AI Studio / Gemini Full-App Generation is Becoming Extremely Frustrating

Google AI Studio
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Is anyone else facing this issue consistently with large-scale app generation?

I’ve been trying to build a production-grade financial infrastructure platform (Next.js + Firebase + PostgreSQL + Razorpay), and the workflow repeatedly collapses after long generations.

Typical cycle:

  • Large architecture prompt

  • AI generates huge codebase

  • One build error appears

  • AI starts “fixing”

  • Dependencies get rewritten

  • package-lock changes unexpectedly

  • unrelated files get modified

  • imports break

  • build completely fails

  • sometimes entire generated sections disappear

The worst part is:

  • massive token usage

  • hours of iteration wasted

  • context degradation after multiple fixes

  • architecture consistency completely breaks

I’ve noticed AI tools are very good at:

  • scaffolding

  • UI generation

  • architecture planning

  • isolated feature generation

But extremely unreliable for:

  • one-shot enterprise app generation

  • maintaining long-term consistency

  • fixing complex dependency/build chains

Current workaround that seems more stable:

  1. Build architecture only

  2. Commit immediately with Git

  3. Add ONE feature at a time

  4. Build-test after every feature

  5. Commit after every stable state

Basically treating AI like:

a very powerful junior engineer

instead of:

a fully autonomous fullstack architect

Would love to know:

  • What workflows are others using?

  • Best practices for preventing project collapse?

  • Better tools than AI Studio for large SaaS projects?

  • How are people handling dependency consistency and context drift?

Feels like the current generation of AI tools are amazing for acceleration, but still not reliable enough for complete enterprise-scale generation in one shot.

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