alt Hacker NewsIt is impossible to duplicate results with an LLM. This strikes me as a serious barrier to calling it a proper skill. If you can’t even somewhat replicate the results you can’t really improve the input consistently. You can’t become “skilled” at it if you can’t even reproduce what you did.
If you enter the same prompt 3 times the results are of pretty significantly different quality. ChatGPT literally has you A/B test for them sometimes. They’re right to call it superstition - it feels like we’re making incantations and hoping for the best a lot of the time.
Prompting LLM’s still feels like a constant game of guess and check. At best you can argue it’s an educated guess. I don’t know about you but I didn’t learn math by guessing and checking, I frequently had to work backwards and review where I went wrong and/or I had the answer given to me with the work shown so I can learn. I can’t do that with a prompt. When I get bad results (which we all frequently do) I just guess what it didn’t like, try again, and pray for a better result.
Replies
> It is impossible to duplicate results with an LLM.
Humans are called experts in many domains whereby they cannot achieve duplicate results. In fact, in what domain can an expert do that?
Nobody crosses the same river twice.
Me typing into emacs is also not replicable, until I git push. Me with emacs and a good coding LLM can generate systems that I see as good, in my extensive professional judgement. For coding, for production grade code, the LLM will mostly be a tool in the hands of the professional. There is a new category of disposable code, which I think will be useful for many adhoc investigations; in neither case is replicability a serious requirement.
I do a lot of guessing and validating in learning maths. It is pretty efficient way to build that conceptual understanding. I even try to predict the next big theorem as I am listening to a lecture or reading a text book. It's engaging.
And honestly, I am enjoying learning this new way to make code I am pleased with. Using the LLM effectively and for quality deliverables is different from typing in many surface ways, but modularity of thought, iterative design and implementation, simplicity and generality, documentation, all still pay off.