>If you can't distinguish bad from good with LLMs, you might as well be throwing crap at the wall hoping it will stick.

This is why I think LLMs are more of a tool for the expert rather than for the novice.

They give more speedup the more experience one has on the subject in question. An experienced dev can usually spot bad advice with little effort, while a junior dev might believe almost any advice due to the lack of experience to question things. The same goes for asking the right questions.

This is where I tell younger people thinking about getting into computer science or development that there is still a huge need for those skills. I think AI is a long way off from taking away problem solving skills. Most of us that have had the (dis)pleasure of needing to repeatedly change and build on our prompts to get close to what we're looking for will be familiar with this. Without the general problem solving skills we've developed, at best we're going to luck out and get just the right solution, but more than likely will at best have a solution that only gets partially towards what we actually need. Solutions will often be inefficient or subtly wrong in ways that still require knowledge in the technology/language being produced by the LLM. I even tell my teenage son that if he really does enjoy coding and wishes to pursue it as a career, that he should go for it. I shouldn't be, but I'm constantly astounded by the number of people that take output from a LLM without checking for validity.