Stephen Blum

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.

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