121–130 of 191 posts
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.
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 for my infrastructure, each service running in its own container. I have a script that has a ./app worktree create worktreename. That creates a worktree as "worktreename" and spins up all of my docker infrastructure with prefixes for things like "WORKTREENAME", and I can access all my urls at worktreename.myapp.test (or just myapp.test for the main worktree).
This is working fine for now, but it'd be cool if one of these apps was compatible with this concept so I could move over to that.
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…
Tell your claude to set this up. Should do it in a single prompt
Earlier quoted context omitted.
People already barely reviewed code, most of it was imported libraries.
People keep saying this like it’s some meaningful point, but the reality is many people in different projects have a shared need for that code to work correctly, and there is a social proof involved in used open source libraries. That is why people look at downloads and dependent projects as heuristics of stability and correctness. That is not the case with (and cannot be obtained with) code authored by generative AI…
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…
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…
I see a bunch of these orchestrators, but is anything out there jj (jujitsu) native? I would really like to avoid hacking onto an existing product.
Isn’t this just vibe kanban? https://github.com/BloopAI/vibe-kanban
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.
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.
> "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 table-stake?