Hello folks, sharing my latest open source project, a kanban board with parallel agents. Trying to improve this with more features, I would love your contributions on this repo, with either code contributions or ideas
Just post the GitHub page if it’s open-source. It’s great you have a domain name, but if your website is going to look the same as every other SaaS product designed by Claude it’s really hard to look past that and look at the novelty or benefits of the product.
These pages do look good. But they all just look the same. And I'm getting bored of them.
I open such a page and I immediately know it was Claude that produced it (probably end-to-end). Not that there's anything wrong with that, but it lacks soul… and that makes me kind of sad.
I've built/am building something similar, but I spent the first half of my tech career as a UI/UX designer before becoming a software engineer and I'd _like_ to think it shows, but there is something about designing-in-code with agents that leads to homogenous outputs if you don't spend equal time on visual design as on the technical parts.
> "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.
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.
Yes, this is like, the best thing ever .. I've generally been doing this, albeit with command-line Jira and a "my workflow is my prompt" philosophy, resulting in a fleet of little kanbans .. and my agents are really, really doing well. They never sleep, eat, etc.
But .. you know something cute? AI makes using Jira fun, again.
I have got more frustrations than successes when I tried to run agents without supervising them. I believe the technology will get there eventually, but right now I need one IDE per agent and its cumbersome to merge the work.
Tangential question for Claude Code subscribers, mid June `claude -p` will move to api pricing (with some "SDK credits" before it kicks in), so headless usage will become 20-30 times more expensive, and all these high level orchestrator tools/workflows depend on it. What the next move for you? How does the OpenAI subscriptions compare? Similar limitations?
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.
A lot of that agent activity is combing over what was previously made, forcing constraints upon it so you have a reasonable expectation of what ends up on your desk for review.
For me, strong file structure helps as well. Reviewing a 3,000 line file it just created is abysmal. I wouldn't accept that from human nor machine :) Multiple files in the right places helps reduce cognitive load.
Sometimes I'll also review with the agent interactively. What is the most important file to review first, etc?
I like to stage changes into a "LGTM" pile. Then if I want changes, I'll have the agent "review unstaged changes - I want something different done here."
Lots of people are working on repetitive simple projects like the Nth website whatever or things like that, boring stuff. This LLM era is already a very big deal for these people.
Personally somehow I am working on stuff that has like 25% not trivial stuff and that is enough to have the same experience as you have.
But also lots of people just don't care about quality and they might be right with their customers/audience. In these cases when someone catches one, an agent is going to iterate on it and make it (seemingly) go away, bandage applied, who cares again. This has a market, I am sure. Lots of programmer folks are just as bad.
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.
So I've been in a hobby project for a few weeks -- transforming an old software modem binary to c code.
I gave it the existing modem, and had it build rigging to build test vectors. I had it specify the work in the modem. And to confirm that legacy<>legacy produced the same streams as the new code. I've also recorded test vectors vs. other modems.
I've since launched it on targeted refactoring and code reduction projects.
I am mostly not looking at the code. There's a 100KSLOC lump of code that is much cleaner than a decompilation but a fair bit dirtier than what I would write myself. It is not factored terribly. I have some hope of getting it to trim this down to 70KSLOC that then I can accept in small blocks.
It outperforms the original softmodem, hitting higher RX rates for the same line quality and using less CPU. It also has additional functionality.
So, you know, I would never have written something this large for a hobby myself. And it's cost me $200 and 20-30 minutes per day for a few weeks to get a huge functional surface that I do believe I will be able to trust at the end of the process.
That depends. When I'm working on a 1 in a million race condition in some multi-threaded code, the agent needs hours to figure out what is going on. (I would probably need weeks - I don't know as I've given up on some of these before I could point an agent at it)
No one is reviewing the code. Managers don't want us to review code either. It's a bottleneck. If something goes wrong (bugs) they are fixed as they come. It's a very sad era of software engineering. If there ever was some engineering in our trade, now it's mostly gone. We are guessing around, writing "skills" files with "please, do not introduce bugs" or "you are an owner, not a renter" or similar stuff. It's just very low effort, very undeterministic. Big apps out there are going down constantly because of AI slop (e.g., Github), and we are seeing it more often as well in non-so popular systems (e.g., in my company and other saas that we use).
Product managers never cared about the code. Engineering managers don't care about code as much as they did when they were engineers. Directors couldn't care less about code. CTOs don't know what code looks like anymore. We are at the end of the chain, and somehow we always took pride of well written and maintainble code because we knew deep inside that good systems are built based on good code. But now we are jeopardizing ourselves, it's us the engineers who don't care anymore about code and with AI that problems is amplified.
I usually aim to have Claude end up with about 500 lines of code after a night of work. Most of what it's doing is experimenting with many different approaches, summarizing them, and then giving me a relatively small diff to review and modify.
Yeah the multi-agent workflow just hasn't been satisfying to me. The more chats I try to run at once, the more I got lost and overwhelmed. I trust Claude to implement a plan correctly after I've reviewed it, but if I don't review all of the plans, I will miss some small detail that it misunderstood and it'll be a pain to fix later.
