Experience · Software component

Error Presenter

Software componentExperienceExperience & Human Oversightarc:ErrorPresenter

A presentation component that translates agent failures into plain-language layered messages stating cause, permanence, expected resolution, and separate user and system recovery actions.

Responsibility. Communicates failures with actionable recovery guidance.

Also known as: Error communication UI, Recovery guidance, Degradation warning display

Direct neighbourhood (hover for relationship types)

Relationships

emits telemetry to dynamic

Trace Collector Ch1.1A

receives data from dynamic

sends data to dynamic

Agent User Interface abstract Ch1.1A Ch1.1B

Design guidance

MUST NOT expose raw exceptions or stack traces to end users by default.
SHOULD indicate whether an error is temporary (auto-retry) or needs user action, with estimated resolution time when known.
SHOULD offer fallback options such as cached results when primary methods fail.
SHOULD log full technical error details separately for debugging.

Classification

Patterns: Layered error disclosureClarification prompt for ambiguous inputCapability-limit disclosurePolicy-block explanation with approval pathGraceful degradation with fallback options
Quality attributes: Interaction capability (ISO/IEC 25010)Reliability (ISO/IEC 25010 | NIST AI RMF: valid and reliable)
Risks mitigated: Trust loss from generic error messagesExposure of raw stack traces to users

Sources

Ch1.1A: T. Nguyen, "Designing User Interfaces for Intuitive Human-Agent Interaction," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.1A. ISBN: 9798244538229.
Ch1.1B: T. Nguyen, "Human-in-the-Loop Patterns and Accessible Design," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.1B. ISBN: 9798244538229.
Ch2.8: T. Nguyen, "Error Handling and Resilience," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 2.8. ISBN: 9798244538229.
Ch2.9: T. Nguyen, "Streaming and Real-Time Responses," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 2.9. ISBN: 9798244538229.