scaling-ai

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#scaling-ai

My friend gave Claude Code and Codex agents a way to talk to each other. Once this went over a hundred agents they reinvented bureaucracy.

Reddit r/AI_Agents ↗ · 3d ago

The article introduces OpenRig, an open-source harness for managing fleets of AI agents like Claude Code and Codex, which uses bureaucratic processes to prevent rogue behavior and ensure scalable coordination.

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#scaling-ai

@LangChain: Next on the Interrupt main stage: Building Jarvis: @jpmorgan’s Agent Building Assembly Line How @useapolloio rearchitec…

X AI KOLs Timeline ↗ · 4d ago Cached

An announcement for talks at the Interrupt main stage covering AI agent building with LangChain, JPMorgan's agent assembly line, and scaling agentic AI at Omnicom.

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#scaling-ai

@GergelyOrosz: I am a sucker for good books, and so especially O'Reilly books. Here's one that is WIP, but in return, it is free, than…

X AI KOLs Following ↗ · 6d ago Cached

A free, work-in-progress O'Reilly book titled 'Scaling AI Adoption in Engineering' offers a pragmatic framework for CTOs and engineering leaders to scale AI adoption and deliver business value.

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#scaling-ai

@omarsar0: Access control bottlenecks teams scaling AI agents. You want agents to move fast, but every new agent adds more permiss…

X AI KOLs Timeline ↗ · 2026-09-17 Cached

Opal Zero is an AI-driven access governance platform that grants just-in-time, task-scoped access to AI agents to mitigate permission bottlenecks in scaling teams.

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#scaling-ai

@_jasonwei: When language models first started using tools well, I was sympathetic to the narrative that instead of scaling up lang…

X AI KOLs Timeline ↗ · 2026-08-17 Cached

The author argues that while tool use allows smaller language models to perform tasks effectively, larger models remain crucial for speed, reliability, and internalized knowledge, emphasizing the ongoing need for scaling in AI.

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#scaling-ai

The foundational elements of AI architecture that IT leaders need to scale

MIT Technology Review ↗ · 2026-07-07 Cached

The article outlines four foundational elements of AI architecture—data quality, context engineering, governance, and human expertise—that IT leaders should prioritize to scale AI systems reliably as models evolve.

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