My impression has always been it's more important the build the correct thing (what the customer needs/wants) rather than more stuff faster.
The process of learning what the customer needs/wants is a heavily iterative one, often involving throwing prototypes at them or betting at a solution, then course-correcting based on their reaction. Similarly, the process of building the correct thing is almost always an iterative approximation - correctness is something you discover and arrive at after research and prototypes and trying and getting it wrong.
All of that benefits from any of its steps being done faster - but it's up to the org/team whether they translate this speedup to quality or velocity. For example, if AI lets you knock out prototypes and hypothesis-testing scripts much faster, you can choose whether to finish earlier (and start work on next thing sooner), or do more thorough research, test more hypothesis, and finish as normally, but with better result.
(Well, at least theoretically. If you're under competitive pressure, the usual market dynamics will take the choice away, but that's another topic.)
why do you think restaurants rarely change their menus.
But people who have only wrote software their entire life wouldn’t know that would they?
It’s like the econ prof’s who theorise about the theory of the firm but have never done it themselves.
When prototypes are harder to build you focus on answering the biggest questions. I feel like you spend more time iterating on details in CAD, even when the larger idea is invalid.
The difference is all that pre-work. The problem with that is some things are only obvious after you've built one and it doesn't fit just right for some reason. That reason is impossibly harder to just reason about and figure out vs iterating where possible. For software things that's easier. For hardware, we have stories like the palm pilot engineer having a wooden block with them for a week before deciding on the form factor for it. Such pre-work is valuable, but if the cost of prototypes is way down, you can afford to iterate instead of trying to psychically predict everything up front. Of course that doesn't work for eg trips to the Moon, but most busineeses aren't doing that.
Even so-called UX and product experts get stuff wrong all the time. Going from idea to prototype to feedback in hours or days rather than days or weeks feels like a superpower, at least in the very customer facing parts of what we do.
Most business software isn’t complicated to implement (i.e. it doesn’t require multiple prototypes to determine which technical approach is best). Usually for most apps you approximately know the technical implementation. What requires taste, experience, or whatever you want to call it, is the user experience and if your software actually solves a real problem. You can’t really just churn on prototypes to solve that. You will lose the patience of your user base.
Also, give it time. Real adoption in boring companies started Q1. Q2 is, I think, this settling in and people learning how to do their work and manage their responsibilities. Q3/Q4 will be the time when I expect to start seeing higher velocities across all IT-adjacent products I use.
Thats just one set of costs but a good starting point.
The biggest downside is the feeling that people sometimes turn their brain off and aren’t even doing basic checks on some of the slop their LLMs produce.