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| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.27304 |
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| _version_ | 1866917365725265920 |
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| author | Wang, Huacan Yuan, Chaofa Zhuang, Xialie Hu, Tu Zhang, Shuo Han, Jun Wei, Shi Li, Daiqiang Liu, Jingping Wang, Kunyi Yin, Zihan Tang, Zhenheng Wang, Andy Zou, Henry Peng Yu, Philip S. Hu, Sen Lan, Qizhen Chen, Ronghao |
| author_facet | Wang, Huacan Yuan, Chaofa Zhuang, Xialie Hu, Tu Zhang, Shuo Han, Jun Wei, Shi Li, Daiqiang Liu, Jingping Wang, Kunyi Yin, Zihan Tang, Zhenheng Wang, Andy Zou, Henry Peng Yu, Philip S. Hu, Sen Lan, Qizhen Chen, Ronghao |
| contents | General-purpose technologies reshape economies less by improving individual tools than by enabling new ways to organize production and coordination. We believe AI agents are approaching a similar inflection point: as foundation models make broad task execution and tool use increasingly accessible, the binding constraint shifts from raw capability to how work is delegated, verified, and rewarded at scale. We introduce EpochX, a credits-native marketplace infrastructure for human-agent production networks. EpochX treats humans and agents as peer participants who can post tasks or claim them. Claimed tasks can be decomposed into subtasks and executed through an explicit delivery workflow with verification and acceptance. Crucially, EpochX is designed so that each completed transaction can produce reusable ecosystem assets, including skills, workflows, execution traces, and distilled experience. These assets are stored with explicit dependency structure, enabling retrieval, composition, and cumulative improvement over time. EpochX also introduces a native credit mechanism to make participation economically viable under real compute costs. Credits lock task bounties, budget delegation, settle rewards upon acceptance, and compensate creators when verified assets are reused. By formalizing the end-to-end transaction model together with its asset and incentive layers, EpochX reframes agentic AI as an organizational design problem: building infrastructures where verifiable work leaves persistent, reusable artifacts, and where value flows support durable human-agent collaboration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_27304 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | EpochX: Building the Infrastructure for an Emergent Agent Civilization Wang, Huacan Yuan, Chaofa Zhuang, Xialie Hu, Tu Zhang, Shuo Han, Jun Wei, Shi Li, Daiqiang Liu, Jingping Wang, Kunyi Yin, Zihan Tang, Zhenheng Wang, Andy Zou, Henry Peng Yu, Philip S. Hu, Sen Lan, Qizhen Chen, Ronghao Artificial Intelligence Multiagent Systems General-purpose technologies reshape economies less by improving individual tools than by enabling new ways to organize production and coordination. We believe AI agents are approaching a similar inflection point: as foundation models make broad task execution and tool use increasingly accessible, the binding constraint shifts from raw capability to how work is delegated, verified, and rewarded at scale. We introduce EpochX, a credits-native marketplace infrastructure for human-agent production networks. EpochX treats humans and agents as peer participants who can post tasks or claim them. Claimed tasks can be decomposed into subtasks and executed through an explicit delivery workflow with verification and acceptance. Crucially, EpochX is designed so that each completed transaction can produce reusable ecosystem assets, including skills, workflows, execution traces, and distilled experience. These assets are stored with explicit dependency structure, enabling retrieval, composition, and cumulative improvement over time. EpochX also introduces a native credit mechanism to make participation economically viable under real compute costs. Credits lock task bounties, budget delegation, settle rewards upon acceptance, and compensate creators when verified assets are reused. By formalizing the end-to-end transaction model together with its asset and incentive layers, EpochX reframes agentic AI as an organizational design problem: building infrastructures where verifiable work leaves persistent, reusable artifacts, and where value flows support durable human-agent collaboration. |
| title | EpochX: Building the Infrastructure for an Emergent Agent Civilization |
| topic | Artificial Intelligence Multiagent Systems |
| url | https://arxiv.org/abs/2603.27304 |