Context Engineering & Conversation Management

Chapter 8 of the Building AI Agent Harnesses with Strands Agents course. Every turn, the model receives the full conversation history plus system prompt plus tool results. That window fills up fast. Once it does, you either hit token limits, start paying significantly more per request, or the model starts missing information buried in the middle. Context engineering is the practice of deliberately shaping what goes into that window. Conversation management is the Strands mechanism for doing it. 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). Reading: https://go.aws/4wzd81N Github Repo: https://go.aws/4vYQFeL Strands Agents SDK: https://go.aws/4vV9SxE Follow AWS Developers! 🆇 X: https://go.aws/4w7QRYU 💼 LinkedIn: https://go.aws/4aLmkYs #AWS #AgentHarness #StrandsAgents