[satvikpendem]

Sometimes I don't want creativity though, I'm just not familiar enough with the solution space and I use the LLM as a sort of gradient descent simulator to the right solution to my problem (the LLM which itself used gradient descent when trained, meta, I know). I am not looking for wholly new solutions, just one that fits the problem the best, just as one could Google that information but LLMs save even that searching time.

[bandrami]

> I'm just not familiar enough with the solution space

Neither is the LLM

[apsurd]

(Trying to find where you might still see this)

I've read the thread and in my mind you're missing that LLMs increase the surface area of visibility of a thing. It's a probe. It adds known unknowns to your train of thought. It doesn't need to be "creative" about it. It doesn't need to be complete or even "right". You can validate the unknown unknown since it is now known. It doesn't need to have a measured opinion (even though it acts as it does), it's really just topography expansion. We're getting in the weeds of creativity and idea synthesis, but if something is net-new to you right now in your topography map, what's so bad about attributing relative synthesis to the AI?

[bandrami]

Because if that's it we've made a ludicrously expensive i-ching.

[imtringued]

If there is something LLMs are good at it's knowing some obscure fact that only 10 other people on this planet know.

[bandrami]

They're also very good at almost knowing an obscure fact that only 10 people know but getting a detail catastrophically wrong about it

[jimbokun]

No, this is the kind of thing LLMs are very good at. Knowing the specifics and details and minutiae about technologies, programming languages, etc.

[bandrami]

Oh Lord, no. Not at all. That's what they're terrible at. They are ok-ish at superficial overviews and catastrophically bad at specific minutiae

[darth_aardvark]

Honest, non-confrontational, non-passive aggressive question: Have you used any of the latest models in the last 6 months to do coding? Or frankly, in the last year?

[bigstrat2003]

I have. And the people who say "use a frontier" model are full of it. The frontier models aren't any better than the free ones.

[satvikpendem]

What are you defining as free versus frontier, and for what purpose? For coding there is a big difference between Opus and GPT 5.3/4 versus Sonnet and other models such as open weight ones.

[satvikpendem]

They note in another comment they don't even use search engines so I don't think they're the right person to ask regarding frontier models.

[darth_aardvark]

I'd ask them what tools they do use, but I doubt they'll see my comment; I'll see if I can mail it to them.

[satvikpendem]

Oftentimes it is though, good enough for my purposes.

[bandrami]

If you're not familiar with the problem space, by definition you don't know whether or not that's the case. The problem spaces I do know well, I know the LLM isn't good at it, so why would I assume it's better at spaces I don't know?

[satvikpendem]

I said familiar enough, not familiar. For example, let's say I'm building an app I know needs caching, the LLM is very good at telling me what types of caching to use, what libraries to use for each type, and so on, for which I can do more research if I really want to know specifically what the best library out of all the rest are, but oftentimes its top suggestion is, like I said, good enough for my purpose of e.g. caching.

[bandrami]

I still don't get what you're saying. If you possess enough information to accurately judge the LLM's suggestions you possess enough information to decide on your own. There's not really a way around that.

[satvikpendem]

Of course I'm deciding on my own, I'm not letting the LLM decide for me (although some people do). But the point is whatever the suggestion is is merely an implementation detail that either solves my problem or not, not sure what part of that is confusing. Replace LLM with glorified Google and maybe it's less confusing.

[jimbokun]

Do you use search engines or do you just memorize all the world’s information?