I'm just speculating why the current structure of companies is not maximizing what AI can offer. Until it becomes completely self-directed and reliable, using a tool that allows you to move fast requires more technical knowledge, not less. What you're missing from your example is releasing to production without breaking it, dealing with increasing complexity as more features are added, maintaining development pace as more features are added, and trying not to create more bugs than are fixed.

The idea is more or less benefiting from doing work in bulk which AI is now allowing. I even think multiple engineers (human redundancy to double check the same code) should team up with one AI system and form a small team that handles millions of lines of code, with the only job to feed incoming tickets and check the AI work. Anyone not reviewing code should be facilitating everything else with their own AIs. I think large companies can collapse entire engineering departments into a few people. The cost would be that everyone else has to think like an engineer to sort out requirements and provide direction, but as you point out, this is now easier with the help of AI.

IMO, a large amount of work, including a large amount of technical work is wasted effort. At startups you see it when they go out of business, at a big companies you see it as bloat. So unless AI is directed at finding the right problems to solve, past some point engineering efficiency via AI at best saves some money and at worst means more ultimately low, zero or negative value work gets done.

Maybe this is why you’re seeing more effort shifted away from technical work. Maybe I’m a nihilist. Maybe both?