The Vibe‑Coded App That Pager-Dutied Us: A Step‑by‑Step Rescue Playbook
Audit what the AI actually shipped, refactor without breaking revenue, and deploy with guardrails that prevent “one prompt to rule them all” from taking prod down again.
Vibe-coded apps don’t fail because the code is “messy.” They fail because nobody can predict what a change will break—and production is where you find out.Back to all posts
Key takeaways
- Treat vibe-coded apps like incident response: stabilize first, refactor second.
- Start with a dependency + security + runtime behavior audit; don’t guess.
- Write characterization tests before any “cleanup” PRs to avoid silent behavior changes.
- Refactor in thin vertical slices using strangler patterns and contracts, not Big Rewrite Energy.
- Deploy with canaries, observability, and rollback hooks—then track MTTR, change failure rate, and SLO burn.
Implementation checklist
- Define 2–3 SLOs (latency, error rate, availability) and instrument `RED` metrics
- Generate SBOM (`syft`) and scan for known vulns (`trivy`, `osv-scanner`)
- Run secrets scan (`gitleaks`) and add a pre-receive/pre-commit gate
- Add baseline lint/format/typecheck (`eslint`, `prettier`, `tsc` or `ruff`, `mypy`)
- Create characterization tests for top 5 revenue/user flows
- Introduce request validation + centralized error handling (e.g., `zod`, `pydantic`)
- Add CI with test + SAST + container scan gates
- Deploy behind canary (`Argo Rollouts`/`Flagger`) and verify rollback works
- Track: change failure rate, MTTR, flaky test rate, vulnerability count, p95 latency
Questions we hear from teams
- How do I know if I should refactor or rewrite a vibe-coded app?
- If you can ship vertical slices behind feature flags, add characterization tests, and get MTTR/change failure rate trending the right direction within 2–4 weeks, a refactor rescue usually wins. If the architecture blocks basic seams (no testability, no deploy isolation, data model fundamentally wrong), you may need a strangler-style rebuild—but still not a “stop the world” rewrite.
- What’s the minimum test suite that actually helps?
- Characterization tests for the top 5 user/revenue flows, plus one integration harness using Testcontainers (or equivalent) so you can trust DB/cache behavior. Add a tiny E2E smoke suite (Playwright) that runs in CI. That combination catches most of the real regressions without boiling the ocean.
- Which tools give the fastest signal on vibe-coded risk?
- `gitleaks` for secrets, `osv-scanner`/`trivy` for vulnerabilities, `semgrep` for high-signal code issues, and `OpenTelemetry` for runtime truth. If you’re in GitHub, CodeQL is also worth enabling for baseline coverage.
- How do I deploy safely if I’m not on Kubernetes?
- You can still do canaries: weighted traffic at the load balancer (NGINX/Envoy), or versioned deployments behind feature flags, or blue/green with fast rollback. The core requirement is the same: automated rollback and metrics that tell you “the new version is hurting users” within minutes.
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