I let AI write 100% of my code for 30 days. Here’s what broke

Описание и применение

AI быстро генерирует скелет и шаблоны кода, но не удерживает целостность системы, иногда пишет правдоподобный, но неверный код и не учитывает крайние случаи. Человеческий обзор и разделение ролей критичны для успешного производства.

Задача

Can an AI generate all application code without human coding, and what failures arise when relying solely on AI for production code?

Результат

AI can rapidly scaffold and boilerplate code, but struggles with system‑wide coherence, subtle logic errors, debugging, and edge‑case handling. Human review and separate roles are essential to catch plausible‑but‑wrong code and maintain architecture integrity.

Рабочий процесс

• 1. Set rules: no hand‑coding, AI writes, reviewer approves, breaks logged after >1h stuck
• 2. Prompt AI for scaffolding (Next.js, Postgres, Drizzle, auth)
• 3. Generate boilerplate (CRUD, Zod, table component)
• 4. Review AI output, reject or re‑prompt as needed
• 5. Log breaks when AI fails to hold system coherence, writes wrong logic, or over‑adds features
• 6. Fix breaks manually after AI fails to resolve
• 7. Iterate until product is production‑ready
• 8. Implement guardrails: separate author, reviewer, and merge gate

Доказательства

The AI optimizes locally. Coherence across a system is still a human job.

Источник

The billing webhook handler it wrote acknowledged Stripe events before persisting them.

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When something broke that the AI couldn't see, asking it to fix it produced changes, not fixes.

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