Track7 lessons
AI agents
How agents work, from the action loop and the harness around the model to skills, security incidents and sandboxing.
Agents are goal-driven action loops: a model chooses actions, uses tools, observes results and decides what to do next, inside a harness that supplies everything the model does not. These lessons teach when a task needs an agent, how the harness, skills, subagents and MCP fit together, and how to bound an agent's reach with approval gates, security practice and sandboxes.