Maybe, just maybe, this is of obvious utility to the many people who have needs that are not yours?

I very regularly need to interact with my work through a python interpreter. My work is scientific programming. So the variables might be arrays with millions of elements. In order to debug, optimize, verify, or improve in any way my work, I cannot rely on any other methods than interacting with the code as it's being run, or while everything is still in memory. So if I want to really leverage LLMs, especially to allow them to work semi-autonomously, they must be able to do the same.

I'm not going to dump tens of GB of stuff to a log file or send it around via pipes or whatever. Why is there a nan in an array that is the product of many earlier steps in a code that took an hour to run? Why are certain data in a 200k-variable system of equations much harder to fit than others, and which equations are in tension with each other to prevent better convergence?

Are interpreters and pdb not great, previously-existing tools for this kind of work? Does a new tool that lets LLMs/agents use them actually represent some sort of hack job because better solutions have existed for years?

Are you aware that you can use tmux (or zellij, etc.), spin up the interpreter in a tmux session, and then the LLM can interact with it perfectly normally by using send-keys? And that this works quite well, because LLMs are trained on it? You just need to tell the LLM "I have ipython open in a tmux session named pythonrepl"

This is exactly how I do most of my data analysis work in Julia.

See related sibling: the use cases are compelling!

My complaint is that tmux handles them perfectly. Exactly the claim that OP is making with their software - is served by robust 18 year old software.

In 2026, it costs nearly nothing to thoroughly and autonomously investigate related software — so yes I am going to be purposefully abrasive about it.

What I do is have a quick command that spins up a worktree on a repo with my ghostty splits as I like them and the tmux named the worktree. I then tell the Claude code about the tmux when it needs to look. It’s pretty good at natively handling the tmux interactions.

Ideally Ghostty would offer primitives to launch splits but c’est la vie. Apple automation it is.

> I'm not going to dump tens of GB of stuff to a log file

In the same vein as the parent comment, the curiosity is why you would vibe code a solution instead of reaching for grep.

You can start a tmux session and tell your agent about it and it will happily send commands and get the output from it.

I saw this post a while ago that turned me on to the idea: https://news.ycombinator.com/item?id=46570397