Comment by mitthrowaway2 21 hours ago
The skill ceiling might be "high" but it's not like investing years of practice to become a great pianist. The most experienced AI coder in the world has about three years of practice working this way, much of which is obsoleted because the models have changed to the point where some lessons learned on GPT 3.5 don't transfer. There aren't teachers with decades of experience to learn from, either.
>persistence and a willingness to start from scratch again and again.
i.e. continually gambling and praying the model spits something out that works instead of thinking.
Gambling is where I end up if I’m tired and try to get an LLM to build my hobby project for me from scratch in one go, not really bothering to read the code properly. It’s stupid and a waste of time. Sometimes it’s easier to get started this way though.
But more seriously, in the ideal case refining a prompt based on a misunderstanding of an LLM due to ambiguity in your task description is actually doing the meaningful part of the work in software development. It is exactly about defining the edge cases, and converting into language what is it that you need for a task. Iterating on that is not gambling.
But of course if you are not doing that, but just trying to get a ”smarter” LLM with (hopefully deprecated study of) ”prompt engineering” tricks, then that is about building yourself a skill that can become useless tomorrow.
Why is thinking important? Think about it a bit.
Moreover, the "ceiling" may still be below the "code works" level, and you have no idea when you start if it is or not.