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CoworkOS framework enhances AI agent collaboration and automation

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced CoworkOS, a new framework designed to enhance the capabilities of AI agents for real-world automation tasks. This system separates strategy from execution, allowing for human-in-the-loop collaboration through shared artifacts and improving model performance via automated post-training. CoworkOS has demonstrated competitive results against existing agent applications like Codex and DeepSeek Harness, and has shown significant performance gains when used for automated post-training on models such as Qwen3.6-35B-A3B. AI

IMPACT This framework could significantly advance the development of AI agents capable of complex, long-horizon tasks and real-world automation.

RANK_REASON The item describes a new research paper detailing a novel framework for AI agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

CoworkOS framework enhances AI agent collaboration and automation

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2 / 100
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The item describes a new research paper detailing a novel framework for AI agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    CoworkOS:Scaling Agent Coworkers for Real-world Automation

    CoworkOS is a long-horizon agent harness that separates strategy from execution, supports human-in-the-loop collaboration via shared artifacts, and improves model performance through sustained automated post-training.

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