A research-grade model of the Labs platform as the surface where data-center-backed engineering and science work is documented, visualized, reviewed, and iteratively improved by humans and Codex.
A candidate branch-point lab for the UnifiedFlow data center platform: governed workers, source boundaries, portable model and IP memory, telemetry, and scientific promotion gates as one inspectable research system.
Queued subsystem lab for how machines become approved UnifiedFlow capacity through bootstrap evidence, heartbeat, capability profiles, leases, and bounded assignment.
Queued subsystem lab for resource telemetry, canary process state, stage health, and how remote scientific runs become inspectable operations.
Queued subsystem lab for read-only source posture, lab-owned raw data, output custody, scratch policy, and source-duration truth.
Queued subsystem lab for portable weights, profiles, calibration artifacts, critic reports, rejected examples, and training evidence.
Queued subsystem lab for replacing fixed-duration assumptions with metadata-confirmed full-source movie coverage and critic agreement.
Queued subsystem lab for profile critics, neuroscience critics, condition governors, event adjudicators, and figure-readiness authorities.
Queued subsystem lab for how working knowledge, evidence artifacts, figures, and review decisions become durable Labs studies.
Queued subsystem lab for bringing new science and engineering domains onto UnifiedFlow, with neuroscience and calcium imaging as the first concrete path.
How I built a single Vercel-hosted API that serves many Custom GPTs via OpenAPI, with strict tenant isolation and safe action execution into warehouses/lakes.