> I went to senior folks at companies like Temporal and Anthropic, telling them they should build an agent orchestrator, that Claude Code is just a building block, and it’s going to be all about AI workflows and “Kubernetes for agents”. I went up onstage at multiple events and described my vision for the orchestrator. I went everywhere, to everyone. (from "Welcome to Gas Town" https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...)
That Anthropic releases Agent Teams now (as rumored a couple of weeks back), after they've already adopted a tiny bit of beads in form of Tasks) means that either they've been building them already back when Steve pitched orchestrators or they've decided that he's been right and it's time to scale the agents. Or they've arrived at the same conclusions independently -- it won't matter in the larger scale of things. I think Steve greately appreciates it existing; if anything, this is a validation of his vision. We'll probably be herding polecats in a couple of months officially.
The main claude instance is instructed to launch as many ralph loops as it wants, in screen sessions. It is told to sleep for a certain amount of time to periodically keep track of their progress.
It worked reasonably well, but I don't prefer this way of working... yet. Right now I can't write spec (or meta-spec) files quick enough to saturate the agent loops, and I can't QA their output well enough... mostly a me thing, i guess?
Same for me, however, the velocity of the whole field is astonishing and things change as we get used to them. We are not talking that much about hallucinating anymore, just 4-5 months ago you couldn't trust coding agents with extracting functionality to a separate file without typos, now splitting Git commits works almost without a hinch. The more we get used to agents getting certain things right 100% of the time, the more we'll trust them. There are many many things that I know I won't get right, but I'm absolutely sure my agent will. As soon as we start trusting e.g. a QA agent to do his job, our "project management" velocity will increase too.
Interestingly enough, the infamous "bowling score card" text on how XP works, has demonstrated inherently agentic behaviour in more way than one (they just didn't know what "extreme" was back then). You were supposed to implement a failing test and then implement just enough functionality for this test to not fail anymore, even if the intended functionality was broader -- which is exactly what agents reliably do in a loop. Also, you were supposed to be pair-driving a single machine, which has been incomprehensible to me for almost decades -- after all, every person has their own shortcuts, hardware, IDEs, window managers and what not. Turns out, all you need is a centralized server running a "team manager agent" and multiple developers talking to him to craft software fast (see tmux requirement in Gas Town).
The fact that Anthropic and OpenAI have been going on this long without such orchestration, considering the unavoidable issues of context windows and unreliable self-validation, without matching the basic system maturity you get from a default Akka installation shows us that these leading LLM providers (with more money, tokens, deals, access, and better employees than any of us), are learning in real time. Big chunks of the next gen hype machine wunder-agents are fully realizable with cron and basic actor based scripting. Deterministically, write once run forever, no subscription needed.
Kubernetes for agents is, speaking as a krappy kubernetes admin, not some leap, it’s how I’ve been wiring my local doom-coding agents together. I have a hypothesis that people at Google (who are pretty ok with kubernetes and maybe some LLM stuff), have been there for a minute too.
Good to see them building this out, excited to see whether LLM cluster failures multiply (like repeating bad photocopies), or nullify (“sorry Dave, but we’re not going to help build another Facebook, we’re not supposed to harm humanity and also PHP, so… no.”).
I remember having conversations about this when the first ChatGPT launched and I don’t work at an AI company.
Like, who cares? Judging from his blog recount of this it doesn't seem like anybody actually does. He's an unnecessarily loud and enthused engineer inserting himself into AI conversations instead of just playing office politics to join the AI automation effort inside of a big corporation?
"wow he was yelling about agent orchestration in March 2025", I was about 5 months behind him, the company I was working for had its now seemingly obligatory "oh fuck, hackathon" back in August 2025
and we all came to the same conclusions. conferences had everyone having the same conclusion, I went to the local AWS Invent, all the panels from AWS employees and Developer Relations guys were about that
it stands to reason that any company working on foundational models and an agentic coding framework would also have talent thinking about that sooner than the rest of us
so why does Yegge want all of this attention and think its important at all, it seems like it would have been a waste of energy to bother with, like in advance everything should have been able to know that. "Anthropic! what are you doing! listen to meeeehhhh let me innnn!"
doesn't make sense, and gastown's branding is further unhinged goofiness
yeah I can't really play the attribution games on this one, can't really get behind who cares. I'm glad its available in a more benign format now
... the "limit" were agents were not as smart then, context window was much smaller and RLVR wasn't a thing so agents were trained for just function calling, but not agent calling/coordination.
we have been doing it since then, the difference really is that the models have gotten really smart and good to handle it.
But this shows how much stuff is still to do in the ai space
Haven't tried Kimi, hear good things.
At least, my M1 Pro seems to struggle and take forever using them via Ollama.
I'm burning through so many tokens on Cursor that I've had to upgrade to Ultra recently - and i'm convinced they're tweaking the burn rate behind the scenes - usage allowance doesn't seem proportional.
Thank god the open source/local LLM world isn't far behind.
Are you spending more than $150k per year on AI?
(Also, you're talking about the cost of your Cursor subscription, when the article is about Claude Code. Maybe try Claude Max instead?)
I guarantee you that price will double by 2027. Then it’ll be a new car payment!
I’m really not saying this to be snarky, I’m saying this to point out that we’re really already in the enshittification phase before the rapid growth phase has even ended. You’re paying $200 and acting like that’s a cheap SaaS product for an individual.
I pay less for Autocad products!
This whole product release is about maximizing your bill, not maximizing your productivity.
