Every coding agent session starts with a strange contradiction. The model is capable. It can read code, reason through architecture, write tests, explain tradeoffs, and debug with patience. But the session itself is often forgetful. It does not remember why we chose SQLite over Postgres for a prototype. It does not remember that the migration layer had a weird compatibility constraint. It does not remember the conversation where we decided not to expose a public API yet. It does not remember the repeated instruction I keep typing into every project: "check the existing pattern first." So the human becomes the memory layer. We paste context. We summarize old threads. We say, "We already tried that." We ask the agent to search the repo again. We re-explain preferences. We lose twenty minutes to rediscovery before the actual work begins. That is the problem local agent memory is meant to solve. Not "AI consciousness." Not magic. Just durable, queryable context that lives near your tools.…