Hacker News Reader

sherdil2022

So it looks like we all need to have firm understanding and tailor our prompts now to effectively use LLMs. Isn't this all subjective? I get different answers based upon how I word my question. Shouldn't things be little bit more objective? Isn't this random that I get different results based upon just wording? This whole thing is just discombobulating to me.

View on HN

And to add to it, here's my experience: sometimes you spend a lot of time on this upfront prompt engineering and get bad results and sometimes you just YOLO it and get good results. It's hard to advocate for a determined strategy for prompt engineering when the tool you're prompting itself is non-deterministic.

Edit: I also love that the examples come with "AI’s response to the poor prompt (simulated)"

Also that non-determinism means every release will change the way prompting works. There's no guarantee of consistency like an API or a programming language release would have.

Reply on news.ycombinator.com