LLMs reward expertise

Domain expertise is the most important factor in getting value from LLMs, not generic prompting tricks. Using Terence Tao's ChatGPT conversation about the Jacobian Conjecture as an example, the author shows that experts extract far more from models because they can steer conversations, identify wrong answers, and suggest better approaches. The same principle applies to software development: deep familiarity with a codebase lets developers push LLMs much harder than novices can. This suggests human expertise remains valuable even as models improve, because the bottleneck is often the human's ability to communicate precisely what solution they want.