Aguilar Dev audits and rebuilds AI-generated codebases — pairing senior engineering judgment with AI-assisted analysis to catch what shipped-fast code usually misses.
Patterns that show up again and again in codebases built fast with AI tools.
A real developer looked at the repo and went quiet.
Every new feature seems to break two old ones.
You're not sure what's actually protecting user data — or if anything is.
Due diligence, a security review, or a new hire is coming, and you're dreading it.
It works today at 50 users. Nobody's checked what happens at 5,000.
Three stages. You can stop after any one of them.
A full pass through the repo — architecture, data handling, auth, error paths, scaling limits, test coverage. You get a prioritized findings report.
A scoped engagement to fix what the audit flagged, starting with anything that could lose you data, users, or a deal.
Monthly retainer for teams still shipping fast with AI tools — architecture and PR review before bad patterns creep back in.
A representative finding from a real category of issue.
Flat and scoped. You know the number before anything starts.
Full findings report with severity ratings and a prioritized fix list.
Scoped fix engagement based on your audit findings, priced after scoping.
Architecture and PR review, monthly. Cancel anytime.
I'm a senior software engineer working daily on a production distributed system with 25+ microservices in active use — keeping real infrastructure from falling over, not just reading about how to. Aguilar Dev applies that same standard to codebases that got built fast and never got checked.
Then you get a short report and peace of mind — that happens, and it's a good outcome. You only move to a rework sprint if there's something worth fixing.
No. I work directly from the repository. If the original builder (human or AI tool) is available for context, that helps, but it's not required.
Most common web stacks — JavaScript/TypeScript, Python, and the databases and cloud platforms (AWS, Azure, GCP) they typically sit on. Ask if you're unsure whether yours fits.
No — it's also a good fit for small teams or agencies that inherited an AI-built app from a client or an earlier hire and need to know what state it's actually in.
Tell me about the codebase. I'll reply with next steps within one business day.