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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

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12,651 Aufrufe • vor 2 Monaten •via X (Twitter)

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8 Kommentare

Profilbild von catman

catmanvor 2 Monaten

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?

Profilbild von Alex Stone

Alex Stonevor 2 Monaten

90% with no humans typing is the crazy part.

Profilbild von 安叫兽|Bird🕊️ 🔶 BNB

安叫兽|Bird🕊️ 🔶 BNBvor 2 Monaten

18,000 个代理一起跑，debug 现场估计比代码还精彩

Profilbild von Alek

Alekvor 2 Monaten

18000 agents?

Profilbild von Max Bevza

Max Bevzavor 2 Monaten

bullish on autonomous agents running wild

Profilbild von Adam · silent data failures

Adam · silent data failuresvor 2 Monaten

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?

Profilbild von Huysolo

Huysolovor 2 Monaten

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

Profilbild von Dima Glushakov

Dima Glushakovvor 2 Monaten

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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