A plan review gate for agent-built features
A practical gate for reviewing agent implementation plans before code exists, with scope, risk, proof, and ownership checks for product teams.
Notes on the choices around the code: architecture tradeoffs, delivery pipelines, product signals, and the operating habits that help teams ship well.
A practical gate for reviewing agent implementation plans before code exists, with scope, risk, proof, and ownership checks for product teams.
A practical review gate for agent-edited product specs, using attribution, version checkpoints, and owner approval before work becomes execution-ready.
A practical runbook for deciding which recurring product-agent workflows deserve triggers, permissions, review, and a clear stop condition.
A practical launch gate for AI product features: small datasets, explicit scorers, human review, rollback paths, and clear pass criteria.
GitHub's new issue automation controls make agent triage safer when teams treat confidence, rationale, and approvals as product workflow signals.
A practical launch ladder for deciding when to use manual gates, percentage rollouts, guarded releases, or full feature-flag machinery.
A practical launch checklist for turning release notes into a traceable product delivery gate, not a hurried marketing chore.
A practical checklist for turning backlog tickets into scoped, reviewable work that coding agents can actually finish.
Two 2026 benchmarks put hard numbers behind a familiar founder problem: early startup signal is real, but noisy. I would use them as a ranking aid, not as a replacement for product judgment.
Starcloud is trying to move AI compute into orbit. This teardown compares the startup case against the boring but proven path of terrestrial data centers.