@skyfire747 @nomenloony The problem with AI is you don’t know when it’s wrong.
🦆@drahardja @skyfire747 @nomenloony @blogdiva
My favorite quote about LLMs is that they are extremely effective for people who already are domain experts on the topic
The UX fail of the century is for every one of these companies to not append “teach me how I would verify this is true?” to every single prompt.
The skill it takes to use the tech is higher than the avg user is going to invest. Every single maker of chatbots has ignored this from day one.
@raineer @drahardja @skyfire747 @nomenloony @blogdiva
Domain expert here: they aren't extremely effective for me in my field (programming) because to tell an LLM precisely enough what to do, I'd have to use a verbose English description, and I've already constructed the solution in my head in a more structural form that isn't words. Turning it back into words to tell an LLM what code to generate is a step backwards.
@petealexharris @raineer @drahardja @skyfire747 @nomenloony @blogdiva Don't you do that anyway when you add comments to your code?
@technicaladept @raineer @drahardja @skyfire747 @nomenloony @blogdiva
No, a duplicate explanation of what the code is doing is not what comments are for.
Comments are more for "why" one method or choice than another, sometimes "why not", than "what".
Except doc comments, which are closer to spec i.e. "what". The code itself is "how", and it doesn't necessarily come via a verbal description in natural language.
@petealexharris @technicaladept @raineer @drahardja @skyfire747 @nomenloony @blogdiva just like you don't explain to the client why you use a nail and not a screw when building a chair. You explain how to use the chair and if there's something that works different to a normal chair.
Edited 17d ago