Common Issues
general
I Can't Add a New Feature Without Breaking Something
You want to add a new feature to your AI-built app, but every time you prompt the AI to add something, it breaks existing functionality. You're stuck in a loop where fixing one thing breaks another.
Common Causes
- The codebase has accumulated too many AI-generated patches on top of patches
- No separation of concerns — everything is intertwined
- The AI doesn't understand the full context of the existing codebase
- No tests, so there's no way to know if a change breaks something
- The architecture wasn't designed to be extended
How to Fix It
- Stop trying to add the feature via prompting if it keeps breaking things
- Describe the feature you want and what keeps breaking to a developer
- The developer can refactor the affected area first, then add the feature properly
- Consider whether the app needs some architectural cleanup before adding more features
- A code review can identify the most fragile areas and suggest how to stabilize them
Real developers can help you.
Stanislav Prigodich
15+ years building iOS and web apps at startups and enterprise companies. I want to use that experience to help builders ship real products - when something breaks, I'm here to fix it.
Matthew Butler
Systems Development Engineer @ Amazon Web Services
Matthew Jordan
I've been working at a large software company named Kainos for 2 years, and mainly specialise in Platform Engineering. I regularly enjoy working on software products outside of work, and I'm a huge fan of game development using Unity. I personally enjoy Python & C# in my spare time, but I also specialise in multiple different platform-related technologies from my day job.
Alvin Voo
I’ve watched the tech landscape evolve over the last decade—from the structured days of Java Server Pages to the current "wild west" of Agentic-driven development. While AI can "vibe" a frontend into existence, I specialize in the architecture that keeps it from collapsing.
My expertise lies in the critical backend infrastructure: the parts that must be fast, secure, and scalable. I thrive on high-pressure environments, such as when I had only three weeks to architect and launch an Ethereum redemption system with minimal prior crypto knowledge, turning it into a major revenue stream.
What I bring to your project:
Forensic Debugging: I don't just "patch" bugs; I use tools like Datadog and Explain Analyzers to map out bottlenecks and resolve root causes—like significantly reducing memory usage by optimizing complex DB joins.
Full-Stack Context: Deep experience in Node.js and React, ensuring backends play perfectly with mobile and web teams.
Sanity in the Age of AI: I bridge the gap between "best practices" and modern speed, ensuring your project isn't just built fast, but built to last.
Vlad Temian
15+ years shipping production infrastructure for startups. Former CTO at qed.builders (acquired by The Sandbox).
Cursor ambassador and agentic tooling builder.
I've scaled systems, automated deployments, and built observability tools for AI coding workflows. I specialize in taking vibe-coded apps from broken prototype to production-ready: fixing Supabase auth/RLS, Stripe integrations, deployment pipelines, and cleaning up AI-generated spaghetti.
I build tools in this space (agentprobe, claudebin, micode) and understand both sides: how AI generates code and why it breaks.
https://blog.vtemian.com/
Krishna Sai Kuncha
Experienced Professional Full stack Developer with 8+ years of experience across react, python, js, ts, golang and react-native. Developed inhouse websearch tooling for AI before websearch was solved : )
Matt Butler
Software Engineer @ AWS
Luca Liberati
I work on monoliths and microservices, backends and frontends, manage K8s clusters and love to design apps architecture
Dor Yaloz
SW engineer with 6+ years of experience,
I worked with React/Node/Python
did projects with React+Capacitor.js for ios
Supabase expert
Jacek Rozanski
Senior PHP/Symfony developer and DevOps engineer with 20+ years of professional experience, running opcode.pl (web development agency, est. 2004).
Day job: I'm the sole backend developer at merketing company where I own and maintain 11 PHP/Symfony microservices on AWS (ECS Fargate, RDS, S3, CloudFront), handle the full CI/CD pipeline (Bitbucket Pipelines, Docker), and manage monitoring with Sentry and CloudWatch. These services handle high request volumes in production every month.
What I bring to AI-built apps:
- I audit and fix security issues (OWASP methodology), performance bottlenecks, and architectural problems in codebases generated by Cursor, Claude Code, Lovable, Bolt, and v0
- I refactor AI-generated prototypes into production-grade applications with proper error handling, testing, and clean architecture (SOLID, DDD, hexagonal architecture)
- I set up the infrastructure AI tools don't touch: AWS hosting, CI/CD pipelines, automated deployments, database optimization, monitoring, and alerting
- I integrate external services: payment providers, email systems, partner APIs, SSO/auth
Tech stack: PHP 8.x, Symfony, React, Next.js, PostgreSQL, MySQL, Docker, AWS (ECS, RDS, S3, SQS/SNS, CloudFront), Terraform, Supabase. I also use AI tools daily (Claude Code, Cursor) in my own workflow, so I understand both the strengths and the gaps in AI-generated code.
Based in Poland (CET timezone). Available for async work and calls during EU/US business hours.
Describe what's wrong in plain English. No technical knowledge needed.
Get HelpFrequently Asked Questions
Is my AI-generated codebase salvageable?
Almost always yes. A developer can refactor the messy parts, add proper structure, and make the codebase easier to extend. It's almost always cheaper than starting over.
Should I start over from scratch?
Rarely. Refactoring specific parts is usually faster and cheaper. A developer can tell you whether a rewrite makes sense after reviewing the code.