A developer's journey through AI coding tools reveals a growing recognition that detailed specifications prevent critical edge cases from being missed. After experiencing what they call "AI psychosis," the author embraced spec-driven development in YAML format to maintain control over complex projects. This approach addresses the limitations of AI assistants that often miss important details during code generation, requiring repeated corrections and creating technical debt.

The solution developed is Acai.sh, a comprehensive tool for managing acceptance criteria through numbered requirements. The platform includes a feature.yaml format for writing specs, a CLI for integration into development workflows, and a web dashboard for tracking progress. The system automatically tags code references to requirements, enabling teams to verify implementation against specifications rather than just reviewing code files.

The workflow emphasizes writing concrete, testable requirements first, then shipping code that references each numbered acceptance criteria. This approach transforms how teams review pull requests by focusing on requirement coverage rather than line-by-line code inspection. The hosted version remains free indefinitely, with source code available under Apache 2.0 license, making it accessible for teams seeking structured AI-assisted development practices.