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Claude Code team just built an agent loop system with 18,000 agents 140,000 steps and 90% of the work runs with zero humans typing 0% → 02:11 - move from API calls to managed agents 25% → 04:33 - ship agents 10-15x faster 50% → 08:48 - cut P95... show more

Lunar

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12,651 次观看 • 2 个月前 •via X (Twitter)

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8 条评论

catman 的头像

catman2 个月前

the 02:11 shift from raw api calls to managed agents feels like the key move here. how are failures surfaced when 18,000 agents are running concurrently?

Alex Stone 的头像

Alex Stone2 个月前

90% with no humans typing is the crazy part.

安叫兽|Bird🕊️ 🔶 BNB 的头像

安叫兽|Bird🕊️ 🔶 BNB2 个月前

18,000 个代理一起跑，debug 现场估计比代码还精彩

Alek 的头像

Alek2 个月前

18000 agents?

Max Bevza 的头像

Max Bevza2 个月前

bullish on autonomous agents running wild

Adam · silent data failures 的头像

Adam · silent data failures2 个月前

Ninety percent with zero humans typing is the number; the one I would want beside it is how many of the 140,000 steps produced an artifact someone opened. A loop that large succeeds by summary unless something reads the output. Does the write-up say what checked the work?

Huysolo 的头像

Huysolo2 个月前

Agentic workflows scaling like this is wild, execution speed is completely leaving human bottlenecks behind

Dima Glushakov 的头像

Dima Glushakov2 个月前

The shift from direct API orchestration to managed execution is the section I would study first. Faster setup helps, but model-led fault tracing is what can make a large agent system practical to operate.

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Claude Code team just built an agent loop system of 18,000 agents 140,000 steps and 90% of the work runs with zero humans typing 02:11 - From API to managed agents 04:33 - Ship agents 10-15x faster 08:48 - Cut P95 latency by over 90% 24:33 - Claude finds the root cause 33:04 - Subagents, memory, dreaming, and vaults This one video is worth more than any paid agentic AI course Bookmark and watch it tonight Then read the article below

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174,850 次观看 • 6 个月前

this is pure f*cking treasure 10 GitHub repos with 165K+ combined stars to build your own AI agent team that works 24/7 most people still use one AI chat for everything. these repos turn Claude into a whole team: one agent researches, one codes, one reviews, and a lead runs them all one resource per step, from your first 3 agents to a full swarm running Claude and Codex together (1/10) CrewAI the easiest way to assemble a team of agents: give them roles and tasks, then hit kickoff ▸ (2/10) LangGraph connect agents into a graph with checkpoints, so if something fails it resumes instead of starting over ▸ (3/10) wshobson/agents ready-made agents for Claude Code (backend, frontend, security, tests, devops) plus an orchestrator to run them ▸ (4/10) oh-my-team 12 specialist agents for Claude Code that split the work and merge the results ▸ (5/10) agent-swarm your own self-hosted AI company: one lead agent hires workers and runs them 24/7 ▸ (6/10) Open-Agents spawns many Claude agents in parallel, so 6 tasks run at once instead of one after another ▸ (7/10) swarms an enterprise-grade framework for when your team grows from 5 agents to 50 ▸ (8/10) Microsoft Agent Framework Microsoft's new framework, the AutoGen successor, for workflows, agents and runtime in one place ▸ (9/10) CLI Agent Orchestrator runs Claude, Codex and other CLIs side by side as one team, with a supervisor watching all of them ▸ (10/10) ensemble launches Codex and Claude together, so they build and ship as one ▸ the loop: assemble → plug in → run → scale → orchestrate pick one, click, let it run, and while everyone else is still typing prompts, your agents are already shipping ↓

this is pure f*cking treasure 10 GitHub repos with 165K+ combined stars to build your own AI agent team that works 24/7 most people still use one AI chat for everything. these repos turn Claude into a whole team: one agent researches, one codes, one reviews, and a lead runs them all one resource per step, from your first 3 agents to a full swarm running Claude and Codex together (1/10) CrewAI the easiest way to assemble a team of agents: give them roles and tasks, then hit kickoff ▸ (2/10) LangGraph connect agents into a graph with checkpoints, so if something fails it resumes instead of starting over ▸ (3/10) wshobson/agents ready-made agents for Claude Code (backend, frontend, security, tests, devops) plus an orchestrator to run them ▸ (4/10) oh-my-team 12 specialist agents for Claude Code that split the work and merge the results ▸ (5/10) agent-swarm your own self-hosted AI company: one lead agent hires workers and runs them 24/7 ▸ (6/10) Open-Agents spawns many Claude agents in parallel, so 6 tasks run at once instead of one after another ▸ (7/10) swarms an enterprise-grade framework for when your team grows from 5 agents to 50 ▸ (8/10) Microsoft Agent Framework Microsoft's new framework, the AutoGen successor, for workflows, agents and runtime in one place ▸ (9/10) CLI Agent Orchestrator runs Claude, Codex and other CLIs side by side as one team, with a supervisor watching all of them ▸ (10/10) ensemble launches Codex and Claude together, so they build and ship as one ▸ the loop: assemble → plug in → run → scale → orchestrate pick one, click, let it run, and while everyone else is still typing prompts, your agents are already shipping ↓

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15,433 次观看 • 29 天前