I'm so married to my existing tmux workflows and layout that I'm not sure whether I'd ever feel open to trying out something like this. At the same time, orchestrating multiple agents with native tmux and git worktree does feel cumbersome.
I built a tool that lets you keep your existing tmux workflow and adds a simple dashboard for monitoring and discovering agents inside tmux: https://github.com/sethdeckard/atria
tmux by itself lets you create any number of sessions, windows and panes. You can arrange them for anything you want to do.
Having a pane dedicated to some LLM prompt split side by side with your code editor doesn't require additional tools, it's just a tmux hotkey to split a pane.
There's also plugins like tmux resurrect that lets you save and restore everything, including across reboots. I've been using this set up for like 6-7 years, here's a video from ~5 years ago but it still applies today https://www.youtube.com/watch?v=sMbuGf2g7gc&t=315s. I like this approach because you can use tmux normally, there's no layout config file you need to define.
It lets me switch between projects in 2 seconds and everything I need is immediately available.
I am in the same boat. It's the unix philosophy. tmux does its job well enough and it is already scriptable. I don't think I was sticking to the same layout for a long time because different projects tend to require different layouts. But that's the fun part of streamlining down your automation. I haven't felt the need to explore other options yet because I haven't felt the limitation of tmux yet.
I don't consider tmux to be very unix-y. It does two different jobs -- connection persistence and window management. Most people these days only use tmux for the former now that tabbed terminal programs are commonplace, but the complexity of the latter still infects tmux.
I liked that the post is self-aware that it's promoting its own product. But the writing seemed more focus on the philosophy behind code reviews and the impact of AI, and less on the mechanics of how greptile differs from competitors. I was hoping to see more on the latter.
I am seeing the doomed future of AI math: just received another set theory paper by a set theory amateur with an AI workflow and an interest in the continuum hypothesis.
At first glance, the paper looks polished and advanced. It is beautifully typeset and contains many correct definitions and theorems, many of which I recognize from my own published work and in work by people I know to be expert. Between those correct bits, however, are sprinkled whole passages of claims and results with new technical jargon. One can't really tell at first, but upon looking into it, it seems to be meaningless nonsense. The author has evidently hoodwinked himself.
We are all going to be suffering under this kind of garbage, which is not easily recognizable for the slop it is without effort. It is our regrettable fate.
