A tool returns 214KB of logs. The context window overflows, reasoning quality drops, and your agent returns worse answers with no error thrown. Another retries the same call fourteen times on ambiguous feedback. A third blocks seventeen seconds on a slow tool and times out. None crash. They just cost money and accuracy as data and complexity grow. This hands on workshop teaches four context engineering strategies through three fixes you build yourself: • Externalize and Select with a memory pointer: keep large data outside the window and pull it back by reference, in single and multi agent setups. Seven times fewer tokens, no information loss. • Compress runaway loops with a debounce and tools that return clear states, so the agent knows when to stop. Fourteen calls to two. • Isolate slow tools behind an async handle that returns immediately and polls, so the agent is never frozen. Seventeen seconds to under two. You run the failing version, build the fix, and compare metrics. You leave with code for all three fixes, a decision framework matching each strategy to its failure, and an open source repo. Build along, not slides, and the patterns work with any agent framework.

Outline: • Introduction: The Infinite Window Is a Myth • The Four Context Engineering Strategies • Module 1: Memory Pointer, Single Agent • Module 2: Memory Pointer, Multi Agent • Module 3: Compress Runaway Loops • Module 4: Isolate Slow Tools • Anti-Patterns, Decision Framework, Resources