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Open source Kanban desktop app that runs parallel agents on every card

kanbots.dev

171–180 of 191 posts

Re: Open source Kanban desktop app that runs parallel agents on every card

#171
post #25

> "Local-first, zero servers. Everything lives in .kanbots/ next to your repo: SQLite database, configs, worktrees. No cloud account, no telemetry, no HTTP server. This is the open-source desktop edition." This is table-stakes for me to consider adoption of a tool like this.

What is ”a tool like this”? If AI is agentic I would expect it takes an hour of chatting for any PM to integrate some agent Ralph loop with Jira. Jira or Trello or Linear or Basecamp all have APIs and I guess CLIs any agent can use to talk to them. No developer or SaaS should be needed to make them understand tasks are checked out when you start work and contain instructions and when you are done you move the ticket…

I didn't say I think this tool makes a ton of sense (let alone for me), just that any tool "like this" -- developed by someone else, which by design might become part of a workflow on which I rely -- has a minimum bar to clear before I'll even consider it.

Re: Open source Kanban desktop app that runs parallel agents on every card

#172
post #49

Earlier quoted context omitted.

I wonder the same. The answer I usually get from people who do manage is that they don't look at the code – or at least not in detail. Personally, I always end up tweaking something the agent produced. I wonder if I should let go of that control...

I never look at code. It used to be that it quickly became unmaintainable spaghetti where the agent struggled to make any change at all, but in the past year (and with a three step plan/develop/review workflow), the quality is so good that I basically just don't look at the code any more. It definitely has fewer bugs than a senior developer, but it really hinges on getting the plan right. 20 minutes of planning and 2…

I'm starting to agree with you; I found the plan/develop/review workflow to work quite well, but I'm not at the point of not looking at the code at all yet.

I guess you actually review and actively participate in making the plan, you just don't review the code afterwards?

Could you share some more details on the specifics of your workflow? (What models/harnesses? do you use the same or different context windows? How exactly do you run the review, and how do you pass along and act upon the information from the review?) Also, how big are the changes you usually implement with one plan/develop/review cycle?

Re: Open source Kanban desktop app that runs parallel agents on every card

#173
post #49

Earlier quoted context omitted.

I never look at code. It used to be that it quickly became unmaintainable spaghetti where the agent struggled to make any change at all, but in the past year (and with a three step plan/develop/review workflow), the quality is so good that I basically just don't look at the code any more. It definitely has fewer bugs than a senior developer, but it really hinges on getting the plan right. 20 minutes of planning and 2…

I'm starting to agree with you; I found the plan/develop/review workflow to work quite well, but I'm not at the point of not looking at the code at all yet. I guess you actually review and actively participate in making the plan, you just don't review the code afterwards? Could you share some more details on the specifics of your workflow? (What models/harnesses? do you use the same or different context windows? How…

Sure! Here: https://www.stavros.io/posts/how-i-write-software-with-llms/

The changes aren't usually very big, basically what you'd put in one ticket. If I need to make large changes, I do them in self-contained stages, if that's possible, otherwise I will tell the LLM to add specific tests in the plan, and I will test thoroughly after.

Re: Open source Kanban desktop app that runs parallel agents on every card

#175

Earlier quoted context omitted.

Most of the narrative is about how AI is writing all/most code, but I’d wager that the fraction of human reviewed code is approaching zero far faster than anyone is realizing or willing to admit.

Very true. Last year I at least glanced at every line of AI generated code. Now if some AI makes a 10k line program for some one-off tasks, I run the program, glance only over the output, and move on.

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Re: Open source Kanban desktop app that runs parallel agents on every card

#176

I keep wondering how people accept a nights worth of agent activity. I feel 30 minutes of planning and 30 minutes of implementation in my solo side project's repo is too big to review. At minute 5, I may ask the AI to redo stuff even as its spitting out code.

They most likely don’t review it ;)

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Re: Open source Kanban desktop app that runs parallel agents on every card

#178

> play nice with tools you already use: codex, Claude, cusrsor, github, sqlite, electron I do not use any of those. Also why all of those vibe coded websites are so slow on mobile. Also I do not understand why Software Developer people are work so hard to make themselves obsolete. Why? You guys do not enjoy eating and having place to sleep?

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Re: Open source Kanban desktop app that runs parallel agents on every card

#179
post #111

Earlier quoted context omitted.

From their page, they say they require cloud account login for this to work, even locally which is why I decided not to try it out. Looks cool tbh. But I have quite a few tools that look cool.

I'm confused, I downloaded their repo and ran it and I had the option to continue locally without signing up/in.

Maybe it works without it, but on their Getting Started this is what they are saying (which might be written by AI) and that is why I skipped even trying it.

Re: Open source Kanban desktop app that runs parallel agents on every card

#180

One thing I don't understand with all of these, is how they're handling different worktree infrastructure spin-up? For example, if I have a webapp, I want each of the worktrees to spin up its own infrastructure, and be accessible on its own unique local url, so that I can see the changes locally for each worktree, or I can have agents automate visual checks using something like agent-browser. Currently I use docker f…

Check out emdash.sh - each task spins up its own worktree with a bunch of pre-defined environment variables that are injected. This includes `EMDASH_PORT` a uniquey port for a 10 port range. Very useful for running multiple services from a single monorepo.

I ended up trying emdash.sh and superset.sh, both have this feature. I managed to get it to work in superset - for whatever reason the Setup script wouldn't work in emdash. So I'll stick with this for now.
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