Indeed, he did not list "out-of-touch suit-at-heart tech leads that failed upwards and have misplaced managerial ambitions" as a category, but that category certainly exists, and it drives me insane.
You might find your professional development would stop being retarded if you got the chip off your shoulder and focused on delivering maximum value to the organizations that employ you in any way possible.
But that's just how being a manager-man goes; so focused on self-aggrandizement and surrounding yourself with yes-men that you lost your edge. Hope you can cover up your incompetence until the next promotion is due, because if ever a rung breaks away from under your feet, it'll probably be a loong way down to a position that matches your actual skill level.
>So, basically, you think all the pro-AI folks are "bad," and defensive because they feel like anti-AI folks are attacking the thing that makes them not bad?
Thanks, I needed a laugh. I have indeed grown bitter over the years, but life has always has a way to make me smile in store.
I was already a very high performer before AI, leading teams, aligning product vision and technical capabilities, architecting systems and implementing at top-of-stack velocity. I have been involved in engineering around AI/ML since 2008, so I have pretty good understanding of the complexities/inconsistencies of model behavior. When I observed the ability of GPT3.5 to often generate working (if poorly written, in general) code, I knew this was a powerful tool that would eventually totally reshape development once it matured, but that I had to understand its capabilities and non-uniform expertise boundary to take advantage of its strengths without having to suffer its weaknesses. I basically threw myself fully into mastering the "art" of using LLMs, both in terms of prompting and knowing when/how to use them, and while I saw immediate gains, it wasn't until Gemini Pro 2.5 that I saw the capabilities in place for a fully agentic workflow. I've been actively polishing my agentic workflow since Gemini 2.5's release, and now I'm at the point where I write less than 10% of my own code. Overall my hand written code is still significantly "neater/tighter" than that produced by LLMs, but I'm ok with the LLM nailing the high level patterns I outline and being "good enough" (which I encourage via detailed system prompts and enforce via code review, though I often have AI rewrite its own code given my feedback rather than manually edit it).
I liken it to assembly devs who could crush the compiler in performance (not as much of a thing now in general, but it used to be), who still choose to write most of the system in c/c++ and only implement the really hot loops in assembly because that's just the most efficient way to work.