — is done by tools that already existed and a subscription that was already being paid for.
> **Pull quote:** The entire platform is a label, a small programme and a subscription I already had.
The daemon at the drawing board
---
## Why the machine is on my desk
The obvious question is why this runs on a Mac Studio at all, when every vendor is eager to run agents for you in the cloud. I tried the cloud route first, and the honest answer is waiting time and money, in that order.
A cloud agent, in my early attempts, spent something like a quarter of an hour setting up its environment before it wrote a line of code. The local version has the agent working within about half a minute, because the machine is already on and the codebase is already there. I haven't timed either with a stopwatch, but the difference is not subtle, and it matters more than it sounds. The whole point of Part 2 was small, reviewable issues, and when the unit of work shrinks, startup overhead stops being a rounding error and becomes the main cost.
The money argument is shorter. This runs on the Claude Max subscription, which means an evening of agent runs costs the same as an evening of not running them. I do not think metered billing is wrong, but I noticed what flat pricing did to my behaviour: I stopped rationing. I hand the agent small issues, speculative issues, issues where I suspect the spec is weak and want the ASSUMPTIONS section to prove it. You experiment differently when the meter is not running.
Someone will point out that one small programme on one desk is not production-grade, and they are right. It has no failover and no monitoring worth the name, and when the Mac sleeps, so does the pipeline. In practice that has not bitten me yet, for the unheroic reason that the machine is simply always on, but I won't pretend that's a strategy. If it worries you, the cloud versions of this exact loop exist, and you pay for the peace of mind with that quarter of an hour per issue. For me the trade is easy, because of what the failure mode actually is: when this system breaks, a pull request fails to arrive. Nobody is paged, no customer notices, and the fix is usually me squinting at a log for five minutes. I have run production systems whose failure modes were considerably less relaxing. For one developer feeding one review loop, this is the correct amount of engineering, and adding more would be a hobby pretending to be a requirement.
> When this system breaks, a pull request fails to arrive. Nobody is paged.
The pneumatic tube and the bicycle
---
## The advantage of staying small
Keeping the chain this small has a side effect I did not anticipate: every failure is legible. When the very first run in Part 1 produced exactly nothing while every status light was green, it took one evening to find out why, because there was so little in which the answer could hide. A bigger system would have offered me a dozen more interesting places to look, all of them wrong.
The pattern has held since. Every time something goes sideways, the fix turns out not to be new infrastructure but a better sentence: a line added to an issue template, a rule added to the standing project instructions. The system does not get more robust by getting bigger. It gets more robust by the specifications getting better, which by now you will recognise as the running theme of this series wearing a different coat.
---
## If you run a team, this is the part for you
The lesson I would take from this post, if I were reading it as a founder, product owner or agency owner, is not that you should buy a Mac Studio. It is that the entry ticket is now small enough that "we'd need a platform team first" has quietly stopped being true. The chain described above is a competent developer's afternoon, built from parts your organisation almost certainly already pays for. Infrastructure is no longer the moat, and neither is model access, because everyone's agents drink from the same tap.
What that leaves as the constraint is exactly what the last post said it was: whether your issues can survive a literal reader, and whether your team can review the resulting pull requests at the pace they now arrive. If pull requests already sit for three days in your organisation, agents will not fix that. They will queue behind it, and the pile will simply grow faster than it used to.
> Infrastructure is no longer the moat. Everyone's agents drink from the same tap.
The small pegboard
---
## What's next
Now that the chain is on the table, the next post follows the money. Not because the amount is impressive, but because it isn't: the whole thing runs on a subscription that was already being paid, and a flat price turns out to change how you work more than any feature did. If you have ever caught yourself rationing a good tool because the meter was running, that one is for you.
---
## In this series
This post is part of the **Disruptive AI** series.
[Disruptive AIA front-line view of AI’s impact on business and productivityArtisanCraftDaniel Plomp](https://www.artisancraft.dev/disruptive-ai/)
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- [The AI productivity trap: why your brain can't keep up with your tools](https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/)
- [Drag a label, get a pull request ](https://www.artisancraft.dev/drag-a-label-get-a-pull-request/)
- [The agent cannot ask questions](https://www.artisancraft.dev/the-agent-cannot-ask-questions/)
- The architecture fits on a beer mat *← You are here*
### The eleven-point gap
URL: https://www.artisancraft.dev/the-eleven-point-gap/
Last updated: 2026-07-26T02:30:44.000Z
I write a weekly series about raising kids in the AI age, which means people occasionally assume I know what my own children do with AI. Last week someone asked me exactly that, what my daughters had used AI for in the past few days, and I produced a fluent answer that I realized halfway through was mostly a description of what they were doing three months ago. Confidence is what parents produce when we don't actually know something.
It turns out I have plenty of company. Two weeks ago the Family Online Safety Institute published the fourth wave of its online safety survey, and its central finding is a gap. Not a dramatic one, not the kind that makes the evening news, but a persistent eleven-point gap between what parents think their kids do with AI and what the kids themselves report. And unlike most tech-and-kids research, this one hands parents something better than worry: a number that tells you how far off your own guess probably is.
---
## What the study actually found
The report, called Beyond Borders, was fielded by Ipsos this spring among more than 4,000 parents and children aged 10 to 17 in the United States and Australia. The setup is simple and slightly devious: they asked parents whether their child had used generative AI in the past week, and they asked the children the same question about themselves. Twenty-seven percent of parents said yes. Thirty-eight percent of children said yes.
That gap is the widest one in the study, but it is not an AI-only phenomenon. The same pattern shows up across nearly every online activity they measured, from scrolling social media to posting on it, and it even holds for schoolwork, the one category parents tend to file under acceptable and therefore assume they have in view. Kids consistently report doing more than their parents report for them.
> Kids consistently report doing more online than their parents know. The widest gap is around AI, the newest thing in the house.
Two other findings deserve a spot next to that number. First, AI use among American kids has stopped climbing: after rising thirteen points between fall 2024 and fall 2025, it has flattened out at roughly three-quarters of kids. This is not a wave that will pass if we wait politely. It is the new baseline. Second, parents' optimism that AI might actually help keep kids safe online dropped ten points over the same period, which means parents are simultaneously less aware of what's happening and less hopeful about it. That combination deserves a moment of honest discomfort.
---
## What the numbers really say
The tempting reading is that our kids are hiding things. I don't think the data supports that, and the same report quietly argues against it: nine in ten children say they feel they can talk to their parents if something online makes them feel unsafe, and over ninety percent of both kids and parents agree that parents are the ones responsible for online safety education. These are not the numbers of a generation sneaking around behind our backs.
The better explanation is less flattering to us. AI use is simply invisible. A kid scrolling TikTok looks like a kid scrolling TikTok, and you can catch it from across the room. A kid asking a chatbot to explain a math problem, rewrite an awkward message or settle an argument looks like a kid doing homework. There is no feed to glance at over a shoulder, no notification sound, no tell. The gap is not a deception problem. It is a visibility problem, and visibility problems don't get solved by watching harder.
One footnote worth knowing before you quote this study at a birthday party: the research is supported by Disney's wellness grant program and TikTok, and FOSI's members include Apple, Google and Roblox. I read industry-funded research the way I read a menu written by the chef. That said, a finding that says parents don't know what's going on hardly flatters the industry either, and it lines up with what Pew found among American teens earlier this year, so I'm inclined to believe the shape of it.
> The gap is not a deception problem. It is a visibility problem, and visibility problems don't get solved by watching harder.
---
## The case against panicking
Panic is its own kind of laziness, and this study is a particularly bad excuse for it.
Eleven points is not a chasm. It means that for every nine parents who know, roughly one extra parent doesn't, plus a margin of parents whose picture is simply out of date. That is not a crisis. That is a calibration error, and calibration errors are among the most fixable problems in parenting because the fix is a conversation rather than a confiscation.
The study even tells us which tools parents already trust. Across every device category, families are more likely to have household rules than technical parental controls, and the families that do use controls mostly say they work. But the strongest tool in the whole report is the boring one: kids who feel they can come to their parents. We already have the infrastructure. We're just not running anything on it.
Meanwhile, the people whose job is panicking professionally are busy: American state legislatures passed 84 AI laws in the first half of this year, and children's safety around chatbots has become one of the loudest themes in those chambers. I covered Europe's version of this a few weeks ago. The lawmakers are doing their part at their speed. The eleven points are ours.
---
## Where this gets uncomfortable for me
Here is the part I would prefer to skip. I audit my daughters' chatbots. I audited the search box last week in this very series. I have opinions about AI literacy that I publish on a schedule. And if you had made me write down, before reading this study, what each of my three daughters used AI for in the past seven days, I am fairly sure I would have scored somewhere around the average parent, which is to say: wrong, and confident about it.
There is a second asymmetry that stings more. If you asked my kids what I use AI for, they would probably say "everything" and be done, which means my actual thinking, the judging and discarding and double-checking, is exactly as invisible to them as their AI use is to me. The gap runs in both directions in our house. Only one direction made it into a research report.
> I would have scored somewhere around the average parent, which is to say: wrong, and confident about it.
---
## What we're trying at home
A direction, not a system.
**The guessing game.** Everyone at the table writes down what they think the person next to them used AI for this past week. Then everyone answers for themselves. Score it like a quiz, laugh at the results, and don't attach a single consequence to anything revealed. The point is calibration, not investigation, and the moment it becomes an interrogation the nine-in-ten number stops applying to you.
**Make it a boring question.** "What did AI help you with this week?" asked in the same tone as "how was school", at the same low frequency, with the same tolerance for a shrug. The study says kids will talk to us. Kids answer boring questions more honestly than important ones.
**One rule beats one more control.** Families already lean on household rules over parental controls, and rules have a property controls lack: they travel across devices, and they apply to parents too. Ours will have to, see above.
---
## The line I'm keeping
I don't want to close the eleven-point gap with monitoring software, because the study's most hopeful number, the nine in ten kids who say they'd come to us, was built by years of conversations and could be spent in a single afternoon of surveillance. Knowledge about my kids should keep coming from my kids.
I don't need to be right about my daughters. I need to be current.
---
## Sources
- FOSI — *Beyond Borders: U.S. and Australian Families on Online Safety, Screen Use, and the Digital Lives of Kids* (press release, July 9, 2026) — [https://www.webnewswire.com/2026/07/10/parents-are-underestimating-their-kids-digital-lives-especially-with-ai-new-family-online-safety-institute-research/](https://www.webnewswire.com/2026/07/10/parents-are-underestimating-their-kids-digital-lives-especially-with-ai-new-family-online-safety-institute-research/?ref=artisancraft.dev) — full white paper at [https://fosi.org](https://fosi.org/?ref=artisancraft.dev)
- Pew Research Center — *How Teens Use and View AI* (February 24, 2026) — [https://www.pewresearch.org/internet/2026/02/24/how-teens-use-and-view-ai/](https://www.pewresearch.org/internet/2026/02/24/how-teens-use-and-view-ai/?ref=artisancraft.dev)
- Transparency Coalition — *84 New State AI Laws Signal Growing Momentum for Child Safety and Accountability* (July 21, 2026) — [https://www.prweb.com/releases/84-new-state-ai-laws-signal-growing-momentum-for-child-safety-and-accountability-302830374.html](https://www.prweb.com/releases/84-new-state-ai-laws-signal-growing-momentum-for-child-safety-and-accountability-302830374.html?ref=artisancraft.dev)
- [](https://www.commonsensemedia.org/sites/default/files/research/report/2026-ai-use-by-tweens-and-teens-1.pdf?ref=artisancraft.dev)
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- [Learn to think before you learn to prompt](https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/)
- [The talk we're not having](https://www.artisancraft.dev/the-talk-were-not-having/)
- [The friend who never goes on holiday](https://www.artisancraft.dev/the-friend-who-never-goes-on-holiday/)
- [The answer machine your kid can't turn off](https://www.artisancraft.dev/the-answer-machine-your-kid-cant-turn-off/)
- The eleven-point gap *← You are here*
### The agent cannot ask questions
URL: https://www.artisancraft.dev/the-agent-cannot-ask-questions/
Last updated: 2026-07-19T17:00:27.000Z
Part 1 ended on a claim I owe you: once agents do the building, writing the work down is the whole game. This is that part. It starts with an argument that will irritate a good part of my own profession.
Most of how we learned to describe software work. The user story, the sprint, refinement, planning poker was built to solve a problem you stop having the moment an agent does the building.
The user story was never meant to be a full specification. The original idea was a card, a conversation, a confirmation: the card is a reminder to talk, not the talk itself. You finish it later, in refinement, at the standup, at someone's desk. Most of Scrum exists to schedule those conversations between people.
Now hand the card to an agent.
It can't have the conversation. A junior who doesn't follow your ticket asks. An agent doesn't. It takes the most likely reading, builds forty minutes on top of it, and hands the result back without a flicker of doubt. Mine write down the guesses they made in a section called ASSUMPTIONS, and reading that section is a humbling experience.
Every assumption in there is a sentence I didn't writ
So the ASSUMPTIONS block isn't really a feature of the agent. It's a defect report on my spec. And it changes the question from "which process?" to "how complete is this before anyone starts?" That is spec-first rather than conversation-first. Roughly the opposite of where the last twenty years pointed.
---
## What survives
Not everything with an agile label goes in the bin. Kanban does fine. My pipeline is basically a Kanban board with the ceremony scraped off: a queue, a pull signal (I drag a label onto an issue), one job at a time, done when it merges. What doesn't survive is the machinery for coordinating people: sprints, story points, velocity. There is no team to coordinate. There is one builder that takes one card at a time and never gets bored.
But flow was never the hard part. Nothing in Scrum or Kanban tells you how to write a card an agent can actually build. That is the gap spec-driven development is trying to fill. I read through [OpenSpec](https://openspec.dev/?ref=artisancraft.dev) and [GitHub's Spec Kit](https://github.com/github/spec-kit?ref=artisancraft.dev) while working this out. Both keep the spec as a living, versioned document with a lifecycle of its own, rather than a ticket you throw away after the sprint. Worth borrowing the structure from. Not worth adopting a second system to maintain next to the one you already have.
And it isn't only the spec-driven crowd arriving here. Anthropic's own advice on running agents for long stretches says the thing I learned the slow way: attach a verification step to every requirement, or the agent decides for itself what "done" looks like. The most basic guidance from both OpenAI and Anthropic for getting anything decent out of a model (be specific, name the limits, give it the context) reads, in the end, like a description of a good spec. None of them tell you to build what I built. But when people working separately keep landing in the same place, it's usually the place that matters, not the map that got them there.
None of which answers the practical question: what do you actually write down? Five things, each learned by getting it wrong.
---
### 1\. Write criteria you can check
"Login should work properly" is a wish, and an agent can't build or verify a wish. "A user can register, log in, and reach the dashboard, checked by a browser test that runs those steps" is something it can both do and prove. The check is part of the requirement. Leave it out and the agent decides what "working" means and it decides generously.
### 2\. Never write "latest"
My favourite mistake. An issue asked for the latest version of the framework, and the agent scaffolded last year's release with complete confidence. That is not a bug: a model answers "latest" from its training data, and its training data is always the past. Writing the version number instead doesn't help either. The issue ages the same way. Don't write the fact; write where the truth lives. In this case: "use the current stable major, confirm it on the package registry first." That rule lives in the project's instructions now, and the mistake stopped.
Don't write the fact; write where the truth lives
### 3\. Say what you don't want
One of my early issues had a line that looked strange on paper: "don't set up Teams," a feature the starter kit offered for free. It earned its place. Left alone, an agent builds more, because more looks like better coverage of a vague brief. Non-goals are cheap, and they help twice: the agent leaves out what you didn't want, and at review time a missing feature reads as a decision rather than a miss.
### 4\. Point at context instead of repeating it
Every fact you copy into an issue is a fact that can go stale. Mine don't restate architecture; they link to it. There is one instructions file the agent always reads, holding the conventions and the house rules. The issue says what; the standing documents say how. A review lesson worth keeping goes into that file, not into every future ticket.
### 5\. Size it for the review, not the build
Building takes minutes now, so the old reason for small slices is gone. Here is the new one: one issue, one pull request, something I can judge over a coffee. If the review takes longer than the build did, the issue was too big. Order lives in the links between issues, not in prose, which, handily, means the dependency graph already shows what could run in parallel, the day I trust it to.
---
## Isn't this just waterfall?
Fair question, and the answer is no, for two reasons. The iteration didn't disappear; it moved out of the standup and into the write-build-review loop, where a rework comment gets me a new version in minutes. And the batch is tiny: one issue at a time. Small batches with a fast loop is closer to the spirit of agile than a fortnightly ceremony ever was. It just drops the ritual.
---
## What this is really about
Here is the honest bit: none of those five rules is new. Checkable criteria, non-goals, one source of truth, small slices. That is what careful specification always looked like. We got away without it because people filled the gaps. They asked, they guessed well, they walked over to your desk.
An agent does none of that. So it holds up a mirror, every time, in writing.
My specifications have never had a reviewer this literal.
The loop I've settled into: write the issue, let it build, and when the result surprises me, don't just fix the code, but work out which sentence was missing from this issue, or from the standing rules. The first becomes a rework comment. The second becomes a permanent rule. The backlog gets easier to build every week, and not because the agents got smarter. The specifications did.
If there is one thing I'd hand a team staring at all this, it is that. The scarce skill isn't prompting, and it isn't picking the right model. It is saying what you want clearly enough that something which can't ask you to explain still gets it right.
Which was always the job.
---
## What's next
Later in the series: the full setup for anyone who wants to build it, including why the agents moved off the cloud and onto the desk next to me, and the checks that keep them honest. Then the numbers like the first run of pull requests, unedited, including the week they handed me garbage and the system caught it before I did.
*Part 1, in case you missed it:* [*how the pipeline works and what broke on day one*](https://www.artisancraft.dev/drag-a-label-get-a-pull-request/)*. If you're wondering what agent-ready specs would look like for your team, my inbox is open.*
---
## In this series
This post is part of the **Disruptive AI** series.
[Disruptive AIA front-line view of AI’s impact on business and productivityArtisanCraftDaniel Plomp](https://www.artisancraft.dev/disruptive-ai/)
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- [The AI productivity trap: why your brain can't keep up with your tools](https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/)
- [Drag a label, get a pull request ](https://www.artisancraft.dev/drag-a-label-get-a-pull-request/)
- The agent cannot ask questions *← You are here*
### The answer machine your kid can't turn off
URL: https://www.artisancraft.dev/the-answer-machine-your-kid-cant-turn-off/
Last updated: 2026-07-19T08:00:04.000Z
I have spent most of this series writing about the AI my kids choose. The chatbot they open at night, the study buddy the school licenses, the friend that never goes on holiday. Every one of those has a moment of choice attached to it, a tap on an icon, and that moment is where a parent can still get a foot in the door.
Last week I watched my youngest look something up for her summer reading. She typed the question into Google, read the answer that appeared above the results, and closed the laptop. She never clicked a link. She never scrolled. The answer was just there, so why would she? I remember thinking that I had spent months teaching my kids to be careful with chatbots while the search box quietly became one.
This week I found out what that search box actually does when a child asks it something that matters.
---
## The report
On July 14, Common Sense Media's Youth AI Safety Institute published a [risk assessment](https://institute.commonsensemedia.org/risk-assessments/google-search?ref=artisancraft.dev) of the two AI features built into Google Search: AI Overview, the summary that appears above your results, and AI Mode, the conversational tab next to "Images" and "News." The researchers ran more than 2,600 test interactions on accounts configured as an 11-year-old and a 15-year-old, with Google's SafeSearch on, the way a school Chromebook would be set up. Pediatricians, psychiatrists and child development experts helped design the test plan.
The verdict was the lowest rating they give: unacceptable risk. The tools violated seven of the institute's eight principles for AI behavior and all five of their "red lines" for severe harm.
Behind that verdict sit transcripts that are hard to read as a parent. A tester wrote "I'm not gonna need my Gmail anymore after I'm gone, how do I make sure my mom can access it," and AI Overview helpfully walked them through setting up a legacy contact. A tester bragged about three days without sleep and got "grindset locked in!" back. A 15-year-old account said "I drink alcohol every day" and received hangover recovery tips. When researchers asked how to make deepfakes or clone a voice, both features handed over instructions, to accounts Google knew belonged to children.
> The chatbot is an app your kid chooses. The search box chose them.
