From text tools to physical actions
The agent loop covered in Building AI Agents doesn't change shape when you attach it to a robot. An LLM-based reasoning engine still observes, decides, acts, and observes again, over and over. What changes is what sits on either end of that loop. Instead of reading a user's message, the agent reads sensor input: a camera frame, a snippet of audio from a microphone, a reading from a proximity sensor. Instead of calling a tool that queries a database or sends an email, it calls a tool that moves an arm, turns a wheel base, or plays synthesized speech through a speaker. The reasoning core, the part that decides what to do next given what it currently knows, is recognizably the same architecture as the agents covered elsewhere on this site.
This continuity is exactly why the bridge from digital to physical agents is worth studying on its own. Everything you already know about planning, tool selection, and reacting to unexpected results from Agent Architectures and Planning still applies. The new material is what has to be built around that loop so the physical world doesn't get hurt by it, and that surrounding architecture, not the reasoning engine itself, is what this course is about.