Quick answer
Gradual rollout for new models and prompts means: ship behind a feature flag, expose to a small tenant cohort, watch error rate and success funnel, then increase percentage—never flip 100% on Friday. Pair Unleash (or PostHog flags) with GlitchTip and product analytics. CorpIM demo todo FLAG-API2 shows increasing API v2 rollout for paid tenants only after CI is green.
Key takeaways
- Flags should target tenant + plan, not only random users.
- Define rollback: previous model ID and prompt version pinned.
- Wednesday release review checks flag % + open errors.
- Security CI gate blocks release if container scan has HIGH findings.
- Changelog and status comms are part of rollout, not afterthoughts.
Who this is for
- Engineering leads shipping model swaps, prompt template changes, or new agent tools.
- Product teams measuring adoption during flag exposure—see adoption metrics.
- Teams that have burned production with a “small prompt tweak” on Thursday evening.
Who should skip
- Single-tenant internal tools with no customer SLA.
- Batch offline pipelines with no user-facing latency—use backfill jobs instead of flags.
- Pre-production prototypes with no metrics instrumentation.
Rollout ladder
| Stage | Exposure | Gate to advance |
|---|---|---|
| 0 — Internal | Staff tenants only | Manual QA + eval set pass |
| 1 — Staging | Preview PR envs | CI green + integration tests |
| 2 — Canary | 5% paid tenants | Error rate ≤ baseline; funnel stable 24h |
| 3 — Expand | 25% → 50% | p95 latency within budget; support tags flat |
| 4 — Full | 100% | 48h clean metrics; changelog published |
What to watch
| Signal | Threshold (typical) | Action |
|---|---|---|
| Error rate | +2× baseline for 10 min | Pause flag increase; consider rollback |
| p95 latency | +30% vs pre-rollout | Check model size / region / queue |
| Success funnel | −5% on exposed cohort | Prompt regression—not “user confusion” |
| Support tag spike | Correlated with flag exposure | Pause; run RCA |
| Security scan | HIGH container finding | Block release until patched |
Rollback checklist
- Pin previous
model_idandprompt_versionin config—not “redeploy and hope.” - Decrease flag to 0% for new model; verify error rate normalizes within 15 minutes.
- Post status update if customer-visible API degraded.
- Log rollback in change-management evidence for SOC 2.
- Postmortem before re-attempting rollout.
Release playbook integration
CorpIM Guide playbook Release v0.x: CI green → security scan → changelog → Unleash increase → 24h GlitchTip watch. Links engineering and product loops. Schedule on Wednesday per weekly operating rhythm—not Friday afternoon.
Common rollout mistakes
- Random user % on multi-seat B2B—one tenant sees mixed models across users.
- No cohort compare—you cannot prove flag caused funnel drop.
- Prompt + model change in one flag—cannot isolate regression.
- 100% on new model because eval leaderboard improved—leaderboard ≠ your task.
- Skip security scan for “AI hotfix”—container CVEs still block enterprise deals.
CorpIM demo
Studio → Product → Flags app; Engineering → security scan blocker. Copilot: “Summarize blockers for release v0.2.”
FAQ
Feature flags vs blue/green deploy?
Blue/green swaps app binaries; flags swap model/prompt logic inside running app. AI products often need both: deploy code safely, then ramp model exposure independently.
PostHog flags vs Unleash?
PostHog ties flags to product analytics cohorts—strong for adoption measurement. Unleash excels at runtime flag delivery in app code. Many teams use both or one integrated stack.
How long between 5% and 50%?
At least 24h of clean metrics at each step for customer-facing API changes. Faster only for internal tenants or non-critical features.
Do we need observability before rollout?
Yes. Without errors + traces + funnels, gradual rollout is gradual blindness.