Comment by stavros
12 days ago
Why does this article not mention what solveit is at all? It talks about what they did, then that they made this tool, then that it's great, but what is it? Watch this video!
No, give me a sentence or two about what it does. I'm not watching a video about a tool while reading a blog post about it because you couldn't be bothered to write a line or two about it.
As someone who participated in the first cohort but is not part of their team, i would say it’s a programming environment for AI assisted literate programming.
It’s like an intelligent notebook. That means you could use this for many different things but at least to me the high order bit is „AI assisted literate programming“
I see, thank you. Is this more of an exploratory programming tool, then? A Jupyter notebook with AI features?
Considering how the folks at answer.ai have been using (successive versions of) it to build this tool itself and judging by student projects and showcases, it definitely goes beyond exploratory. You can build big stuff with it.
Personally I’m using it to learn the whole fastai ecosystem.
1 reply →
That's fair! I guess since it's a new thing that doesn't quite neatly fit in a category, we were perhaps too shy about trying to define it. Also, we really want to focus on the methodology, rather than the platform. But yes, you're right we should explain the platform too. :) I'll have a go here, and will then go and add it to Johno's article.
So basically, you can think of the platform as combining all these: ChatGPT; Jupyter Notebook + nbdev; Bits of vscode/cursor (we embed the same Monaco editor and add similar optional AI and non-AI autocompletion); a VPS (you get your own persistent full VPS running Linux with a URL you can share for public running applications); Claude Code (all the same tools are available); a persistent terminal.
Then there's some bits added that don't exist elsewhere AFAIK: something like MCP, but way simpler, where any Python function can be instantly used as an AI tool; the ability to refer directly to any live Python variable in AI context (but optional, so it doesn't eat up your context window); full metaprogramming of the environment (you can through code or AI tools modify the environment itself or the dialog); context editing (you can -- and should -- directly edit AI responses instead of tell the AI it's wrong); collaborative notebook coding (multiple people can edit the dialog, run code, etc, and all see live updates).
The combination of these things is rather different (and IMO better!) than the sum of its parts, but hopefully this helps a bit?
That helps a lot, thanks!