How to Manage Agents and Skills in Your Software Factory

Managing AI agents and reusable skills is presented as a critical governance gap in software factories, where unregistered tools can introduce security, operational, and accountability risks through unmanaged credentials, unclear ownership, and untraceable actions. Agents are described as privileged non-human identities with runtimes, permissions, costs, and operational owners, while skills are versioned, reusable capabilities that require library-like lifecycle management, certification, and domain ownership. The recommended approach includes automatically discovering agents, skills, and MCP servers from existing sources such as Git repositories and cloud platforms; maintaining centralized inventories; assigning owners; limiting each agent’s data and tool access; and separating read, propose, and act permissions, particularly in production. Organizations are also encouraged to publish skills through standardized workflows, evaluate and certify them before use, require agents to pass task-based evaluations before promotion, and log each execution with its inputs, tools, changes, approvals, and affected services. Underlying these practices are traceability, certification, enforcement, and continuous optimization, intended to let platform teams scale agentic engineering while retaining auditability, cost visibility, and control.

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