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 |
Trust architecture is the engineered foundation for human-agent relationships. It is the practice of designing the structures that allow humans to delegate authority to autonomous AI systems with confidence \u2014 including how trust is formed, how it is calibrated over time, how it is maintained during autonomous operation, and how it is repaired when things go wrong.
Agentic AI operates autonomously, often in the human's absence, making decisions with real-world consequences. Without engineered trust structures, delegation becomes a leap of faith rather than a designed relationship. Trust architecture provides the predictability, transparency, recovery mechanisms, and calibration processes that make confident delegation possible.
Trust architecture operates across four layers: (1) the Foundational Layer \u2014 predictability and reliability; (2) the Agency Layer \u2014 intent alignment and transparency; (3) the Relational Layer \u2014 communication and recovery; and (4) the Temporal Layer \u2014 evolution and adaptation over time. Each layer addresses a fundamental aspect of the human-agent relationship.
AI safety focuses on preventing harmful outcomes from AI systems. Trust architecture is broader \u2014 it addresses the entire human-agent relationship, including how trust is formed before delegation, how it is maintained during autonomous operation, how it is calibrated as the relationship evolves, and how it is repaired after failures. Safety is a component of trust architecture, not a substitute for it.
In human relationships, trust is often an emergent property, built over time through shared experiences and observed behavior. With autonomous AI agents, we do not have the luxury of this slow, organic process. Agents operate in our absence, making decisions with real-world consequences. The stakes are too high to leave trust to chance. An architectural approach is necessary because it moves our thinking from reactive to proactive. Instead of asking \"How do we make this agent seem more trustworthy?\" we ask, \"What foundational structures must be in place for a human to confidently delegate tasks to this agent?\" Without a formal architecture, trust becomes a brittle, surface-level construct. It might be gained through a slick user interface or persuasive language, but it will shatter at the first sign of unexpected behavior or error. Furthermore, an architectural approach provides a shared language and a set of blueprints for designers, developers, and stakeholders. It allows teams to reason about trust in a structured way, to identify potential failure points before they manifest, and to build systems that are trustworthy by design. Just as a building's architecture ensures its stability and habitability, a trust architecture ensures the stability and viability of human-agent collaboration. A robust Trust Architecture is built upon four distinct but interconnected layers, each addressing a fundamental aspect of the human-agent relationship. These layers work in concert to create a comprehensive foundation for delegation and autonomy. This is the bedrock of trust. It answers the question: \"Does the agent do what it says it will do?\" This layer is about the agent's core performance, its consistency, and the reliability of its underlying technology. It involves clear communication of capabilities and limitations (the This layer addresses the question: \"Does the agent understand my goals and is it working in my best interest?\" It involves ensuring the agent has a