I'm like a 1-2 chats at a time kind of guy. I just don't see how I could keep my exact vision for the project otherwise.
I agree, but for small tasks - <20 lines that I can understand in a minute or two - perfect. Thinking about it - I have hundreds, if not thousands of tasks that I would like to do, improving pipelines, migrating from one tool to another, but never have time. The only question is - if I don't have time to do it, do I have time to prompt it?
You care about code quality. Many don’t. I had someone tell me this week that a 6000 line class was ok because it was easier for the model to understand and that’s more important than human comprehension. And I get his point but that seems like a big risk to take.
whenever i found a guy who uses parallel overnight agents, i asked them how many users they have. Crickets.
They do not have any users. Meanwhile, i've to do code reviews and all otherwise my 12,000+ users will be pissed off if anything in their workflow breaks.
This means i really cannot release more than 1 tiny feature a day. And using parallel agents, well that's good for testing but i don't think i need to add that many features to add anything.
I understand and agree with the feeling but then I also feel AI is too slow and too expensive.
My most successful autonomous runs have been expanding scrapers across a number of similar but different portals. I had examples and targets and it just kept searching for new ones and adding them.
But even doing basic ML auto research k have found it to be surprisingly poor except at trivial but useful augmentation of models. Yes it can implement things but somehow I am required a lot even though I set up a lot of framework around it.
My mental model is that it's very good at complex deterministic work like reading bad API docs and getting some connectors to work.
But perhaps I care less about being stuck in a local optimum there.
I never review anything writtend by codex in my pet projects. It works or it doesn't and then I prompt again. I can see how it's easy to multiply agents in this case.
Now when using it for my job... that's a totally different story: I review all the changes, so a single chat session with an agent can lead to a whole day of review. And it's great, sometimes the agent uses patterns and functions I don't know, so I learn a lot.
No one reads code that results from this. Those who say otherwise either lie or are very bad developers which is essentially the same as not reading that code.
the bottleneck moves from generation to review. agents parallelize, humans review sequentially — 8 parallel cards means 8x the diffs to read, none of the timelines overlap
Personally, this is somewhat close to what I want.
I want to have a fullblown cursor instance/window for each task I have, and a central Hub that manages spawning those instances, setting up the worktrees, etc.
Cursor seems to pretty much have all the available tools there already (it can already spawn agents to their own worktrees with proper setup scripts, for example). I don't get why they don't do it and instead insist on a buggy and confusing agents experience.
Unfortunately, most attempts at this seem to assume I want a model where "1 task = 1 agent = 1 chat", whereas what I really want is "1 task = 1 worktree = 1 full IDE around it".
With the full IDE I can have multiple agents/conversations, review code thoroughly and also chip in once in a while. I can have multiple models (that I pick) in multiple chats, iterate forwards, backwards, you name it.
I really don't understand why there seems to be this idea that "parallel agents" should live in their own little restricted flow that's limited to a tiny chat interface. I want the full flow for every agent!
I was hoping cursor would do this, but they really seem to be going the direction of turning their absolutely terrible web agents UI (where you can't even CHANGE THE MODEL!!!!) into a desktop thing. Sad, as I've been an Ultra paying customer and might have to leave soon with the direction they're heading.
one of your pages return 404 /comparison... but cool project! I guess we're just still not there to let agents run without supervision. At least for me.
This reminds me of Vibe Kanban (https://vibekanban.com/) which I use to manage coding agents on most of my projects.
The Vibe Kanban developers unfortunately decided that they didn't see a path to profitability and have stopped investing in the project. It's open source and so you can run it locally / fork it, but it has stopped improving and there are still annoying bugs that need to be fixed (and I don't have time to maintain it personally). This makes me sad because I would be willing to pay for Vibe Kanban, but I didn't need the features their paid plan offered (in retrospect maybe I should have paid anyway).
I'll give Kanbots a go :) I'd recommend liberally copying features from Vibe Kanban. In particular the remote support and "Open in VS Code" button (which in my case opens a local VSCode client pointing to a remote VSCode server) are critical for me.
The parallel agents concept is interesting. How does it handle state sync between agents when they're modifying the same board? Or is there built-in conflict resolution?
This is dope! We basically built something very similar internally for our team and it's been a very natural and intuitive way to manage agents (as opposed to having a bunch of terminals to track). Not every task/conversation can be done in the background, so it's been helpful for us internally to be able to seamlessly transition between "interactive conversation" and "background job done by agents" even within a single card.
91 comments
[ 2.0 ms ] story [ 75.6 ms ] threadI open such a page and I immediately know it was Claude that produced it (probably end-to-end). Not that there's anything wrong with that, but it lacks soul… and that makes me kind of sad.
I'm a bit anxious about putting myself out there, but I'd be curious if my efforts cross that bar for you or not? https://ouijit.com/ (and the repo is at https://github.com/ouijit/ouijit)
[0] https://windsurf.com/blog/windsurf-2-0
This is table-stakes for me to consider adoption of a tool like this.
