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by jiggawatts 27 days ago
"19 August 2025"

This may as well have been written in the stone ages, when we were banging AI rocks together.

I just did a ~6 month project in ~2 weeks using a frontier model.

I wouldn't even have attempted this kind work a year ago, with or without the AIs available at the time!

4 comments

>I just did a ~6 month project in ~2 weeks using a frontier model.

Claims like this are hard for me to take seriously because 'good' models have been available since the start of the year. So, if they really 10x one's productivity, then people should be able to have gotten done 5 years worth of work since then, but I've never actually seen anybody show any project like this.

> 'good' models have been available since the start of the year

today: https://www.anthropic.com/news/redeploying-fable-5

35 days ago: https://www.anthropic.com/news/claude-opus-4-8

70 days ago: https://openai.com/index/introducing-gpt-5-5/ <-- first model I've found useful

77 days ago: https://www.anthropic.com/news/claude-opus-4-7

119 days ago: https://openai.com/index/introducing-gpt-5-4/

182 days ago: The start of the year

Opus 4.5/4.6 are what many people consider the first 'good' models and it's from last year/start of this year.

But fine, let's say everything before gpt 5.5 was unusable crap. Then there should still be projects that would normally have previously taken ~2 years done in just two months. Where are they?

I’m starting to see huge solo projects with 100 commits per day turning up on GitHub.

Last year these were unusable slop.

Now they’re “getting there”. Not quite as good as hand crafted code written by humans, but usable.

My guess at what's happening is that people are mostly using the tools on low impact or speculative projects. Notice that he said he wouldn't have attempted it without AI.

That's been my experience too. I had an idea that I didn't need so I hadn't bothered doing it, but AI made it easier to just have a go. I suspect people aren't using AI as much on their main profit-making projects (which also are going to be bigger, more complex and not greenfield - which is all harder for AI).

Also give it a chance - as you said "good" models have only been available very recently and you wouldn't expect everyone to start using them instantly.

Sure, but "10x faster, but only applies on small greenfield, throwaway projects" is a major caveat. In fact, there's a good chance this doesn't disprove the original blog post, you could be way faster on small projects but slower on 'real' projects.

>Also give it a chance - as you said "good" models have only been available very recently and you wouldn't expect everyone to start using them instantly.

But I'm not expecting everyone to have built something like that, but surely among millions of users someone should have, especially the people proclaiming insane productivity gains? There are no super impressive open source projects done using AI and all the companies boasting about how all their code is AI written now don't show much improvement either.

That's amazing. What's even more incredible is that somehow you managed to do a real code review and testing in that time-frame.
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What was the project? Could you share the code?