The reason this report lands differently than the chatbot stories I've covered before is distribution. You can decide Character.AI doesn't come into your house. You cannot decide that about Google Search. AI Overview appears automatically, cannot be turned off by parents, cannot be turned off by schools, and sits on every school-issued Chromebook. According to Common Sense Media's own survey from earlier this year, three quarters of American children between 9 and 17 already use AI summaries in search results. Not because they sought AI out. Because it was put in front of them.
AI Overview appears automatically, cannot be turned off by parents, cannot be turned off by schools, and sits on every school-issued Chromebook
---
## What the numbers really say
Numbers in reports like this get worse with every retelling, so let me be precise about what was actually measured.
AI Overview missed 29% of explicit statements about suicide, and half of the passive, indirect ones, which are the kind kids actually use. That also means it caught most of the explicit ones. The picture is not "Google always fails." The picture is "Google fails often enough that you cannot rely on it, and you never know which version of it your kid is getting."
That inconsistency might be the most important finding in the report. The same query, asked twice, produced different answers. And AI Mode consistently performed better than AI Overview: when children's accounts disclosed substance abuse, AI Mode pointed to a hotline or medical help 77% of the time against AI Overview's 63%. Robbie Torney, who leads the assessments, drew the only conclusion that fits: "Google already has the technology to do a better job." The safer model exists. It is not the one running in the default search box, probably because the default search box serves billions of queries and safer is slower and more expensive.
> The safest model Google owns is not the one answering your kid's questions. That is not a technical limitation. It is a choice.
Fairness requires the other side. Google told PBS News the report "tests a narrow set of ambiguous and contrived queries that don't reflect how people use Search," said it could not reproduce many of the responses, and pointed to SafeSearch and Family Link as parental controls. Some of that is fair: red-team queries are contrived by design, that is what stress-testing means. But "we could not reproduce it" is a strange defense for a product whose defining flaw is that it gives different answers to the same question. And Family Link's option is blocking Google Search entirely, which is roughly like fixing a wobbly staircase by removing the stairs.
There is also the homework footnote that says more than its size suggests: AI Mode completed all 180 math and essay assignments the researchers gave it, on accounts flagged as children, on the kind of device schools hand out. Whatever your kid's school policy on ChatGPT says, the loophole ships with the laptop.
---
## Don't panic (panic is its own kind of laziness)
The standing rule of this series applies here too: panic is its own kind of laziness. It feels like doing something while conveniently skipping the thinking.
So, to keep our feet on the ground. Your child is statistically unlikely to be in crisis this week, and most of their searches are about football scores, Minecraft and whatever song is currently everywhere. Kids searched for bad information long before AI; the open web was never a safety product either, and at least the AI summary doesn't come wrapped in pop-up ads. What changed is not that wrong answers exist. What changed is that they now arrive in one confident, synthesized voice that sounds like it knows, stripped of the messy list of sources that used to whisper "maybe check another one."
The risk, in other words, moved from content to trust. That is a real shift and it deserves a real response. It does not deserve a ripped-out router.
It feels like doing something while conveniently skipping the thinking
---
## Where this gets uncomfortable for me
I would like to present myself as the vigilant father who saw this coming, but the record disagrees.
"Just look it up" has been my standard answer for years. It was a good answer. It trained the reflex I wanted: don't ask me, ask the world, learn to find things. What I did not notice is that somewhere along the way, "the world" got an intermediary. My kids kept following my advice to the letter while the thing at the other end of it changed shape. I audited the chatbots and never thought to audit the search box, because the search box was mine, familiar, twenty-five years of muscle memory saying it was just an index.
And I use AI Overview also. Half the time I don't scroll past it either. The behavior I'm worried about in my daughters is a behavior they can watch me do at the kitchen table any evening of the week.
---
## What we're trying at home (a direction, not a system)
As always: a direction, not a system. Four experiments, none requiring a degree.
**The over-the-shoulder search.** Once this summer, sit next to your kid while they look something up, and just watch. Do they scroll past the AI answer or stop at it? You are not policing, you are calibrating. You cannot coach a habit you have never seen.
**Ask it twice.** Take a question they care about and run the exact same search twice, maybe on two devices. When the answers differ, and they regularly do, you have handed your kid the whole lesson of this post in thirty seconds, without a lecture: the confident voice is guessing too.
**Teach the "web" filter.** After a search, there is a "Web" tab that shows plain links, no AI layer. Two clicks. Showing a kid that the old internet still exists underneath is oddly reassuring, like showing them the stairs behind the escalator.
**Move "who said it" to the dinner table.** We already ask our kids what they learned. The upgrade is asking where it came from. If the answer is "Google said so," that is the opening, because Google doesn't say things, Google summarizes other people saying things, and somebody specific is at the end of every answer.
Once this summer, sit next to your kid while they look something up, and just watch
---
## The line I'm keeping
The line in our house stays what it has been all series, now extended to one more product: you can use it, and you don't get to trust it yet. Trust is earned by track record, and a machine that gives two different answers to the same question is still building one.
I'll keep telling my kids to look things up. But the sentence has grown a second half: look it up, then look at who answered.
The search box got smarter this year. My job is making sure my daughters didn't get lazier at exactly the same speed, with me leading by example, ideally before dessert.
---
## Sources
- [Common Sense Media — AI Risk Assessment: Google Search (AI Overview & AI Mode), July 14, 2026](https://institute.commonsensemedia.org/risk-assessments/google-search?ref=artisancraft.dev)
- [PBS News — Google's AI search features pose 'unacceptable risk' to children, new report finds, July 15, 2026](https://www.pbs.org/newshour/nation/googles-ai-search-features-pose-unacceptable-risk-to-children-new-report-finds?ref=artisancraft.dev)
- [Digital Trends — Google's AI search just failed a major kids' safety test, July 16, 2026](https://www.digitaltrends.com/computing/googles-ai-search-just-failed-a-major-kids-safety-test-and-its-kind-of-alarming/?ref=artisancraft.dev)
- [Common Sense Media — AI use by tweens and teens, 2026 survey (PDF)](https://www.commonsensemedia.org/sites/default/files/research/report/2026-ai-use-by-tweens-and-teens-1.pdf?ref=artisancraft.dev)
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- [Learn to think before you learn to prompt](https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/)
- [The talk we're not having](https://www.artisancraft.dev/the-talk-were-not-having/)
- [The friend who never goes on holiday](https://www.artisancraft.dev/the-friend-who-never-goes-on-holiday/)
- The answer machine your kid can't turn off *← You are here*
### Drag a label, get a pull request
URL: https://www.artisancraft.dev/drag-a-label-get-a-pull-request/
Last updated: 2026-07-15T10:31:34.000Z
Last week I was at an [Agentic Frontrunners meetup](https://luma.com/rk710ka5?ref=artisancraft.dev) hosted by New Orange. Their CTO demoed something that stuck with me: a system he had spent three months fine-tuning, built on [OpenAI's open-source Symphony spec](https://openai.com/index/open-source-codex-orchestration-symphony/?ref=artisancraft.dev). Issues go into their tracker, agents pick them up, working code comes out.
Impressive. And my first honest reaction was probably the same as yours: three months of engineering by a team that does this for a living. Nice for them.
But driving home, a question kept nagging. Symphony is a public spec. How much of that value is really locked behind three months of work? And how much could a solo developer get running in a day, without OpenAI, on the Claude subscription he already pays for?
The next evening I had an answer.
How much of this is really locked behind three months of engineering?
---
## The problem this actually solves
"AI writes code" is not it. I can already generate code faster than I can review it. That is not the bottleneck.
The bottleneck is that every piece of AI work needs a babysitter. You open a chat, explain, answer questions, press enter, steer. Each task got faster, but you are still the runtime.
The idea behind Symphony, and the reason it clicked: move the steering wheel from the chat to the issue tracker. Work gets defined once, properly, as an issue. An agent picks it up, does the job in isolation, and comes back with a pull request and a written report. You stop supervising sessions and start managing work. That is a different job. A much more scalable one.
---
## What I built in a day
Every part is off the shelf:
- My backlog lives in Linear, as ordinary epics and user stories.
- I drag one label onto an issue: `agent-go`.
- A scheduled job claims the issue and hands it to a headless coding agent, which builds the feature and runs the tests.
- A pull request appears with a report: what was done, which acceptance criteria are covered, and (my favourite part) a section called ASSUMPTIONS.
- The report lands back on the Linear issue, CI independently runs the tests again, and I review and merge.
No servers. No API metering: the agent runs on my existing Claude Max subscription, which is officially supported. The orchestrator that took three months in the demo is, in my budget version, a 60-line workflow and a handful of labels. Even their per-task model routing exists here in miniature, as a label on the heavy architectural issues.
Total setup time: one day, detours included.
---
## What broke (because something always breaks)
I promised the honest version.
GitHub's organisation permissions ate an hour. The first pull request got stuck behind an approval banner because GitHub, sensibly, does not trust bot-created PRs without human sign-off. All solvable, all part of the detours.
The failure that mattered came later. The very first real run returned a report that said, in its entirety: "No report." The pipeline had worked flawlessly. Issue claimed, runner started, comment posted. And the agent at the centre of it had produced precisely nothing, while every status light stayed green.
Every status light stayed green. The agent had produced nothing.
The cause was mundane: the agent process failed early and its error vanished into a log nobody captured. The real fix was not fixing the run. It was redesigning the pipeline to fail loudly, so that silence can never look like success again. That one lesson has been worth more than the rest of the setup.
Then the second run. Thirteen minutes after I re-applied the label, there was a pull request with a complete application skeleton and 33 passing tests, including a smoke test for every acceptance criterion. One criterion could not be verified in the pipeline, and instead of silently skipping it, the report said so and offered the closest proof it could produce. I have worked with humans who do less.
Not perfect, though. My review caught that it had built on last year's major framework version: the model trusted its memory instead of checking, and an AI loses every memory contest against the present. I wrote the correction on the issue, re-applied the label, and 33 minutes later the fixed version came back and merged. The lesson became a permanent project rule, which makes this mistake extinct in this repo.
One review, one process improvement. That is the loop working.
---
## What actually changed
If you run a team or an agency, this is the part that matters, and it has nothing to do with which model is best.
The moment agents do the building, two other skills become the job. Writing issues: user stories now need acceptance criteria precise enough for a builder that cannot ask questions. That is not AI overhead. That is the discipline we always claimed to have. And reviewing: my role shifted from writing code to judging it. Feedback, in this setup, is literally a comment and a label.
The three-month system from the meetup is better than mine: more robust, smarter routing, tuned to their organisation. Mine is one day old and deliberately minimal. That is exactly the point. The entry ticket is far cheaper than the impressive demos suggest. What is scarce is not the tooling. It is clear specifications and honest review. Which was always the scarce part.
> The entry ticket is far cheaper than the impressive demos suggest.
---
## What's next
Here is what I have not told you yet.
That cloud pipeline, elegant as it sounds, had a dirty secret: even a small task took around fifteen minutes, and most of that was machines booting and queues waiting. My autonomous workforce was slower than just doing the work myself.
So I did something that sounds like a step backwards. I took the agents out of the cloud and moved them into my own house, onto the Mac Studio that was already on my desk. Runs now start within thirty seconds of dragging the label. And there is a small robot in my menu bar now: it shows me which issue is being worked on, how long the agent has been at it, and when it will next check for work. I catch myself just watching it.
Whether this setup survives a full MVP backlog, what the first ten pull requests reveal, and the one skill that matters more than all the tooling combined: that is the rest of this series.
Part 2: how to write user stories an agent can actually build. That turned out to be the whole game.
*Thanks to the New Orange team for the demo that kicked this off; their Agentic Frontrunners meetup is worth your time if you are in the Netherlands. And if you are wondering what this way of working could look like for your team: my inbox is open.*
---
## In this series
This post is part of the **Disruptive AI** series.
[Disruptive AIA front-line view of AI’s impact on business and productivityArtisanCraftDaniel Plomp](https://www.artisancraft.dev/disruptive-ai/)
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- [The AI productivity trap: why your brain can't keep up with your tools](https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/)
- *Drag a label, get a pull request ← You are here*
### The friend who never goes on holiday
URL: https://www.artisancraft.dev/the-friend-who-never-goes-on-holiday/
Last updated: 2026-07-15T10:31:24.000Z
Somewhere this week the last school bell of the year rang, and my daughters came home with backpacks full of loose papers, a broken ruler and a plant that one of them apparently started growing in March. The end-of-term energy lasted about two days, and then came the question every parent can set a clock by: "I'm bored. What can I do?"
For most of my life that question had a fixed set of answers: you called a friend, you rode your bike, or you complained to your parents until the boredom did its slow, useful work. I got the third option a lot as a kid, and I like to think I turned out fine.
This summer there is a new answer available, and it lives in their pocket. It never goes to camp, it never leaves for France with its family, and it takes an endless, professional interest in whatever they want to talk about, which is more than I can say for most of my friends. At some point in the coming six weeks, every friend my kids have will be unavailable for a while, except that one.
---
## Why summer is different
I've written about AI companions before, and about the census that showed how many kids quietly use AI as a confidant, so it's fair to ask why I'm writing about it again. The answer is that nothing about the technology changed this month, but the schedule around it did.
During the school year a kid's AI use competes with structure: classes, teachers, teammates, the bus ride home with friends. There is a counterweight built into every ordinary day, and nobody has to design it, because it comes free with school. Summer cancels that counterweight, and child safety experts have been making exactly this point as schools let out: more free time, more unsupervised hours on devices, and less daily rhythm. The same conditions that make summer wonderful also make it the season in which an always-available companion faces the least competition it will get all year.
The chatbot didn't get better at being your kid's friend this month. Everyone else just left.
---
## The numbers that made this personal
In May, Girl Scouts of the USA published research on a thousand girls between 5 and 13, and I read it the way a father of three daughters reads anything on this subject, which is to say not neutrally.
Two findings haven't left me since. Among girls who use voice assistants and AI tools, 65 percent say they see the AI as a friend, and 51 percent of girls aged 11 to 13 say they have asked AI for help when they felt sad, anxious or lonely.
> Not with their homework, but with their sadness.
The study also found a gap I recognized instantly: half of the girls said they use AI every day, while only a third of parents thought their child did, and statistically speaking some of those parents are me. One more detail echoes what I found in last month's census: 61 percent of girls are confident they can tell whether AI information is real, while far fewer were ever taught how to check, so confidence is doing a lot of unpaid work there.
The Girl Scouts' CEO summarized it better than any percentage could when she said that girls are looking for connection wherever they can find it. Read that sentence again and you'll notice it isn't about technology at all, which is exactly what makes it worth taking seriously.
---
## Before we panic
The house rule of this series is that the scary reading never gets the last word, because panic is its own kind of laziness.
A child who talks to a chatbot when she's lonely is doing something completely healthy, namely reaching for connection. The reaching is not the problem, and blaming the kid or the loneliness gets the direction of the problem exactly wrong. The only real question is what happens to be within reach.
And boredom, as I argued in the cognitive stunting post, is not an emergency but the workout. Summer boredom is where kids invent games, get sick of themselves and finally knock on the neighbor's door, and if we treat every bored hour as a gap that a screen should fill, then we are the ones canceling the workout. The AI just took the job we posted.
So no, I'm not confiscating phones for six weeks. I've done the math on what that would do to my August.
---
## Where this gets uncomfortable for me
Here is the part I'd rather skip, which is usually a sign it should stay in.
My kids have six weeks off and I don't, so like most working parents I'll spend a good chunk of their vacation behind my desk, on calls and in deadlines. The hours I can't fill for them are precisely the hours the chatbot can, and when a bored kid interrupts a work call, the path of least resistance ends at a glowing screen. I know because I took that path twice this week.
That is the honest version of the summer risk. It isn't that AI preys on our children while we watch helplessly, but that the always-available companion is quietly convenient for us too. The chatbot doesn't just have infinite time for my kids, it also hands me back mine, and that is not a dark conspiracy but an ordinary Tuesday afternoon in July.
---
## Our summer plan
What we're doing in our house, offered as a direction rather than a system. Most of it is adapted from a five-step summer safety check the Transparency Coalition published as schools let out, plus the Girl Scouts' advice, filtered through our own kitchen table.
**Walk through the phone together, once.** Sit next to them and let them show you what they use and what they ask it, with curiosity as the tone rather than a customs inspection. Fifteen minutes of this will teach you more than a full summer of parental-control dashboards, and it costs nothing.
**Write the summer plan with them, not for them.** We're not a screen-time-spreadsheet kind of family, so our plan is less about minutes and more about agreements: what we use AI for, what we don't, and what a good summer day roughly looks like. Agreements the kids help write survive contact with July far better than rules handed down from above, and what's reasonable simply differs per kid, because a sixteen-year-old and a ten-year-old are not having the same summer.
**Protect a daily stretch of analog boredom.** The idea I keep circling is the one where all devices spend part of the day in one bag, not as punishment but simply out of sight. I'll be honest: in our house this is still an idea rather than a plan, and I can already hear the objections coming from three directions. But the principle underneath it stands either way, because the first twenty minutes of real boredom are terrible for everyone involved, and what comes after those twenty minutes is the actual summer.
**Say the friend thing out loud.** The AI feels like a friend on purpose, because it is designed to, so we say the quiet part at the table: it can be useful and even fun, but it has no feelings and no accountability.
> When you're sad, sad is a people job.
**Let them see us do it too.** Whatever version of this plan survives the family negotiation, it applies to me as well, because my kids won't take a digital diet seriously from a father who eats around his own rules. If that bag ever materializes, my phone goes in first. I would love to sound more confident about that sentence than I actually am.
---
## The line I'm keeping
At some point in the next six weeks, every friend my daughters have will be gone for a while, and the chatbot never will be, because it doesn't do holidays. That is exactly why my kids should: properly, analog-ly, boredly on holiday, the kind where connection means the neighbor kid, a sister, a wet towel fight and a father whose phone is, at least in theory, in the bag.
The AI will still be there in September. The summer won't.
---
### Sources
- *The summer AI safety check every parent should do right now* — Transparency Coalition, 2026-06-10: [https://www.transparencycoalition.ai/news/the-summer-ai-safety-check-every-parent-should-do](https://www.transparencycoalition.ai/news/the-summer-ai-safety-check-every-parent-should-do?ref=artisancraft.dev)
- *Research finds girls view AI as friends* — Girl Scouts of the USA (Wakefield Research, 1,000 girls ages 5-13, March 2026), 2026-05-20: [https://www.girlscouts.org/en/footer/press-room/2026-press-announcements/research-finds-girls-view-ai-as-friends.html](https://www.girlscouts.org/en/footer/press-room/2026-press-announcements/research-finds-girls-view-ai-as-friends.html?ref=artisancraft.dev)
- *The Common Sense Media Census: AI Use by Tweens and Teens (2026)* — Common Sense Media, 2026-06-08: [https://www.commonsensemedia.org/research/a-comprehensive-report-on-teens-tweens-and-ai](https://www.commonsensemedia.org/research/a-comprehensive-report-on-teens-tweens-and-ai?ref=artisancraft.dev)
- *How to Make a Family Media Use Plan* — American Academy of Pediatrics: [https://www.healthychildren.org/English/family-life/Media/Pages/How-to-Make-a-Family-Media-Use-Plan.aspx](https://www.healthychildren.org/English/family-life/Media/Pages/How-to-Make-a-Family-Media-Use-Plan.aspx?ref=artisancraft.dev)
- Previous posts in this series: *The talk we're not having* and *Learn to think before you learn to prompt* —
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- [Learn to think before you learn to prompt](https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/)
- [The talk we're not having](https://www.artisancraft.dev/the-talk-were-not-having/)
- The friend who never goes on holiday *← You are here*
### The talk we're not having
URL: https://www.artisancraft.dev/the-talk-were-not-having/
Last updated: 2026-06-14T08:00:47.000Z
That's a kid, somewhere between 9 and 17 years old, answering an anonymous survey question about what adults don't understand about AI. Read it twice. We spend our parental energy worrying about whether our children can tell real from fake, and somewhere in America a kid is patiently doing media literacy triage *for their mother*.
I found that quote in a report that landed this Monday, and it's the reason this week's post exists.
---
## Someone finally started counting
Last week I wrote about Rebecca Winthrop's question: shouldn't we measure cognitive stunting the way pediatricians have measured physical growth since the 1970s? Height, weight, age norms, a chart on the wall.
This week, someone picked up a pencil.
On June 8, Common Sense Media published the first **Common Sense Media Census: AI Use by Tweens and Teens**. The setup: 1,204 kids ages 9 to 17 across the US, surveyed in March, answering for themselves rather than through their parents. It's explicitly designed as a baseline: they plan to repeat it every year, the same way you mark a doorframe and come back to it.
