AI-Built Software Production Readiness
Your AI-built software works. But is it production-ready?
Independent, principal-led assessment for software built with Cursor, Claude Code, Copilot, Lovable, Bolt, Replit, Devin, and similar tools. From a 2-day health check to full production architecture.
The Reality
It works. Nobody planned for what happens next.
AI coding tools produce working code — session by session, prompt by prompt. What accumulates is a system that runs, but was never designed as a whole. No capacity model. No failure strategy. No integration plan. Structural decisions accumulate with no coherent design intent tying them together.
This is how prompt-driven development works. The faster you shipped, the wider the gap between what you have and what production demands.
Warning signs
- Architecture accumulated, never designed
- Scaling assumptions match the prototype, not the roadmap
- One departure would make the codebase opaque
- No observability designed in — failure modes surface in production
- No defensible answer when a customer, investor, or regulator asks how the system was built
The Spectrum
Not all reviews are the same
There is a wide spectrum of options for reviewing AI-built software. Understanding where each sits helps you choose the right depth for your situation.
Low cost, high volume
Automated Scan
Finds known patterns. Cannot evaluate architecture, scalability, or whether the system survives its next growth step.
Mid-range
Code Review
Tells you what is wrong with the code. Does not tell you whether to fix it, rewrite it, or stop.
Principal-led engagement
Production-Readiness Assessment
A principal architect reviews architecture, security, maintainability, scalability, testing, deployment, and operations as an integrated whole. The output is a decision — not a findings dump.
We operate in the third category. Independent of implementation.
The Journey
Four steps. Start with one.
Each step answers one question. The journey adapts to what the diagnosis reveals — many engagements stop after Step 1.
Decide — What should we do?
Single defensible recommendation with Anti-Recommendation Rationale (why rejected paths were rejected)
You stop when you have your answer. No obligation to continue.
Why Us
What makes this different
Builder, not auditor
We bring hands-on experience shipping AI platforms to production — not theoretical audit frameworks. We review AI-generated code with pattern recognition grounded in building, not just scanning.
Diagnosis without implementation bias
No implementation team. No fix to sell. The recommendation can be: stop, do not productionize. That is a valid finding we will deliver clearly.
Decision-grade output
Output is a Five-Outcome Scorecard, an Anti-Recommendation Rationale, and a 30/60/90 action plan. A decision a CTO can sign — not a list of issues to interpret.
Architecture decisions in days, not quarters
The same principal who architected production systems under compliance and scale pressure — now applied to AI-built codebases.
Getting Started
Choose your entry point
Scope matched to your situation. Every engagement starts with a discovery call to confirm fit.
Startup CTO, funded founder
Quick Health Check
2–3 days
Know in 2–3 days if your AI-built system is production-safe. Fast, bounded assessment with a clear go/no-go signal and prioritised action plan.
View Vibe-Coded Software Review details
Head of Engineering, PE portco CTO
Production Decision
2–3 weeks
Full diagnosis plus a defensible path-forward recommendation. Cost/time/risk modelling for each viable option, with anti-recommendation rationale.
View Decision Sprint details
Enterprise CTO, PE operating partner
Enterprise Assessment
4–8 weeks
Complete production-readiness assessment for regulated or mission-critical systems. Full architecture blueprint with output calibrated for leadership, investment committee, or compliance review.
View Production Blueprint details
Trust & Rigour
How we work
10-Dimension Review Framework
Each dimension scored with evidence. AI-code-specific lens applied across all dimensions. Security is assessed at the architecture level — exposure and posture, not penetration testing or certification.
Principal Credentials
- Multi-year enterprise architecture across regulated, high-compliance environments
- AI platform builder — prototype to production
- Daily practitioner across the AI coding tool ecosystem
Code Handling Protocol
- NDA signed before any repo access
- Code reviewed under strict handling policy
- No code retained after engagement closes
- AI tool usage disclosed transparently
- Full security protocol shared during discovery
Fit
Is this right for you?
This is for you if...
- Your AI-built system is about to face enterprise customers, investors, or regulators
- You need an independent answer before committing to a fix, refactor, or rewrite
- Your team cannot confidently explain the architecture underneath the working software
- You are a PE operating partner evaluating an AI-built acquisition target
- You inherited an AI-assisted codebase and need a production-readiness baseline
- A product agency delivered fast and you need pre-launch confidence
This is not for you if...
- You need an automated code scan — there are good tools for that
- You want the auditor to also fix the code — we are independent of remediation
- Your system is pre-product with no users and no timeline pressure
- You need ML model performance tuning — different specialisation
- You need a penetration test or SOC2 certification — we flag exposure, we do not certify
Questions
Frequently asked
Ready to know?
A 30-minute discovery call. No commitment. We will tell you whether an assessment makes sense for your situation — or point you to the right alternative if it does not.
Typical response within 24 hours.