AI agents seem complicated. But once you look under the hood, they're built from a few simple ideas.
In this talk, I'll use a real AI agent to show how its core loop fits in around 80 lines of code. We'll then explore the key ideas behind modern agents, including tool calling, conversation history, and stopping conditions.
I'll also explain what frameworks actually do and which problems they're designed to solve. You'll leave with a clear mental model of how AI agents work and the confidence to choose the right approach for your own projects.
Table of contents:
- AI agents are simpler than you think: an 80-line implementation
- What do we actually send to the LLM?
- How does the LLM know what to do next?
- How does tool calling work?
- Conversation history
- Stopping conditions
- Where frameworks really help: retries, fallbacks, security, and conversation management
This talk has been presented at AI Coding Summit Berlin, check out the latest edition of this Tech Conference.























