AI App Development: What I Learned in One Month
Article Summary
Antoine van der Lee shipped an AI-powered app in one month and hit a wall so hard he almost killed the project. His biggest mistake? Moving too fast.
Van der Lee documented his first serious attempt at AI-native app development, building Vydio (formerly YT Studio Optimizer) using AI agents and tools like Codex. What started as an exhilarating sprint turned into a cautionary tale about the hidden costs of AI-accelerated development.
Key Takeaways
- Tech debt compounds faster with AI: agents create assumptions without strict guidance
- Google rejected his OAuth app twice, forcing a complete rebrand three weeks in
- Using the app daily on iOS revealed critical issues invisible during Mac development
- AGENTS.md files and SwiftLint became essential after losing control of the codebase
- ChatGPT suggested terrible names; real conversations with humans saved the brand
AI agents can 10x your development speed, but without proper guardrails and dependency validation, you'll either drown in tech debt or build something you can't ship.
About This Article
After a month of AI-accelerated development, Antoine van der Lee's codebase spiraled out of control. Files multiplied beyond what a three-column layout could display, and he had no idea how the folder structure worked or what each file actually did.
Van der Lee wrote an AGENTS.md file to document best practices. He set up SwiftLint to enforce code standards automatically. Then he built a consistent refactoring process where agents cleaned up obsolete code after finishing each task.
These guardrails gave Van der Lee back control of his codebase. He could now apply changes manually and efficiently, and the project became sustainable beyond the initial proof-of-concept stage.