I don’t need agents to talk to each other. I need one agent to do the job right.
Wonder how they compare?
No polecats smh
I love that we are in this world where the crazy mad scientists are out there showing the way that the rest of us will end up at, but ahead of time and a bit rough around the edges, because all of this is so new and unprecedented. Watching these wholly new abstractions be discovered and converged upon in real time is the most exciting thing I've seen in my career.
Then, in your prompt you tell it the task you want, then you say, supervise the implementation with a sub agent that follows the architecture skill. Evaluate any proposed changes.
There are people who maximize this, and this is how you get things like teams. You make agents for planning, design, qa, product, engineering, review, release management, etc. and you get them to operate and coordinate to produce an outcome.
That's what this is supposed to be, encoded as a feature instead of a best practice.
This sounds more like an automation of that idea than just N-times the work.
Just ask claude to write a plan and review/edit it yourself. Add success criteria/tests for better results.
You run out of context so quickly and if you don’t have some kind of persistent guidance things go south
```
Rules:
- Only one disk can be moved at a time.
- Only the top disk from any stack can be moved.
- A larger disk may not be placed on top of a smaller disk.
For all moves, follow the standard Tower of Hanoi procedure: If the previous move did not move disk 1, move disk 1 clockwise one peg (0 -> 1 -> 2 -> 0).
If the previous move did move disk 1, make the only legal move that does not involve moving disk1.
Use these clear steps to find the next move given the previous move and current state.
Previous move: {previous_move} Current State: {current_state} Based on the previous move and current state, find the single next move that follows the procedure and the resulting next state.
```
This is buried down in the appendix while the main paper is full of agentic swarms this and millions of agents that and plenty of fancy math symbols and graphs. Maybe there is more to it, but the fact that they decided to publish with such a trivial task which could be much more easily accomplished by having an llm write a simple python script is concerning.
this does eat up tokens _very_ quickly though :(
Though I do hope the generated code will end up being better than what we have right now. It mustn't get much worse. Can't afford all that RAM.
It's just HN that's full of "I hate AI" or wrong contrarian types who refuse to acknowledge this. They will fail to reap what they didn't sow and will starve in this brave new world.
I don't need anything more complicated than that and it works fine - also run greptile[1] on PR's
https://github.com/FredericMN/Coder-Codex-Gemini https://github.com/fengshao1227/ccg-workflow
This one also seems promising, but I haven't tried it yet.
https://github.com/bfly123/claude_code_bridge
All of them are made by Chinese dev. I know some people are hesitant when they see Chinese products, so I'll address that first. But I have tried all of them, and they have all been great.
https://www.augmentcode.com/product/intent
can use the code AUGGIE to skip the queue. Bring your own agent (powered by codex, CC, etc) coming to it next week.
1. GPT-5.2 Codex Max for planning
2. Opus 4.5 for implementation
3. Gemini for reviews
It’s easy to swap models or change responsibilities. Doc and steps here: https://github.com/sathish316/pied-piper/blob/main/docs/play...
This new orchestration feature makes it much more useful since they share a common task list and the main agent coordinates across them.
[1] https://github.com/pchalasani/claude-code-tools?tab=readme-o...
This seems handled by this new agent which is cool.
I gave up on worktrees and hacked together a solution with fine-grained lockfiles for editing, running builds, etc that worked surprisingly good for what it was
We cannot allow model providers to own the browsers, CLIs, memory, IDEs, extensions and other tooling. Its not just a matter of power but also they just suck at it as i experience every time i have to use claude code instead of amp.
I truly hope we get the pattern of innovation that looks like:
- some dude vibecodes a really cool idea
- model providers build into their reference implementations
- model providers optimize models to work optimally
- startup and/or open source projects step in and build something that is actually usable and opens a new market segment
We saw this play out beautifully with amp, kilo, roo, cline, continue
Another aspect is that we do not want interfaces just made for agents to work in teams, we want software made for humans and agents, that are true platforms for these agent teams to collaborate in.
Why do agents need to speak to each other if they’re just doing the work correctly the first time?
Is it an admission that a single agent is not useful and reliable enough?
I've switched this over to a team of 4 now that talk to each other to discuss issues they find and it's amazing. They confirm between themselves and if they wrongly identified something the others correct them.
I understand that it works better, but I am rightfully pointing out that it's less efficient.
An analogy would be putting a V8 engine into a pickup truck to make it go as fast as a Mazda Miata.
Assign roles to different models and have them coordinate: Claude as the lead, Codex on backend, Gemini on frontend, etc.
I wrote about my experiences with multi-agent orchestration here: https://x.com/khaliqgant/status/2019124627860050109?s=46
Meanwhile, the same issues that have plagued these tools since their inception are largely ignored: hallucination, innacuracy, context collapse, etc. These won't be solved by engineering, but by new research and foundational improvements.
On one hand, solid engineering was sorely needed, and can extract a lot of value from the current tech. But on the other, all these announcements and improvements feel like companies grasping at straws to keep the hype cycle going by any means necessary. Charts must go up and to the right, or investors get antsy.
It's all adding to the mountain of signs that suggest that this isn't the path to artificial intelligence. It's interesting tech, with possibly many valuable applications, but the "AI" narrative is frankly tiring. I wish I could fast forward on this speculative phase, go past the inevitable crash, and arrive at a timeframe where we've figured out what this tech is actually good for, and where we hopefully use it more for good than evil.
(i thought gas town was satire? people in comments here seem to be saying that gas town also had multi-agent file sharing for work tracking)
