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 Explainability and Observability framework is an AXD methodology for making autonomous AI agent behaviour transparent and understandable. It distinguishes between observability (what the agent did) and explainability (why it did it), providing design patterns for both dimensions across different audiences and contexts.
Observability provides the factual record: what actions were taken, what data was accessed, what decisions were made. Explainability provides the reasoning: why those actions were chosen, what alternatives were considered, and what trade-offs were made. Both are essential for trust calibration but serve different purposes.
Different stakeholders need different levels of explainability: end users need outcome explanations (what happened and why), operators need decision explanations (how the agent chose between options), auditors need process explanations (the complete reasoning chain), and regulators need compliance explanations (how the agent satisfied legal requirements).
Framework 09 of 12 · Continuous Phase · Decision legibility Explainability & Observability Design Standard Making agent reasoning legible to humans in normal operation Commerce Application: Decision rationale for regulators Domains: Regulated Industries · Financial Services · Healthcare · Legal Making agent reasoning, decisions, and actions legible to humans in normal operation - not just at failure. The 'why did you do that?' layer. In regulated industries, this is not optional. Users must understand not just what the system did, but why it did it. Explainability & Observability: Core Principles In regulated industries, explainability is not optional. In all industries, it is the foundation of trust. An agent that cannot explain its reasoning is an agent that cannot be trusted with consequential decisions. Explainability & Observability: Implementation Patterns Explainability & Observability: Commerce Applications Observability is not surveillance. It is the design of ambient transparency - the ability to understand what the agent is doing and why, without having to watch it constantly. Explainability & Observability: Guidance for Teams Explainability & Observability: Lifecycle Connections Explainability & Observability: What Comes Next Explainability makes agent reasoning visible. The next framework - Explainability & Observability: The Framework Ecosystem Navigate the complete lifecycle of Agentic Experience Design. Each framework addresses a distinct phase of the human-agent relationship. Multi-Agent Orchestration Visibility Model Agent Memory & Context Continuity Framework Explainability & Observability Design Standard Onboarding & Capability Discovery Framework Ethical Constraint & Value Alignment Architecture