From vibe-coded to production-ready
You built your app fast with AI, and it worked: real users, real momentum. Now it needs to hold up. Security, tests, deploys, monitoring. We harden AI-built apps for production while you keep shipping.
assessment first · fixed quotes · your stack · focused hardening plan
What happens after the prototype works?
Who it fits: teams whose AI-built app has users, customer data, or an enterprise prospect and now needs a dependable release process.
The assessment: we inspect the important user flows, code, permissions, tests, deployment, data handling, and monitoring. You receive a prioritized plan with evidence and a clear account of what was checked.
Hardening work: after you review the plan, we agree on a fixed scope and quote for the fixes, tests, CI, deployment, or monitoring work you want done. The handoff includes the changes and how to operate them.
Access and scope: we agree on repositories, environments, credentials, data, and safe test boundaries before starting. We can work in your environment where that is required.
Quote and timing: a discovery call sets the assessment scope, fixed quote, and timeline. Hardening is quoted separately from the findings, so you can choose what to implement.
Tell us about your app →The app is real. Now make it solid.
This engagement exists because founders kept asking us for it. The story is always the same, and it’s a good story.
You built it fast, and it worked
Lovable, Bolt, v0, Claude Code: you turned an idea into a real product in weeks. People are using it. Building fast with AI was the right call, and we’d have made the same one.
Now it’s carrying real weight
Paying customers, an investor, an enterprise prospect asking about security. A codebase that was perfect for finding product-market fit is now holding up things that matter.
Production-ready starts with a focused checklist
The difference between vibe-coded and production-grade is a set of specific, fixable things: security, tests, deploys, monitoring, data safety. We work through them while you keep shipping.
Six dimensions of production-ready
Focused improvements across the foundations that help your application stay reliable as it grows.
Security
Customer isolation, credentials, payment checks, and usage limits. We investigate the gaps and implement focused fixes.
Plan your security checks →Tests & CI
A test suite that covers the workflows that matter, wired into CI to protect checkout through every change from your team or AI.
Deploys & environments
Real environments, boring repeatable deploys, rollbacks that work, and a consistent path for every production change.
Monitoring & reliability
Error tracking, logging, uptime alerts, and backups that restore keep your team informed early and make recovery routine.
Data model & architecture
Schema cleanup, query performance, and the structural decisions that keep the application ready to grow.
Maintainability
Conventions, docs, and a legible codebase help the next engineer or agent become productive in days.
See everything before we fix anything
Assessment first, then a prioritized plan with fixed quotes. You stay in control of scope the whole way.
Assessment
We map the application and inspect the workflows that matter, combining code analysis, configuration review, and targeted checks across security, reliability, tests, deploys, and data.
Prioritized plan
A concrete list ordered by risk and business impact, with the complete plan available for your review before implementation begins.
Hardening sprint
We fix the critical items, alongside you or solo, while you keep shipping features. Scope stays fixed and progress stays visible throughout.
Handoff
Docs, conventions, and a walkthrough of what changed and why. If you want ongoing backup after, that’s our startup advisory.
Curtis Myzie
Curtis has spent 20+ years taking software to production, as an engineer and as CTO, VP of Engineering, and VP of Product at venture-backed startups.
Today he builds Deep Noodle’s own SaaS and agent products with AI-native workflows, and runs AI-accelerated security reviews for client codebases. He knows how to identify what already works, strengthen the parts carrying risk, and preserve your momentum.
CTO, VP Engineering, and VP Product at venture-backed startups
Ships his own AI-built products to production today
Runs AI-accelerated security reviews for client codebases
Works with frontier AI models and agent tooling every day
Open-source maintainer (Dive, Risor, Wonton) with 1,000+ GitHub stars
Common questions
// built fast? good. now make it hold.
Get your app ready for real users
Book a call and tell us what you built. We’ll scope the assessment and you’ll know exactly where you stand within days.