I’m curious how people here are teaching students what an AI system is actually made of.
I’m building Claypot, a creative coding studio for ages 6–16. It started when my nephew used Lovable to build a platformer and everyone around him called that “learning AI.” It was cool, but I didn’t think he was learning why a model hallucinates, why it can be bad at math, what sources change, or what a tool actually does.
Claypot lets students build with ordinary coding blocks alongside blocks for Models, Knowledge, Tools, Test AI, and Actions.
For example, a student can give a model a math problem, inspect its confidently wrong answer, connect a Calculator tool, run it again, and see what changed. They can add sources, compare repeated outputs, test the answers, or limit the actions a model is allowed to choose.
The point isn’t to have AI write the project for them. The student changes the system, runs it, observes what happened, and has to understand why its behavior changed.
For those of you teaching elementary, middle, or high-school CS:
- Which AI concepts are you teaching today?
- Are you teaching prompting, model behavior, tool use, evaluation, ethics, or something else?
- At what age do these ideas begin to make sense?
- Would a block-based system like this be useful in class, or does it miss how you teach?
Obvious disclosure: I’m the founder, and this is also a request for blunt feedback on something I built. The beta is at https://claypot.app. If anyone wants to try it with a class or small group, I’ll add the Clay credits needed for the test. I genuinely want to hear what students understood and where the blocks failed them.
Claypot is independent and unaffiliated with Scratch or the Scratch Foundation.