It is ironic that in the gpt-4 era, when we couldn't see much value in this tools, all we could hear was "skill issues", "prompt engineering skills". Now they are actually quite capable for SOME tasks, specially for something that we don't really care about learning, and they, to a certain extent, can generalize. They perform much better than in gpt-4 era, objectively, across all domains. They perform much better with the absolute minimum input, objectively, across all domains. If someone skipped the whole "prompt engineering" and learned nothing during that time, this person is more equiped to perform well. Now I wonder how much I am leaving behind by ignoring this whole "skills, tools, MCP this and that, yada yada".

Prompt engineering (communicating with models?) is a foundational skill. Skills, tools, MCPs, etc. are all built on prompts.

My take is that the overlap is strongest with engineering management. If you can learn how to manage a team of human engineers well, that translates to managing a team of agents well.

Minimal prompting yielding better results? I haven't found this to be the case at all.

Any thoughts on your wondering? I too am wondering about the same mistake I might be making.

My answer is that the code they generate is still crap, so the new skill is in being able to spot the ways and places it wrote crap code, and how to quickly tell it to refactor to fix specific issues, and still come out ahead on productivity. Nothing like an ultra wide screen monitor (LG 40+) and having parallel codex or claude sessions going, working on a bunch of things at once in parallel. Get good at git worktree. Use them to make tools that make your own life easier that you previously wouldn't even have bothered to make. (chrome extensions and MCPs!)

The other skill is in knowing exactly when to roll up your sleeves and do it the old fashioned way. Which things they're good/useful for, and which things they aren't.