• 5 min read • Namanyay Goel

Your AI-Built App Hit 50,000+ Lines and Now You're Lost: What to Do

airecoveryplaybookscalefounder

When vibe coding turns into chaos past 50k lines, use this four-step rescue plan to steady the ship without hiring a full engineering team.

Crossing 50,000 lines feels like winning until everything snaps. Features stop agreeing with each other, prompts drift, and the repo starts to feel like a haunted house. This is the recovery roadmap we use with non-technical founders who hit that wall.

Phase 1: Freeze and Inventory #

Step 1. Pause New Features for 10 Days #

You can’t regain control while shipping reactive patches. Announce a stability sprint to users and stakeholders. Promise reliability, not velocity.

Step 2. Map the System #

Run a repository census:

  • List every app route, API handler, scheduled job, and background worker.
  • Identify ownership (even if it’s “AI wrote this”).
  • Note environment variables in use across staging and production.
  • Capture integration points (Stripe, Supabase, third-party APIs).

If you don’t have a fancy tool, use a spreadsheet. The goal is plain awareness.

Step 3. Surface Active Fires #

Create a wall of shame: every known regression, bug report, and flaky test. Rank by customer impact. This becomes your crisis backlog.

Need help running the inventory fast? Talk with the Giga team and get a line-by-line map in 48 hours.

Phase 2: Establish Truthful Signals #

1. Install Observability First #

Before refactoring, give yourself visibility:

  • Error tracking: Sentry or Highlight for real-time exceptions.
  • Logging: Logflare or OpenTelemetry with consistent correlation IDs.
  • Performance: Vercel Analytics, LogRocket, or Supabase dashboards.

Plug these into a “Regressions” Slack channel. Every future claim of “fixed” references these dashboards.

2. Author a Smoke Test Suite #

Ship a command like:

npm run smoke

Include login, onboarding, billing, core feature usage, exports, and any process with high user value. Each test becomes the acceptance criteria for future AI-generated changes.

3. Rewrite Your Prompts with Guardrails #

Clarify non-negotiables:

  • Never touch /payments without explicit permission.
  • Always run smoke tests before claiming success.
  • When unsure, say “UNVERIFIED.”

Borrow language like “say UNVERIFIED if you cannot prove it” so the assistant stops guessing.

Phase 3: Cleanse and Consolidate #

1. Slash Dead Code #

Search for:

  • Feature flags permanently on/off
  • API routes unused in 30 days
  • Cron jobs with zero consumers
  • UI components buried under outdated experiments

Delete ruthlessly. Every line removed is one less surface area to drift.

2. Rebuild Shared Libraries #

Cursor loves duplicating utilities. Consolidate:

  • Date/time helpers
  • Validation schemas
  • Client SDK wrappers
  • Prompt templates

Write canonical versions, export them, and remove duplicates. Add lint rules to block reintroduction.

3. Restore Directory Ownership #

Assign yourself modules: “Authentication,” “Metrics,” “Exports,” “AI Coaching.” Ownership means you review every change touching that area—even AI-generated ones.

4. Reintroduce CI/CD Discipline #

Minimum pipeline:

  • Type-checks and lint
  • Smoke tests
  • Deploy previews (Vercel, Railway, Render)
  • Manual QA checklist before production deploy

Automate as much as you can. Every manual step invites drift.

Phase 4: Relaunch with Governance #

1. Create a New Roadmap Based on Outcomes #

Stop measuring features shipped. Start measuring:

  • Successful daily active users
  • Conversion to paid
  • Support tickets per 100 sessions
  • Infrastructure cost per user

Tie every planned feature to one of those outcomes. If it doesn’t move a number, it waits.

2. Reopen Feature Work Gradually #

  • Start with small, reversible changes.
  • Feature flag anything that touches core flows.
  • Demand evidence (tests, demos, logs) for every release.

3. Schedule Recurring Audits #

Every two weeks, review:

  • Prompt health (are instructions still obeyed?)
  • Observability dashboards (any new classes of errors?)
  • Dead code (did drift reappear?)

4. Update Documentation in Lockstep #

Your README, runbooks, and onboarding docs should evolve with the repo. Let AI draft, but let humans approve.

Want someone to run the relaunch cadence with you? Grab the Giga handbook and get a simple operating system.

Prevention Strategies for the Next 50k Lines #

  • Define “done” in code, not conversation. Automated tests and dashboards talk louder than reassurance.
  • Limit prompts to bounded scopes. “Refactor the sync queue” beats “Clean up the project.”
  • Budget time for maintenance. Hold 25% of capacity for guardrails.
  • Practice saying no. If a feature does not move revenue, retention, or trust, park it.
  • Handle security drift early. Use the vibe-coded security checklist to tighten sensitive endpoints before the next crisis.

When to Bring in Help #

  • You don’t know where data flows. You need a forensic audit.
  • Deploys fail more than they succeed. You need a release manager (fractional works).
  • AI responses feel random. You need a prompt overhaul.
  • Customer trust is eroding. You need to ship reliability, now.

If the 50,000-line cliff feels familiar, get support before the next optimistic message pushes you further off course.

Let’s rebuild control together. Meet Giga for a roadmap session and leave with a plan you trust.

Control is not about memorizing every line. It is about spotting trouble fast and having the tools to fix it.