Designing intent for autonomous AI agents. Mandate patterns that govern how humans express delegation scope, constraints, and objectives..
| Dimension | Traditional UX | Agentic Experience Design (AXD) |
|---|---|---|
| Primary material | Attention and affordance | Trust and delegation |
| User state | Present, navigating | Absent, delegating |
| Design output | Screens and interfaces | Outcomes and constraints |
| Temporal model | Session-based | Relationship-based |
| Success metric | Task completion | Trust calibration |
Mandate patterns are recurring structures for how humans delegate authority to AI agents. They define the shape of delegation: standing mandates (ongoing authority), episodic mandates (one-time tasks), conditional mandates (triggered by events), and collaborative mandates (shared human-agent decision-making). Each pattern requires different design approaches.
Agentic commerce primarily uses standing mandates (ongoing purchasing authority for regular needs), conditional mandates (buy when price drops below threshold), and episodic mandates (find and book the best flight for this trip). Each pattern requires different trust calibration, scope definition, and observability design.
Mandate patterns are recurring structures for how humans delegate authority to AI agents. They define the shape of delegation: standing mandates (ongoing authority), episodic mandates (one-time tasks), conditional mandates (triggered by events), and collaborative mandates (shared human-agent decision-making). Each pattern requires different design approaches.
Agentic commerce primarily uses standing mandates (ongoing purchasing authority for regular needs), conditional mandates (buy when price drops below threshold), and episodic mandates (find and book the best flight for this trip). Each pattern requires different trust calibration, scope definition, and observability design.
Introduction: The Most Important Interface You Have Never Designed Every interface you have ever designed assumes the same thing: a human will be present to make decisions. The button expects a click. The form expects input. The confirmation dialogue expects a conscious choice. This assumption is so deeply embedded in design practice that most designers do not even recognise it as an assumption. It is simply how things work. This is the mandate problem. Not "how do we build smarter agents?" but "how do we design the interfaces through which humans express what they want, how much they are willing to spend, what constraints matter, and when the agent should stop and ask?" The mandate is the contract between human intention and machine autonomy. It is the most consequential new design surface in This essay catalogues those patterns. It is a practitioner's guide to designing the interfaces through which humans delegate authority to machines - not as an abstract exercise, but as the concrete, buildable design work that will define whether A mandate is a structured expression of human intent that authorises an autonomous agent to act within defined boundaries. It is distinct from a command, which specifies a single action ("buy this item"), and distinct from a goal, which specifies a desired outcome without constraints ("find me the best deal"). A mandate occupies the space between the two: it specifies an outcome, the constraints within which the agent may pursue that outcome, and the conditions under which the agent must pause, escalate, or stop. The concept draws from legal theory, where a mandate is an authorisation granted by a principal (the human) to an agent (the AI) to act on their behalf within specified limits. In contract law, the validity of an agent's actions depends entirely on whether they fall within the scope of the mandate. The same principle applies in This legal framing is not metaphorical. The For designers, this means that the mandate interface is