About two weeks ago I open-sourced an ML utility I made to solve a problem I had and I figured it might help a few other people. It's pretty niche.
In that time, more than 3,000 people have run it. There have been 769 unique GitHub cloners and 2,800 Docker Hub pulls. I just did one LinkedIn post and one Show HN post, and the HN post got zero upvotes.
Not only are people using it, but it's being deployed on serious hardware: there are ~100 pulls of my intermediate Docker images, and the only reason you'd do that is to add support for NVIDIA Blackwell. That's big iron.
I'm sharing this not to brag (though yes it does feel good to see usage) but to show how far a little utility can go. I just built this for myself, to solve my problem, and shared it.
The big enabler here was agentic coding. I could get the LLM to build something relatively sophisticated, quickly, to solve my problem. And I'm not the only one with this problem — apparently more than 3,000 of you have it as well.
And that's what I hope you take away from this post: if you're sitting on something useful, share it. It doesn't have to be big. mixlab is small, MIT licensed, and now apparently some stranger is adapting part of it for Blackwell hardware. I still can't quite get over that.
Maybe your tool will solve someone else's problem, too.
mixlab on GitHub →