https://github.com/AndyMik90/Aperant did this during the peak of the macmini auto claude phase but last update was 5 months ago
Open source Kanban desktop app that runs parallel agents on every card
151–160 of 191 posts
Re: Open source Kanban desktop app that runs parallel agents on every card
#152[flagged]
Re: Open source Kanban desktop app that runs parallel agents on every card
#153Earlier 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.
A huge factor I don’t see mentioned often enough, is the rapid increase of AI-coding in a language unknown to the dev.
Re: Open source Kanban desktop app that runs parallel agents on every card
#154One 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…
i have shell scripts that create/tear down worktrees. the shell script finds unique unused ports across all existing worktrees and assigns in local .env upon worktree creation. when the worktree gets merged and is torn down the ports get released. secrets that are not worktree-specific i don't keep in local .env i inject via shell.
honestly creating these local scripts for automating the dev work was trivial and they combine well with all other cli tooling. thats why i havent tried any of the GUI apps yet. im not sure they're able to compete with my custom local setup that works exactly the way i want.
Re: Open source Kanban desktop app that runs parallel agents on every card
#155I 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.
Without agentic coding the number go up narrative dies. There's your answer.
Re: Open source Kanban desktop app that runs parallel agents on every card
#156Earlier quoted context omitted.
People already barely reviewed code, most of it was imported libraries.
The assumption used to be that you respected the library enough and believed it was well reviewed and architected by the maintainer(s). But now even that's unreliable because libraries are being slopified at an unreviewable pace too.
> The assumption used to be that you respected the library enough and believed it was well reviewed and architected by the maintainer
I don't know many serious software engineers who'd take that approach, the convention was always to actually open up the code, evaluate the quality, see if they seem to know what they're doing, then chose the libraries you know works and could be adjusted to fit whatever you wanted it. At least for professional development inside companies, not a single library would be included unless you at least reviewed that the top-level dependency you pull in actually had code worth pulling in in the first place.
And this approach just as well today as it used to, you literally have to spend like 3-5 minutes browsing the code, evaluate the abstractions they've built and then say "Yes, looks good enough to try to use" or "Clearly these people just hacked this together as fast as they could".
Re: Open source Kanban desktop app that runs parallel agents on every card
#157Earlier 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.
This is fine for one off tools and I do the same. But building long-lived "professional grade" production software this fails real quickly.
My team is using AI for most of the code, but the human review layer is crucial and unavoidable if you're interested in things like reliability, uptime, controlled feature rollouts, the integrity if your user's data, etc.
Re: Open source Kanban desktop app that runs parallel agents on every card
#158Earlier 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.
People already barely reviewed code, most of it was imported libraries.
Which people? I’ve never worked at a place where reviews weren’t taken seriously. For small changes a cursory glance, sure, but anything medium-sized meant checkout+local test. If anything we’d spend too much time on code reviews or pair programming?
Re: Open source Kanban desktop app that runs parallel agents on every card
#159Re: Open source Kanban desktop app that runs parallel agents on every card
#160Earlier quoted context omitted.
Parsing single file is easier than navigating a file system for an LLM. Until the models have context windows large enough to hold the entire codebase in one shot, single files will beat multiple files every time.
This. I suspect the codebases in the future will be made of a small number of gigantic source files. These will be able to be transpiled into a more human friendly that produces multiple smaller files per big file in human-debug mode.
As a human who typically uses large files, 10k to 30K lines of code files are pretty common, I find the agents don’t read the whole file after the first time, they almost always do a range select for the bit they are interested in.