Why most AI apps fail in production (not in demos)

A demo is a story.
Production is a stress test.

I’ve seen AI apps that feel like magic on a laptop…
then crash the moment 10 users show up.

Why?

Latency kills the experience

LLM outputs become unpredictable at scale

No fallback when the API rate limits hit

Prompt engineering works once, not for every edge case

I learned this the hard way:
Reliability > cleverness.

If your AI stops working at 2 AM on a Sunday…
users don’t care how good the demo was.

Build for chaos, not for applause.