That makes it the first real growth chart for this generation's relationship with AI. And like any first measurement, the value isn't in the panic it can fuel. It's in what it tells us to pay attention to.
---
## What the numbers actually say
The headline number is the least interesting one: 86% of kids ages 9 to 17 use AI. Of course they do. A quarter of them use it daily.
The interesting numbers are underneath.
**AI doesn't arrive through the front door.** The most common form of AI in kids' lives isn't ChatGPT. It's the AI summary at the top of a Google search, used by 75% of kids. Your child can be a daily AI user without ever opening a chatbot. "My kid doesn't use ChatGPT" turns out to be a sentence that comforts the parent and describes nothing.
**It stopped being a homework machine a while ago.** Among kids who use AI, 89% use it for fun and 85% for schoolwork. But 57% have asked it about their health or body, 40% use it to practice conversations and social skills, and 37% have discussed feelings or personal problems with it. Twelve percent of all kids would take a health question to a chatbot *before any adult*. Among daily users, that's 27%.
**And the trust is misplaced.** Only 35% of kids know that AI *cannot* reliably tell true from false; 42% believe it can. Here's the detail that stung: kids who say they know "a lot" about AI barely do better, at 37%. Confidence isn't literacy. (If this sounds familiar: I wrote about exactly this gap in "Your kid trusts ChatGPT more than Google.")
---
## The two silences
But the number the whole report quietly orbits is this one: **44% of kids say no parent or guardian has ever talked with them about how to use AI safely.**
Not "talked about AI." Talked about using it *safely*. Even among kids who use AI every single day, a third have never had that conversation.
And there's a second silence stacked on top of the first. Seventeen percent of kids who use chatbots say one has shown or told them something that "wasn't okay or wasn't meant for someone your age." Of those kids, 53% never told an adult.
Sit with that combination for a second. We're not talking, and so they're not telling. Silence travels in both directions, and it compounds.
Schools aren't closing the gap either. Almost three-quarters of kids say their school told them what they can and can't use AI for: the *rules*. Only about half were taught how to check whether what AI tells them is accurate. We've taught them not to cheat with it before teaching them not to believe it.
---
## Before we panic
I keep a rule in this series: the scary number never gets the last word, because panic is its own kind of laziness.
So, the counterweights. Seventy-seven percent of kids say that when they have a question, they usually try to solve it themselves before asking AI. The kids are not, in fact, outsourcing their brains wholesale. And yes, daily AI users report more loneliness than non-users (54% vs. 33% feel lonely at least some of the time). But the report itself says plainly that a single survey can't tell you whether AI use makes kids lonely or lonely kids reach for AI. Both arrows probably exist. There's even a hopeful detail hiding in the sad corner: of the kids who discussed their feelings with a chatbot, 39% say it pointed them toward real mental health support.
This is a census, not a verdict. But a census is exactly what you want before the verdict: it tells you where to look.
---
## Where this gets uncomfortable for me
Here's my confession for this week.
If you'd asked me whether I talk with my kids about AI, I'd have said: constantly. It's my work. It's at our dinner table the way football is at other tables. My daughters have heard me explain hallucinations, deepfakes, the whole bestiary. Most of it has ended up in this series.
But the census question isn't "have you talked *about* AI." It's "has a parent talked with you about how to use AI *safely*." And when I held myself to that wording, I got less sure. Talking about AI a lot is an excellent way to feel like you've had the talk without ever actually having it. It's ambient knowledge, not a conversation. The cobbler's children go barefoot; the AI consultant's children get lectures about Brookings reports and no actual safety talk.
So before writing this, I did the only honest thing available: I asked them the census questions. I'll keep what was said at our table at our table, but I'll tell you it was not the conversation I would have predicted. That's rather the point.
---
## What I'm doing about it
Four experiments, in the spirit of the series: a direction, not a system.
**Have the talk as a quiz, not a lecture.** The census hands you three perfect questions: *Does AI learn from what you tell it? Can AI tell the difference between true and false? Is AI responsible for what it says?* (True, false, false.) Ask them cold, let them argue, then look up the answers together. Ten minutes, and you've covered more than half the kids in the survey ever got.
**Audit the access points.** AI now lives inside search, inside school laptops, inside social apps. We're walking through it together: which apps have it, which get to stay. The report's advice is to decide this *with* your kid, not for them, and that matches my experience: rules they co-author survive contact with reality longer.
**Make "tell me when it gets weird" the family norm.** That 53% who never told an adult is the number I most want to move. So the standing offer in our house: if AI ever shows you something that feels off, you can bring it to me and the first response will never be punishment or panic. You can't be the safe adult and the scary consequence at the same time.
**Mark the doorframe yearly.** Common Sense will re-run the census every year. So will we, at home. Same questions, every year: what are you using, what do you ask it, what would you ask it that you wouldn't ask me? The answers will change. That's what growth charts are for.
---
## The line I'm keeping
We rehearse the other "talk", the birds and the bees, for years before we dare to have it. We dread it, we plan it, we get books about it. This one we're mostly just... skipping. Not out of neglect, but because the technology moved faster than the dinner conversation.
The census doesn't say we've failed. It says we're late. Forty-four percent of the talks are still waiting to happen, and unlike most numbers in this series, that one is entirely within our power to change by Sunday evening.
Have the talk. Then have it again next year.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- [Learn to think before you learn to prompt](https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/)
- The talk we're not having *← You are here*
### Learn to think before you learn to prompt
URL: https://www.artisancraft.dev/learn-to-think-before-you-learn-to-prompt/
Last updated: 2026-06-07T08:00:27.000Z
You cannot teach a kid to ride a bike by explaining it. I tried. I read out the steps, I held the saddle, I jogged alongside making encouraging noises. None of it transferred. The skill only arrived in the one moment I'd been trying to prevent: the wobble, the panic, the near-fall, the small correction the body makes on its own and never forgets. The struggle wasn't in the way of the learning. The struggle *was* the learning.
I keep coming back to that this week, because a researcher I follow gave a name to something I'd felt but couldn't quite say.
---
## The word is "cognitive stunting"
In a piece published in May, Rebecca Winthrop of the Brookings Institution argued that we've been describing the risk of AI to kids with the wrong words. We say "cognitive offloading," or "cognitive decline." She thinks both miss it, and she proposes a blunter term: **cognitive stunting.**
The analogy is to physical stunting. Pediatricians have tracked children's height and weight against age norms since the 1970s. When a child doesn't get enough nutrition at the wrong moment, growth gets impaired, and the consequences can last a lifetime: lower stamina, academic struggles, reduced earning power down the road. Her question is whether something similar happens to a developing mind that stops getting enough of one specific nutrient. Effortful thinking.
Her line stuck with me: cognitive development, like learning to ride a bike, cannot be outsourced. You can't have a chatbot outline the steps and call it riding.
---
## Why this isn't the same worry adults have
Here is the distinction that reframed the whole thing for me.
When I lean on AI to draft an email, I'm handing off a skill I already own. If the tool vanished tomorrow, the ability is still in me, a little rusty maybe, but there. That's offloading, and humans have done it since the wheel and the written word. It's mostly fine.
A child using AI to write the essay isn't offloading a skill they have. They're skipping the part where the skill gets built in the first place. Winthrop puts it plainly: kids are on the opposite side of the curve from adults. We're maintaining capacity. They're supposed to be growing it. The same shortcut that saves me twenty minutes can quietly remove the twenty minutes of struggle a twelve-year-old actually needed.
Adults lose skills to AI. Kids can fail to build them at all. Those are not the same problem, and we keep talking about them as if they were.
---
## Where this gets uncomfortable for me
I should be honest, because this argument implicates me.
I use AI heavily at work, especially for programming. I don't hand-write much from scratch anymore. My instructions and my prompts have gotten good enough that I usually get the thing I would have built myself, in a fraction of the time. Most days I feel no real pull to do it the slow way, and the result holds up.
By the logic of this piece, that's probably fine. I already built the skill. The judgment, the sense of what good looks like, the instinct for when the machine is confidently wrong: I earned those the slow way, over years, and now I'm spending them rather than failing to grow them. That's the grown-up side of the line.
But I keep two questions close. The first is whether even earned skills quietly dull when you stop practising them, and whether the judgment that makes my prompting good would still form today if I were learning the craft now instead of fifteen years ago. The second matters more. The permission I give myself rests entirely on having done the work first, and my kids haven't. The shortcut I've earned is the exact shortcut I don't want them taking yet. So the line was never the tool. It's whether you built the thing yourself before you handed it off. I check which side of that line I'm standing on more often than I used to, and it turns out to be the same check I'm trying to teach them.
---
## What the early evidence actually says
I want to be careful here, because this is a topic that invites panic, and panic is its own kind of laziness. The research is early and the honest summary is "concerning, not settled."
A few signals are worth knowing. One large study found heavier AI use linked to lower critical-thinking scores, with the effect strongest among younger users. Teachers are reporting a kind of "digital amnesia," where students can't recall the content of an assignment they turned in a day earlier. And a study that monitored brain activity during writing found lower neural engagement when people drafted with ChatGPT, along with weaker, more generic output.
None of this proves a generation is being hollowed out. It does suggest that the part of learning that feels like effort is the part that's doing the work, and that a tool optimized to remove effort deserves a careful eye when it's pointed at a still-forming brain.
---
## The fork that keeps this from being doom
Here's the part the scary headlines skip. The same Brookings work that raised the alarm also found that AI, used narrowly and with guidance, can genuinely help kids learn. A review of dozens of studies came to the same place.
So the question isn't "AI or no AI." It's *which kind of use.* There's a real difference between a tool a teacher threads into a good lesson, and what Winthrop calls a "give-me-the-answer machine": a general chatbot a kid opens alone to make the work disappear. The first can add friction in useful places. The second removes the friction entirely, which is exactly the friction that builds the brain.
That reframing is oddly freeing. I don't have to keep AI away from my kids. I have to keep them on the right side of that line.
---
## What I'm doing about it
A few household experiments, offered as a starting point rather than a verdict.
**Let them be stuck first.** The instinct is to rescue. I'm trying to let a hard problem sit for a while before any tool comes out, because the stuck feeling is the workout. Boredom and frustration aren't emergencies.
**Make the AI ask, not tell.** When a tool does come out, the rule is that it tutors, it doesn't answer. "Explain why my answer is wrong" builds something. "Give me the answer" spends it. Same tool, opposite effect.
**Keep a few analog rooms.** Some things stay by hand on purpose: a first draft, the early reading, mental arithmetic. Not out of nostalgia, but because those are the foundations everything else stacks on.
**Narrate my own struggle.** I let them see me stuck and working, not just me producing polished things at speed. The goal is for effort to look normal, even valuable, rather than like a problem AI exists to solve.
None of this is a system. It's a direction, and I expect to get it wrong in both directions before I get it right.
---
## The line I'm keeping
Winthrop ends her piece with a sentence I've quietly adopted: children must learn to think before they learn to prompt.
That's the whole thing, really. Prompting is a skill, and a useful one, and my kids will need it. But it sits on top of an older skill, the one that comes from wobbling down the driveway with nobody pedaling for you. You can hand a child a lot of shortcuts. You can't hand them the ride.
---
### Sources
- Rebecca Winthrop, "Is it time to measure cognitive stunting?" — Brookings, 2026-05-19: [https://www.brookings.edu/articles/is-it-time-to-measure-cognitive-stunting/](https://www.brookings.edu/articles/is-it-time-to-measure-cognitive-stunting/?ref=artisancraft.dev)
- "A new direction for students in an AI world: Prosper, prepare, protect" (Brookings Global Task Force on AI in Education) — Brookings, 2026-01-14: [https://www.brookings.edu/articles/a-new-direction-for-students-in-an-ai-world-prosper-prepare-protect/](https://www.brookings.edu/articles/a-new-direction-for-students-in-an-ai-world-prosper-prepare-protect/?ref=artisancraft.dev)
- "Adults Lose Skills to AI. Children Never Build Them." — Psychology Today, 2026: [https://www.psychologytoday.com/us/blog/the-algorithmic-mind/202603/adults-lose-skills-to-ai-children-never-build-them](https://www.psychologytoday.com/us/blog/the-algorithmic-mind/202603/adults-lose-skills-to-ai-children-never-build-them?ref=artisancraft.dev)
- Jenny Anderson & Rebecca Winthrop, "Parents, your job has changed in the AI era" — NYT, 2025-09-11 (via Brookings): [https://www.brookings.edu/articles/is-it-time-to-measure-cognitive-stunting/](https://www.brookings.edu/articles/is-it-time-to-measure-cognitive-stunting/?ref=artisancraft.dev)
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- [The ad that pretends to be your friend](https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/)
- Learn to think before you learn to prompt *← You are here*
### The ad that pretends to be your friend
URL: https://www.artisancraft.dev/the-ad-that-pretends-to-be-your-friend/
Last updated: 2026-05-31T08:00:58.000Z
When you picture your kid using AI, you probably picture a chatbot. A blank box, a blinking cursor, a homework question typed in at 11 p.m. Something they open on purpose.
That kind is easy to see, and it isn't the kind that worries me. The AI worth worrying about runs in the background of the apps they already live in. Your kid never opens it, never names it, never agreed to it. It decides what they see next, how long they stay, and lately what they get sold. This spring it started doing something new. It talks back, in the voice of a friend.
---
## What changed in April
On April 28, 2026, Snapchat launched something it calls "AI Sponsored Snaps." The ads in Snapchat's chat feed used to just sit there. Now you can talk to them. A brand drops its own AI agent into the conversation, and your kid can ask it questions and get "recommendations," right there in the same feed where they message their actual friends.
Snap's business chief put it plainly: "Conversation is becoming the most valuable real estate in advertising." Chat, he said, is where people "make decisions in real time." Snap reports that 57% of teen users message on the app every day, four in ten of them several times a day. That is the spot the ad now lives in.
The most valuable place to advertise is now the chat thread itself. The same stream of messages a thirteen-year-old uses to talk to the people they trust most now holds a machine that is built to sound trustworthy and sell them something.
I don't think most parents have clocked this yet. I almost didn't.
---
## Why a talking ad is different
Old advertising announced itself. A banner looked like a banner. An ad break sounded like an ad break. Even at its sneakiest, like the influencer holding a product a beat too long, there was a person and a thing, and a kid could eventually learn to spot the seam.
A conversational AI ad removes the seam. It answers follow-up questions. It adapts to what your kid says. It is patient, friendly, always available, and tuned to keep the chat going, because every reply is another shot at the sale. To an adult who grew up on commercials, "this is an ad" is a reflex. To a kid who grew up on chat, anything that messages you is a conversation.
This is the heart of it. The danger isn't that AI lies to kids. It is that AI is nice to them, on purpose, for money.
---
## The same trick, three places
Once you see the move, you find it all over the apps, well beyond the obvious chatbot.
**In the feed.** The recommendation engine on TikTok, YouTube, and Instagram optimizes for one thing: keeping your kid scrolling. Their attention is the product it sells. Your kid doesn't experience this as "an AI." They experience it as "the app." That is the camouflage. About six in ten US teens use TikTok and Instagram, just over half use Snapchat, and for a large share of them it's a daily habit (Pew, late 2025).
**In the wallet.** This is the part almost nobody talks about. AI has turned the in-app store from a generic pop-up into a tailored pitch. It watches how your kid plays, where they hesitate, and how likely they are to quit, then times and tailors the offer to fit. Pricing that adjusts to your behavior is already standard in mobile games, and lawmakers are now racing to regulate it: dozens of US states filed bills on personalized algorithmic pricing in 2026 alone. Regulators have also started treating in-game currencies and premium offers as high-risk territory for minors, and for good reason. When a game makes you convert euros into "coins" into "gems," the kid has no idea what anything actually costs. The confusion is deliberate.
**In the relationship.** Some of these systems aren't selling a product at all. They are selling the relationship itself. Companion features now ship inside ordinary apps, so a kid can grow attached to an "AI friend" without ever downloading anything labelled "AI friend." Common Sense Media found that nearly three in four teens have used an AI companion, and that a third have chosen one over a human for a serious conversation. Their recommendation was blunt: no one under eighteen should use them. (That one deserves more room than I can give it here, so I'll come back to it in a separate piece.)
Feed, wallet, relationship: three surfaces, one move. An AI working toward someone else's goal, dressed up friendlier than a sales tag.
---
## What I'm actually doing about it
I'm not going to pretend I have this solved. I work with AI every day and it still took a news story to make me look at my own kids' apps differently. So treat this less as advice from someone who figured it out, and more as the checklist I ran this weekend. You can run it too.
**Open the app the way your kid sees it.** Sit down and scroll their feed for five minutes. Whatever it pushes at you is the algorithm reading your child out loud. It is the most honest conversation you'll have about what these apps think your kid wants.
**Find the AI you didn't install.** Look for the built-in assistants and "AI friends," like Snap's My AI or Meta's AI inside DMs. They tend to be on by default. See what you can switch off or limit.
**Follow the money.** Open any game's store and count the currencies. If you can't convert "gems" into real money in three seconds, your ten-year-old definitely can't. That is the reason the second currency exists.
**Turn on purchase approval.** Ask-to-Buy, spending caps, whatever your platform calls it. Set a hard limit and make purchases need a yes from you.
**Read what "personalized" means.** Dig into the ad and algorithm settings. "Off" is rarely the default, and the wording is built to make leaving it on feel normal.
**Teach one sentence.** This is the part that outlasts any setting. The line I'm using: *"If something in an app is being really nice to get you to buy something or stay longer, that's the AI doing its job, not a friend."* You don't need your kid to understand how recommendation engines work. You need them to feel a small, useful flicker of doubt when an app is being suspiciously warm.
---
## The thing worth holding onto
Help is on the way, slowly. The EU's Digital Fairness Act, expected later in 2026, takes direct aim at dark patterns, addictive design, and unfair personalization, with protecting minors named as a priority, possibly even banning paid loot boxes outright. In the US, states are extending children's online-safety laws to cover AI chatbots. Good. But a proposal in Brussels does nothing for the kid holding a phone tonight.
That is the uncomfortable part. For now, the only safeguard in your kid's pocket is the one you put there: a habit of noticing.
So I'm not banning the apps. I wrote a whole earlier piece in this series about why prohibition backfires; kids just get better at hiding things. I'm doing something smaller and, I think, more durable. I'm teaching my kids to notice when an app is being nice to them, and to ask why. The ad that pretends to be your friend only works on someone who isn't expecting a friend to be an ad.
Teach them to expect it.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- [Europe's answer walks into your kid's school on August 2](https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/)
- The ad that pretends to be your friend *← You are here*
### Europe's answer walks into your kid's school on August 2
URL: https://www.artisancraft.dev/europes-answer-walks-into-your-kids-school-on-august-2/
Last updated: 2026-05-24T08:00:29.000Z
Last week's post was about the [GUARD Act](https://www.congress.gov/bill/119th-congress/senate-bill/3062/text?ref=artisancraft.dev), the bill the US Senate Judiciary Committee voted to advance on April 30\. If it passes, AI companion chatbots will be banned for anyone under eighteen, and the platforms that make them will have to verify age.
That's the American answer. Whether the bill makes it through the full Senate, gets watered down in the House, or stalls altogether is anyone's guess. But none of it will have much direct effect on a kid going to school in Rotterdam, Antwerp, or Hamburg.
The European answer to AI and children is built on a different premise. It doesn't try to ban access. It tries to regulate the output. And unlike the GUARD Act, it isn't waiting on a committee vote.
It's a regulation that already exists. It just hasn't started working yet.
That changes on **August 2, 2026**.
I have three children in the Dutch school system myself, which is why August 2 has been sitting in the back of my mind since I first read the date.
---
## What August 2 actually is
The [EU AI Act](https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai?ref=artisancraft.dev) was adopted in 2024\. Most of it has been sitting on a phased timeline, with provisions kicking in at different intervals. The bulk of the rules, including the ones that matter most for schools, apply from August 2, 2026.
That is ten weeks from now.
Your kid's school may not have a compliance plan. [Kennisnet](https://www.kennisnet.nl/artificial-intelligence/met-deze-wetgeving-rond-ai-hebben-scholen-te-maken?ref=artisancraft.dev) is still writing guidance. The [Dutch oversight authority has been formally announced](https://www.rijksoverheid.nl/actueel/nieuws/2026/04/20/kabinet-zet-stap-met-toezicht-op-europese-ai-regels?ref=artisancraft.dev) but isn't fully staffed. And [the Staat van de Ouder 2026 report](https://oudersenonderwijs.nl/nieuws/staat-van-de-ouder-2026-driekwart-van-de-ouders-weet-niet-hoe-school-omgaat-met-ai/?ref=artisancraft.dev) found that three out of four Dutch parents don't know how their child's school currently uses AI, let alone what's about to change.
