Comment by pkoiralap
3 hours ago
In the 1930s, when electronic calculators were first introduced, there was a widespread belief that accounting as a career was finished. Instead, the opposite became true. Accounting as a profession grew, becoming far more analytical/strategic than it had been previously.
You are correct that these models primarily address problems that have already been solved. However, that has always been the case for the majority of technical challenges. Before LLMs, we would often spend days searching Stack Overflow to find and adapt the right solution.
Another way to look at this is through the lens of problem decomposition as well. If a complex problem is a collection of sub-problems, receiving immediate solutions for those components accelerates the path to the final result.
For example, I was recently struggling with a UI feature where I wanted cards to follow a fan-like arc. I couldn't quite get the implementation right until I gave it to Gemini. It didn't solve the entire problem for me, but it suggested an approach involving polar coordinates and sine/cosine values. I was able to take that foundational logic turn it into a feature I wanted.
Was it a 100x productivity gain? No. But it was easily a 2x gain, because it replaced hours of searching and waiting for a mental breakthrough with immediate direction.
There was also a relevant thread on Hacker News recently regarding "vibe coding":
https://news.ycombinator.com/item?id=45205232
The developer created a unique game using scroll behavior as the primary input. While the technical aspects of scroll events are certainly "solved" problems, the creative application was novel.
The story you're describing doesn't seem much better than one could get from googling around and going on stackoverflow
Isn't that the whole point? We were already burning steam trying to find better ways around search and bettering our search engines.
Now we have something that understands the question better than any search engine on earth (prior to the advent of LLMs), has relevant information about the question, presents the information in a way we can understand it, remembers the whole context so that when we say that it didn't get it quite right, it understands that, and gets us more information until we find what we are looking for.
The process described above (at least for me) replaces googling and SO searches.
In fact, you can try this on your own as well. Here is a challenge: Try to build a simple game. In the game you create a target that's randomly generated on the screen and have a player at the middle of the screen that needs to hit the target. When a key is pressed, the player swings a rope attached to a metal ball in circles above it's head, at a certain rotational velocity. Upon key release, the player has to let go of the rope and the ball travels tangentially from the point of release. Each time you hit the target you score.
Try it without LLMs and only with google and SO first and see if LLMs help with efficiency :)
It doesn’t have to be, really. Even if it could replace 30% of documentation and SO scrounging, that’s pretty valuable. Especially since you can offload that and go take a coffee.