Why is AI so bad at fixing bad back-end?
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AI definitely has come a long way, progressed beautifully in front-end, but when it comes to fixing bad backend code, it still struggles a lot.
The complexity often requires human intuition and deep understanding.
It can help spot some issues or suggest improvements, but relying solely on AI to untangle messy backend problems often falls short.
Has anyone had surprisingly good or bad experiences with AI in this area?
I'd love some advice (or you're free to rant)
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I literally built Airbolt.ai because I was so frustrated from having to rebuild backends when building AI apps. My strategy now is to just try to hardest to:
1. Just have as little code as possible and rely more on trusted libraries and managed services
2. Ideally have no backend at all
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@mark_watson_28 Sounds like a dream. I hope you get as many users as you want pretty soon.