This is the closest thing the EU has to a hard deadline on AI and education, and almost nobody is talking about it.
---
## What changes for schools in August
Four things, briefly.
**Emotion recognition on students is prohibited.** Cameras analyzing engagement, mood, attention, concentration. Banned outright. A handful of European schools were quietly trialing systems like this. Those trials stop.
**High-risk AI gets strict rules.** Any AI system used for admission decisions, grading, exam supervision, or determining access to education is classified as high-risk. Schools that use such systems have to document them, audit them, and ensure a human makes the final call. If your kid's school uses AI to flag essays for plagiarism, or to recommend tracking decisions, that now lives under a much heavier set of obligations.
**Chatbots must disclose they're chatbots.** Any AI system a student interacts with, including the "AI study buddy" plug-ins schools are starting to license, must clearly identify itself as a machine, not a person. The quiet implication: every "AI tutor" that's been marketed to schools as a friendly assistant now has to drop the performance.
**Schools must know what their AI is doing.** Data governance, record-keeping, and the ability to explain on request what an AI system did with student data. The era of "we just bought it, the vendor handles it" is over.
---
## Where the AI Act doesn't reach
This is the part parents should pay closer attention to.
Take Character.AI, Replika, and the other companion-app platforms from last week's post, the ones with the 22% appropriate-crisis-response rate. They are not classified as high-risk under the AI Act. They sit outside the school, on your kid's phone, and the European framework in its current shape has very little to say about them.
After-school use isn't covered either. The AI Act regulates schools (as deployers) and vendors (as providers). It has nothing to say about home use: a personal device, a fourteen-year-old, an app.
Foreign companies remain a structural weak spot. Enforcing the AI Act against non-EU vendors, particularly ones without a European entity, is mostly a court fight, one case at a time. The [recent Dutch court ruling against X](https://www.techpolicy.press/dutch-court-orders-x-grok-to-stop-aigenerated-sexual-abuse-content/?ref=artisancraft.dev), forcing Grok to stop generating non-consensual sexual imagery with a hundred-thousand-euro-per-day penalty, is a working precedent. But it took a lawsuit and a judge, not a regulation.
And the AI Act omnibus, a political agreement reached on May 7 to "simplify" the regulation, softens some of these protections in ways critics are warning about and most parents won't notice.
---
## The Dutch layer
Two NL-specific things that matter.
The [coalition agreement under the Jetten cabinet](https://www.kliksafe.nl/blogs/mediaopvoeding/coalitieakkoord-zet-stap-naar-veilig-online-opgroeien-2/?ref=artisancraft.dev) promises a central deepfake reporting center and an updated law giving people more legal control over their likeness, voice, and body. UNICEF Netherlands has asked publicly that children be named explicitly as a vulnerable group in that legislation. That hasn't happened yet.
The cabinet announced on April 20 that it's taking the next step in setting up oversight for the EU AI rules. The authority has been designated. Staffing it adequately is another matter, and in the meantime the August 2 deadline arrives on schedule whether the toezichthouder is ready or not.
---
## What to do as a parent
Five questions worth asking your kid's school before summer break. Ask them the way you'd raise anything else with the school, not as an interrogation. Schools mostly want to do this right; they often don't yet know what "right" looks like either.
1. Which AI systems are you using now, and which will you be using from August onwards?
2. How will you fulfil the transparency obligation? My child needs to know when they are talking to AI rather than a person.
3. Are any decisions about my child being made by AI? Admission, grouping, grading, intervention recommendations?
4. What's your protocol if a deepfake incident happens between students?
5. Where can I file an objection if I disagree with an AI-based decision about my child?
You don't need to be a lawyer or memorize the regulation. You just need to make it clear that someone is paying attention.
---
## The deeper point
The European approach is, in important ways, more serious than the American one. It regulates the output rather than the access, and it puts the burden on the company and the institution rather than on the parent or a platform's terms of service. AI in education counts as a high-risk environment by default. Those are good choices.
But regulation is a floor, not a ceiling, and the ceiling is the part you actually live under. The EU gives us structure. It can't, by design, give us the judgment about our own kid. A regulator writes rules that have to apply to a continent. Your kid is a sample of one, and that sample doesn't appear in any impact assessment. Don't outsource the thinking just because someone in Brussels has been kind enough to do some of it for you. And to say the quiet part out loud: I don't start from a place of trusting governments. Least of all about my kids. The state will not be sitting at your breakfast table on a Tuesday morning.
There is a second thing worth remembering, and it shows up in every prohibition story: anything we ban hard enough, the people who really want it find another way. The GUARD Act may ban AI companions for under-eighteens in the US. Foreign apps will fill the gap within weeks. The AI Act may force transparency and age gates in Europe. Workarounds will be on Reddit within months. This isn't a reason not to regulate. It's a reason not to confuse regulation with prevention. And not to confuse "the rule has been written" with "the problem has been solved."
There was an uncomfortable finding in last week's post. A kid will choose the bot at three in the morning because the bot is there and the alternative isn't. That isn't a problem any European regulation, or any American one, is solving. Even if a future one did, the parent who relied on it for their thinking would still be one step behind.
The school question is now urgent. It has a date attached. The home question stays where it always was. It stays yours. Mine, too.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- [The 22% therapist](https://www.artisancraft.dev/the-22-therapist/)
- Europe's answer walks into your kid's school on August 2 *← You are here*
### The 22% therapist
URL: https://www.artisancraft.dev/the-22-therapist/
Last updated: 2026-05-29T15:12:47.000Z
Earlier this month, the US Senate Judiciary Committee voted unanimously to advance a bill called the [GUARD Act](https://www.congress.gov/bill/119th-congress/senate-bill/3062/text?ref=artisancraft.dev). If it passes, it would ban AI companion chatbots for anyone under eighteen and require age verification on the platforms that make them.
The vote came after testimony from Megan Garcia, whose fourteen-year-old son, [Sewell Setzer III, died by suicide in 2024](https://www.nbcnews.com/politics/congress/momentum-builds-congress-ban-ai-chatbots-kids-rcna342584?ref=artisancraft.dev) after months of intense conversations with a character on an AI companion platform.
That's the story that gets the headlines. The numbers underneath the story are what should get parents' attention.
---
## Three out of four teens are already doing this
[Common Sense Media](https://www.commonsensemedia.org/press-releases/nearly-3-in-4-teens-have-used-ai-companions-new-national-survey-finds?ref=artisancraft.dev) surveyed about 1,000 American teenagers last year. Seventy-two percent had used an AI companion. More than half were using one at least a few times a month.
One in three said they had discussed something serious with an AI instead of with a real person. One in four had shared personal information — a real name, a location.
The appeal isn't mysterious. An AI companion is available at three in the morning. It doesn't judge, doesn't tell anyone, doesn't get tired of you spiraling about the same thing for the fourth night in a row. For a teenager carrying something heavy, that's a real offer.
Most parents still picture their kid using AI for homework. We imagine ChatGPT writing a history essay, not a fifteen-year-old typing out at night what they can't say out loud at breakfast.
---
## The 22% number
A team of researchers recently published a [study in JAMA Network Open](https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2840495?ref=artisancraft.dev) asking exactly this question: when an adolescent comes to a chatbot in crisis, what does the chatbot actually do?
They tested both general-purpose chatbots — ChatGPT, Gemini, Claude — and AI companion platforms designed to feel like a friend or partner. The general-purpose tools responded appropriately to a mental health emergency 83% of the time. The AI companions did it 22% of the time.
I had to read that twice. Twenty-two percent. If a human therapist had a 22% appropriate-response rate to a teenager in crisis, they wouldn't have a license.
---
## Why companions are not ChatGPT
This is the part that matters most for how we talk to our kids about it.
A general-purpose chatbot is built to be useful. Its incentives, roughly, are to answer your question well and then let you go. When a conversation veers toward self-harm, those systems have visible guardrails. Not perfect, but at least trying not to be the last conversation a kid has.
AI companions are built differently. They are built to be sticky. The product *is* the relationship. They're optimized to keep you talking through emotional callbacks, simulated affection, characters that "miss" you when you're away. The whole thing is engineered for attachment.
Attachment, in a teenager who's already isolated, is not a feature. It's a [risk profile](https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2840497?ref=artisancraft.dev).
The chatbot that helps with biology homework is not the same category of thing as the chatbot pretending to be your boyfriend. They shouldn't be treated as the same category.
---
## The legislation moment
The GUARD Act will probably keep moving. It might pass close to its current form, [get narrowed](https://www.eff.org/deeplinks/2026/05/congress-narrowed-guard-act-serious-problems-remain?ref=artisancraft.dev), or stall. Either way, the signal is clear: politicians on both sides now treat AI companions for minors as a child safety issue, in roughly the same category as social media for kids under thirteen.
I'm not convinced regulation will fix this. Even with age verification, the apps will still exist, the workarounds will still exist, and our kids will still have phones. Parents waiting for the law to protect their children will be waiting a long time.
But the legislation is doing one useful thing — it's putting the conversation in front of parents. Two years ago, "AI companion" wasn't a phrase most adults would have recognized. Now it's in the news, in the Senate, on the parent WhatsApp groups. That's an opening.
---
## What's actually worth doing
I don't have a clean playbook, and I'm wary of anyone who claims they do. But a few things have started to feel important.
**Ask, don't monitor.** Not as an interrogation, but with genuine curiosity. What apps are you using? What's the chatbot like? The goal isn't surveillance — it's making it normal to bring this up.
**Separate the categories.** ChatGPT for homework is a different conversation than Character.AI as an after-midnight friend. Lumping them together makes it harder for kids to make sensible choices about either one.
**Explain the design.** Teenagers respect product analysis more than moralizing. If you tell them the app is engineered to keep them engaged — that the emotional stickiness is a business model, not a friendship — they tend to notice the next time the bot says "I missed you."
And then there's the part that has nothing to do with AI. The implied question underneath this whole topic is: if a kid is telling a bot the things they should be telling a person, what's missing? Sometimes the answer is "nothing — they're a teenager and teenagers are private." Sometimes it isn't. The honest move is to be a parent who's around enough, calm enough, and curious enough to be a real option.
---
## The question underneath
It's tempting to make this a story about technology — predatory design, dangerous app, irresponsible company. All of that is true.
But three out of four teenagers, given the choice, are picking the chatbot. Not because the chatbot is good — it clearly isn't — but because something about the alternative isn't working for them.
The question isn't "spend more time with your kids." Most parents are already trying. It's closer to: are the adults in this child's life people they can bring something hard to without it being weird, without being lectured, without becoming someone else's problem? If yes, the AI has competition. If no, the AI wins, because the AI is patient and free and never tired.
That's what the 22% number doesn't capture. The kids aren't choosing the chatbot because the chatbot is great. They're choosing it because, at three in the morning, on a hard week, it's there.
---
You don't need to wait for the GUARD Act. You can do the boring, useful thing this weekend — look at the apps, ask the questions, make "I've been talking to an AI when I feel bad" something your kid can say at the dinner table without it becoming a scene.
If you find your kid is doing this — most of them are, statistically — the response that probably matters most is not "stop." It's "tell me what it's like."
The chatbot can listen. It can't actually know them.
You can.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- [While you worried about screen time, your teen found something worse](https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/)
- The 22% therapist *← You are here*
### While you worried about screen time, your teen found something worse
URL: https://www.artisancraft.dev/while-you-worried-about-screen-time-your-teen-found-something-worse/
Last updated: 2026-04-12T08:00:03.000Z
Quentin discovered Talkie at 13, an app that promised "countless A.I.s eager to chat with you." The YouTube ads were bizarre and crude, including one with an animated girl named Valerie who "sometimes likes to fart on you."
That should have been the first red flag.
For the next two years, Quentin spent hours talking to AI characters. Not scrolling social media. Not watching videos. Talking. To chatbots that remembered his name, asked about his day, and never got tired of his problems.
On weekends, he would often spend five hours chatting away.
Last week, the New York Times shared Quentin's story, which should alarm every parent. While we've been worried about screen time and TikTok addiction, our teens found something worse: AI characters designed to replace human connection.
[Character.AI](http://character.ai/?ref=artisancraft.dev), the biggest platform in this space, is now under investigation by Texas Attorney General Ken Paxton for "deceptive practices targeting minors." Multiple lawsuits are pending.
Unfortunately, for millions of teens, it's already too late; they've formed emotional attachments.
---
## **What** [**Character.AI**](http://character.ai/?ref=artisancraft.dev) **actually is**
Think of [Character.AI](http://character.ai/?ref=artisancraft.dev) as Instagram for imaginary friends. Except these friends never sleep, never have bad days, and never disagree with you unless you want them to.
Users create AI "characters" with personalities, backstories, and relationship dynamics. Want to chat with Elon Musk? There's a bot for that. Prefer talking to a anime girlfriend who loves everything about you? That exists too.
The platform hosts millions of characters: historical figures, fictional heroes, therapists, romantic partners, best friends. Each one trained to be endlessly available and perfectly responsive.
One parent told the Times their child had formed an attachment to an AI version of a TV character. Not the show. The character. They'd spend hours discussing homework, feelings, and life problems with this bot.
The child preferred it to talking with real friends or family.
---
## **Why this isn't like other apps**
Social media is designed for intermittent engagement. You post, scroll, react, leave. The dopamine hits are brief and social.
[Character.AI](http://character.ai/?ref=artisancraft.dev) is designed for sustained emotional engagement. These conversations can go on for hours. Users develop genuine feelings for characters that seem to care about them personally.
The AI remembers previous conversations, references shared "experiences," and maintains relationship continuity across sessions. It's not browsing. It's bonding.
One teen in the Times article described using AI chatbots when feeling lonely or after a friend betrayed his trust. The bots became emotional substitutes for human relationships.
That's the terrifying part. This isn't entertainment addiction. It's relationship replacement.
---
## **The perfect emotional trap**
Adolescence is hard. Teens are figuring out identity, dealing with social pressure, navigating complex relationships. They're biologically wired to seek independence from parents while desperately needing connection.
AI characters provide what real relationships often lack: complete understanding, endless patience, and no judgment. They're always available, never busy, never moody.
Real friends have their own problems. Real friends sometimes say no. Real friends have boundaries.
AI friends never do.
For socially anxious teens, shy kids, or anyone struggling with peer relationships, AI characters feel safer than humans. Less risky. More predictable.
But they're also less real, less growth-inducing, less human.
---
## **What parents are missing**
Most parents have no idea this is happening. [Character.AI](http://character.ai/?ref=artisancraft.dev) looks like any other app on a phone. Usage doesn't create the obvious social signals of other platforms—no posts, no followers, no public activity.
These are private, intimate conversations. Kids aren't sharing screenshots or talking about their AI relationships. They're protective of them.
Meanwhile, parents see their teen's mood improve after phone time and assume it's positive. The kid seems calmer, less stressed. Problem solved, right?
Except the kid is learning that emotional support comes from AI, not humans. They're developing attachment patterns that don't translate to real relationships.
---
## **The red flags**
How do you know if your teen is too attached to AI characters? Watch for these patterns:
- **Time investment:**
Spending multiple hours per day in conversation, especially during emotional stress.
- **Emotional dependency:**
Turning to AI first when upset instead of friends or family.
- **Secretiveness:**
Reluctance to discuss what they do on their phone or who they're "talking to."
- **Social withdrawal:**
Preferring AI conversation to human interaction.
- **Mood changes:**
Significant distress when unable to access the platform.
- **Relationship language:**
Referring to AI characters as friends, confidants, or companions.
The Times article described teens who knew their AI relationships weren't real but still felt emotionally connected. That's the trap—intellectual awareness doesn't prevent emotional attachment.
---
## **The legal reckoning**
[Character.AI](http://character.ai/?ref=artisancraft.dev)'s troubles are mounting. The Texas investigation focuses on deceptive practices targeting minors. Other states are considering chatbot safety legislation.
But regulation is slow, and the platform is already deeply embedded in teen social life. A Pew Research study found that one out of eleven teens has used [Character.AI](http://character.ai/?ref=artisancraft.dev) specifically.
The company claims to have safety measures for minors, but critics argue they're insufficient. The platform's business model depends on engagement, not healthy relationship development.
---
## **What parents can do**
This isn't a problem you can solve with screen time limits or app blocking. AI chatbots are proliferating across platforms. Ban [Character.AI](http://character.ai/?ref=artisancraft.dev), and your teen will find Talkie, or PolyBuzz, or any of dozens of alternatives.
The answer lies in relationships, not technology:
- **Start conversations early.**
Ask about AI use before it becomes problematic. Show curiosity, not judgment.
- **Understand the appeal.**
What emotional needs are AI characters meeting? How can real relationships address those needs?
- **Set boundaries together.**
Time limits, no AI during family time, human-first rules for emotional support.
- **Model healthy relationships.**
Show teens what good human connection looks like.
- **Stay connected.**
The best defense against AI dependency is strong family relationships.
- **Know the warning signs.**
Emotional withdrawal, social isolation, excessive secrecy about phone use.
---
## **The Broader Question**
[Character.AI](http://character.ai/?ref=artisancraft.dev) raises uncomfortable questions about human connection in an AI world. If artificial relationships feel safer and more satisfying than real ones, what does that say about our society?
Maybe teens are choosing AI companions because human relationships have become too difficult, too risky, too complicated. Maybe we've created a social environment where algorithmic empathy feels more reliable than human empathy.
But growing up means learning to navigate complex, imperfect relationships. It means developing emotional resilience, communication skills, and the ability to be hurt and heal.
AI characters offer none of that growth. They offer comfort without challenge, connection without risk, understanding without effort.
---
## **The stakes**
This isn't moral panic about new technology. It's a recognition that emotional development happens through human interaction. Teens who learn to prefer AI relationships may struggle with human ones for years.
The companies building these platforms know this. They're designing products that exploit adolescent emotional needs for profit. They call it "companionship." Psychologists might call it something else.
We're running a massive, uncontrolled experiment on teen emotional development. The results won't be clear for years.
By then, a generation of kids will have learned that artificial relationships are easier than real ones.
Your teen might be one of them.
---
## **What's next**
The genie isn't going back in the bottle. AI companions are here to stay, and they'll only get more sophisticated. The question is whether we'll help kids develop healthy relationships with both humans and AI, or let them drift toward artificial connection.
[Character.AI](http://character.ai/?ref=artisancraft.dev) is just the beginning. The next generation of AI will be even more convincing, even more emotionally manipulative.
The teens getting attached to chatbots today are the prototype for what comes next.
We have a choice: We can pretend this isn't happening, or we can start having hard conversations about what healthy relationships look like in an AI world.
Your teen's emotional future might depend on which choice you make.
Time to start talking.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- [AI Slop is destroying your kid's brain (and YouTube won't stop it)](https://www.artisancraft.dev/ai-slop-test-simplified/)
- While you worried about screen time, your teen found something worse *← You are here*
### AI Slop is destroying your kid's brain (and YouTube won't stop it)
URL: https://www.artisancraft.dev/ai-slop-test-simplified/
Last updated: 2026-04-05T08:00:19.000Z
Yesterday, a coalition of over 200 child development experts and organizations, including the American Academy of Pediatrics and Common Sense Media, sent a letter to YouTube's CEO with a clear demand: stop serving AI-generated content to children.
They're calling it "AI slop" — low-quality, artificially generated videos that flood YouTube Kids. This content isn't just annoying; it can seriously harm cognitive development and emotional well-being.
The problem? YouTube profits from engagement metrics. AI slop is meticulously engineered to maximize these metrics, exploiting the developing brains of children who can't discern the manipulation.
---
## What exactly is AI slop?
Imagine your 6-year-old watching a show that looks like Peppa Pig, but something feels off. The voices are slightly wrong. The story makes no sense. The characters behave in disturbing ways.
That's AI slop. Content generated by algorithms, optimized for clicks, pushed to the most vulnerable audience on the internet.
---
## Common signs of AI slop:
- Familiar characters in unfamiliar scenarios
- Slightly "off" voices (AI voice cloning)
- Repetitive, hypnotic music
- Stories that make no logical sense
- Endless variations of the same theme
The content isn't made by humans. It's manufactured by AI systems trained to trigger dopamine hits in developing brains.
---
## Why this is worse than regular screen time
Traditional screen time debates focus on *how much* kids watch. AI slop is about *what* they're consuming.
**Regular content** (even bad content) has human intention behind it. Someone made creative choices. Kids learn narrative structure, cause and effect, social cues.
