LLMs have dramatically different results depending on the domain. Getting LLMs to help me learn typescript is a joy, getting them to help me fix distributed consensus problems in my fully bespoke codebase make them look worse than useless.

Some people will find them amazing, some will find them a net negative.

Although finding truly zero use for them makes it hard for me to believe that this person really tried with creativity and an open mind

Very much this, I have > 25 years programming experience, but not with typescript and react, it’s helping me with my current project. I ignore probably 2/3 of its auto suggestions, but increasingly I now highlight some code and ask it to just do x for me, rather having to go google the right function/ css magic

Does that feel as rewarding as doing it yourself?

I'm fine with it, I've forgotten more frameworks and libs for now dead devices/services/OS etc over the years that it's largely pointless memorising these things, I'm very happy for a machine to help me get to where I want to be, and less time faffing about with google/stackoverflow the better, like I said the failure rate is still fairly high, but still useful enough.

> getting them to help me fix distributed consensus problems in my fully bespoke codebase make them look worse than useless.

Often the complex context of such problem is more clear in your head than you can write down. No wonder the LLM cannot solve it, it has not the right info on the problem. But if you then suggest to it: what if it had to do with this or that race condition since service A does not know the end time of service Z, it can often come up with different search strategies to find that out.

> or are you smarter than those results?

“Smarter than” are your words. I’ve just yet to get any real utility from them.

> When I read such comments I ask myself, do you even use stackoverflow

I find this a strange comparison.

I’ve yet to see people replacing employees with “stack overflow” or M$FT shoe horning “stack overflow” into their flagship product or former NSA members joining the board of “stack overflow” or billions in funding pouring into “stack overflow” or constant posts to HN asking “how do you use ‘stack overflow’ to improve productivity?”.

To me the SO comparison makes sense.

5 years ago (and up to this day) when I stumbled into a non obvious problem, i resorted to a search engine to read more about the context of such problem. Often a very similar question had been posed on SO. There a problem/solution pair was presented very similar to mine. I did the translation between the proposed solution into mine. This all made perfect sense to me, and dozens of colleagues did the same.

Today you can do the same with an LLM, with the difference that often the LLM does the translation, in often very complex ways, from a set of similar problem/solution pairs into my particular problem/solution pair. It also can find out if some set applies or not, to my particular problem. I can ask it more questions to find out if/why the solution is good.

So that alone is a very big timesaver. But in fact what I described is just the tip of the iceberg in ways the LLM helps me.

So now my question is, do you use such SO problem/solution pairs for help, or do you simply find things out by a lot of thinking combined with reading and experimenting?

Your last sentence was me earlier this year ... seeing headlines about productivity, etc. and then trying out the tools and not finding that.

I have however found it to be very helpful, completely replacing usage of StackOverflow for instance. Instead of googling for your problem, ask AI and provide very specific information like version numbers of libraries, etc. and it usually comes back with something helpful.

All those headlines and nonsense, like most content online these days it looks like marketing content, not journalism. AI tools are helpful and in some ways feel like an evolution of search engine technology from ~25 years ago. Treat its output like a junior developer or intern. It does require some effort, like coaching a junior dev or intern. You can also ask it stupid questions, things like tech you haven't worked on in a while but you "should know". Its helpful to get back up to speed on things like that.