AI tools have put friction where it should be - by eliminating incidental friction. By incidental friction I mean, things that were really not ambiguous, but were made so due to lack of access to resources.
As an example, if i needed to navigate, I used a paper map. There was friction in pulling out a map, planning a route etc. This took time. With digital mapping apps this sort of incidental friction is not there.
Real friction is inherent ambiguity. For example, what product does the market need ? By eliminating incidental friction, AI allows us to focus on the smallest hard-problem where there is real-friction.
The wrinkle that needs to be added is that there are no truly universal rules as to what counts for incidental vs ambiguous friction - the definitions are relative to individual/project goals. I am working with some scientific instruments to map out chemical data, and 3d modeling is needed. I don’t particularly care about 3d modeling - it is incidental to me. The chemistry is the focal point. So the STL files are vibe coded so I can keep my focus on chemistry. But if I were working for the latest marvel movie, the reverse would be true. The actual chemistry would need to fit the script and the visual effect intended. To a scientist the visualization just needs to be good enough. To the film director, the world building physics and chemistry instead become the supporting actor.
People do this all the time. It's such a common problem in startups that all of the books, courses, advisors, and everyone else with experience talks about finding product market fit early and shipping MVPs to validate the product.
It's the most common startup advice and people still ignore it and build unvalidated things for years anyway.
It's too easy to get started on your big idea and then switch to a rhythm of working on the next task without ever stopping to validate the big direction
That does happen on occasion, the commonly-cited example being Half-Life. How awesome would it have been if the Valve team hadn't had to waste so much time, money, and personal energy on their initial failed prototype?
Unfortunately most studios ship their failures, either because they don't realize they built something crappy or because the alternative is bankruptcy. A cynic would say that if AI can reduce the cost of experimentation, it will only result in more bad games, while an optimist would argue that it will result in more good games. I think we'll find that they're both right.