Brief queue substrate

@@ -39,7 +39,7 @@ The Brief Queue Substrate delivers five operational properties that the platform

**Capture-edit pipeline simplification.** The previous pattern required the capture pipeline to write directly to corpus JSONL files during the editorial session, which created ordering dependencies between the Doorman's audit-routing logic and the corpus file's append position. The queue removes that dependency: the Doorman writes an event record to `queue/` and returns immediately; the drain worker serializes corpus appends in arrival order without blocking the inference path.

**Customer Tier 1 alignment.** The queue architecture matches the pattern that Ring 1 ingest services (service-fs, service-people, service-email, service-input) already use for durable event capture at the tenant boundary. A customer extending the platform with an additional MCP server can use the same four-directory queue pattern for their ingest events. Consistency across tiers reduces the surface area a contributor needs to understand.
**Customer Tier 1 alignment.** The queue architecture matches the pattern that Ring 1 ingest services (service-fs, [[service-people]], [[service-email]], service-input) already use for durable event capture at the tenant boundary. A customer extending the platform with an additional MCP server can use the same four-directory queue pattern for their ingest events. Consistency across tiers reduces the surface area a contributor needs to understand.

**Future PointSav-LLM readiness.** The apprenticeship corpus — the accumulation of draft-created, draft-refined, and creative-edited JSONL events — is the intended training signal for a future PointSav-LLM continued-pretraining run [1]. The Brief Queue Substrate ensures that corpus growth is uninterrupted by compute-tier transitions, idle shutdowns, or preemption events. Every editorial session contributes to the corpus regardless of which compute tier handled the inference.