Low risk work is tremendously accelerated. Just look at the memes that people re building. One of my favorite right now are derivations of this thing: https://x.com/jamesonhodge/status/2118733265372860826
People are running away with it in hilarious ways using all sorts of storyboarding, 3d environments, gameplay, etc etc.
I work in a highly regulated environment. My AI spend is ~$300/week and it has been tremendously helpful in troubleshooting incidents(!), increasing test coverage, gaining understanding of legacy/inherited code, applying fixes, etc. But shipping new features is something that impacts us in many many many ways and the uptake there has been quite slow.
https://chimera-vocal-synth.vercel.app/
Thanks for the share, I love it.
Clearly, acceleration is possible. So maybe we should move on to the conversation of what will make further acceleration possible, instead of arguing it only works for iteration one.
Then the next challenge is scaling it to the world - and Twitter themselves struggled with that, the first years were full of fail whales, or stories of servers churning for ages whenever Justin Bieber made a tweet because (for some reason) they updated everyone's feeds even if they weren't actually online / looking at them.
But solving that also wasn't what made Twitter or Facebook popular, and no LLM will ever solve that because none of the successful software projects were successful because of code, code volume, development speed, number of people involved, or anything like that.
(That said I am convinced you can do the same amount of coding with less people at good enough quality, and said quality will improve over time as we've seen in the past ~2 years. The providers just need to add the software quality guardrails that we as software engineers learned over the years, and I'm sure there's dozens of companies working on just that)
"One occasionally reads newspaper accounts of how two programmers in a remodeled garage have built an important program that surpasses the best efforts of large teams. And every programmer is prepared to believe such tales, for he knows that he could build any program much faster than the 1000 statements/year reported for industrial teams. Why then have not all industrial programming teams been replaced by dedicated garage duos? One must look at what is being produced."
Brooks argues that the coding that happened in the garage only is a fraction of what you need for the final product:
"It costs nine times as much. But it is the truly useful object, the intended product of most system programming efforts."
What we're seeing right now does not feel much different. You can greatly accelerate a first draft, a greenfield project, an experiment, or at least the initial iteration of one. Changing a live production system or a widely used library is an entirely different proposition.