Surviving the great commoditizer: Stop getting «good» at LLMS (www.hitsubscribe.com)

The author warns digital technicians—individual contributors like developers, writers, designers and accountants—that becoming “good” at LLMs (exemplified by ChatGPT) can be a career trap. Using Michael Gerber’s technician/manager/entrepreneur taxonomy, they show how labor moves through a commoditization lifecycle (innovation → skilled labor → unskilled VA → full automation). ChatGPT isn’t just another tool: it behaves like a “black hole” that collapses stages 2–4, rapidly lowering barriers and making formerly skilled knowledge work interchangeable, price-driven, and easily self-served with a bit of prompt engineering. Even though LLMs still have technical weaknesses for some skilled tasks, perception and business incentives mean clients will equate faster, LLM-assisted output with cheaper labor. The practical implication: mastering prompt craft to speed up execution can inadvertently destroy your own value—you're essentially optimizing to commoditize your work. To survive, technicians must stop treating LLM fluency as a career endgame and instead move “one jump ahead”: specialize in genuinely hard-to-automate problems, productize or own outcomes (not hours), focus on domain judgment, orchestration, and innovation, or transition into roles that set strategy and design the systems LLMs automate. In short, don’t train the tool to replace you; use it to amplify distinctive capabilities that resist commoditization.