AI Agents For Beginners – OpenClaw Case Study
freeCodeCamp.org
Starts with how LLMs work, tokens and context windows, and calling a model through its API, then builds agents from a plain loop, adding tools, memory and multiple agents. The final part takes OpenClaw’s codebase apart to show how a production agent handles concurrency, testing with LLM-as-a-judge, observability and security. Hands-on labs come with the course.
What you'll learn
- Tokens, context windows and API message roles
- The difference between fixed workflows and autonomous agents
- Writing an agent loop with tools from scratch
- Memory with sliding windows and vector databases
- Multi-agent systems and frameworks such as LangChain and Mastra
- Testing and monitoring agents, using OpenClaw as an example
