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6. Capability Invocation

This section defines how capabilities are invoked at runtime, how context is propagated, and how the architecture behaves under normal and degraded conditions.

6.1 Invocation Patterns​

Capabilities may be invoked using several supported patterns:

  1. Synchronous Invocation
    • Used for low-latency, user-facing outcomes
    • Caller waits for a result
    • Common in DXP interactions
  2. Asynchronous Invocation
    • Used for long-running or resource-intensive execution
    • Returns a correlation identifier
    • Results are retrieved or pushed when available
  3. Chained Invocation
    • One capability invocation triggers others
    • Orchestration is explicit and observable
    • Prevents hidden coupling between executors

All invocation patterns:

  • Are explicit and declarative
  • Use the same capability contracts
  • Are mediated through the capability gateway

6.2 Context Propagation​

Context is propagated alongside inputs during invocation.

Context includes:

  • Security context (identity, tenant, permissions)
  • Execution constraints (latency, cost, execution mode)
  • Environmental metadata (region, environment, compliance zone)

Context propagation rules:

  • Context is immutable once invocation begins
  • Only declared context fields are accepted
  • Executors must not infer or fabricate context

This ensures consistent and auditable execution.

6.3 Deterministic Invocation Path​

In the deterministic path:

  1. Capability invocation is received and validated
  2. Policy confirms deterministic execution is permitted and available
  3. Deterministic executor is selected
  4. Execution occurs using predefined logic or integrations
  5. Output is returned with full provenance

Characteristics:

  • Predictable latency
  • Stable and testable outputs
  • Suitable for high-volume, high-trust use cases

This path is the default wherever supported.

6.4 AI-Assisted Invocation Path​

In the AI-assisted path:

  1. Capability invocation is received and validated
  2. Policy evaluates whether AI-assisted execution is allowed
  3. AI executor is selected with defined constraints
  4. Execution occurs using model-backed reasoning or transformation
  5. Output is returned with confidence scoring and provenance

Additional controls:

  • Input and output validation
  • Cost and token usage limits
  • Observability and trace capture

AI-assisted invocation is used only when deterministic execution is unavailable or insufficient.

6.5 Error Handling and Degradation​

The architecture is designed to fail gracefully and predictably.

Error handling principles:

  • Errors are explicit and structured
  • Failures do not cascade across layers
  • Consumers receive actionable error information

Degradation strategies include:

  • Fallback to deterministic execution when AI fails
  • Partial results with reduced confidence
  • Manual or deferred execution paths

The DXP is informed of:

  • Failure type
  • Recovery options
  • Confidence impact

This enables resilient user experiences even under degraded conditions.