AI coding tools build fast. But fast builds accumulate synthetic technical debt — duplicated logic, hidden security risks, fragile deployments. We fix that.
LLMs generate similar code across prompts without context. The result is redundant modules, conflicting implementations, and a codebase that fights itself.
Exposed secrets, unsafe auth flows, missing rate limits. AI tools don't enforce security discipline — they produce whatever compiles.
Design decisions fragmented across hundreds of prompts. There's no coherent intent — just accumulated responses that happened to work in demo.
No CI/CD, missing environment config, no monitoring. Works on localhost, collapses in production. The gap between demo and deployment is enormous.
Normalize structure, remove duplicated and hallucinated components, stabilize dependencies, restore architectural coherence. Your codebase becomes understandable again.
Scan for exposed secrets, review auth and access control, audit dependencies, identify injection vulnerabilities. Your project becomes safe to expose to users.
Containerization, deployment pipelines, logging, monitoring. The gap between your demo environment and production gets closed — permanently.
You shipped the MVP. It works in demos. But you know the codebase is fragile. Scaling it feels risky. aiunslop is the engineering layer between prototype and production.
aiunslop is accepting early access members. Be among the first to bring your AI-built project onto a stable production path.
Request Early Access →