What you do
- Describe the desired outcome, constraints, and authority boundary.
- Review material design choices or production-risk gates.
- Inspect verification, review findings, and residual risk before release.
Product and engineering teams delivering repository changes / engineering
A delivered change with an explicit flow, truthful tracker state, proportionate verification, independent review, and release evidence.
The problem
AI can coordinate discovery, implementation, testing, and review across a long-running change while StackOS preserves dependencies and proof.
What you do
What the agent does
When this workflow helps
Before it starts
What proves it worked
Workflow path
A real run expands these stages around the request, context, selected tools, approvals, and dependencies.
Restate the engineering goal, delivery mode, constraints, project setup, host-agent format, and missing context.
Convert user intent into explicit user, data, system, and business flows, acceptance criteria, non-goals, and evidence expectations.
Map affected scopes, real execution paths, ownership boundaries, downstream readers, tests, docs, and signoff fallout.
Create or update tracker tasks/tickets with dependencies, sequencing, blockers, owned scopes, and definition of done.
Identify canonical ownership, shared operations, data invariants, adapter surfaces, grants, docs, tests, rollout, and rollback implications.
Challenge the requirements, impact map, ticket plan, and design before implementation.
Own the full proof plan before delivery: TDD/red-first automated tests, verification commands, agent-executed E2E/manual flow scenarios, expected…
Claim ready tracker tickets, implement one by one, update status, and record focused verification evidence.
Run and report the mandatory verification stack for the actual diff and risk profile.
Review completed delivery across behavior, QA, integration contracts, security boundaries, docs, tracker evidence, and release risk.
Safe stopping and recovery
Specialists inside this workflow