Phased Rollout, KPIs, and Risk Management
Rollout sequence
Analysis-first → draft-PR-only → guarded merge → scaled merge.
- Foundation: component registry, dependency graph, generated-code heuristics, ownership graph, telemetry pipeline.
- Pilot: agents do analysis + PR drafting only, no merges.
- Guarded scale: merges in a few well-tested components with strong owner engagement.
- Broad scale: expand concurrency + blast radius only after stable metrics on PR quality, rollback rate, stakeholder latency.
Illustrative timeline (Aug 2026 – Sep 2027)
| Phase | Window | Work |
|---|---|---|
| Foundation | Aug–Oct 2026 | Inventory graph, ownership map, SBOM, generated-code heuristics; OTel pipeline, dashboards, cost telemetry, alerting; sandbox runner, IAM/OIDC, secrets, policy engine |
| Pilot | Nov 2026–Jan 2027 | Analysis-only agents + triage UI; draft-PR pilot in low-risk packages |
| Guarded scale | Feb–Apr 2027 | Targeted merge enablement with merge queue; expand to 100–200 active lanes |
| Broad scale | May–Jul 2027 | Cross-team routing, richer review bot, nightly batch analysis; expand to 300–500 active lanes, larger waves |
| Full fleet | Aug–Sep 2027 | 1,000 logical agents with bounded active concurrency |
KPI gates (decide whether next wave may scale)
| KPI | Target direction |
|---|---|
| PR pass-through rate without manual rewrite | ↑ |
| Mean repair loops per task | ↓ |
| Stakeholder question rate per task | ↓ |
| Stakeholder answer SLA compliance | ↑ |
| Rollback/revert rate after merge | ↓ |
| Median lead time task-start → merged PR | ↓ |
| Cost per merged PR | ↓ |
| Cross-path conflict rate | ↓ |
Stop metrics (any worsens materially after scale increase → pause wave, fix platform before adding concurrency):
- rollback rate
- merge-queue instability
- stakeholder backlog growth
- model-cost anomalies
Top risks + mitigations
Risks are organizational as much as technical.
| Risk | Mitigation |
|---|---|
| Unclear ownership | Canonical component ownership |
| Weak test oracles | Dynamic evidence from traces; test-density-first canaries |
| Oversized PRs | Smaller task scopes; small reversible PRs |
| Hidden runtime coupling | Trace/eBPF evidence in inventory |
| Over-aggressive concurrency | Hard caps on active edit lanes |
| Generated code churn | Stricter generated-code exclusion |
| Reviewer fatigue | Reviewer bots explaining changes in business language |
A 1,000-agent program is realistic not because 1,000 editors write at once, but because the platform turns a massive migration into a well-observed stream of small, reversible, policy-compliant decisions.