How to Give Coder Agents Your Company's Institutional Knowledge

Coder’s AI Operating Layer approach proposes managing institutional knowledge for coding agents through four governed layers: a deployment-wide system prompt for universal standards and routing guidance, repository-based skills for domain playbooks, organization-scoped MCP servers for internal knowledge systems, and workspace-specific MCP configurations for repository tools. Coder Agents operates through the Coder control plane and workspace agents, allowing administrators to centralize policies while keeping repository and user preferences appropriately scoped. The guide explains how skills are discovered, loaded lazily, versioned, refreshed, and constrained by naming, size, path-safety, and snapshot limits, alongside how MCP servers can be configured with availability policies, authentication, tool restrictions, and identity forwarding. It also describes repository context files, template selection signals, and the distinction between guidance and enforceable controls such as permissions and tool allow-lists. For operational governance, it recommends treating the deployment-wide system prompt and related agent settings as infrastructure configuration managed through Git, Terraform, CI/CD, review processes, and least-privilege credentials, while noting that implementation details and APIs may change across Coder versions.

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