Agents

In Part 1 we established the simple truth: LLMs can only produce text. The harness is the babysitter that turns that text into action. Today we build the action part. The tools. The hands. This is the fun chapter, by which I mean it’s the one where we voluntarily give a probabilistic text generator the ability to touch the filesystem and then act surprised when it tries to read /etc/passwd. All the code below is lifted straight from the repo — a single agent.py file you can clone and run. Strap in. ...

You’ve seen the demos. AI agents booking flights, writing code, querying databases, probably filing your taxes while whispering sycophantic flattery. Very impressive. Very “the future is here, and it’s kinda scary.” Here’s the simple secret nobody mentions in the keynote: LLMs can only produce text. That’s it. They can’t run code. They can’t check the time. They can’t read a file. They are the world’s most confident interns — full of opinions, zero ability to actually do anything. All they do is predict the next token and hope you’re impressed. ...