Honestly, how are you guys running multiple agents, presumably with them all writing code?
I find myself to be a huge bottleneck, having to do technical design and design reviews, to make sure they're actually working on the right things.
I feel like there's not enough coding work to justify multiple agents, that part doesn't take long, and then it's back to design again.
> I find myself to be a huge bottleneck, having to do technical design and design reviews, to make sure they're actually working on the right things.
I find this depends on the LLMs being used and the person using them and the problems being solved.
Like, Fable can be sent off to do some big thing for a long while and I find myself getting bored and move over to push on some other thing. Or, while reading a paper I have a string of follow up questions and ideas and launch them via web or CLI agent. Or I bounce between multiple chores in different packages, each of which is fast for an LLM and a low cognitive burden for me. Then other times, something needs my full, ongoing and serial attention where the LLM turn is only a minor element. I'll use the brief LLM interludes to get up, walk around a bit, stretch and think.
As for Herdr, it seems nice when I tried it a few weeks ago. But, I'm surprised it is getting so much attention (kudos). Like many people, I've developed more than one work-alike before Herdr hit the scene. They were based on tmux which I have concluded I simply detest. In the end, I made a little agent hook script that speaks to Kitty terminal and that plus Kitty and a stable SSH persistent connection gives 80% of what I was looking for. I do still like the "control panel" aspect of my past and herdr's tries. Adding that would get me another 10%.
> presumably with them all writing code?
Not always. In fact, I use multiple agents when writing my technical design docs and giving feedback to design reviews.
The amount of time I spend writing a design doc and the amount of details I can include in the paper is greatly improved.
Ask it questions about your code base, such as if all of your data base indexes are being utilized or if you can remove them.
Ask it questions about logs, like how many api calls are made to a serve every day.
Ask it questions about your environment, like how robust your downstream is.