Developer shares 15-stage framework to fix AI coding's hidden pitfalls beyond the prototype

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A software developer with over a decade of experience has outlined the systemic challenges that emerge when using AI tools to build production-grade software. While AI can generate working code quickly, problems such as context drift, security gaps, redundant abstractions, and lack of consistency tend to surface as codebases grow larger. After completing three major AI-assisted projects, the developer identified that a structured process — not better prompts or tools — was the missing ingredient. This led to a 15-stage development framework covering planning, architecture, testing, security, and automation, designed to impose engineering discipline on AI-driven workflows. The developer has compiled these insights into a handbook titled 'Vibe Coding with Confidence' to help others avoid repeating common mistakes.

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