I have to say that it's been bizarre watching people say how much of a "game changer" LLMs are. There is clearly an advance there, no doubt, but it hasn't really been able to solve any actual problems that I have.
It's not like writing a history paper where you can write "Napoleon was a French general who conquered Europe in 1987" and just be wrong in a way that requires cross-checking facts. Computers are less forgiving of things that are wrong.
But I do feel like I see incorrect documentation proliferating a bit more, and I'm curious whether we'll see an up-tick in more subtle bugs that is wrong but not so wrong that it is rejected early on. I haven't personally seen that in my work yet. I do also see more code that I don't like during code reviews, that I'm sure was spat out by an AI, but often I conclude that my preference isn't really "right" or even better, but just a preference that doesn't really matter.
Their current status is basically "very junior programmer with a photographic memory, who has read a sizable chunk of the internet". They are excellent if you regularly need to implement code that has been done before.
If I'm doing something obscure or niche forget it, it'll just make up a bunch of nonsense. But I wish it was easier to get it to say "I think it should work like x but I'm not sure about y part" instead of just going all in and making stuff up.
We need to train it on old LessWrong posts so it learns about degrees of belief and such lol
It literally says "If you do not know something, just tell me, don't make something up".
Also, "Don't worry about me feeling insulted, no need to apologize for everything", which eliminates a lot of the groveling.
When dealing with niche topics it helps to literally copy-paste relevant chunks of the manual in. You can't expect it to know about everything (yet).
I use it to work through architecture problems that are over my head or find answers to things that aren’t obvious in documentation. These are things I used to have to ask staff engineers for advice with. I’ve even had it write large sections of code for me. At this point most of the code it puts out works.
You can also do things like ask ChatGPT to use multiple specific technology stacks to implement your solution, which is really useful for when you’re trying to come up with a solution that fits within existing infrastructure.
It’s like a mega-brain that’s an expert in everything and understands your specific prompt without giving you the junk you don’t want that has similar words.
But the way those actions have changed just also isn't that big a deal. I have much better "intellisense" by using copilot, and I have much better stack overflow via interactive chat that will tell me answers immediately rather than linking to a kinda-sorta-the-same duplicate question after an hour. But using code completion and searching stack overflow weren't activities that took up much of my time. They took up some of my time, and it's really awesome that I'm using that time much more efficiently now, but it's still a small proportion.
I still spend most of my time reading code and docs, talking to my colleagues about things, and thinking about how to structure interfaces and larger components in order for them to be more useful and to evolve more easily as we hire more people and adapt to different business initiatives. The AI assistants help me some with these tasks, sometimes I ask them to summarize stuff I'm reading, or (honestly hardly ever) to help me understand unfamiliar code, but these are quite small value adds. They aren't anywhere near the point where they can replace my work on these tasks. They just can't store enough context on the business or do enough different kinds of things or take enough initiative to do this part of my work.
All of this is to say: I'm bullish on "LLMs as coding assistants" but - for the moment - remain bearish on "LLMs as replacement for a software engineer".
I'm sure more evolved LLMs will begin to replace jobs soon, but it will mostly be the low hanging fruit. By the time it gets to what I'm doing we'll be in Wall-E floating chair [1] ubi territory.
Can this product scale to 10M users? No clue. Does it have all the features that I wanted? Not yet. But is it live, usable, useful and profitable?
Absolutely.
E.g. I think not even Gartner is talking about automatic IT environment configuration and monitoring anymore.
This is so foreign to me as someone who has become dependent on LLM's
Does it solve problems for me? No, not really - but it's a huge productivity booster in helping me find solutions.