Being able to run Jupyter cells independently is a feature until it’s not.

I’d say for most of my one-off work, it’s fine. But for stuff I want to share it’s not.

I tried experimenting with what is ultimately a treesitter based approach - https://github.com/0x007BA7/codebook

And really liked it. Definitely nowhere near production ready but I think theres room for a player to come in and do something similar.

It’s not much of a moat, but it’s more than a lot of orgs have.

But I switched from ChatGPT to Claude 3 months ago because my account was down for like 6 hours. I haven’t used it since. It’s too easy to switch away from chatbots on a whim. There is no moat for that.

But maybe you should checkout the tools it’s based on, sem - https://github.com/Ataraxy-Labs/sem and ultimately treesitter. They at least give a more structured approach to dealing with code than simple text.

It’s a better code reader built on top of sem (treesitter). I’m getting a lot of massive PRs at work now, and this has helped a lot with reading them. It decomposes the changes into entities and sorts based on what has the most dependencies. This tends to put the most important functions first. Plus I can click through the dependencies for each function and mark things as reviewed as I’m reading them. It’s a big improvement over the GitHub review flow for me at least.

It’s always a little disappointing to me when I think I’ve run into something unique but it ends up being user error or something.

My metric is: how much code that I create today do I depend on in 3 months (incl learnings and one off data pulls etc.) and its waaay less than what I generate. A lot of it is frankly noise.

If you have particularly specific knowledge in pretty much any domain, combining that with AI can lead to huge gains.

Yes

> It incentivises high-impact research

It incentivizes work that sounds impressive to laymen. Actual work tends to be technical and might not sound super exciting.

If 20 years ago, a politician had to get up and explain that we were spending millions of dollars training computers to recognize a strawberry, likely the entire field of machine learning would not exist today.

^ I say shouldn’t because I work in research engineering. Most of the needs of our users are pretty unique. We’ve had people come in and try and specify every piece of work, -and ended up building a crud app no one wanted or used.

I’m going to guess that this is Gell-Mann amnesia more than anything, and it’s going to get a lot of organizations into a lot of weird places.