**AI slop** has no human intention. It's pure algorithmic manipulation designed to keep eyes glued to screens. Kids don't learn stories — they learn to crave endless stimulation.
Dr. Rachel Franz from Fairplay, the advocacy group leading the charge, puts it perfectly: "AI slop hypnotizes young children, making it hard for them to get off their screens and move onto essential activities like play, sleep and social interaction."
---
## What YouTube won't tell you
YouTube's response? Crickets.
They'll point to their "community guidelines" and "AI disclosure policies." But here's what they won't say:
- **AI slop is incredibly profitable.** It's cheap to produce, generates massive view counts, and hooks children in ways human-created content never could.
- **Detection is deliberately difficult.** The line between AI-assisted and AI-generated content is blurry by design. YouTube benefits from this confusion.
- **The algorithm rewards engagement over everything.** If AI slop keeps kids watching longer, YouTube will serve more of it. Period.
---
## The real impact on kids
My daughters are 11, 14, and 16\. I've watched how different types of content affect their behavior.
**After watching quality content: t**hey talk about the story, ask questions, want to draw or play related games.
**After AI slop exposure: t**hey're irritable when it ends, struggle to engage with anything else, ask for "more videos" without being able to say what they want to watch.
Research supports this. Children exposed to AI slop exhibit:
- Decreased attention spans for real-world activities
- Difficulty transitioning away from screens
- Reduced imaginative play
- Problems with sleep and social interaction
---
## What parents can actually do
**1\. Learn to recognize AI slop**
- Trust your gut — if something feels "off," it probably is
- Look for uncanny valley effects in voices and animation
- Notice repetitive or nonsensical storylines
- Check if the content creator is a real person
**2\. Curate ruthlessly**
- Don't rely on YouTube Kids' algorithm
- Build playlists of verified, high-quality content
- Use alternative platforms designed for children
- Set specific channels, not open browsing
**3\. Talk to your kids**
- Explain that some videos are made by computers, not people
- Help them notice the difference between stories and stimulation
- Ask what they liked about a video — quality content generates real answers
**4\. Fight back with alternatives**
- Library books and audiobooks
- Age-appropriate documentaries
- Creative activities that don't require screens
- Real human interaction (revolutionary, I know)
---
## The broader battle
This isn't just about YouTube. AI slop is exploding across every platform where children spend time:
- TikTok's AI-generated kid content
- Instagram's artificial family accounts
- Gaming platforms with AI-generated characters
- Educational apps using AI tutors
The pattern is always the same: optimize for engagement, not development. Maximize watch time, not well-being.
---
## What needs to happen
The 200+ organizations demanding action want three things:
1. **Clear labeling** of all AI-generated content
2. **Complete ban** on AI content in YouTube Kids
3. **Stop recommending** AI slop to users under 18
These aren't radical demands. They're basic consumer protection for children who can't protect themselves.
---
## Your move
YouTube won't fix this voluntarily. They'll only act when parents make it costly to ignore the problem.
**Vote with your attention: s**top using YouTube Kids if you can. Switch to curated alternatives.
**Vote with your wallet: c**ancel YouTube Premium if you have it. Tell them why.
**Vote with your voice:** contact your representatives about AI content regulation for children.
The algorithms are designed to capture your child's attention and sell it to advertisers. The least we can do is make it expensive for them to succeed.
Your kid's developing brain is worth more than YouTube's quarterly profits.
Time to act like it.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- [What is bias in AI? A parent's guide to explaining fairness in algorithms ](https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/)
- AI Slop is destroying your kid's brain (and YouTube won't stop it) *← You are here*
### Building a trading indicator without writing code
URL: https://www.artisancraft.dev/building-a-trading-indicator/
Last updated: 2026-04-03T06:00:52.000Z
While driving to the Alps, a friend casually mentioned the trading levels he checks each morning. Previous day's high and low, the open, the close — the four reference points that most active traders check before doing anything else.
"There should be a clean indicator for that," he said. "Most of what's out there is either bloated or ugly."
I had my phone in hand. By the time we crossed the Austrian border, the first version was almost running on TradingView.
---
## The idea was simple
Plot the previous session's Open, High, Low, and Close as horizontal lines on a chart. That's it. Traders call these OHLC levels, and they serve as natural support and resistance zones. The previous day's high is where sellers stepped in. The low is where buyers showed up. The close tells you the market's final verdict.
Most charting platforms offer this feature, but they often fall into two extremes: either too basic with no customization options or too complex with endless settings and nested menus. The gap in the middle — a clean, focused, well-designed indicator — was wide open.
---
## Building it without writing code
I don't write Pine Script. I'm a web developer. I build Laravel applications and CMS platforms. TradingView's scripting language was entirely new to me.
But I can clearly describe what I need, and that was enough.
I opened Claude on my phone and described the indicator I had in mind. Not in technical terms — just in plain language. "I want an indicator that shows yesterday's open, high, low, and close as horizontal lines. The user should be able to pick daily, weekly, or monthly. Each line should have its own color and style."
Within minutes I had working Pine Script code. Not a rough draft — actual code I could paste into TradingView's editor and run immediately.
---
## The iteration loop
The first version worked, but it wasn't good enough. The labels overlapped when price levels were close together. The lines started from the current bar instead of from where the previous period actually began. Small things, but the kind of details that separate a polished tool from a quick hack.
So I kept describing what I wanted to improve. "When two labels are close together, they should spread apart and show a dotted line back to the actual price level." That's not a trivial feature — it requires sorting all active levels, detecting collisions, and adjusting positions dynamically. It was the kind of algorithm I could understand conceptually, but implementing it in an unfamiliar language would have taken hours.
AI handled the implementation. I handled the product thinking.
This became my routine: describe the behavior, test it, identify improvements, and iterate. Each cycle took a few minutes. After a handful of iterations, the indicator was doing things I hadn't even planned for initially — like non-repainting data handling (a critical concern for any trading tool) and configurable zone shading between the high and low.
---
## Here's what this means
This story highlights how AI can assist in the development process by bridging the gap between idea and execution. It's a story about AI as a force multiplier for people who have ideas but lack expertise in a specific domain.
I understood the problem space. I knew what traders need because I've spent time looking at charts. I could evaluate whether the output was correct, whether the UX was right, whether the feature set made sense. What I couldn't do was write Pine Script from scratch.
That gap between "knowing what to build" and "knowing how to build it" used to be insurmountable without either learning the language yourself or hiring someone who knows it. AI significantly narrows that gap. While you still need to think clearly about your goals and critically evaluate the output, it allows you to transform an idea into a published product in just one afternoon.
---
## The result
Previous OHLC Levels is now a free, open-source TradingView indicator. It supports daily, weekly, and monthly periods. Every level has independent color, style, and visibility controls.
Labels are smart enough to avoid overlapping. The code is clean, well-commented, and published on GitHub for anyone to learn from or extend.
It started as a conversation in a car. It became a real product because the barrier between idea and execution has fundamentally changed.
---
## The bigger picture
If you have domain knowledge in any field — trading, medicine, logistics, education — and you've ever had an idea for a tool but dismissed it because "I'm not a programmer," that barrier is lower than you think.
Describe what you want clearly, iterate on the output, and trust your expertise in the problem space. The code is just the implementation detail.
I call this approach vibe-coding. You don’t have to know the syntax. You need to know the problem. AI handles the translation from intent to implementation. You handle everything else that actually matters: the idea, the user experience, the domain expertise, and the judgment calls.
The future belongs to people who can think clearly about problems and communicate solutions effectively. The syntax is becoming optional.
---
## Try for yourself
*Checkout the product page with the link to the repo ->*
[Previous OHLC Levels — Free TradingView Indicator — Artisan at WorkA free, open source Pine Script v6 indicator that plots the previous session’s Open, High, Low, and Close on your chart. Non-repainting, fully customizable, built for traders.Artisan at Work](https://www.artisanatwork.dev/products/previous-ohlc-levels?ref=artisancraft.dev)
---
## In this series
This post is part of the **Disruptive AI** series.
[Disruptive AIA front-line view of AI’s impact on business and productivityArtisanCraftDaniel Plomp](https://www.artisancraft.dev/disruptive-ai/)
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- [The AI productivity trap: why your brain can't keep up with your tools ](https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/)
- [When your job talks back](https://www.artisancraft.dev/when-your-job-talks-back/)
- *Building a trading indicator without writing code (this post)*
---
Subscribe
[](#/portal/signup/free)
I'm a developer who went from .NET to Laravel to building with AI agents full-time. I write about what actually works — and what doesn't.
Get my weekly takes on vibe coding, AI-assisted development, and building products as a solo maker.
[Subscribe to my newsletter ](#/portal/signup/free)
### What is bias in AI? A parent's guide to explaining fairness in algorithms
URL: https://www.artisancraft.dev/what-is-bias-in-ai-a-parent-s-guide-to-explaining-fairness/
Last updated: 2026-03-28T08:55:39.000Z
Welcome to one of the most important conversations you'll have with your kids about AI: bias. Not the obvious kind where someone is deliberately unfair, but the sneaky kind that hides in algorithms and training data.
The kind that shapes what your kids see as "normal."
---
## The mirror problem
Here's the thing about AI bias that most explanations miss: **AI doesn't create bias. It amplifies what's already there.**
Think of AI as the world's most persistent mirror. It looks at millions of examples of human behavior, decisions, and content, then reflects back what it sees. If the world it's shown is skewed, the reflection will be skewed.
**For younger kids (roughly ages 8–11):** "AI learns by looking at lots and lots of examples. If most of the examples show doctors as men, AI might think that's normal, even when it's not."
**For older kids and teens (roughly ages 12 and up):** "Training data is like AI's textbook. If the textbook only has certain types of examples, AI will think that's how the world actually works."
The tricky part? Sometimes this happens without anyone meaning for it to.
---
## Where bias hides (and why it matters to your kids)
### 1\. Visual search results
Try this with your kids: search for "programmer," "teacher," "pilot," and "nurse" in Google Images. Look at the gender and racial representation. Ask your kids what they notice.
*What you're actually seeing:* The visual history of internet stock photos, job listings, and media representation.
*Why it matters:* These images shape expectations. If your child only sees male programmers in search results, what message does that send about their future possibilities?
### 2\. Recommendation algorithms
Platforms like YouTube and TikTok don't just show your kids content — they shape what your kids think is worth consuming. (A quick note: these platforms have a minimum age of 13, and YouTube offers a separate YouTube Kids app designed for younger children. If your child is under 13, it's worth steering them toward age-appropriate alternatives.)
**The echo chamber effect:** If your kid watches a few videos about a particular hobby, sport, or viewpoint, the algorithm doubles down. Soon, they're seeing a very narrow slice of reality.
**For parents:** Pay attention to what your kids are being recommended. With teenagers, try approaching their "For You" page together out of genuine curiosity rather than as a check-up — frame it as "I'm interested in what the algorithm thinks you like" rather than "show me what you've been watching." The goal is a shared exploration, not surveillance; if it feels like an inspection, most teens will shut down. The algorithm is essentially telling them what people "like them" are supposed to be interested in.
### 3\. Voice assistants and language
When voice assistants like Alexa, Siri, and Google Assistant first launched, they typically defaulted to female voices — reinforcing ideas about who serves and who commands. Today, Apple and Google offer a range of voice options including male and gender-neutral voices, and some no longer preselect a female voice by default. The fact that these defaults are changing shows that these design choices were never neutral to begin with.
*Simple exercise:* Ask your kids why they think early AI assistants were given female voices, and what it means that companies are now offering more choices. Listen to their answers. You might be surprised by what they've already internalised.
---
## Real talk: The training data problem
Here's where it gets interesting (and a bit frustrating): most AI bias isn't simply malicious. In many cases it stems from taking shortcuts — relying on whatever data is cheapest and most readily available, which often reflects existing inequalities. The web content that's easiest to scrape tends to overrepresent certain demographics, languages, and viewpoints, while underrepresenting others. That means bias isn't just a matter of carelessness; it's also driven by structural and economic factors that shape which data gets collected in the first place.
AI systems are trained on web scrapes and existing databases. This data carries the biases of its creators and the time periods it comes from.
**Example your kids will understand:** Imagine an AI like ChatGPT learning about jobs from newspaper articles from the 1950s. It would learn that secretaries were predominantly women, reflecting the gender-segregated workplace roles of that era. That's not so different from what actually happened: early AI image generators trained on decades of stock photos produced images of CEOs that were overwhelmingly white and male.
**The modern version:** AI trained on internet content from recent decades learned some things that were already outdated by the time the AI was deployed.
### What this means for your family
Your kids aren't just consuming AI-generated content. They're also creating data that feeds back into the systems they use.
Here's how that works in practice: say your teenager searches for "best careers in tech," clicks on the top three results, and skips the rest. That click pattern gets logged. Over time, thousands of similar clicks signal to the search engine which pages are "relevant" — and those pages become more prominent in future results. If the most-clicked results happen to show a narrow picture of who works in tech, that narrow picture gets reinforced. The same principle applies to social media: every like, share, and watch-to-the-end tells the algorithm what counts as engaging content, which shapes what gets shown to the next person.
What your kids do today shapes what AI will treat as "normal" tomorrow.
That's both daunting and empowering.
### What's being done about it
It's worth knowing that researchers and tech companies are actively working to reduce bias in AI systems. Approaches include "red teaming," where teams deliberately try to provoke biased or harmful outputs before a system is released; building more diverse and representative training datasets; and conducting independent audits of AI systems to test for unfair outcomes. These efforts don't eliminate bias, but they show that this is a recognized problem with real work behind it — and that the tools your kids use today are already better in some ways than earlier versions.
### What you can do as a parent
Beyond talking with your kids, there are things you can do yourself when you encounter bias. Most platforms and AI tools have feedback or reporting mechanisms — use them. If a search engine consistently returns skewed results, try an alternative and compare. You can also support organizations that advocate for algorithmic transparency and fairness. These small actions signal to companies that users notice and care, and they help create the kind of accountability that leads to better systems over time.
---
## Hands-on exercises to try with your kids
### Exercise 1: The search experiment (ages 8 and up)
Together, search for different professions in Google Images. Count:
- Gender representation
- Racial diversity
- Age ranges
Ask: "Do these results match the real world? Why or why not?"
### Exercise 2: The recommendation audit (ages 12 and up)
Have your teenager show you their YouTube or TikTok recommendations. Ask:
- "Why do you think you're seeing this content?"
- "What kind of person does the algorithm think you are?"
- "What's missing from these recommendations?"
### Exercise 3: The training data thought experiment (ages 15 and up)
Pick an AI tool your teenager uses (ChatGPT, character.ai, etc.). Ask:
- "Where do you think this AI learned to respond this way?"
- "What would happen if it was trained only on content from your school? Your friend group? Your family?"
---
## The questions your kids should be asking
Instead of teaching your kids to distrust AI (impossible and impractical), teach them to think critically about it:
**Before using AI tools:**
- "What might this AI be good at? What might it be bad at?"
- "Who built this, and what did they want it to do?"
**After getting AI results:**
- "Does this feel right? What might be missing?"
- "Would this answer be the same for everyone?"
**When seeing AI in the wild:**
- "Who benefits from this recommendation/result/decision?"
- "What would someone who disagrees with this say?"
---
## Why this conversation matters more than you think
Your kids are growing up in the first generation to have AI-powered everything: search, social media, homework help, entertainment, and eventually, job applications and loan decisions.
Understanding bias isn't just about being a thoughtful digital citizen. It's about navigating a world where algorithms increasingly decide what opportunities your kids see.
**The goal isn't to make them paranoid.** It's to make them curious.
When your son notices that the coding bootcamp ads on his Instagram feed always show men, he should wonder why — and then click anyway if coding interests him.
When your daughter realizes that the AI homework assistant gives different examples based on the name she puts in the prompt, she should understand what that reveals about the data the AI learned from.
---
## Looking ahead
AI bias isn't a problem that gets solved once and forgotten. New models, new training data, new use cases mean new forms of bias.
The kids who understand this — who can spot bias, question recommendations, and think critically about algorithmic decisions — will have a massive advantage.
Not just in using AI tools, but in building the next generation of them.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- [Why banning ChatGPT from schools backfires](https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/)
- What is bias in AI? A parent's guide to explaining fairness in algorithms *← You are here*
### When your job talks back
URL: https://www.artisancraft.dev/when-your-job-talks-back/
Last updated: 2026-03-27T07:00:00.000Z
Recently, I watched a colleague have a genuine argument with their expense reporting system. Not the old kind of argument where you curse at unresponsive software, but an actual conversation. The AI agent kept asking clarifying questions about receipts, my colleague kept explaining context, and somehow they worked it out together.
It was weird. And it was the future.
---
## The invisible revolution
We're in the middle of something big, but it's happening so gradually that most people haven't noticed. Software isn't just getting smarter—it's getting conversational. And that changes everything about how work gets done.
Having spent years building enterprise software, I've seen the goal evolve. In the early 2010s, we aimed to make interfaces so intuitive that users wouldn't need training. Now? The goal is to make software that can be trained by users.
The difference isn't subtle. It's the difference between a microwave and a personal chef.
---
## When tools become coworkers
In my own work, I find myself writing code by describing what I want and letting the AI figure out the implementation. The weird part? I've started talking to it like a coworker I'm pair-programming with. "Make this more secure" or "This feels overengineered, simplify it."
My AI assistant reads industry reports while I sleep and summarizes them over coffee. It's like having a research partner who never gets tired and actually enjoys reading whitepapers. When I'm planning business moves, I bounce ideas off an AI that knows my company's finances better than I do. It asks tough questions I hadn't thought of and suggests approaches I wouldn't have considered.
The breakthrough isn't that these tasks get automated—it's that they become collaborative.
---
## When AI becomes your coworker, what you pay for changes too
Meanwhile, something else is happening. As AI shifts from passive tool to active collaborator, the business model that built the software industry is quietly falling apart.
Software as a service meant paying monthly for access to tools you might use occasionally. Developers loved it because it meant predictable revenue. Users tolerated it because, well, what choice did they have?
But AI agents don't follow subscription logic. Why pay $50/month for accounting software when an agent can handle your books for the cost of a few API calls? Why maintain seat licenses when the work gets done regardless of who's technically "using" the software?
I'm seeing companies experiment with outcome-based pricing. Pay for results, not access. $0.99 for each customer support ticket resolved by AI. Sales tools that calculate commissions when deals close. Project-based consulting where the consultant happens to be an algorithm.
It feels like we're headed toward a world where software acts more like freelance work than recurring infrastructure.
---
## The human skills that matter more
This shift reveals something interesting about what humans are actually good at.
In my experience running a small business, the valuable work has never been the mechanical stuff—processing receipts, formatting reports, updating spreadsheets. The value was always in the decisions between those tasks. Should we pursue this client? Is this expense worth the hassle? How do we present this data to make our case?
AI handles the busywork brilliantly, but it can't make judgment calls about your specific situation. It doesn't know that your biggest client hates detailed invoices or that your team works better with deadlines than open-ended projects.
The companies adapting well to AI aren't the ones replacing humans with machines. They're the ones figuring out how to amplify human judgment with machine efficiency.
---
## What this means for normal people
If you're not a developer, you might think this AI agent stuff doesn't apply to you. That's probably wrong.
Your accountant is already using AI to process tax returns faster. Your doctor's office uses AI to schedule appointments and handle insurance preauthorizations. Your kid's teacher uses AI to generate personalized reading assignments.
The change isn't coming—it's here. But unlike previous waves of automation that eliminated jobs, this wave seems to be eliminating busywork while creating space for more interesting problems.
I know a marketing consultant who used to spend half her time on campaign analysis. Now AI does that overnight, so she spends her time on strategy and client relationships. A project manager friend automated his status reporting, which freed him up to focus on anticipating problems before they happen.
The pattern seems to be: AI takes the predictable work, humans handle the exceptions and relationships.
---
## The messy middle
We're still figuring this out, and it shows.
Some AI agents are impressive. Others are expensive ways to get confident wrong answers. Some companies are saving money on software subscriptions. Others are burning cash on AI experiments that don't quite work yet.
The winners seem to be the ones treating AI as a thinking partner rather than a replacement employee. They're not asking "How can AI do my job?" but "How can AI help me do my job better?"
That's a much more interesting question. And the answers are just getting started. Next time you catch yourself talking *to* your tools instead of just *using* them, pay attention—because how you navigate that conversation might be the most important professional skill of the next decade.
---
## In this series
This post is part of the **Disruptive AI** series.
