Diagnose
- Audit codebase, dev workflow, and AI usage patterns
- Find what's hurting, what's working, what's missing
- Prioritize fixes by business impact
Output: A clear diagnosis and a prioritized fix plan
Vibecoded MVP → working business
Your vibecoded MVP isn't broken. The delivery system around it is missing.
You've tried switching AI tools. You've tried refactor sprints. The fix is the delivery system AI never built.
I find what's missing, build it, and leave you with a codebase that ships without me.
So you can ship without fear of breaking what works.
- 15+years of engineering
- 4K+RPS production systems
- 14+teams delivery accelerated
The cracks in a vibecoded MVP show up the same way every time.
- One feature gets added. Three others quietly break. You spend the next two days figuring out which.
- There are parts of your code nobody fully understands — including you. Touching them feels like Russian roulette.
- AI keeps rewriting the same code differently. Each fix undoes the last one. You're paying for tokens to go in circles.
- Demo works fine. A real user enters something weird, and prod breaks at 3 AM. You stare at the code, no idea how it works.
None of these are bugs. They're what's missing — the system AI doesn't ship with the code.
The five layers of system AI doesn't ship
Five separate layers, each enforces something AI doesn't. Together they're the system that keeps your codebase shipping.
Why me
I don't replace your AI. I build the system around it. Same pattern as the startup-mode codebases I've cleaned up for years — different generator, same fix.
Victor Demin
Fractional CTO / engineering delivery consultant
- 15+ years across PHP, Python, Java, TypeScript, Node, C++, C#, iOS, Android (and yes, Flash once). The codebase patterns that kill delivery don't change with the stack. AI just made them faster.
- I've fixed this pattern at Wowworks — startup-mode codebase to EU-ready production — and at an EdTech scale-up. The cleanup pattern is older than AI — different source, same fix.Wowworksbugs ↓10×delivery ↑3×efficiency ↑4×EdTechdelivery ↑2×downtime ↓10×eNPS −100→100
- Wrote about this exact cleanup pattern on Habr in 2023, before AI accelerated it. Same fix, different generator.
- I do the work, not just advise. Architecture, guardrails, AI workflow tuning, refactoring — hands-on.
How I work
No pre-decided fixes. First we see what's actually broken. Then we make changes safe to ship. Then we make the system one that scales.
01
Diagnose
1–2 weeks
02
Safety net
Weeks to ~2 months
03
Scale
Ongoing — months
Safety net
- Set up dev fundamentals: git, CI/CD, monitoring, logs
- Add all five guardrail layers including AI-workflow
- Fix critical bugs they surface
Output: Production-safe codebase, critical bugs fixed, AI works inside guardrails
Scale
- Define target architecture and refactor toward it safely
- Tune for your real load profile
- Hire targeted specialists only if scaling demands it
Output: Maintainable codebase, team scales without re-breaking it
The goal isn't a heroic refactor sprint. The goal is reduced chaos, predictable shipping, and the confidence to keep going.
What to expect
- First improvements in CI/CD and monitoring within 2-4 weeks
- Critical bug fixes typically within the first month
- Architectural maturity unfolds over months — pace depends on starting state and team velocity
FAQ
Will I have to stop using my AI tools?
No. I'm a vibecoder myself — my own toolkit is Claude Code + Codex + JetBrains IDE. I'm stack-agnostic, so whatever your team uses is fine. The fix is the system around your AI workflow, not abandoning it.
How much does it cost?
Monthly retainer, hands-on, 2-4 months typical. Specific pricing depends on scope — we work it out in conversation.
Will I have to hire a bunch of new expensive developers?
Not necessarily. First we squeeze more from what AI is already doing — better rules, better guardrails, better architecture around it. If scaling demands specific expertise after that, we bring in targeted specialists. Hiring isn't the first move.
Will you work with our existing developer or CTO?
Yes. The system I build is meant to make whatever team you have ship faster — not replace anyone. If you have a CTO or developer, they stay in the picture and we collaborate on what gets implemented.
We've already tried switching AI tools / a refactor sprint / hiring a senior. What's different here?
Switching tools doesn't fix what's missing — the same patterns keep showing up. Refactor sprints without tests in place create new bugs instead of fixing old ones. A senior dev alone needs the system around the code to make changes safely. The difference is building that system first, enforced by tooling, not by team discipline.
What specifically do you put in place?
Standard tooling: Agents.md, linters (ESLint, PHPStan, mypy), type checkers, security scanners, test frameworks (Jest, Pytest, PHPUnit), GitHub Actions, Sentry/DataDog. None of it is exotic. The work is wiring them together so AI agents can't drift around them on the next request.
Is my user data at risk right now?
It might be. Vibecoded MVPs often have hardcoded credentials, missing input validation, and untracked dependencies — AI doesn't ship secure by default. Computer security was my university specialty; I treat it as a primary requirement, not an add-on. Phase 2 (Safety net) systematically addresses these patterns.
Who I'm not for
- Marketing and sales are your real bottleneck. You need a GTM operator, not a delivery one.
- You don't have a working MVP yet. Build it before fixing it.
- You're looking for free or DIY help. That's a different kind of service than this.
You don't need another AI tool. You need a fix that holds.
Just write me. We'll figure out fit fast and the right next step toward shipping without fear.