To the folks comparing this to GasTown: keep in mind that Steve Yegge explicitely pitched agent orchestrators to among others Anthropic months ago:
> 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.
I’ve been mostly holding off on learning any of the tools that do this because it seemed so obvious that it’ll be built natively. Will definitely give this a go at some point!
This is great and all but, who can actually afford to let these agents run on tasks all day long? Is anyone here actually using this or are these rollouts aimed at large companies?
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.
I absolutely cannot trust Claude code to independently work on large tasks. Maybe other people work on software that's not significantly complex, but for me to maintain code quality I need to guide more of the design process. Teams of agents just sounds like adding a lot more review and refactoring that can just be avoided by going slower and thinking carefully about the problem.
While i appreciate anthropic making a proof of concept like they did with claude code cli on which they can then do RL to optimise the patterns that work, I expect this to be as unusable as the cli itself. Its a big difference if a model provider internalises something like thinking mode which mainly depends on context and text or if they try to grab a part of the agent loop which has to run on the side of the systems we build and use.
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.
I’m looking for something like this, with opus in the driver seat, but the subagents should be using different LLMs, such as Gemini or Codex. Anyone know if such a tool? just-every/code almost does this, but the lead/orchestrator is always codex, which feels too slow compared to opus or Gemini.
This sounds very promising. Using multiple CC instances (or mix of CLI-agents) across tmux panes has always been a workflow of mine, where agents can use the tmux-cli [1] skill/tool to delegate/collaborate with others, or review/debug/validate each others work.
This new orchestration feature makes it much more useful since they share a common task list and the main agent coordinates across them.
I was working on my own alternative to Beads... then I realized I could do exactly this with something similar to Beads, I'm planning on open sourcing it soon because I like what I have so far, I also made it so I can sync my tasks directly to my GitHub projects as well. I think its more useful to have agent tasks eventually synched back up to real ticketing systems for historical reasons. Besides, its better to have alternatives that are agent agnostic.
Are people using Claude max 20x plan for personal pet projects? Are these expensed? Have you liquidated all other hobbies to fund this? Asking for a friend.
I just built a quick plugin to automatically add agents & skills then fire off a team with them, depending on your task: https://github.com/drbscl/dream-team
Been waiting for this to drop and excited to test it out. We've been building something in this space - https://github.com/AgentWorkforce/relay, a real-time messaging layer that lets AI coding agents talk to each other across any CLI.
Assign roles to different models and have them coordinate: Claude as the lead, Codex on backend, Gemini on frontend, etc.
something i really like from tryin git out over the last 10 minutes is that the main agent will continue talking to you while other agents are working, so you don't have to queue a message
Excited to try this out. I've seen a lot of working systems on my own computer that share files to talk between different Claude Code agents and I think this could work similarly to that.
(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)
I find it amusing that the innovation in this space for the past year+ has been mostly centered around engineering: MCP, "agents", "skills", etc. Now "agent" orchestration is the new hotness.
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.
Any self respecting engineer should recognize that these tools and models only serve to lower the value of your labor. They aren't there to empower you, they aren't going to enable you to join the ruling class with some vibe-rolled slop SaaS.
Using these things will fry your brain's ability to think through hard solutions. It will give you a disease we haven't even named yet. Your brain will atrophy. Do you want your competency to be correlated 1:1 to the quality and quantity of tokens you can afford (or be loaned!!)?
Their main purpose is to convince C-suite suits that they don't need you, or they should be justified in paying you less.This will of course backfire on them, but in the meantime, why give them the training data, why give them the revenue??
I'd bet anything these new models / agentic-tools are designed to optimize for token consumption. They need the revenue BADLY. These companies are valued at 200 X Revenue.. Google IPO'd at 10-11 x lmfao . Wtf are we even doing? Can't wait to watch it crash and burn :) Soon!
Orchestrate teams of Claude Code sessions
(code.claude.com)384 points by davidbarker 5 February 2026 | 216 comments
Comments
> 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.
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.
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.
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...
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
(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)
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?
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.
Using these things will fry your brain's ability to think through hard solutions. It will give you a disease we haven't even named yet. Your brain will atrophy. Do you want your competency to be correlated 1:1 to the quality and quantity of tokens you can afford (or be loaned!!)?
Their main purpose is to convince C-suite suits that they don't need you, or they should be justified in paying you less.This will of course backfire on them, but in the meantime, why give them the training data, why give them the revenue??
I'd bet anything these new models / agentic-tools are designed to optimize for token consumption. They need the revenue BADLY. These companies are valued at 200 X Revenue.. Google IPO'd at 10-11 x lmfao . Wtf are we even doing? Can't wait to watch it crash and burn :) Soon!