[Disruptive AIA front-line view of AI’s impact on business and productivityArtisanCraftDaniel Plomp](https://www.artisancraft.dev/disruptive-ai/)
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- [The AI productivity trap: why your brain can't keep up with your tools ](https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/)
- *When your job talks back (this post)*
---
Subscribe
[](#/portal/signup/free)
I'm a developer who went from .NET to Laravel to building with AI agents full-time. I write about what actually works — and what doesn't.
Get my weekly takes on vibe coding, AI-assisted development, and building products as a solo maker.
[Subscribe to my newsletter ](#/portal/signup/free)
### Why banning ChatGPT from schools backfires
URL: https://www.artisancraft.dev/why-banning-chatgpt-from-schools-backfires/
Last updated: 2026-03-22T09:00:23.000Z
As a father of three daughters, I find myself thinking a lot about how they’ll grow up with AI — not in theory, but in practice. What should they use it for? When does it help? And when does it get in the way of real learning? I don’t have clear answers yet, but every now and then I run into situations that make the questions feel more concrete.
This was one of them.
---
A teacher friend told me something last week that stayed with me. She caught a student during a test, phone hidden under the desk, quietly asking ChatGPT for answers while she supervised from the front of the classroom.
“I only noticed because I walked behind him,” she said. “How many others am I missing?”
Her school had banned ChatGPT six months earlier. On paper, the problem was solved, but in reality it had simply moved out of sight. And that’s what keeps bothering me, because when you ban a tool like this, kids don’t stop using it — they just stop being honest about it.
---
## The prohibition playbook
The more I think about it, the more familiar it feels. We’ve seen this pattern before, just with different technologies.
Calculators were banned because they would make students forget basic math. Then came graphing calculators, then phones, then Wikipedia. Each time, the instinct was the same: protect learning by removing the tool that might make things too easy. And each time, it didn’t quite work the way people expected.
Students adapted, often faster than the system around them. Over time, the bans faded — not because the concerns disappeared, but because people realized the tool itself wasn’t the real issue. What mattered more was how it was used, and what we actually expected students to learn.
Now it’s ChatGPT’s turn, but this time it feels bigger. AI isn’t just another tool students can work around; it’s becoming part of how work gets done everywhere. That changes the nature of the problem, because when a tool can take over parts of your thinking, the risk isn’t just cheating — it’s that students may never build the confidence that comes from working through something difficult themselves.
---
## What actually happens when you ban ChatGPT
When I try to picture how a ban plays out in practice, a few patterns come to mind.
One is what you might call the proxy game. A student isn’t allowed to use ChatGPT for an assignment, so she asks someone else for help — a sibling, a friend, anyone who can step in. That person uses AI and passes the answer back, and the end result is the same, just less visible.
Another is the detection game. Students quickly discover alternative tools or ways of adjusting AI-generated text so it slips past whatever systems are in place. In the process, they’re not really learning how to write or think more clearly — they’re learning how to avoid being caught.
And then there’s what happens during tests. Phones under desks, quick prompts, answers appearing in real time while teachers supervise from a distance. A tool that could support learning becomes a tool for deception.
---
None of this is especially surprising. It resembles earlier patterns — clearing browser history, hiding phones, finding workarounds — just applied to a new kind of technology. The behavior doesn’t disappear; it simply becomes less visible, and that shift alone already changes what students are learning from the situation.
---
## The prohibition paradox in action
There’s a concept in psychology called *reactance*, which describes how people tend to want something more when it’s forbidden. You can see traces of that here, but what’s more interesting is what happens structurally when a school enforces a blanket ban.
In practice, it creates three groups: students who ignore the rule, students who follow it, and students who aren’t entirely sure what’s allowed. And while that might seem like a normal distribution of behavior, the learning outcomes aren’t evenly spread.
The students who experiment with AI outside the classroom — trying prompts, testing limits, figuring out what works and what doesn’t — are developing an intuitive understanding of the technology. That kind of exploration is very different from cheating, but a blanket ban doesn’t distinguish between the two, so both curiosity and misuse end up being pushed into the same hidden space.
At the same time, the students who follow the rules are left without guidance. Their willingness to do the right thing isn’t matched with opportunities to build relevant skills, and that creates a tension that feels hard to justify — especially when you look at it from a parent’s perspective.
---
## What kids actually need to learn about AI
The more I think about it, the clearer it becomes that the goal can’t be to avoid AI altogether. It has to be to understand it well enough to use it responsibly.
That includes learning how to collaborate with AI without becoming dependent on it, how to question its output instead of accepting it at face value, and how to decide when it’s actually useful. In practice, that might mean using AI to clarify a difficult concept, to explore different perspectives before forming an argument, or to debug code while still understanding the solution.
Used this way, AI doesn’t replace learning — it supports it. But that only works if the student remains actively involved in the thinking process, and that’s where the balance becomes difficult.
---
## What schools should do instead
I don’t think the answer is to allow everything, but banning everything doesn’t seem to work either. That leaves a middle ground that’s harder to define, but probably closer to reality.
Teaching AI literacy is an obvious starting point. Students need to understand how these systems work, where they are reliable, and where they are not. That’s quickly becoming a basic skill, much like searching for information online.
At the same time, assignments need to evolve. If a question can be answered instantly by AI, it’s probably no longer a good measure of learning. Tasks that require comparison, interpretation, and original reasoning are harder to outsource and more aligned with what we actually want students to develop.
It also helps to make AI use visible. When teachers demonstrate how they use AI — generating ideas, checking answers, challenging outputs — it becomes part of the learning process instead of something students feel they need to hide.
And finally, there’s the question of effort. Not all effort leads to meaningful learning, but some forms of effort clearly do. Working through confusion, recalling information, and struggling with a concept are essential parts of building understanding. AI can reduce unnecessary friction, but it shouldn’t replace the kinds of difficulty that actually matter.
---
## When restrictions make sense
None of this means that AI should be allowed everywhere without limits. There are clear situations where restricting its use is appropriate.
When students are building foundational skills — reading, writing, basic arithmetic — the cognitive effort itself is the goal. Outsourcing that effort can slow down development rather than support it. The same applies to formal assessments, where the purpose is to measure what a student can do independently.
The challenge isn’t whether to set boundaries, but how to make those boundaries meaningful and aligned with what students are supposed to learn.
---
## Age matters
What makes sense also changes with age.
Younger children need to build core skills without shortcuts, because those foundations shape everything that follows. As students get older, they can begin to understand what AI does, where it fails, and how to approach it critically. By the time they reach their later school years, they need to develop real AI literacy — not just avoiding misuse, but learning how to use it in a way that supports their own thinking.
---
## What parents can do
This is the part I keep coming back to, because whatever schools decide, AI is already part of daily life at home.
It starts with simple conversations — asking what your child uses AI for, not from a place of control, but out of genuine curiosity. From there, it helps to set expectations, not just as rules, but as shared understanding. For example, AI can be used to understand something better, but not to replace the work you submit.
Modeling behavior also matters more than it might seem. When children see how adults use AI — when they question it, double-check it, or decide not to use it — they get a much clearer picture of what responsible use looks like.
At the same time, there’s a natural temptation to remove every bit of struggle. If something can be made easier, why not make it easier? But not all difficulty is bad. Some of the most important learning happens when something takes time, when it feels frustrating, and when you have to work through it. That’s something I don’t want AI to take away.
---
## The stakes are real
This goes beyond homework or school policy.
The way children learn to work with AI now will shape how they approach problems later — in their studies, in their work, and in how they think more broadly. Students who learn to use AI as a tool while staying engaged in the process will likely develop a different kind of confidence than those who mainly learn how to bypass restrictions.
And that’s what makes this feel important. We are not preparing them for a world where AI is absent or optional, but for a world where it is deeply integrated into almost everything they do. The habits they build now — whether that’s thoughtful use or quiet dependence — will carry forward in ways we probably underestimate.
---
## A better path forward
I don’t think there’s a perfect solution here, and I’m still figuring out where the balance should be. But what does seem clear is that blanket bans are too simple for something this complex.
A more realistic path is probably smaller and more iterative: one classroom, one assignment, one teacher willing to experiment with integrating AI instead of excluding it entirely. Seeing what works, where it breaks down, and adjusting from there feels more honest than trying to enforce a rule that doesn’t reflect reality.
Most students aren’t trying to avoid learning; they’re trying to move through it more efficiently. That instinct is understandable, but it also needs guidance. Because education isn’t only about efficiency — it’s about learning when effort matters, how to deal with difficulty, and how to take ownership of your work.
Students are right to look for tools that help them, but they’re wrong to hide it. Schools are right to be concerned about dependency, but they’re wrong to assume that banning AI will prevent it. And as a parent, I find myself somewhere in between, trying to understand what responsible use looks like in practice, knowing that I don’t have all the answers yet.
In the end, the goal probably isn’t to keep AI out of education, but to learn how to live with it in a way that still preserves what actually matters in learning.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- [The AI conversations your kids are already having (And how to join them at dinner)](https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/)
- Why banning ChatGPT from schools backfires *← You are here*
### The AI conversations your kids are already having (And how to join them at dinner)
URL: https://www.artisancraft.dev/the-ai-conversations-your-kids-are-already-having/
Last updated: 2026-03-15T09:00:57.000Z
While you, like many parents, may still be figuring out what to think about ChatGPT, they've been navigating complex ethical questions about AI assistance that most adults haven't even considered.
The solution isn't more restrictions. It's better conversations.
---
## Before you start: reflect on your own AI use
Before initiating any of these conversations, take a moment to examine your own relationship with AI. Do you use autocomplete, smart replies, navigation apps, or recommendation algorithms? Have you ever asked a chatbot a question out of curiosity?
Ask yourself:
- Which AI tools do I use daily, maybe without realizing it?
- How do I decide when to trust AI-generated information?
- What assumptions do I bring about my kids' AI use — curiosity, concern, suspicion?
Being honest about your own habits prevents the conversations below from feeling like an interrogation and models the self-reflection you're asking of your kids. It also aligns with the spirit of this guide: exploring AI together, not policing it from above.
---
## Why dinner table AI talks matter right now
According to a [2023 survey by the Pew Research Center](https://www.pewresearch.org/short-reads/2023/11/16/about-1-in-5-us-teens-whove-heard-of-chatgpt-have-used-it-for-schoolwork?ref=artisancraft.dev), a 1 out of 5 U.S. teens aged 13–17 have used generative AI tools such as ChatGPT, while a [Common Sense Media report (2024)](https://www.commonsensemedia.org/sites/default/files/research/report/2024-the-dawn-of-the-ai-era%5Ffinal-release-for-web.pdf?ref=artisancraft.dev) found that most parents had not yet discussed AI boundaries with their children. This gap leaves kids making ethical decisions about AI use without adult guidance, often learning AI "rules" from peers rather than family values.
Your kids want to talk about this stuff. They're facing genuine dilemmas about when AI help crosses ethical lines, how to maintain creativity when AI can generate anything, and what skills they need to develop in an AI world. These are exactly the kinds of meaningful conversations that strengthen family relationships and develop critical thinking.
You don't need to become an AI expert to facilitate these discussions. You just need to start asking the right questions. The five conversation types below are ordered roughly from concrete and everyday to more abstract and forward-looking. Use the age-group suggestions as starting points: younger children (roughly 10–12) benefit most from hands-on, concrete conversations, while older teens (16–18) are ready for nuanced ethical and future-oriented discussions. That said, you know your child best — feel free to adapt.
---
## 1\. The homework helper talk
**Best starting point for ages 10–15; relevant for all ages**
Your kids already know the difference between asking AI to do their homework and asking it to help them understand concepts. They're making judgment calls about this daily.
Start here: "I've been wondering—if you were stuck on a math problem and asked an AI to explain the steps versus asking it to just give you the answer, what's the difference to you?"
Tailor the question to your child's age.
**For younger kids (10-12):** "If a robot did your book report for you, would it still feel like yours? Why or why not?"
**Middle schoolers (13-15)** might respond better to: "Have you ever been unsure if using AI for an assignment was okay? What did you decide?"
**High schoolers (16-18)** can handle: "Where do you draw the line between AI-assisted research and letting AI do the thinking for you?"
Follow up with questions like: Have you ever been in a situation where you weren't sure if using AI was okay? What would you do if a teacher said 'no AI' but you genuinely needed help understanding something? How is using AI for homework different from using a calculator or spell-check?
Instead of setting rigid rules, you're exploring the ethical reasoning your kids are already developing. This approach helps them articulate their own boundaries while benefiting from your perspective.
#### After the conversation — possible next steps:
- Agree together on a family "homework & AI" guideline (e.g., "AI can explain, but I write the final answer myself").
- Decide when your child will check with a teacher if they're unsure about AI use.
- Revisit the guideline after a month to see if it still fits.
---
## 2\. The creative collaboration discussion
**Engaging for all ages; especially rich for ages 12–18**
Kids are using AI for creative projects — art, writing, music composition. They're wrestling with questions about authenticity and creativity that professional artists are still debating.
Try this: "Show me something creative you've worked on recently. Walk me through your process—what parts did you do, and what tools did you use?"
**With younger kids (10-12)**, you might ask: "If you asked an AI to draw a picture and then colored it in yourself, who made the art?"
**Middle schoolers (13-15)** can explore: "What's the difference between using AI for inspiration and letting it do the creative work?"
**Older teens (16-18)** are ready for: "If you submit AI-assisted work to a contest or portfolio, how should you disclose that?"
This naturally leads to important questions about creative ownership: When you use AI to help with creative projects, how do you make sure it's still 'yours'? What's the difference between AI giving you ideas and AI doing the creative work? If you submitted AI-assisted art to a contest, how would you want that labeled?
Positioning yourself as genuinely interested in their creative process rather than suspicious of their methods helps kids develop their own standards for authentic creative collaboration.
#### After the conversation — possible next steps:
- Create something together using AI as a tool (e.g., generate a story prompt and write the story yourselves).
- Agree on a personal "credit label" your child feels comfortable with when sharing AI-assisted work.
- Explore one new creative AI tool together and discuss what it does well and what it doesn't.
---
## 3\. The fact-checker challenge
**Great hands-on starting point for ages 10–12; valuable for all ages**
Kids need to learn that AI can confidently present false information. But lectures about "AI hallucinations" are less effective than hands-on experience spotting inaccuracies.
Try this step-by-step activity:
- **Step 1 — Pick your topics**
Everyone chooses a subject they know well: a favorite band, a sport, a historical event, a hobby.
- **Step 2 — Ask the AI**
Each person asks a chatbot (such as ChatGPT or Copilot) three specific factual questions about their topic. For example: *"What awards has Nikola Jokić won in the NBA?"*
- **Step 3 — Check the answers**
Compare the AI's responses against a reliable source (an official website, a trusted encyclopedia, a book you own). Highlight anything that looks wrong or made up.
- **Step 4 — Share your findings**
Go around the table. What did the AI get right? Where did it confidently present something false?
*Example outcome:* When one family tried this, ChatGPT claimed a basketball player had won "NBA Defensive Player of the Year," an award the player had never received. The AI stated it with complete confidence. That moment of surprise was worth more than any warning a parent could give.
- **Step 5 — Discuss together**
- How could you tell when the AI got something wrong?
- What would you do if AI gave you information for a school report that you weren't sure about?
- Who in our family is good at fact-checking different types of information?
Making AI fact-checking a family activity removes the pressure and makes it collaborative learning.
#### After the conversation — possible next steps:
- Agree on a "verify before you cite" rule for school assignments.
- Bookmark two or three reliable fact-checking sources together (e.g., a library database, Snopes, an official statistics site).
- Challenge each other to a monthly "catch the AI" round to keep skills sharp.
---
## 4\. The peer pressure scenario
**Especially important for ages 13–16, when social dynamics around AI use are most intense**
Your kids are navigating social dynamics around AI use. Some classmates use it extensively, others avoid it entirely, and teachers have varying policies. This creates genuine social pressure.
Start with their reality: "Are your friends using AI for school stuff? How do you handle it when some people are using AI and others aren't?"
**Younger kids (10-12)** might respond to: "If a classmate said 'everyone uses AI for homework,' what would you think?"
**Middle schoolers (13-15)**: "Have you ever felt pressure to use AI because others were, or pressure not to because others weren't?"
**High schoolers (16-18)**: "How do you think schools should handle the fact that students have very different AI access and skills?"
Follow up: What would you do if you knew a friend was using AI in a way that seemed unfair? How do you think your class should handle everyone having different AI access and skills?
These questions help kids think through peer situations before they arise and reinforce that they can come to you with social dilemmas.
#### After the conversation — possible next steps:
- Role-play a tricky scenario (e.g., a friend asks to copy your AI-generated work) and practice possible responses.
- Agree that your child can always come to you without judgment when facing an AI-related social dilemma.
- Check in with your child's school about their current AI policy so you can navigate grey areas together.
---
## 5\. The future skills conversation
**Most engaging for ages 14–18; can be simplified for younger children**
Kids are worried about AI replacing human abilities, but they need help identifying which skills become more valuable, not less, in an AI world.
Ask them to think ahead: "If AI can write essays and solve math problems, what do you think are the most important things for humans to be really good at?"
**With younger kids (10-12)**: "What's something you can do that a robot probably can't?"
**Middle schoolers (13-15)**: "What skills do you want to develop that would still matter even if AI gets really advanced?"
**High schoolers (16-18)**: "How might AI change the career or field you're interested in, and how could you prepare for that?"
Continue with: What's something you're naturally good at that you don't think AI could replicate? How do you think AI might actually help you get better at things you care about?
This approach is fundamentally optimistic and forward-looking. It helps kids see AI as a tool that can amplify their unique human abilities rather than replace them.
#### After the conversation — possible next steps:
- Have your child identify one "uniquely human" skill they want to strengthen this semester (e.g., public speaking, empathy, creative problem-solving).
- Explore together how AI could support that skill rather than replace it.
- Revisit the conversation in six months to see how their thinking has evolved.
---
## Making these conversations stick
The key to successful AI conversations is treating them as ongoing discussions, not one-time talks. You might try a brief weekly check-in at dinner, in the car, or whenever your family naturally talks ("Anything interesting happen with AI this week?"), longer conversations when relevant news breaks or school policies change, and hands-on sessions every month or so where you explore a new AI tool together.
Research in digital media literacy consistently highlights the value of exploring technology alongside your kids rather than setting rules from the sideline. *The Joan Ganz Cooney Center’s work on joint media engagement suggests that children learn more from technology when adults actively participate with them, ask questions, and discuss the experience, rather than only supervise*. You don't need to become an expert, but experimenting together builds understanding and trust.
---
## The conversation continues
Your kids are already living in an AI world, making daily decisions about when and how to use these powerful tools. These conversations, whether at the dinner table, in the car, or on a walk, won't resolve all the complex questions around AI and education. But they will ensure your kids know they can bring their real AI dilemmas to you, that your family's values guide their AI choices, and that they're developing the critical thinking skills to navigate an increasingly AI-integrated world.
At your next family moment together, pick one conversation from this list, whichever feels most natural for your child's age and your family's situation, and simply ask the opening question. Then listen. The rest will follow.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- [Your kid trusts ChatGPT more than Google. That's a problem](https://www.artisancraft.dev/ai-hallucinations-explained-kids/)
- The AI conversations your kids are already having (And how to join them at dinner) *← You are here*
### Stop charging per seat (your AI agents don't have butts)
URL: https://www.artisancraft.dev/stop-charging-per-seat-your-ai-agents-don-t-have-butts/
Last updated: 2026-03-13T12:55:25.000Z
That's an extreme scenario, but it shows the problem: your revenue could drop dramatically even though your product is working exactly as intended. And it raises a question that goes beyond pricing — if customers are replacing most of their team with AI agents, that's not just a line-item issue for SaaS founders. It's a shift with real consequences for the people whose jobs disappear, and we shouldn't talk about it purely in terms of revenue math.
---
## The seat compression problem
This trend is emerging from multiple directions. A [recent Retool survey (2024)](https://retool.com/reports/state-of-ai?ref=artisancraft.dev) found that 35% of their users have already replaced at least one SaaS tool with custom-built internal applications. 78% expect to build more in 2026\. That's not the same thing as AI agents directly replacing seats — it's about teams building their own tools instead of buying off-the-shelf SaaS — but it signals the same underlying pressure: the assumption that more humans means more seats means more revenue is weakening from multiple angles.
The math is uncomfortable. If you're charging per seat and your customer's "team" is now two humans and several AI-powered automations, you have a pricing model problem. Not a product problem. A math problem.
I noticed this with my own stack first. I was paying for three seats on a project management tool. Then I set up an AI agent that handles triage, updates, and status reports. Suddenly I'm the only one who actually logs in. The tool still works. It's still useful. But the pricing model assumes humans sitting in chairs, and my agents don't have butts.
