Functional copilots: build the place where the work happens

Functional copilots are enterprise AI agents designed for a specific business function and embedded directly in the software and workflows where users already work, enabling them to handle tasks such as contract reviews, approvals, and access requests while retaining human control over final decisions. Using a legal-contract example called Open Harvey, the post describes a five-step approach: researching workflows, defining accessible context and gated actions, specifying and building the application with CopilotKit and AG-UI hooks, securely deploying it, and adding governance measures such as approval gates, decision logs, authentication, audit trails, and evaluations. Rather than merely answering questions in chat, these copilots can read documents, apply policies, draft changes, route approvals, and preserve organizational knowledge as versioned, human-approved “skills.” The post also introduces CLiF, or Continual Learning from Full-Stack Trajectories, an open format that combines agent actions with users’ clicks, edits, and decisions to generate product insights, reusable skills, evaluation cases, and training data. CopilotKit provides an open-source repository and starter applications for building such copilots, emphasizing that the goal is to create a shared work environment in which agents support, record, and extend human judgment rather than replace it.

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