Conventional wisdom is that AI coding raises the floor — that it allows mediocre engineers and even non-coders to be more productive. To some degree this is true, but when it comes to serious engineering projects it’s largely backwards. AI is making bad engineering expensive for the first time.
I’m a consultant. I dive into codebases I’ve never seen and get productive faster than the developers who’ve worked on them for years. When people ask how, the honest answer isn’t “I read faster” or “I ask good questions.” It’s that I apply working knowledge of how systems behave before reading the specific code. I can infer a lot of structural things, behaviors and potential bugs from seemingly superficial details — because there are rules that govern all systems. Doing something over the network or async? Somewhere there should be a timeout, and most likely it’s ill-defined. Using timestamps? I already know what time-related bugs to look for, because developers always make wrong assumptions about time. This isn’t magic — it’s years of experience and theoretical knowledge about systems, hardware, and physics that amalgamated into intuition.