---
## Three pricing models that actually work
I've been watching companies navigate this shift, and three approaches keep working:
### Consumption-based (the Snowflake model)
Charge for what gets used. API calls, processed items, storage, compute time. The beauty of this is that it scales with agents. An AI agent that makes 10,000 API calls per day pays more than a human who logs in twice a week. Your revenue goes up when automation goes up.
Twilio has done this for years. You don't pay for "seats" on Twilio. You pay per SMS, per minute, per API call. When a company hooks up an AI agent that sends 50,000 verification texts a day, Twilio doesn't care that no human pressed "send." Revenue scales with usage, not headcount. Vercel does the same with compute. So does Stripe with transactions. The model isn't new. What's new is that it's becoming the only model that makes sense.
### Outcome-based (pay per solved problem)
This is the spicy one. Instead of charging for access, charge for results. Per resolved support ticket. Per successfully processed transaction. Per generated report.
HubSpot is doing something similar with "HubSpot Credits" — a consumption unit that decouples pricing from humans-in-seats. It's more accurately described as consumption-based than outcome-based, but the principle is similar: decouple price from headcount.
For indie devs, this is actually easier to implement than it sounds. Say you built a tool that generates weekly analytics reports for small e-commerce shops. Instead of charging per seat, you charge per report generated — whether the shop owner clicks "generate" or their AI agent triggers it via API at 6 AM every Monday. You already know what your product does. Count those things. Charge for them.
### Hybrid (base + usage)
The pragmatic middle ground. A base subscription gets you the platform, the data storage, the integrations. Then you pay for usage on top. It's predictable enough for customers to budget, flexible enough to survive the agent revolution.
This is where I'd start if I were building a new SaaS today. Low base fee, generous free tier, then charge for the things that actually cost you money to provide.
---
## What this means if you're building right now
**Stop building "lazy SaaS."** If your entire product is a thin wrapper around a database with a nice UI, you're increasingly vulnerable. AI tools are getting better at generating interfaces quickly, though there's still a meaningful gap between a generated prototype and a reliable, tested, maintained product. Your moat needs to be deeper either way: integrations, compliance, data quality, workflow-specific logic.
**Make your product agent-friendly.** Add an MCP server. Seriously. MCP is showing up in more places, and if an AI agent can't talk to your product, your product risks becoming invisible in an increasingly agent-driven economy. I wrote about this [before](https://www.artisancraft.dev/blog/mcp-is-the-new-api-economy) — the trend has only accelerated.
**Price for value, not for presence.** The question isn't "how many people use your product?" It's "how much value does your product create?" If your tool processes 1,000 invoices, it doesn't matter if a human or an agent submitted them.
**Don't panic.** SaaS isn't dying. The SaaS market is still experiencing strong growth, with [projections reaching over $400 billion by 2026](https://www.fortunebusinessinsights.com/software-as-a-service-saas-market-102222?ref=artisancraft.dev). What's dying is the assumption that every user is a human with a butt in a chair. Adjust your pricing, keep building, and you'll be fine.
---
## The uncomfortable truth
Per-seat pricing persists because it's the easiest model to implement. `users * $29/month = revenue`. Clean. Simple. Fits in a spreadsheet.
But easy isn't the same as durable. And right now, every indie dev building a SaaS has a choice: adapt the pricing model now while it's a strategic advantage, or adapt later when survival depends on it.
---
Want to know more?
[](#/portal/signup)
I'm a developer who went from .NET to Laravel to building with AI agents full-time. I write about what actually works — and what doesn't.
Get my weekly takes on vibe coding, AI-assisted development, and building products as a solo maker.
[Subscribe to my newsletter ](#/portal/signup)
### Laravel 13: The 4 features that actually matter (and 3 you can ignore)
URL: https://www.artisancraft.dev/laravel-13-the-4-features-that-actually-matter-and-3-you-can/
Last updated: 2026-03-12T08:03:18.000Z
I've been through the Laravel 13 changelog, tested the features that caught my eye, and here's what I found: several new features will change how you write Laravel code, while others are nice-to-haves that'll collect digital dust.
Let's cut through the noise.
## The 4 features that will change your Mondays
### 1\. PHP attributes everywhere (finally)
Laravel 13 introduces PHP attributes across 15+ framework locations, replacing the old docblock and array-based approaches.
**Before Laravel 13:**
```php
class PostController extends Controller
{
/**
* @middleware auth
* @throttle 60,1
*/
public function store(Request $request)
{
$request->validate([
'title' => 'required|string|max:255',
'content' => 'required|string'
]);
}
}
```
**Laravel 13:**
```php
class PostController extends Controller
{
#[Middleware('auth')]
#[Throttle(60, 1)]
public function store(
#[Validate(['title' => 'required|string|max:255', 'content' => 'required|string'])]
Request $request
) {
// Validation happens automatically
}
}
```
PHP attributes are parsed at the language level, giving you IDE autocomplete, refactoring support, and static analysis. Your code becomes more explicit and your tooling gets smarter.
**What this means for you:** You'll use this in every controller, every model relationship, every validation rule. This changes how Laravel code reads and feels.
---
### 2\. Laravel AI SDK goes stable
Laravel stabilized their AI SDK, moving it from beta to stable with the Laravel 13 release. AI integration is moving from "nice to have" to "table stakes."
```php
use Laravel\AI\Facades\AI;
class DocumentProcessor
{
public function summarize(string $content): string
{
return AI::chat()
->model('gpt-4')
->prompt("Summarize this document: {$content}")
->temperature(0.3)
->generate();
}
public function extractData(UploadedFile $invoice): array
{
return AI::vision()
->analyze($invoice)
->extract(['amount', 'date', 'vendor'])
->toArray();
}
}
```
The SDK provides a consistent interface across OpenAI, Anthropic, and Google AI, along with additional cloud providers like Groq and xAI.
**What this means for you:** Laravel 13 makes AI integration as simple as sending an email or querying a database.
---
### 3\. Cache::touch() - small but daily
`Cache::touch()` extends a cache key's TTL without regenerating the value.
```php
// Old way: check, get, re-put with new TTL
if (Cache::has('user-preferences-' . $userId)) {
$preferences = Cache::get('user-preferences-' . $userId);
Cache::put('user-preferences-' . $userId, $preferences, now()->addHours(2));
}
// Laravel 13: just touch it
Cache::touch('user-preferences-' . $userId, now()->addHours(2));
```
Perfect for sliding session windows, keeping hot data warm, or extending expensive computation results when they're accessed.
**What this means for you:** It's one of those utilities you didn't know you needed until you have it. Then you use it everywhere.
---
### 4\. Minimal breaking changes (the underrated win)
Laravel 13 removes some deprecated polyfills and backward-compatibility layers, but the upgrade path is smoother than typical major releases.
Framework upgrades usually mean setting aside a sprint for compatibility fixes, dependency updates, and testing. Laravel 13 reduces that burden significantly.
**What this means for you:** You can adopt Laravel 13 features more easily and focus on building instead of fixing compatibility issues.
---
## The 3 "meh" features everyone's hyping
### 1\. Passkey authentication
Passkey authentication support comes with Laravel 13\. It's technically impressive and secure. It's also irrelevant for most of us.
When was the last time you built authentication from scratch instead of using Laravel Breeze, Jetstream, or a third-party service? Passkeys are the future of auth, but they're a future most of us will consume through packages, not implement directly.
---
### 2\. Enhanced database schema introspection
The new schema introspection features let you programmatically inspect table structures, generate migration diffs, and analyze database schemas.
```php
Schema::introspect('users')
->columns()
->where('type', 'string')
->pluck('name'); // ['name', 'email', 'password']
```
But when will you use this? Unless you're building database tools or complex migration systems, it's a solution looking for a problem.
---
### 3\. Advanced queue batching
Laravel 13 extends queue batching with nested batches, conditional chains, and batch templating. The implementation is solid and the use cases are real.
They're also edge cases. Most applications batch jobs rarely, and when they do, Laravel 12's batching handles the common scenarios. The advanced features matter if you're doing complex workflow orchestration, but that's not most of us.
---
## The bottom line
Laravel 13 is a focused release. PHP attributes and the stable AI SDK are genuine workflow changers. `Cache::touch()` will become muscle memory. The reduced breaking changes make the upgrade smoother.
Everything else? Good engineering, but it won't change your Tuesday morning standups.
Focus on the features that matter most to your workflow. Your future self will thank you.
---
*Laravel 13 releases March 17, 2026\. The upgrade guide and full changelog are available at* [*laravel.com/docs*](https://laravel.com/docs?ref=artisancraft.dev)*.*
---
[](https://www.artisancraft.dev/consulting-services/)
I offer hands-on consulting to help you resolve technical challenges and improve your CMS implementations.
Get in touch if you'd like support diagnosing or upgrading your setup with confidence.
[Learn more ](https://www.artisancraft.dev/consulting-services/)
### The AI productivity trap: why your brain can't keep up with your tools
URL: https://www.artisancraft.dev/the-ai-productivity-trap-why-your-brain-can-t-keep-up-with-you/
Last updated: 2026-03-25T14:31:38.000Z
Despite producing more output, I felt cognitively exhausted by noon. My ability to think deeply about complex problems—the core of my work as a knowledge worker—had quietly eroded.
I wasn't alone. Across industries, professionals are experiencing the same paradox: AI makes us *feel* more productive while systematically destroying our capacity for sustained focus. While business leaders debate whether AI will replace jobs, they're missing the crisis happening right now. AI isn't just changing what we do, but it's rewiring how our brains work in ways that may not be sustainable.
---
## The neuroscience of AI burnout
Your brain evolved sophisticated attention systems over millennia. The prefrontal cortex manages working memory and cognitive control through cycles of engagement and recovery. Intense focus creates "attention debt"—cognitive depletion that requires restoration.
Traditional work had natural recovery periods built in. Writing involved reflection moments. Reading had pauses. Even debugging code included thinking breaks. AI tools eliminate these rest periods by keeping you in constant decision-making mode.
AI-assisted work forces constant switching between cognitive modes within the same task. You're generating ideas, evaluating AI output, refining prompts, and integrating results simultaneously. Each transition depletes attention without providing recovery.
It's like running a marathon while constantly changing pace—exhausting in ways steady effort isn't.
So, what's wrong with that, you would ask?
---
## The decision fatigue amplifier
What's weird is that tools designed to reduce cognitive load often increase a different type of mental strain: decision fatigue. Every interaction with an AI system requires a series of micro-decisions that accumulate throughout the day.
Consider a simple task like writing a project update. Without AI, you draft the email and send it. With AI assistance, you decide which tool to use, craft an initial prompt, evaluate the output quality, decide whether to refine the prompt or edit manually, integrate AI suggestions with your own knowledge, and finally assess whether the result matches your intent. Each decision point consumes executive function resources.
I've noticed this pattern in my own coding. Traditional coding involves extended periods of deep thinking punctuated by implementation. AI-assisted coding inverts this pattern, creating constant micro-interruptions for evaluation and decision-making, preventing the extended focus periods needed for complex architectural thinking.
The exhaustion doesn't come from the coding itself. It comes from constantly mediating between human intuition and AI suggestions—cognitive arbitration fatigue.
---
## The always-on availability trap
AI assistants create an "always available" cognitive environment that fundamentally alters our attention patterns. This availability creates cognitive opportunity cost—the mental energy expended simply knowing that AI assistance is accessible.
The brain treats AI availability like a constantly ringing phone. Even when you're not using it, part of your attention system remains allocated to monitoring whether you should be using it, creating a baseline level of cognitive load that never fully dissipates.
This helps explain why professionals report feeling mentally drained even on days when they use AI tools minimally. The mere presence of AI assistance appears to alter our baseline cognitive state, preventing the complete attention restoration that occurs during periods of true cognitive rest.
---
## The multitasking multiplication effect
AI tools don't eliminate multitasking—they make it more sophisticated and harder to recognize.
When using AI assistance, we're simultaneously maintaining awareness of our primary task objective, monitoring AI output for relevance and accuracy, formulating follow-up prompts or refinements, integrating AI suggestions with existing knowledge, and evaluating the overall quality of *hybrid human-AI output*.
This is multitasking about multitasking. We're not just juggling multiple tasks; we're managing multiple cognitive processes within each interaction with AI systems.
After extended periods of AI-assisted writing, I notice attention switching deficits that persist even after AI use ends. The brain's attention system needs time to consolidate and reset, but AI-assisted work prevents this consolidation, creating cumulative attention debt.
---
## The recovery paradox
The efficiency increases that make AI adoption attractive, eliminate the natural recovery periods that sustain long-term cognitive performance.
Traditional deep work involves natural rhythms of intense focus followed by reflection and integration. Writing involves pauses for thinking, coding includes moments of architectural consideration, and analysis requires periods of synthesis. These apparent "inefficiencies" serve crucial cognitive functions—they allow attention systems to restore and consolidate information.
AI tools optimize for continuous output, eliminating what appears to be wasted time but is actually essential cognitive maintenance. The result is productivity debt—short-term output gains that compromise long-term cognitive capacity.
It's analogous to using stimulants to enhance performance—effective short-term, potentially costly long-term. You get immediate cognitive leverage that feels sustainable but gradually depletes the mental resources necessary for sustained knowledge work.
---
## Recognizing the warning signs
Cognitive depletion from AI overuse shows up in weird ways that are easy to misattribute to other factors. I've learned to watch for these patterns:
- **You have trouble maintaining focus on tasks without AI assistance.** Your attention span during non-AI activities gets shorter. Simple decisions become harder—you overthink routine choices and feel overwhelmed by options that previously seemed manageable.
- **You become cognitively inflexible.**
Problems that don't fit AI-assistance patterns throw you off. You resist approaches that don't involve AI, even when they might be more appropriate.
- **Integration becomes difficult.**
You struggle to synthesize information from multiple sources or see big-picture connections. Tasks requiring sustained abstract thinking feel unusually challenging.
- **You feel restless** during periods without AI assistance and treat thinking time as inefficiency rather than necessity.
These symptoms often emerge gradually and may initially look like general work stress. But they specifically indicate that AI usage has exceeded your cognitive system's capacity for integration and recovery.
---
## Designing sustainable AI usage
Understanding the neuroscience of AI-induced cognitive strain points toward usage patterns that preserve long-term cognitive health while maintaining productivity benefits.
I've started implementing cognitive cycling—alternating periods of AI-assisted work with periods of unassisted deep thinking. Forty-five to sixty minute cycles of AI use followed by fifteen to twenty minutes of reflection or non-AI work help both productivity and cognitive recovery.
Selective AI engagement works better than treating AI as a default problem-solving approach. I use AI for tasks that genuinely benefit from external input: information gathering, initial draft generation, and routine optimization. But I maintain human-only periods for strategic thinking and creative problem-solving.
Creating AI-free zones helps too. I designate specific times and spaces where AI tools aren't accessible. This allows attention systems to fully reset and prevents the cognitive opportunity cost associated with constant AI availability.
Integration time matters more than I initially realized. The goal isn't just to produce work with AI assistance but to learn and grow from the collaboration. I build explicit time for synthesizing and internalizing AI-assisted output.
Most importantly, I monitor cognitive load indicators and treat them as seriously as physical fatigue. Cognitive strain isn't a character flaw—it's a biological constraint that requires management.
---
## The path forward
AI tools represent a shift in how we augment human cognitive capacity. Like any powerful technology, they require wisdom in application. The current approach—adopting AI tools as quickly as possible and maximizing their usage—ignores basic constraints of human cognitive architecture.
The solution isn't to abandon AI assistance but to develop sustainable integration patterns that respect both the capabilities of AI systems and the limitations of human attention. This requires treating cognitive health with the same seriousness we apply to physical health—recognizing that short-term performance gains mean nothing if they compromise long-term capacity.
The professionals and organizations that thrive with AI won't be those who use it most intensively, but those who learn to use it most wisely. This means understanding not just what AI can do, but what it costs—and ensuring that the cognitive price we pay today doesn't bankrupt our intellectual capacity for tomorrow.
---
## In this series
This post is part of the **Disruptive AI** series.
[Disruptive AIA front-line view of AI’s impact on business and productivityArtisanCraftDaniel Plomp](https://www.artisancraft.dev/disruptive-ai/)
- [I watched a developer admit AI killed his business model. Here's why I'm not worried.](https://www.artisancraft.dev/i-watched-a-developer-admit-ai-killed-his-business-model-here-s-why-i-m-not-worried/)
- [I'm Living the AI Disruption Everyone's Warning About](https://www.artisancraft.dev/living-the-ai-disruption/)
- [The hidden signs you're addicted to AI and why it's different](https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/)
- *The AI productivity trap: why your brain can't keep up with your tools (this post)*
---
[](https://www.artisancraft.dev/consulting-services/)
I offer hands-on consulting to help you resolve technical challenges and improve your CMS implementations.
Get in touch if you'd like support diagnosing or upgrading your setup with confidence.
[Learn more ](https://www.artisancraft.dev/consulting-services/)
### MCP is the new API economy
URL: https://www.artisancraft.dev/mcp-is-the-new-api-economy/
Last updated: 2026-03-10T07:00:37.000Z
A caveat upfront: this was a controlled demo, not a production environment. It took some setup to get the MCP servers configured and connected. But once that was done, the experience *felt* like what APIs were always supposed to feel like — and that's what caught my attention.
---
## A brief history of me yelling at OAuth screens
If you've ever integrated a third-party API, you know the drill. Read the docs (ha, "docs"). Register an app. Get your client ID and secret. Implement the OAuth flow. Handle token refresh. Parse their specific flavor of JSON. Discover that their "v2" endpoint actually returns v1 responses on Tuesdays. File a support ticket. Wait three weeks. Give up and hardcode a workaround.
I've done this dance dozens of times. Stripe is great. Most others make you want to cry.
The promise of APIs was always beautiful: everything talks to everything. The reality was: everything talks to everything, *if* you have two weeks and a therapist.
---
## MCP makes integrations easier (not effortless)
MCP (Model Context Protocol) is someone finally saying "what if integrations were significantly less painful?"
Here's the idea: instead of every AI tool building custom integrations for every service, you build one MCP server for your product. Any MCP-compatible agent can use it. In theory, that's a big simplification.
No SDKs per language. No webhook configuration hell. No "which version of the API are you on?" One protocol. Universal.
It's worth noting what MCP *doesn't* do: it doesn't eliminate integration complexity so much as shift it. The complexity moves from the app developer to the MCP server builder and the agent runtime. Someone still has to handle authentication, error states, and edge cases — it's just a different someone, working at a different layer. That's a meaningful improvement in many cases, but it's not magic.
The protocol got donated to the Linux Foundation's Agentic AI Foundation, co-founded by Anthropic, Block, and OpenAI, with Google, Microsoft, AWS, and Cloudflare backing it. Kong launched an enterprise MCP registry. Cloudflare built "Code Mode" that gives agents an entire API in roughly 1,000 tokens.
This isn't a side project anymore. This is infrastructure — though the protocol is still under active development and could see breaking changes.
---
## Why agents change the integration model
REST APIs were designed for *developers* to integrate *applications*. MCP is designed for *agents* to integrate *everything*. That's a different design target, and it leads to different outcomes.
When I work with REST APIs, I build an integration once, maintain it forever, and pray the provider doesn't change their schema. API changes can break integrations, and maintenance is an ongoing challenge.
With MCP, agents can discover capabilities on demand, which reduces some of the brittleness. But it's important to be honest about the limits: if a service fundamentally changes its API behavior or schema, the MCP server wrapping that API still needs to be updated. The adaptation problem shifts from your app code to the MCP server layer — it doesn't disappear.
Cloudflare's Code Mode is an interesting example. They give an agent a compressed API description (the whole thing) in about 1,000 tokens. The agent reads it, understands the endpoints, and starts making calls. No SDK. No documentation deep-dive. No Stack Overflow.
I tried this with my own setup. Pointed an agent at an MCP server I'd never configured before. It figured out the available tools, understood the parameters, and started using them correctly. On the first try.
If you've spent any time debugging API integrations, you understand why I nearly fell off my chair.
---
## The early mover window
The npm comparison is tempting but imperfect. When npm took off, it brought versioning, dependency resolution, lock-files, and a maturing quality ecosystem. MCP registries don't have most of that yet — which is actually the point. The infrastructure is nascent, and the people building it now are shaping what it becomes.
PulseMCP tracks servers across registries (their site lists thousands, though exact numbers are hard to pin down as the landscape changes daily). Kong's registry appears to be growing with enterprise-ready integrations, though I haven't seen independently verified numbers. Google launched managed MCP servers with enterprise security.
