Governance Model designed
GPUaaS governance exists to keep contract-first development, security posture, agent execution, testing, and release promotion auditable. The model is designed for a team where humans and agents both produce changes, so the evidence and review trail matters as much as the patch.
Governance Stack
| Layer | Purpose |
|---|---|
| Machine-readable policies | Define enforceable behavior for agents, production controls, review gates, and API linting |
| API and event contracts | Keep REST and event changes contract-first and reviewable before implementation |
| Coding and testing standards | Define handler shape, service boundaries, error model, test pyramid, and Definition of Done |
| Security verification | Track control implementation, evidence, exceptions, and review ownership |
| CI and guard scripts | Keep gate logic portable and reusable across CI hosts |
| Agent work model | Define lanes, context packets, evidence, reviews, and handoffs |
| Release authority | Promote known source SHAs through platform-control policy instead of ad hoc branch edits |
| Local automation utilities | Convert repeated CI, deploy, UAT, evidence, closeout, ops smoke, and release checks into deterministic packets |
Change Discipline
- Start with the contract, architecture, or product source doc that owns the change.
- Implement only after the owning spec is clear.
- Add focused tests and evidence for the changed behavior.
- Record review from the right domains.
- Promote only from known source state with release evidence.
- Convert repeated manual checks into report-only guards, then warning, then blocking gates.
What New Developers Should Know
- Error responses use the shared error catalog and include correlation IDs.
- Mutations must be idempotent unless a documented endpoint exception applies.
- Events are published through the transactional outbox, not directly from handlers.
- Billing ledger and audit logs are append-only.
- Policy values come from policy storage, not hardcoded service constants.
- Sensitive data must be sanitized before logs or traces.
- Cross-domain data access must go through events, APIs, or explicit shared services.
- User-facing work must pass UX/IA and contract gates before broad implementation.
Agent-Native Governance
Agents are useful because they can move many small tasks quickly. They are risky when context, ownership, and evidence are unclear. GPUaaS governance handles that by requiring:
| Mechanism | Why it exists |
|---|---|
| Work queues and lanes | Prevent multiple agents from silently editing the same ownership area |
| Source-doc references | Keep generated portal pages and implementation tasks tied to canonical docs |
| Evidence-first completion | Avoid “done” without tests, checks, screenshots, or review notes |
| Review domains | Route work to product, architecture, security, ops, frontend, backend, or content reviewers |
| Guard graduation | Move from visibility to enforcement only when the team can tolerate the gate |
| Deterministic utilities | Keep pass/fail and release truth in scripts/artifacts, with optional LLM summaries only as non-authoritative summaries |
Release Governance
Release promotion should be based on exact source state, evidence, and ownership. The platform-control release rule is simple: fix and merge to the source branch first, then promote the selected SHA through the release policy. Do not hand-edit the release branch as normal workflow.
Current Fairway Operating Rule
Fairway is the durable coordination record. Provider chats, tmux panes, CI watchers, and CLI sessions are replaceable execution attachments. Medium and high-risk work needs task evidence, provider/session checkpoints, review-domain records, and active reconciliation before closeout. CI/deploy waits should use deterministic monitor utilities and handbacks rather than agent-side polling.