User memory
Auto-loaded every turn. Routing rules, preferences, audit-trail tail.
/memories/*.md
Hot / warm / cold context. A networked brain that scales from one workstation to a team. And the actual day-to-day choreography of a single working session.
The pattern starts on a single workstation, but the semantic-brain pillar is designed to network. Run the brain as a containerized service exposing HTTP and Server-Sent Events, and any number of agents on any number of machines hit the same recall surface — no per-seat duplication of the corpus, no drift between team members, no re-embedding when a new agent joins.
remember() calls. Always writable.recall() queries both collections in parallel, merges by distance, returns top-N. Caller never sees the seam.remember by one agent is queryable by every other within seconds.claim() / release() / handoff() / pulse_others() so agents don't step on each other on a shared task.This is how the same architecture scales from "one developer, one machine, one Copilot" to "a team of humans + agents working a multi-month codebase together" without redesigning anything below the brain layer.