One thing we've seen repeatedly is that AI rarely creates the hard production problems it just lets you reach them much faster.

The prototype proves "can we build it?" Production has to answer "can we operate it?" That's where authentication, observability, retries, background jobs, rate limits, data migrations, and failure recovery become the actual product.

The teams moving fastest aren't rebuilding AI-generated code from scratch, but they also aren't deploying it unchanged. They use AI to compress the discovery phase, then apply engineering discipline to everything users don't see but absolutely depend on. That's the gap that separates a successful launch from a stressful first week.