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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 просмотров • 2 месяцев назад •via X (Twitter)

Наука и технологии Образование

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Комментарии: 8

Фото профиля catman

catman2 месяцев назад

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?

Фото профиля Alex Stone

Alex Stone2 месяцев назад

90% with no humans typing is the crazy part.

Фото профиля 安叫兽|Bird🕊️ 🔶 BNB

安叫兽|Bird🕊️ 🔶 BNB2 месяцев назад

18,000 个代理一起跑，debug 现场估计比代码还精彩

Фото профиля Alek

Alek2 месяцев назад

18000 agents?

Фото профиля Max Bevza

Max Bevza2 месяцев назад

bullish on autonomous agents running wild

Фото профиля Adam · silent data failures

Adam · silent data failures2 месяцев назад

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?

Фото профиля Huysolo

Huysolo2 месяцев назад

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

Фото профиля Dima Glushakov

Dima Glushakov2 месяцев назад

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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