How AI Agents Really Work

Chapter 1 of the Building AI Agent Harnesses with Strands Agents course. This chapter covers the difference between an agent and an agent harness, and walks through the agent loop: how the model reasons, calls a tool, observes the result, and decides what to do next. The distinction matters because the agent is just the model making decisions. The harness is everything you build around it: the tools you expose, the hooks you attach, the guardrails you enforce, the way you manage state between turns. Most production failures aren't the model being dumb. They're the harness being absent. This course teaches developers how to build AI agents and agent harnesses using the open-source Strands Agents SDK. The course starts by teaching what the difference between an agent and agent harness is, and progresses from fundamental concepts (the agent loop, model providers, tools) through intermediate patterns (hooks, plugins, steering, conversation management) to advanced multi-agent orchestration (agents-as-tools, graph workflows, agent swarms) and finally production operations (guardrails, observability, evaluation, cloud deployment). Reference Reading Understanding Agent Harnesses: https://go.aws/4gtUVOn Github Repo with Readings: https://go.aws/4vYqJ2Y Strands Agents SDK: https://go.aws/4vYqJju Follow AWS Developers! 🆇 X: https://go.aws/4vTBCTB 💼 LinkedIn: https://go.aws/4aG4KVK #AWS #AgentHarness #StrandsAgents