But .. you know something cute? AI makes using Jira fun, again.
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.
For me, strong file structure helps as well. Reviewing a 3,000 line file it just created is abysmal. I wouldn't accept that from human nor machine :) Multiple files in the right places helps reduce cognitive load.
Sometimes I'll also review with the agent interactively. What is the most important file to review first, etc?
I like to stage changes into a "LGTM" pile. Then if I want changes, I'll have the agent "review unstaged changes - I want something different done here."
Personally somehow I am working on stuff that has like 25% not trivial stuff and that is enough to have the same experience as you have.
But also lots of people just don't care about quality and they might be right with their customers/audience. In these cases when someone catches one, an agent is going to iterate on it and make it (seemingly) go away, bandage applied, who cares again. This has a market, I am sure. Lots of programmer folks are just as bad.
I gave it the existing modem, and had it build rigging to build test vectors. I had it specify the work in the modem. And to confirm that legacy<>legacy produced the same streams as the new code. I've also recorded test vectors vs. other modems.
I've since launched it on targeted refactoring and code reduction projects.
I am mostly not looking at the code. There's a 100KSLOC lump of code that is much cleaner than a decompilation but a fair bit dirtier than what I would write myself. It is not factored terribly. I have some hope of getting it to trim this down to 70KSLOC that then I can accept in small blocks.
It outperforms the original softmodem, hitting higher RX rates for the same line quality and using less CPU. It also has additional functionality.
So, you know, I would never have written something this large for a hobby myself. And it's cost me $200 and 20-30 minutes per day for a few weeks to get a huge functional surface that I do believe I will be able to trust at the end of the process.
Product managers never cared about the code. Engineering managers don't care about code as much as they did when they were engineers. Directors couldn't care less about code. CTOs don't know what code looks like anymore. We are at the end of the chain, and somehow we always took pride of well written and maintainble code because we knew deep inside that good systems are built based on good code. But now we are jeopardizing ourselves, it's us the engineers who don't care anymore about code and with AI that problems is amplified.
I'm like a 1-2 chats at a time kind of guy. I just don't see how I could keep my exact vision for the project otherwise.
They do not have any users. Meanwhile, i've to do code reviews and all otherwise my 12,000+ users will be pissed off if anything in their workflow breaks.
This means i really cannot release more than 1 tiny feature a day. And using parallel agents, well that's good for testing but i don't think i need to add that many features to add anything.
Maximize providers profits. What can go wrong.
My most successful autonomous runs have been expanding scrapers across a number of similar but different portals. I had examples and targets and it just kept searching for new ones and adding them.
But even doing basic ML auto research k have found it to be surprisingly poor except at trivial but useful augmentation of models. Yes it can implement things but somehow I am required a lot even though I set up a lot of framework around it.
My mental model is that it's very good at complex deterministic work like reading bad API docs and getting some connectors to work.
But perhaps I care less about being stuck in a local optimum there.
Now when using it for my job... that's a totally different story: I review all the changes, so a single chat session with an agent can lead to a whole day of review. And it's great, sometimes the agent uses patterns and functions I don't know, so I learn a lot.
I want to have a fullblown cursor instance/window for each task I have, and a central Hub that manages spawning those instances, setting up the worktrees, etc.
Cursor seems to pretty much have all the available tools there already (it can already spawn agents to their own worktrees with proper setup scripts, for example). I don't get why they don't do it and instead insist on a buggy and confusing agents experience.
Unfortunately, most attempts at this seem to assume I want a model where "1 task = 1 agent = 1 chat", whereas what I really want is "1 task = 1 worktree = 1 full IDE around it".
With the full IDE I can have multiple agents/conversations, review code thoroughly and also chip in once in a while. I can have multiple models (that I pick) in multiple chats, iterate forwards, backwards, you name it.
I really don't understand why there seems to be this idea that "parallel agents" should live in their own little restricted flow that's limited to a tiny chat interface. I want the full flow for every agent!
I was hoping cursor would do this, but they really seem to be going the direction of turning their absolutely terrible web agents UI (where you can't even CHANGE THE MODEL!!!!) into a desktop thing. Sad, as I've been an Ultra paying customer and might have to leave soon with the direction they're heading.
The Vibe Kanban developers unfortunately decided that they didn't see a path to profitability and have stopped investing in the project. It's open source and so you can run it locally / fork it, but it has stopped improving and there are still annoying bugs that need to be fixed (and I don't have time to maintain it personally). This makes me sad because I would be willing to pay for Vibe Kanban, but I didn't need the features their paid plan offered (in retrospect maybe I should have paid anyway).
I'll give Kanbots a go :) I'd recommend liberally copying features from Vibe Kanban. In particular the remote support and "Open in VS Code" button (which in my case opens a local VSCode client pointing to a remote VSCode server) are critical for me.
Just a heads up, the website is extremely choppy on WebKit (Orion Browser) for me when scrolling
edit: not working with Claude Code on Amazon Bedrock, it needs a claude scription