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 |
Silent degradation is the most common and most dangerous erosion pattern. Because the human has delegated precisely to avoid monitoring every action, gradual performance decline goes unnoticed until the cumulative effect is significant. Proactive performance reporting - where the agent monitors and reports its own performance deviations - is the primary design intervention.
Yes, but only through designed intervention. Spontaneous trust recovery is rare. The earlier erosion is detected, the easier it is to reverse. This is why erosion monitoring - instrumentation that detects early signals of each erosion pattern - is a structural requirement of trust architecture, not an optional feature.
Trust failure is a discrete event - a single catastrophic action that collapses trust. Trust erosion is a continuous process - a gradual accumulation of micro-failures that individually seem insignificant. Failure is dramatic and visible; erosion is silent and invisible. Both require designed responses, but the design strategies are fundamentally different.
The dominant narrative around trust failure in AI systems focuses on catastrophic events: the agent that makes a disastrous financial decision, the autonomous vehicle that causes an accident, the chatbot that produces harmful content. These events are dramatic, newsworthy, and relatively rare. The far more common - and far more dangerous - mode of trust failure is Erosion is dangerous precisely because it is invisible. There is no moment of crisis, no error message, no dramatic failure. The human simply stops delegating - and often cannot articulate why. The AXD designer's task is to make erosion visible, measurable, and preventable through designed intervention patterns. Proactive performance reporting. The agent must be designed to monitor its own performance against baseline metrics and report deviations before they accumulate. This requires the agent to maintain a model of its own expected performance - a form of computational self-awareness that is a core requirement of This pattern is particularly insidious because neither party is "wrong." The human's expectations are legitimate. The agent's behaviour is competent. But the gap between them widens over time, creating a growing sense of unease that the human may not be able to articulate. In agentic commerce, expectation drift manifests when a shopping agent optimises for price while the human has gradually shifted to prioritising quality, or when a financial agent maintains a risk profile that no longer matches the human's evolving life circumstances. Periodic alignment rituals. The system must be designed to periodically surface the agent's current operating parameters and invite the human to confirm, adjust, or recalibrate. These are not interruptions - they are trust maintenance ceremonies that prevent the slow divergence of expectation and behaviour. The human does not lose trust in a single moment of confusion. Instead, each slightly-opaque decision adds a thin layer of uncertainty. Over time, these layer