We published the full walkthrough and runnable implementations in JavaScript and Python in Lesson 2: tool calling - how a chat model gets hands. You can follow the breakdown, inspect the exact failure modes, and test the ring directly in the harness against a virtual localStorage filesystem without leaving your browser tab.

A chat model cannot check the weather, read a file, or send an email. It can only generate text. An AI agent is not born from a complex orchestration framework, a planning module, or an external memory layer; it is born from an agreement that turns generated text into an executable instruction. The model simply halts its raw text output to emit a structured schema containing a function name and arguments, your application executes the native code, and you pass the return value back into the conversation array under the matching call ID.

https://buttercup.sh/lessons/202...

The first lesson! For building AI Agents. We start with using WebLLM for clinet-side language model inference. Note that the full syllabus has been posted if you are interested in the upcoming lessons.

At least four weeks, with a chance of a few bonus weeks. This is a short event that will only last a short while. Make sure not to miss it!

AI Agent basics to adding vision to your agent. The syllabus isn't finalized. The topics can be influenced by the participants.