SHORT DEFINITION
The governance design layer that captures, encodes, and enforces what an organization means for its AI agents to do — before deployment.
Intent Architecture is the governance design layer that captures, encodes, and enforces what an organization means for its AI agents to do before those agents are deployed. It is the structured answer to the Intent Gap: the policies, boundaries, approval logic, and accountability assignments that exist in writing before an agent touches a production workflow. Intent Architecture treats agent intent as an engineering artifact — something that must be designed, reviewed, versioned, and audited — not an assumption that can be reconstructed after a governance failure.
CANONICAL EXAMPLE
Before a financial services firm deploys a Copilot Studio agent to handle client onboarding, its Intent Architecture document specifies: the data sources the agent may query, the decisions it may make autonomously, the decisions that require human approval, the team accountable for its behavior, and the condition under which it must be taken offline. That document is the Intent Architecture for that agent.
USAGE GUIDANCE FOR CONTENT
Use Intent Architecture as the solution frame that follows the problem frame of Intent Gap. It appears naturally in posts and newsletter editions that move from 'here is what is broken' to 'here is what a governed organization does differently.' It is not a product name or a vendor framework — it is an organizational practice. Do not use it interchangeably with Zero Trust for AI or any Microsoft product.