[cml123]

The approach I've been trying to use at work is making heavy use of AI for the generation of experimental prototypes, but with little intention of keeping all that code verbatim. I can get something to the demo stage much more quickly than before, allowing me to show it to coworkers and users to get feedback on random possibilities. From there, I make a case to properly delegate time for "doing it the right way" as a slotted piece of work. That's resulted in a number of high-impact features being added to our app in the last few months, that in the past would have taken much longer or never came to fruition.

I'm using this specifically in the context of concepts/features that are hard to explain/sell without some working visual or prototype, but which aren't immediately evident needs or features requested by our users. Some of them go nowhere, but I think the net result is an increased ability for me to get my experiments from the "lab" to production.