Scaling Human-AI Coding Collaboration Requires a Governable Consensus Layer
Vibe coding turns natural-language intent into working software, but code generation alone does not give humans and agents a shared account of what they are building. As collaboration spans participants, components, and releases, design choices must remain understandable and open to revision. We argue that scaling human and AI coding collaboration requires a governable consensus layer. Agentic Consensus organizes collaboration around a versioned project-state model linking selected intent, structural commitments, executable artifacts, and evidence. Participants can clarify intent before implementation and coordinate proposed changes against commitments that humans can inspect and revise. ...
| Authors | Tianfu Wang, Zhezheng Hao, Yin Wu et al. |
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| Primary category | cs.SE |
| Published | 20 April 2026 |
| Last updated at source | 13 October 2026 |
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