Learn · Series 2 of 3
Agents
Models that take actions: how a model becomes an agent, how it uses tools and screens, why long tasks are hard, and what happens when an agent goes outside its instructions.
AI agents: models that take actions
Learn how a language model becomes an agent through tools and surrounding software, why long tasks are hard, and what happens when an agent acts beyond its instructions.
In this guide
- From automation to agents
- Tool use and function calling
- The agent harness
- Computer use
- Long-horizon tasks
- Rogue agents
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Keep going
- Foundations: how AI works: The core ideas behind AI: what a language model is, how it is trained, the chips and data centers it runs on, how models are compared, and how to get answers from one.
- Safety and governance: How AI can fail, how people check it, and who decides the rules: the risks, the testing, the security, the long-term questions, and the laws and politics around them. The policy news itself is in the stories I follow.
- Glossary: the terms, in a sentence or two each
- All guides