https://gist.github.com/plembo/409a8d7b1bae66622dbcd26337bbb...
2,031 karma · joined June 26, 2018
https://gist.github.com/plembo/409a8d7b1bae66622dbcd26337bbb...
https://play.google.com/store/apps/details?id=com.newstargam...
https://play.google.com/store/apps/details?id=com.newstargam...
I think this tech (modern p2p) represents what agent-to-agent (a2a) should be built on.
Every agent should be reachable to each other without hosting itself as an http server.
related prototypes
HTML/artifact canvases have a lot of potential
https://x.com/backnotprop/status/2064951065439834378?s=20
https://x.com/backnotprop/status/2065436433985474726?s=20
https://github.com/plannotator/effective-html
Shared context workspaces are important
I review agent messages, some specs/plans, and conduct local code reviews with Plannotator [1].
For skills, I have a bunch of custom ones for my own workflow. and for public skills I really only use the interrogate skill from cursor's lauren [2].
Key workflow stuff:
- Almost all work I do gets done in a git worktree.
- ghostty + Mac OS gives me all the organization I need for multi-agenting
- turn off all agent memory, this has only ever caused problems for me.
[2] https://github.com/cursor/plugins/blob/main/pstack/skills/in...
> agents do a good job of looping over PR comments
This is the easy part. Most harnesses enable some sort of integration now, so you can actually create a smooth local experience around this as well - better code before it ships to more costly review or bloats PR threads.
> guided, educational code review tool
This is a bit tougher, and I find the main harness chat tends to work best. I learn better when I'm more engaged and aware of what I'm asking. It's easy to stick a code tour type of thing on a screen. It's hard to really nail the right attention and learning mechanism around it.
Shame us all for moving away from something so perfect, precise, and that "doesn't have edge cases."
Hey - if you invent a programming language that can be used in such a way and create guaranteed deterministic behavior based on expressed desires as simple as natural language - ill pay a $200/m subscription for it.
The constant urge I have today is for some sort of spec or simpler facts to be continuously verified at any point in the development process; Something agents would need to be aware of. I agree with the blog and think it's going to become a team sport to manage these requirements. I'm going to try this out by evolving my open source tool [1] (used to review specs and code) into a bit more of a collaborative & integrated plane for product specs/facts - https://plannotator.ai/workspaces/
As a layer of abstraction, it also creates more requirements: need a browser, likely need includes/cdn libs to avoid bloat, all sorts of other things. Markdown is consumable, diffable, shareable in raw form - and you can add enrichment layers on top without much effort.
But like I said, this is something for those users. I launch many review processes locally with `claude -p`
this is the original thread https://x.com/ClaudeDevs/status/2054610152817619388?s=20
If you're an active `claude -p` user, it will now cost you API rates vs being able to user your subscription.
UPDATE: https://x.com/lydiahallie/status/2054650920768807313?s=20
Still confused.
Visual explainers certainly come in hand. You need to have both the extra time and cost of tokens accounted for when you ask for these. As well as maintainability - you lose things like vcs/diffs over plans that are much more readable as markdown.
The more interactivity on the surface, the better. Esp if they create feedback loops with the agent. Simple annotations to start.
Markdown still goes a long way. I’ve effectively been enriching plan rendering in Plannotator. Now supporting GFM, custom svgs, etc.
https://github.com/backnotprop/plannotator
For fun, I also enabled annotations on top of these type of svgs, see here https://x.com/plannotator/status/2052851731998941380?s=46
free & open source: https://github.com/backnotprop/plannotator