arXiv:2607.02389v1 Announce Type: new Abstract: Coding agents are capable; human oversight is the bottleneck. Unconstrained agents introduce security risks, erode codebase scalability, and make human review increasingly costly. We argue that the same methods used for decades to manage large human engineering teams: access control, network policies, strict coding conventions enforced by tooling; transfer directly to coding agents, and are cheaper (in token) than recent agentic scaffolding. We sketch a start-to-end system on this principle, and report a controlled experiment in scalable oversigh
The rapid deployment of increasingly capable AI agents has immediate parallels to human team management challenges, necessitating robust oversight mechanisms as their capabilities grow.
This development addresses critical bottlenecks in AI agent deployment, allowing for their safe and scalable integration into complex operational environments, especially in coding.
The focus shifts from internal agentic scaffolding to external, established engineering management principles for controlling AI agents, enabling faster and more secure enterprise adoption.
- · Software Development Teams
- · Cybersecurity Firms
- · Enterprises Adopting AI Agents
- · AI Agent Developers
- · Unconstrained AI agents
- · Companies with weak AI governance strategies
Increased enterprise adoption of AI coding agents due to enhanced security and control.
Reduced software development costs and accelerated innovation ciclos in companies leveraging agent oversight.
The emergence of new regulatory frameworks and compliance standards specifically for the oversight and accountability of autonomous agents.
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Read at arXiv cs.AI