AXD for Developers

Implement trust state as a first-class data model - track trust level, history, and calibration state for every human-agent relationship in your system.

Build trust boundaries as middleware that enforces what agents can and cannot do at each trust level, not as scattered conditional checks.

Design your trust architecture with explicit layers: identity verification, authority validation, action auditing, and outcome verification.

Implement trust recovery protocols that automatically reduce agent autonomy after failures and provide structured paths to restore it.

Use event sourcing for trust-relevant actions so that every delegation, execution, and outcome is auditable and replayable.

Implement MCP (Model Context Protocol) endpoints to expose your system's capabilities to external agents in a standardised, discoverable format.

Build A2A (Agent-to-Agent) communication channels with structured message schemas that carry delegation context, authority scope, and trust state.

Integrate x402 payment flows for machine-native transactions - implement the HTTP 402 response pattern with Stripe's payment token infrastructure.

Expose UCP (Universal Commerce Protocol) merchant manifests that declare your products, capabilities, APIs, and policies in structured JSON.

Design protocol adapters that translate between different agent communication standards while preserving delegation chain integrity.

Model delegation as a first-class entity with explicit scope (what), duration (when), conditions (if), and revocation rules (how to stop).

Implement authority chains that track the full delegation path from human principal through any intermediary agents to the executing agent.

Build scope enforcement as a runtime constraint system - agents should be structurally unable to exceed their delegated authority, not just warned against it.

Design revocation as an immediate, propagating operation - when a human revokes authority, every agent in the delegation chain must stop within defined time bounds.

Implement delegation audit logs that capture not just what was delegated but why, enabling post-hoc review of authority decisions.

Implement structured logging that captures agent reasoning, not just actions - record what the agent considered, what it chose, and why.

Build observability dashboards that surface agent behaviour at multiple levels of abstraction - from high-level outcome summaries to detailed action traces.

Design circuit breakers that automatically halt agent operations when error rates exceed thresholds, with clear escalation paths to human operators.

Implement graceful degradation patterns - when an agent fails, the system should fall back to a less autonomous but still functional state, never to a dead end.

Build post-mortem tooling that reconstructs the full context of agent failures - what the agent knew, what it did, and what it should have done differently.