alt Hacker NewsClaude Code's new hidden feature: Swarms
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This is just sub agents, built into Claude. You don’t need 300,000 line tmux abstractions written in go. You just tell Claude to do work in parallel with background sub agents. It helps to have a file for handing off the prompt, tracking progress, and reporting back. I also recommend constraining agents to their own worktrees. I am writing down the pattern here https://workforest.space while nearly everyone is building orchestrators i also noticed claude is already the best orchestrator for claude.
I want it to generate better code but less of it, and be more proactive about getting human feedback before it starts going off the rails. This sounds like an inexorable push in the opposite direction.
I can see this approach being useful once the foundation is more robust, has better common sense, knows when to push back when requirements conflict or are underspecified. But with current models I can only see this approach as exacerbating the problem; coding agents solution is almost always "more code", not less. Makes for a nice demo, but I can't imagine this would build anything that wouldn't have huge operational problems and 10x-100x more code than necessary.
I'd really like to see a regular poll on HN that keeps track of which AI coding agents are the most popular among this community, like the TIOBE Index for programming languages.
Hard to keep up with all the changes and it would be nice to see a high level view of what people are using and how that might be shifting over time.
The problem I’ve been having is that when Claude generates copious amounts of code, it makes it way harder to review than small snippets one at a time.
Some would argue there’s no point reviewing the code, just test the implementation and if it works, it works.
I still am kind of nervous doing this in critical projects.
Anyone just YOLO code for projects that’s not meant to be one time, but fully intend to have to be supported for a long time? What are learnings after 3-6 months of supporting in production?
>You're not talking to an AI coder anymore. You're talking to a team lead. The lead doesn't write code - it plans, delegates, and synthesizes.
They couldn't even be bothered to write the Tweet themselves...
Looks like agent orchestrators provided by the foundation model providers will become a big theme in 2026. By wrapping it in terms that are already used in software development today like team leads, team members, etc. rather than inventing a completely new taxonomy of Polecats and Badgers, will help make it more successful and understandable.
We call it Shawarma where I come from
Listen team lead and the whole team, make this button red.
Claude Code in the desktop app seems to do this? It's crazy to watch. It sets of these huge swarms of worker readers under master task headings, that go off and explore the code base and compile huge reports and todo lists, then another system behind the scenes seems to be compiling everything to large master schemas/plans. I create helper files and then have a devops chat, a front end chat, an architecture chat and a security chat, and once each it done it's work it automatically writes to a log and the others pick up the log (it seems to have a system reminder process build in that can push updates from other chats into other chats. It's really wild to watch it work, and it's very intuitive and fun to use. I've not tried CLI claude code only claude code in the desktop app, but desktop app sftp to a droplet with ssh for it to use the terminal is a very very interesting experience, it can seem to just go for hours building, fixing, checking it's own work, loading it's work in the browser, doing more work etc all on it's own - it's how I built this: https://news.ycombinator.com/item?id=46724896 in 3 days.
How is this different from GSD: https://github.com/glittercowboy/get-shit-done
I've been using that and it's excellent
Also created my own version of this. Seems like this is an idea whose time has come.
My implementation was slightly different as there is no shared state between tasks, and I don't run them concurrently/coordinate. Will be interesting to see if this latter part does work because I tried similar patterns and it didn't work. Main issue, as with human devs, was structuring work.
> You're not talking to an AI coder anymore. You're talking to a team lead. The lead doesn't write code - it plans, delegates, and synthesizes.
Even 90 word tweets are now too long for these people to write without using AI, apparently.
A guy who worked at docker on docker swarm now works at Anthropic so makes sense
It feels like Auto-GPT, BabyAGI, and the like were simply ahead of their time
I'm a fan of AI coding tools but the trend of adding ever more autonomy to agents confuses me.
The rate at which a person running these tools can review and comprehend the output properly is basically reached with just a single thread with a human in the loop.
Which implies that this is not intended to be used in a setting where people will be reading the code.
Does that... Actually work for anyone? My experience so far with AI tools would have me believe that it's a terrible idea.
Hasn't cursor been doing this with it's Plan mode for a while? Or is this different?
Is this significantly different that the subagents that are already in CC?
Answering the question how to sell more tokens per customer while maintaining ~~mediocre~~ breakthrough results.
Isn't this pretty much what Ruv has been building for like two years?
hey that's exactly how I made Gemini 2.5 Flash give useful results in Opencode! a few specialized "Merc" subagents and a "Master" agent that can do nothing but send "Mercs" into the codebase
This no doubt takes some inspiration from mcp_agent_mail https://github.com/Dicklesworthstone/mcp_agent_mail
I'm already burning through enough tokens and producing more code than can be maintained - with just one claude worker. Feel like I need to move into the other direction, more personal hands-on "management".
Am I the only one still looking at different and correcting the AI abiyt design and algorithms so it stays on the path I want, or do you just YOLO at this point?
https://xcancel.com/NicerInPerson/status/2014989679796347375
In his second post he included a link to GitHub: https://github.com/mikekelly/claude-sneakpeek
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I'm not going to try this. Anthropic will probably ban me again.
Everyone is wrapping Claude Code in Tmux and claiming they are a magician. I am not so good at marketing but I've done this here https://github.com/mohsen1/claude-code-orchestrator
Mine also rotate between Claude or Z.ai accounts as they ran out of credits
Ok it might sound crazy but I actually got the best quality of code (completely ignoring that the cost is likely 10x more) by having a full “project team” using opencode with multiple sub agents which are all managed by a single Opus instance. I gave them the task to port a legacy Java server to C# .NET 10. 9 agents, 7-stage Kanban with isolated Git Worktrees.
Manager (Claude Opus 4.5): Global event loop that wakes up specific agents based on folder (Kanban) state.
Product Owner (Claude Opus 4.5): Strategy. Cuts scope creep
Scrum Master (Opus 4.5): Prioritizes backlog and assigns tickets to technical agents.
Architect (Sonnet 4.5): Design only. Writes specs/interfaces, never implementation.
Archaeologist (Grok-Free): Lazy-loaded. Only reads legacy Java decompilation when Architect hits a doc gap.
CAB (Opus 4.5): The Bouncer. Rejects features at Design phase (Gate 1) and Code phase (Gate 2).
Dev Pair (Sonnet 4.5 + Haiku 4.5): AD-TDD loop. Junior (Haiku) writes failing NUnit tests; Senior (Sonnet) fixes them.
Librarian (Gemini 2.5): Maintains "As-Built" docs and triggers sprint retrospectives.
You might ask yourself the question “isn’t this extremely unnecessary?” and the answer is most likely _yes_. But I never had this much fun watching AI agents at work (especially when CAB rejects implementations). This was an early version of the process that the AI agents are following (I didn’t update it since it was only for me anyway): https://imgur.com/a/rdEBU5I