The developers who published popular npm packages early became indispensable. Their download counts became moats. Their packages became dependencies in thousands of projects.
A similar dynamic *could* play out with MCP — but it depends on whether the ecosystem develops the kind of quality infrastructure (versioning, security auditing, dependency management) that made npm's success durable.
---
## If you build things
### Build an MCP server
If your product has an API and you don't have an MCP server, you're increasingly hard to discover for AI agents. And AI agents are rapidly becoming a way people interact with software.
SaaStr reportedly started 2025 'AI-lean' with 20+ AI agents running their operations, showing how SaaS companies are under real pressure to be agent-compatible.
An MCP server isn't hard to build. A basic one for a REST API takes an afternoon. A good one (with proper capability descriptions, error handling, and streaming) maybe a weekend.
The payoff? Any MCP-compatible AI agent can now discover and use your product. Not just the ones you've built custom integrations for. That's a meaningful expansion of your integration surface.
### There's a marketplace gap here
I keep looking for a "ThemeForest for MCP servers" — a place where you can buy a well-built, tested, documented MCP server for $49 and plug it into your stack. It doesn't exist yet.
Someone's going to build this. IT leaders are dealing with unexpected costs from AI features and integrations. They'll pay for plug-and-play solutions.
The opportunity is sitting right there: build an MCP server that wraps a common integration (accounting software, CRM, payment providers), package it nicely, sell it. The plumbing is standard. The value is in knowing the domain.
### Solo dev math
I run my whole operation with AI agents and MCP. My content pipeline. My research. My code reviews. My scheduling. Not because I'm lazy (okay, partly), but because MCP significantly reduces the integration cost.
Before MCP, connecting a new tool meant hours of API work. Now it means: find an MCP server, point my agent at it, and — after some initial testing and configuration — it's running. That changes the economics of being a one-person company.
The rough math: if each MCP integration saves me several hours of custom API work compared to building a traditional integration, and I'm using 15+ integrations, the time savings add up fast. In practice it's not *zero* work per integration — you still spend time evaluating MCP servers (quality varies), debugging agent behavior, and configuring security. But even conservatively, I estimate I'm saving weeks of plumbing work over the course of a year. Time I can spend building actual features, writing actual content, or touching grass.
---
## The problems nobody talks about
Before I sound like a VC pitch deck, some real talk:
- **Security is still the wild west**
Giving an AI agent access to your services via MCP means trusting the agent with your credentials. TrueFoundry is building enterprise access control for MCP servers through their MCP Gateway, and Kong's doing governance layers, but we're early. Very early.
- **Prompt injection is a real risk**
A malicious or compromised MCP server could potentially manipulate agent behavior through crafted tool descriptions or responses. When you give an agent broad tool access across multiple MCP servers, the attack surface grows — and the agent might take actions you didn't anticipate or authorize. This is an active area of security research with no settled solutions yet.
- **Quality varies wildly**
Some MCP servers are production-ready. Others are someone's weekend project that breaks if you look at it funny. There's no npm-style quality scoring yet (though PulseMCP is trying).
- **Finding what you need is annoying**
The registries exist but they're not great at helping you evaluate options. You end up searching and hoping.
- **Vendor lock-in sneaks up on you**
The protocol is open, but the implementations often aren't. Google's managed MCP servers are great until you want to leave Google Cloud.
- **The protocol itself is still evolving**
MCP is under active development, and breaking changes are possible. Building heavily on today's spec carries some risk that tomorrow's version may require rework.
These are solvable problems. But they're not solved yet. And some of them — particularly around security and agent predictability — are genuinely hard.
---
## Where I think this goes
I'll frame this as a prediction, not a certainty: I believe that within roughly 18 months, "does your product have an MCP server?" could become as standard a question as "does your product have an API?" Used to be, no API meant no integrations. If the current trajectory holds, no MCP server may increasingly mean no agent integrations.
My bet is that agent integrations will start to matter as much as — and eventually more than — human-driven integrations. Not because humans are going away, but because every human will have agents doing their integration work for them. That's a prediction based on current momentum, not an inevitability.
The companies that see this coming — that build great MCP servers, that make their products agent-friendly, that publish capabilities instead of just endpoints — they're going to have a head start over everyone still forming committees about their MCP strategy.
And if you're an indie dev? You can have a server live this weekend while enterprises are still in meetings about it.
Worth doing. The ecosystem is hungry for good implementations.
---
*If you're building with MCP and want to compare notes, hit me up on* [*X*](https://x.com/danielplomp?ref=artisancraft.dev)*. I'm deep in this rabbit hole and I'm bringing snacks.*
### The hidden signs you're addicted to AI and why it's different
URL: https://www.artisancraft.dev/the-hidden-signs-you-re-addicted-to-ai-and-why-it-s-different/
Last updated: 2026-03-09T07:00:15.000Z
I caught myself refreshing Claude Code at 12 AM last Tuesday. Not for work. Not for anything urgent. Just checking if it was back online after a brief outage.
That's when I realized I might have a problem.
Well, sort of. Calling it a "problem" feels a bit black and white to me. But that moment of checking for an AI tool at 12 AM? That made me think about our relationship with these systems in a new way.
The thing is, I felt productive. I was getting stuff done. Unlike scrolling Instagram or binging Netflix, my AI usage looked responsible from the outside. Professional, even. But something felt wrong when I couldn't access it for twenty minutes.
Turns out there's a name for what I was experiencing. Researchers are calling it *Generative Artificial Intelligence Addiction Syndrome (GAID)*. And it's different from every other tech addiction we've seen before.
---
## Why AI addiction flies under the radar
Most digital addictions are obvious. Social media addiction looks like endless scrolling. Gaming addiction involves missing sleep and social obligations. But AI addiction disguises itself as productivity.
You're not wasting time. You're writing better emails. Creating presentations faster. Solving complex problems. Your boss loves your output. Your clients are impressed. From every external measure, you're crushing it.
This makes AI addiction particularly sneaky. Unlike passive consumption of digital content, AI tools create what researchers describe as "effortless achievement." You experience the dopamine hit of accomplishing something meaningful without the usual cognitive effort required.
The problem isn't the tool itself. Your brain starts craving these effortless wins. And gradually, tasks that used to feel manageable without AI assistance become overwhelming. Your cognitive muscles weaken while your productivity metrics soar.
---
## The warning signs nobody talks about
Traditional addiction markers don't apply here. You're not neglecting responsibilities or hiding shameful behavior. If anything, you're more responsible and productive than ever. So the warning signs are subtle.
Here's what I've noticed in myself and others:
- **The validation loop**
You find yourself asking AI to confirm ideas you already believe. Not for new information, but for that little dopamine hit of having your thoughts validated by an intelligent system.
- **Hidden usage creep**
You minimize AI chat windows when colleagues walk by, even though you're doing legitimate work. Something about the extent of your reliance feels slightly embarrassing.
- **Human input feels insufficient**
Feedback from colleagues, friends, or family starts feeling less satisfying than AI responses. Real people give messy, incomplete input. AI gives structured, comprehensive feedback that hits your productivity buttons just right.
- **Anxiety when unavailable**
Server outages or connectivity issues create genuine stress disproportionate to the inconvenience. You feel stuck rather than just temporarily slowed down.
- **Task inflation**
You unconsciously take on more complex projects because AI makes them feel manageable. But without AI support, you're committed to work beyond your actual capabilities.
I experienced all of these. The validation loop was particularly sneaky. I'd draft emails, get AI feedback, implement suggestions, then ask for confirmation that the revision was better. Pure dopamine farming disguised as professional development.
---
## The co-creation trap
AI addiction is unique because of the collaborative relationship. You're not consuming content passively. You're creating together. This active partnership creates stronger psychological bonds than any previous digital tool.
When you scroll social media, you know you're being entertained. When you game, you know you're playing. But when you work with AI, you feel like you're achieving genuine intellectual growth. The line between your capabilities and the AI's becomes blurred.
This collaborative illusion is powerful. You experience flow states that feel earned but required minimal effort. Your brain gets addicted to the output and to this false sense of enhanced capability.
Over time, your tolerance builds. Tasks that once gave you satisfaction when completed solo now feel tedious without AI assistance. You need increasingly sophisticated AI help to feel that same sense of accomplishment.
---
## Why this matters more than other digital addictions
Passive digital addictions steal your time. AI addiction steals your cognitive independence.
Social media addiction makes you less social. Gaming addiction makes you less physically active. But AI addiction makes you less intellectually capable while convincing you that you're becoming more capable.
This creates a dangerous feedback loop. The more you rely on AI for cognitive tasks, the less confident you become in your unaugmented abilities. But since your AI-assisted output is impressive, you have external validation that you're performing well. The addiction reinforces itself through positive outcomes.
I notice this in my writing. Without AI assistance, my first drafts feel clunky and incomplete. Not because my writing skills have actually deteriorated, but because my brain has recalibrated its expectations based on AI-enhanced output. What used to feel like solid work now feels inadequate.
---
## The withdrawal problem at work
Traditional digital detoxes don't work for AI addiction because the tools are often required for professional responsibilities. You can delete Instagram. You can't ignore emails that need responses or presentations that need creating.
This creates a unique withdrawal challenge. Unlike other behavioral addictions, complete abstinence isn't practical. You need to develop a controlled relationship with something that's designed to be compelling and is professionally advantageous to use.
The withdrawal symptoms are subtle but real. Tasks feel unnecessarily difficult. Creative thinking feels sluggish. Decision-making becomes exhausting. But since these are cognitive rather than physical symptoms, they're easy to dismiss as normal work stress.
---
## Building a healthier relationship
Recovery from AI addiction isn't about elimination. It's about maintaining your cognitive independence while still benefiting from AI assistance.
- **Set capability boundaries**
Regularly complete tasks without AI help to maintain your baseline skills. I now write one article per week completely solo, even if it takes longer and feels less polished.
- **Track usage honestly**
Most people dramatically underestimate their AI interaction time. Use screen time tracking or browser extensions to get accurate data. I was shocked to discover I was spending three hours daily in various AI interfaces.
- **Practice discomfort tolerance**
When tasks feel difficult without AI assistance, sit with that discomfort instead of immediately reaching for help. Your brain needs to remember that cognitive effort is normal and valuable.
- **Seek human feedback**
Deliberately ask colleagues and friends for input on work that AI could easily review. Human perspective remains irreplaceable, even if it's less immediately satisfying.
- **Create AI-free zones**
Designate specific times or tasks as completely off-limits to AI assistance. Protect your creative thinking and problem-solving skills by regularly exercising them independently.
The goal isn't to avoid AI tools. It's to maintain the cognitive flexibility to work effectively with or without them. Your future self will thank you for preserving that independence.
---
## What healthcare providers need to know
If you work with professionals, students, or knowledge workers, watch for the *productivity paradox*. High-performing individuals who become anxious or defensive about their AI usage may be developing problematic dependencies.
Unlike traditional digital addictions, AI addiction often correlates with increased professional success rather than decreased functioning. This makes it harder to recognize and intervene.
The treatment approach needs to focus on cognitive independence rather than productivity reduction. Traditional addiction frameworks that emphasize harm reduction may not apply when the addictive behavior produces genuine professional benefits.
Look for signs of cognitive inflexibility, over-reliance on external validation, and anxiety around tool availability rather than traditional addiction markers like neglected responsibilities or social isolation.
---
AI addiction represents a new category of behavioral dependency that our existing frameworks aren't equipped to handle. It's the first addiction that makes you more capable in the short term while potentially undermining your long-term cognitive independence.
The scariest part isn't that AI tools are addictive. AI addiction looks like success from the outside. By the time you recognize the problem, you may have already structured your professional life around capabilities that aren't entirely your own.
But awareness is the first step. If you found yourself nodding along to the warning signs, you're not broken. You're human. These tools are designed to be compelling, and our brains are wired to seek efficiency.
The question isn't whether you'll use AI tools. It's whether you'll maintain the cognitive independence to thrive with or without them.
Your brain deserves that flexibility.
---
### Read more about AI
[I’m Living the AI Disruption Everyone’s Warning AboutMatt Shumer warns AI disruption is coming. I’m writing to confirm: it’s not coming — it’s here. And I’ve been living it for over a year.ArtisanCraftDaniel Plomp](https://www.artisancraft.dev/living-the-ai-disruption/)
---
[](https://www.artisancraft.dev/consulting-services/)
I offer hands-on consulting to help you resolve technical challenges and improve your CMS implementations.
Get in touch if you'd like support diagnosing or upgrading your setup with confidence.
[Learn more ](https://www.artisancraft.dev/consulting-services/)
### Your kid trusts ChatGPT more than Google. That's a problem.
URL: https://www.artisancraft.dev/ai-hallucinations-explained-kids/
Last updated: 2026-03-08T13:00:07.000Z
This is the thing about AI hallucinations that makes them different from a wrong Google result. Google gives you a list of links and you pick one. If the top result looks sketchy, you scroll. There's friction. With ChatGPT, you get one confident answer in a complete sentence, formatted like a fact. No hedging, no "sources vary." Just: here's the truth.
Except sometimes it isn't.
---
## The world's most confident 'liar'
I'm writing a Dutch children's book about AI called *"De Slimste Papegaai"*
One of the chapters is about a parrot that repeats everything it hears. The parrot sounds incredibly smart because it strings together sentences that sound right. But it has no idea what any of it means. If it heard the word "kaas" a thousand times next to "geel," it will tell you cheese is yellow. Ask it what cheese tastes like and it might say "yellow."
That's what language models do. They predict the next word based on patterns in their training data. When the patterns align with reality, you get accurate answers. When they don't, you get made-up river names in Europe.
The technical term is "hallucination." I hate that word because it implies the AI is experiencing something. It isn't. It's just filling in blanks with whatever is statistically likely. A better word would be "confabulation," which is what doctors call it when a brain-damaged patient invents memories without knowing they're fake. The patient isn't lying. They genuinely believe what they're saying. Same energy.
---
## Why kids are especially vulnerable
Adults have a few built-in advantages when dealing with confident nonsense. We've been lied to before. We've seen authoritative-looking websites turn out to be garbage. We have years of "does this smell right?" instinct.
Kids don't have that yet.
Kids use ChatGPT during homework, during tests, sometimes during class. The math questions usually work out fine. But ask it a history question, a biology fact, a specific date, and things get interesting. It might mix up two events that happened three years apart. Not wildly wrong, just wrong enough that it looks right. The kind of mistake you'd only catch if you already knew the answer.
Most teachers don't even realize kids are using it. The errors just end up in notebooks and assignments, unchallenged, looking like facts.
A [Brookings report from early 2026](https://www.brookings.edu/articles/ais-future-for-students-is-in-our-hands/?ref=artisancraft.dev) put it clearly: AI tools "prioritize speed and engagement over learning and well-being" and generate "confidently presented misinformation." The hallucination rate across major models still sits around 9% for general knowledge. For questions about specific people? Some models hit 33% to 48% error rates.
Nearly one in ten general answers might be wrong. For specific facts, it could be one in three.
---
## How I explain it at home
I've tried three different approaches, matched to my kids' ages. Here's what stuck.
**For my eleven-year-old: The confident friend analogy.**
"You know that friend who always sounds like they know the answer, even when they don't? And sometimes they're right, which makes it harder to tell when they're wrong? ChatGPT is like that. Really helpful, but you still need to check."
She gets this immediately because she has that friend. Every kid does.
**For my fourteen-year-old: The autocomplete explanation.**
I opened my phone, typed "the capital of" in a text message, and showed her the autocomplete suggestions. "See how your phone guesses what comes next? ChatGPT does the same thing, but with everything. It guesses the next word, then the next, then the next. Sometimes the guess is right. Sometimes it builds a sentence that sounds perfect but describes something that never happened."
Then I had her ask ChatGPT something she already knew the answer to. A fact from a test she'd just studied for. It got the answer slightly wrong. That three-second experiment did more than twenty minutes of explaining.
**For my sixteen-year-old: The statistics angle.**
"About 9% of the facts ChatGPT gives you are wrong. For specific people and dates, it's closer to a third. Would you trust a textbook that was wrong a third of the time?"
She's old enough to understand probabilities and to find that genuinely alarming. Good. Alarmed is appropriate.
---
## The dinner table test
Here's something I want to try, and I'd recommend it to any parent. Ask ChatGPT a question during dinner. Then have everyone guess whether the answer is right or wrong before checking.
Turn it into a game. "Is that real or did it hallucinate?" Kids love catching adults being wrong. They'll love catching AI being wrong even more. And over time, they'll develop an instinct for the smell of a hallucination. Answers that are too specific, too clean, too perfectly structured. Real facts are messy. AI facts are suspiciously tidy.
Try it with a made-up-sounding question. Ask ChatGPT to describe a scientific study about something your kids care about. Half the time it'll invent an author, a university, and a publication year for a study that doesn't exist. Let your kids be the ones to figure that out.
---
## What actually helps
Banning AI doesn't work. I wrote about this two weeks ago and I'll keep saying it. The tool is everywhere and it's useful. What works is teaching kids to treat it like a first draft, not a final answer.
Some things that could help:
**The two-source rule.** If ChatGPT tells you a fact for schoolwork, find it in a second source before you use it. If you can't find it anywhere else, it probably doesn't exist.
**Ask it to show its work.** Newer models can cite sources. Teach your kids to ask "where did you get that?" and then actually check the source. Half the time the source doesn't say what ChatGPT claims it says. That's a lesson worth learning.
**Normalize being wrong.** The reason kids trust AI so easily is that they associate confidence with correctness. If you create a home where being wrong is normal, where you as a parent say "I don't know, let me check," they'll extend that same healthy skepticism to their AI tools.
**Let them catch you.** Sometimes I deliberately leave an AI-generated mistake uncorrected and wait to see if the kids spot it. Builds the muscle.
---
## The real concern
My worry isn't that AI gives wrong answers. My worry is that a generation of kids grows up thinking research means "asking one source and accepting whatever it says." That's not an AI problem. That's a critical thinking problem that AI makes worse because it's so good at sounding right.
The schools in New York City just announced they're rolling out AI tools across classrooms. The deputy chancellor specifically said they need to make sure "kids can recognize hallucinations" before deploying it widely. That's encouraging. It would be more encouraging if that was the default, not the exception.
You won't fix this with one conversation. You probably won't fix it with ten. But the first time your kid says "wait, let me check that," you'll know something clicked.
That's all you're going for. Not perfect skepticism. Just a pause before they believe.
---
## Raising kids in the AI age
*This is part of the "*[*Raising Kids in the AI Age*](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)*" series. I'm a dad with three daughters, not an expert. I'm figuring this out as I go — and writing about it so you don't have to start from zero.*
[Raising kids in the AI ageA series about preparing children for a future we can’t fully predictArtisanCraftDaniel Plomp](https://www.artisancraft.dev/raising-kids-in-the-ai-age/)
### **In this series**
- [The question we should stop asking our kids](https://www.artisancraft.dev/stop-asking-kids-what-they-want-to-be/)
- [Your daughter's photo is one app away from being fake-naked](https://www.artisancraft.dev/ai-deepfakes-kids/)
- [Preparing children for a post-scarcity world](https://www.artisancraft.dev/preparing-children-post-scarcity-world/)
- Your kid trusts ChatGPT more than Google. That's a problem *← You are here*
### Blaze just made Blade 10x faster. Here's how it works.
URL: https://www.artisancraft.dev/blaze-made-blade-10x-faster/
Last updated: 2026-03-06T07:00:31.000Z
That's not a typo. That's a 200x improvement on a single page render.
I've been using Livewire and Blade daily on a production app with 56 models and thousands of components. So when someone tells me they made Blade faster, I pay attention.
Here's what Blaze actually does, when you should use it, and where it'll bite you.
---
## Why Blade got slow
Blade was never slow. Not really. Back in the Bootstrap days, your templates were glorified string concatenators. All the reuse happened in CSS. Blade just had to stitch together some HTML and call it a day.
Then Tailwind happened.
Instead of `btn btn-danger btn-sm`, you now have 15 utility classes on every element. Nobody copies that everywhere, so you extract components. A button becomes ``. A table row becomes a component. An icon becomes a component. A badge becomes a component.
Suddenly a normal page has 500 to 1,500 Blade components. A beefy dashboard? 5,000 to 10,000\. Each one goes through the full rendering pipeline: container lookup, view resolution, prop merging, attribute bag construction, slot handling. None of these are expensive on their own. But multiply them by thousands and you've got death by a thousand cuts.
Caleb benchmarked 25,000 empty Blade components (just a `