What is intentional compaction? @DexHorthy, founder of HumanLayer, explains: “When context is noisy, you deliberately compress the useful parts into a clear markdown artifact, verify it, and then start a fresh conversation. Frequent intentional compaction is the building block for building software with AI. How do we get the most out of today’s models, how do we control what we’re putting into the context window so we get the best results, which means doing as much work as possible in the smart zone, the first hundred thousand tokens. 1. The research step: we go read a bunch of code and turn it into a doc: that’s our compaction. We take that forward. 2. In the next session we read the ticket and the intent and turn that into a design document: here’s the high-level current state, desired end state, and a bunch of design questions. 3. Then you take the research and the design and you do a new session, new context: you’ve compressed the intent, and you’ve compressed the state of the codebase, so you can then do your planning.”