The only thing here that _maybe_ has a durable long term moat is the first point. Even then, I don't see why stronger models can't also have discernment once mo

The only thing here that _maybe_ has a durable long term moat is the first point. Even then, I don't see why stronger models can't also have discernment once more companies close the loop with their AI and their relevant company metrics. The other 3 you literally just get for free as models improve. The "state of the art" of "prompting" changes literally every week. It was loops, then graphs, now its harnesses (and self automating harnesses)? Why are these not just obviated by better models? These are barely skills, and are imo, just the tech equivalent of tabloids advertising 5 minute exercises or pills to get rid of stubborn belly fat. No amount of prompt engineering or graphs or loops could get your previous version of GPT to perform like Fable, and yet somehow Fable can do all of that and more without any random built in "ai engineering skills." The labor chart for SWEs will look like a slope up as productivity with AI increases, and then past a certain point where AI is like 99% good enough, employment will fall off a cliff. We are already seeing this with junior hiring, and who is to say that AI will magically only ever be as capable as a junior engineer?