Engineering AI Agents
Bounded tool-using loops with durable state, guardrails, and evals
Learn how an AI agent actually runs: a model choosing actions in a loop that your application code executes, bounds, and stops. This Deep Dive covers least-privilege tool contracts and approval gates, plans that survive failed assumptions, memory with provenance and deletion boundaries, checkpointed execution that recovers without repeating unsafe side effects, and evaluations that turn recorded runs and fault-injected trials into success rates you can trust.