Which part interested you the most?

Great point, and yes — I've seen this play out more than once. What you're describing is actually an extension of the same root cause: we assume the solution is done once it's deployed. But I think production is really where the learning starts. Moving something to production (infrastructure-wise) doesn't mean it's the final version — it just means it's ready to be observed. That's why I try not to over-invest in the first attempt. Delivering a solution (regardless of the results) to a real problem is already the first win. AI solutions are no different, and honestly, they might require even more of this cycle because their behavior can be less deterministic than traditional code. So the "layer that isn't visible" you mentioned — I'd argue it should actually be the goal when you go live. And when you finally realize that behavior varied once users start using your proposed solution, isn't that a layer starting to reveal itself? Tweak it, and be ready for the next one.

It depends on the provider you use. It's common to use standard api key.