alt Hacker NewsI think a pretty good example I had at work, we had the option to buy a software package from a 3rd party company. After reviewing the specs we needed, I told my manager to give me a few hours to see if I could produce what we needed with AI instead. Lo and behold, I was able to do it in just a few hours, AI package was tested, integrated, and we moved on. No where was any of that recorded that I just saved the company lots of money using AI. I bet there are lots of examples like this that just aren't adequately tracked at both micro and macro levels. For some reason we expected to to be able to see these huge gains from AI but we never bothered putting systems in place to observe them.
Replies
I think this is probably going to be the mainstream. Once you are able to define what you need LLMs are able to produce it. If you are able to understand what is delivered, it ends up working as expected.
I needed and embedded document based database, a friend of mine with 30 years experience was vibe coding a database in Rust and I asked him if he can make it support Swift and be embedded in iOS and in few minutes he delivered that using Claude. Then I started vibe coding on it with Codex adding features I wanted and integrating it into my project. It worked as expected. I think it is close to reaching parity with MongDB, years of work vibe coded in a weekend.
There’s going to be fundamental changes in how we program computers and consequently the IT industry.
Yes. We needed to do a huge migration project that would otherwise have taken us six months and/or cost more than $100k. With the help of Opus 4.5 we finished it in three weeks for a total token cost of $1200. I posted about it last month.
So if you want to think of it in economic terms, some software consulting firm that would otherwise have made six figures instead did not. The vast majority of the money we would have spent stayed in our pocket. Slight decreases like this in “velocity of money” no doubt add up to significant sums.
I suspect we are still at the stage where for every story like this there's an offsetting story in the other direction of "I (more commonly reported as my coworker) tried to implement something with AI, messed it up, and ended up wasting a ton of time and resources on that mistake".
It's not that AI can't be useful, but that there's a learning curve, and early in the learning curve we should expect as many resources to be spent learning as resources are saved by using the thing. A macro level view of the economy as a whole sees this as "zero economic growth".