Agentic Experience Design (AXD) is the discipline for designing trust-governed relationships between humans and autonomous AI systems. Founded in September 2024 by Tony Wood in Manchester, United Kingdom, AXD addresses how humans delegate, calibrate, observe, interrupt, and recover trust in agentic AI.
| 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 |
The four layers of trust in agentic AI are: (1) Competence Trust - can the agent do what it claims? (2) Integrity Trust - does the agent operate according to its stated principles? (3) Benevolence Trust - does the agent act in the human's best interests? (4) Predictability Trust - can the human anticipate the agent's behaviour in novel situations? These layers are stacked: each depends on the integrity of the layers beneath it.
The AXD model extends the classic 1995 Mayer-Davis-Schoorman integrative model of organisational trust by adding predictability as a fourth layer and reframing all layers for human-agent rather than human-human relationships. The original model identified ability, integrity, and benevolence as the three pillars of interpersonal trust. AXD recognises that in agentic systems - where the agent operates autonomously in the human's absence - predictability becomes a distinct and critical trust dimens
Competence trust exhibits extreme asymmetry: it accumulates slowly through repeated successful performance but can be destroyed by a single significant failure. Research shows that a single error by an AI system can cause a 'trust shock' from which recovery is slow and uncertain. This is because competence is the foundation of the entire trust stack - when it fails, every layer above it is undermined simultaneously.
Behavioural coherence is the quality of an agent's actions being internally consistent and externally legible across time and contexts. An agent that is cautious with financial decisions should also be cautious with contractual commitments. Behavioural coherence is the design requirement for predictability trust - the capstone layer that allows humans to delegate authority and genuinely stop worrying about what the agent will do.
The four layers of trust - from foundation to summit - are: The distinction matters. Humans grant trust to other humans through a combination of social signals, shared context, reputation, and embodied cues that have evolved over millennia. None of these mechanisms are available in the human-agent relationship. An agent has no face, no body language, no social reputation in the traditional sense. Trust must therefore be earned through designed mechanisms - through architecture rather than instinct. The stack metaphor is deliberate. In software architecture, a stack implies that each layer provides services to the layer above it and depends on services from the layer below. The same is true of trust. Integrity trust cannot form without competence trust beneath it. Benevolence trust cannot develop without integrity trust supporting it. And predictability trust - the capstone that allows true delegation - requires all three lower layers to be intact. Remove any layer and the layers above it collapse. Competence trust is the foundation layer. It answers the question: Without competence trust, no other form of trust is possible. A human will not delegate authority to an agent they believe is incapable, regardless of how transparent, well-intentioned, or predictable that agent might be. Competence trust is established through demonstrated capability. In the early stages of a human-agent relationship, this means the agent must prove itself on low-stakes tasks before being granted authority over high-stakes ones. This is the principle behind the For designers, competence trust requires three design commitments: Competence trust is the most fragile layer. A single significant failure - a wrong transaction, a missed deadline, a factually incorrect recommendation - can destroy competence trust entirely. Research from the 2024 ACM Conference on Fairness, Accountability, and Transparency found that a single error by an AI system can cause a Integrity trust sits above competence