I really pulled out all the stops for the new version of beads_viewer (bv). The original version of bv was made in a single day and was just under 7k lines of Golang. This new version is… 80k lines. I added an insane number of great features. Your agents will love it (you, too).


Some more screenshots of the feature that lets you automatically export your beads to a static site on GitHub pages using the gh utility:

If you want to follow along live as I conjure this complex, powerful agent memory system out of thin air today using all my tricks, I just finished the process of drafting the final markdown plan document (the agents did; I haven’t even read it all yet!):

github.com/Dicklesworthst… x.com/doodlestein/st… The transformation of this 5,500-line master plan document into hundreds of interconnected beads is now in process... once I have these created, which will take multiple rounds and passes to iterated and improve them, I will boot up a big ol' swarm of agents to knock it all out.

My coding agent workflow has really changed a lot ever since I gave them access to messaging so that they can directly communicate with each other. Now, I have one of them come up with a super detailed plan and sometimes have GPT Pro review and improve the plan in the webapp.

Then I start up 4 or 5 Codex instances in the same project folder and tell them:

"Before doing anything else, read ALL of AGENTS dot md and register with agent mail and introduce yourself to the other agents. Then coordinate on the remaining tasks left in PLAN_TO_DO_XYZ.md with the other agents and come up with a game plan for splitting and reviewing the work."

Then I can queue up a ton of the following message in codex, and it will just keep plodding along until the context gets full:

"Proceed meticulously with the plan, doing all remaining unfinished tasks systematically and continuing to notate your progress in-line in the plan document and via agent mail messages."

Then they just keep cranking on their own for a really long time. And you don't need to supervise them much so you can be juggling multiple projects like this at once and make really great progress on all of them. If you want to try it yourself, it's totally free and open source:

https://x.com/doodlestein/status/1982631024774316220

I finally got around to making a tool I've wanted for a long time: you can basically think of it as being "like Gmail for coding agents."

If you've ever tried to use a bunch of instances of Claude Code or Codex at once across the same project, you've probably noticed how annoying it can be when they freak out about the other agent changing the files they're working on.

Then they start doing annoying things, like restoring files from git, in the process wiping out another agent's work without a backup.

Or if you've tried to have agents coordinate on two separate repos, like a Python backend and a Nextjs frontend for the same project, you may have found yourself acting as the go-between and liaison between two or three different agents, passing messages between them or having them communicate by means of markdown files or some other workaround.

I always knew there had to be a better way. But it's hard to get the big providers to offer something like that in a way that's universal, because Anthropic doesn't want to integrate with OpenAI's competitive coding tool, and neither wants to deal with Cursor or Gemini-CLI.

So a few days ago, I started working on it, and it's now ready to share with the world. Introducing the 100% open-source MCP Agent Mail tool. This can be set up very quickly and easily on your machine and automatically detects all the most common coding agents and configures everything for you.

I also include a ready-made blurb (see the README file in the repo, link in the next tweet) that you can add to your existing AGENTS dot md or CLAUDE dot md file to help the agents better leverage the system straight out of the gate.

It's almost comical how quickly the agents take to this system like a fish to water. They seem to relish in it, sending very detailed messages to each other just like humans do, and start coordinating in a natural, powerful way. They even give each other good ideas and pushback on bad ideas. They can also reserve access to certain files to avoid the "too many cooks" problems associated with having too many agents all working on the same project at the same time, all without dealing with git worktrees and "merge hell."

This also introduces a natural and powerful way to do something I've also long wanted, which is to automatically have multiple different frontier models working together in a collaborative, complementary way without me needing to be in the middle coordinating everything like a parent setting up playdates for their kids.

And for the human in the loop, I made a really slick web frontend that you can view and see all the messages your agents are sending each other in a nice, Gmail-like interface, so you can monitor the process. You can even send a special message to some or all your agents as the "Human Overseer" to give them a directive (of course, you can also just type that in manually into each coding agent, too.)

I made this for myself and know that I'm going to be getting a ton of usage out of it going forward. It really lets you unleash a massive number of agents using a bunch of different tools/models, and they just naturally coordinate and work with each other without stepping on each other's toes. It lets you as the human overseer relax a bit more as you no longer have to be the one responsible for coordinating things, and also because the agents watch each other and push back when they see mistakes and errors happening. Obviously, the greater the variety of models and agent tools you use, the more valuable that emergent peer review process will be.

Anyway, give it a try and let me know what you think. I'm sure there are a bunch of bugs that I'll have to iron out over the next couple days, but I've already been productively using it today to work on another project and it is pretty amazingly functional already!


Here's the link to the repo:

github.com/Dicklesworthst…

Now that I’ve had more time to think about the Rich Sutton interview with Dwarkesh, I have some further thoughts about why I think Sutton’s criticisms of LLMs are not compelling, and ultimately miss the point. And why LLMs can and will take us to the promised land of AGI/ASI… So first, to articulate the main objections he has:

LLMs are stateless, they can’t learn “on the job” in a continual way. Fixed training and deployment limits them fundamentally.

They just mimic things and don’t have a “real” world model.

They don’t have experience or goals.

Recently, I've noticed people making a big deal about how we haven't yet seen massive disruption to job markets and knowledge work from AI, and so they're starting to doubt that it will happen soon. And investors are wondering if they can just sort of ignore it for a while. This makes me think of the great Alfred Loomis, an amazing character if you've never heard of him before (there's a book about his life called Tuxedo Park, highly recommended).

He was a very successful Wall Street operator who did a lot of electrical utility deals in the 1920s.

Thread: Top 10 ways you can use #ChatGPT for #music:
1) modify a chord progression according to some directive, like composer or genre: 2) Write lyrics that follow some scenario or genre/influence:

@PastelNetwork This has been a real labor of love, and I am very proud of the results. A thread below on why we think this is important and has the real potential to change the NFT world: @PastelNetwork 1. First, what is this demo? This is a first peek of Pastel's state-of-the-art duplicate detection system and rareness scores. It's an interactive demo where users can submit images and within a minute or so get back a detailed visual report.