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#code#agents#don#kanban#agent#review#https#something#github#claude

Discussion (71 Comments)Read Original on HackerNews
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, I always end up tweaking something the agent produced. I wonder if I should let go of that control...
It definitely has fewer bugs than a senior developer, but it really hinges on getting the plan right. 20 minutes of planning and 20 of implementation sounds about right for my workflow as well, just make sure you have GPT as a reviewer. It's very nitpicky and finds lots of bugs.
First, that this is challenging to scale across large orgs. Even if your plans produce high quality code, that isn’t true for everyone. I’m definitely struggling with slop code being collectively mailed to me for review my our 1,000 engineers that were told to use their AI subscription all at once.
I feel like we should be taking “prompt engineering” more seriously. And when people mail me code to review, it should also include the agentic workflow and plan. So that when code isn’t up to quality, and can have a discussion about the prompts used to generate it.
My second thought is related to your senior engineer comment. This isn’t surprising, because in most engineering orgs, seniority is completely unrelated to code quality. In fact, many orgs incentive the opposite: “senior” devs that push out buggy code quickly and push accountability downhill to the junior devs.
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 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.
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.
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.
I've been working for the last week or two on getting my new tool up to parity with VK with additional improvements. I've been posting some screenshots into the Vibe Kanban discord as well. Hopefully it'll be a great fit for your use case when I finally am ready to launch it.
(My tool aims for better features than VK in both the Kanban board and agent workspaces, while adding extra systems like desktop windowing, plugins, in-browser VSCode integration, and htmx-like server-rendered UI. The remote access also works differently - you host the whole thing like OpenClaw and access the remote desktop UI from the browser, rather than run a webserver on your laptop to access remote coding agents.)
This is table-stakes for me to consider adoption of 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 to DONE.
[0] https://windsurf.com/blog/windsurf-2-0
jira-cli and hermes, for example.
in fact, wiring hermes up to an existing Jira(/other_PM_system) is, well .. fruitful.
Also, Linear themselves are also working on this.
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
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.
I am working on exactly this interface for my new tool called Kotkit. You start with kanban board management of workspaces. Each workspace (worktree on one/multiple repos) is a feature-rich IDE interface in a remote-capable in-browser desktop. You can spawn multiple agents with a good UI wrapper and full auditable logs, solve worktree rebase/merge with 1-click AI features, and there is also an embedded VSCode to solve edge cases. It also supports very deep plugin integration like IntelliJ.
Currently dogfooding it on my own projects and will be released sometime soon.
But .. you know something cute? AI makes using Jira fun, again.
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)
I think a lot of the problems with the homogenous outputs of front-end design wouldn't be such a problem if the models naturally make their designs so much simpler, but they are LLM's so they are always going to be overly verbose.
I was curious so I had asked my agent to redesign and recreate your front page for comparison and it gave me this: https://ouijit-redesign.vercel.app
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.