Vibe-Code to Production — Harden Your AI-Built App for Real Users. Marc Lee Pack, CodeWrangler.
Your vibe-coded app works. Let's make it survive.
Cursor, Claude, Lovable, Bolt — AI coding tools have made it possible to ship something real in days. That's genuinely remarkable. But "it works on my machine" and "it handles 500 concurrent users with a security audit and a PagerDuty alert" are very different things. I bridge that gap.
Before.
After.
Auth that works but has no rate limiting or brute-force protection
Auth hardened: rate limiting, session management, and secure password flows
API routes with no input validation or error boundaries
Every API route validated, sanitized, and failing gracefully
Secrets stored in .env files checked into git
Secrets in a vault. Git history cleaned. Environment properly segmented
No logging — you find out about errors when users complain
Structured logging, error tracking, and uptime monitoring from day one
Database queries with no indexes, no connection pooling
Optimized queries, proper indexes, and connection pools that handle load
No CI/CD — deploy is a manual process or broken
Automated CI/CD pipeline — every push tested before it ships
A codebase the next developer will spend a week just understanding
Documented, typed, and organized so any developer can contribute immediately
The hardening
process
Codebase Audit
I read every part of your app — auth flows, API routes, data models, environment configuration, and third-party integrations. You get a written report with every production risk ranked by severity. Nothing starts until you've seen the full picture.
Security Hardening
Input validation on every route. Rate limiting and brute-force protection on auth. Secrets moved out of git and into proper environment management. SQL injection and XSS vectors closed. This is the layer that stops you from becoming a breach headline.
Reliability & Error Handling
Structured logging and error tracking set up from day one. Every API endpoint returns meaningful errors instead of 500s. Critical paths wrapped in try/catch with alerting. You find out about problems before your users do.
Performance & Scalability
Database queries profiled and optimized. Indexes added where they're missing. Connection pooling configured. Slow endpoints identified and fixed. The app that handled 10 users now handles 10,000 without rewriting it.
CI/CD & Deployment Pipeline
Automated tests written for the critical paths. GitHub Actions (or your preferred CI) configured to test every push. Preview deployments for PRs. Zero-downtime production deploys. No more crossing fingers when you ship.
Documentation & Handoff
Architecture documented. Onboarding guide written. Environment setup automated. The codebase is organized so that any developer — or any AI coding agent — can contribute from day one without asking you how anything works.
Common Questions
Ready to ship
with confidence?
Share your codebase and tell me what you've built. I'll review it, identify the real risks, and give you an honest production-readiness assessment before any engagement begins.