Comment by lubujackson

I think to effectively use LLMs in a controlled way, they can help with three things: - Help you pump out boilerplate, or otherwise "obvious" code, that you can review at a glance - Help you gain understanding, either through rapid plan writing/revision or code quality/architectural/security analysis. The gotcha is that it can only help along one axis at a time, or at least can only communicate information sensibly to humans this way - Cross-cutting or fuzzy matching across a codebase. This is the hugest win, like "replace this pattern with the new approach everywhere". This used to be the scariest sort of task, and now it is one of the more stable things LLMs get right.

Where things go off the rail is when you want it to plan AND implement features. The blind spots of LLMs are not where they are for humans and way more work to anticipate. You have to stay on top of the bucking bronco, but you CAN move much faster if you can architect your system so more tasks fall in the "obvious" bucket - that is where the art of engineering still lives. Human understanding remains the goal.