Project 25: Trust-Centered UX for Human-Agent Collaboration

Design and instrument a human-facing interface that makes agent behavior inspectable, interruptible, and recoverable.


Quick Reference

Attribute Value
Difficulty Level 3: Advanced
Time Estimate 10-18 hours
Language TypeScript (Next.js)
Prerequisites UX fundamentals, Projects 6 and 10
Key Topics confidence UX, provenance, uncertainty messaging, override/rollback

Learning Objectives

  1. Present confidence and risk without misleading precision.
  2. Provide provenance and explanation affordances users can act on.
  3. Implement undo, override, and escalation pathways.
  4. Measure trust and correction behavior with UX telemetry.

The Core Question You’re Answering

“How do you design an agent interface users can trust without surrendering control?”


Concepts You Must Understand First

Concept Why It Matters Where to Learn
Trust calibration Prevents overtrust and undertrust HCI references
Provenance UX Supports verification explainability guidance
Escalation patterns Handles high-risk outcomes product design patterns
Context repair loops Maintains conversation quality conversational UX methods

Theoretical Foundation

Agent Decision -> Confidence/Risk UI -> User Response -> Override/Escalation -> Outcome + Telemetry

Trust emerges from clear controls and recoverability.


Project Specification

What You’ll Build

A web interface with:

  • Confidence and risk badges
  • Explain/provenance drawer
  • Clarification and disambiguation prompts
  • Override and rollback actions

Functional Requirements

  1. Display confidence + uncertainty labels
  2. Show source provenance links
  3. Provide one-click human override
  4. Support multi-turn correction flow

Non-Functional Requirements

  • Consistent risk language
  • Accessible controls
  • Low-friction recovery actions

Real World Outcome

$ npm run p25:demo
[ui] confidence=0.62 risk=MEDIUM provenance_links=3
[user] clarify_prompt_used=true
[override] action=blocked_and_edited_by_user
[rollback] rollback_id=rb_7a2 status=complete

Architecture Overview

UI Layer -> Decision Explainer -> Provenance Service -> Override API -> Telemetry Sink

Implementation Guide

Phase 1: Risk/Confidence Display

  • Build normalized labels and visual language.

Phase 2: Explain + Override Flow

  • Add provenance panel and explicit override actions.

Phase 3: Telemetry and Iteration

  • Instrument confusion and correction metrics.

Testing Strategy

  • Usability tests for high-risk actions
  • Recovery-time tests for overrides
  • Ambiguous-intent correction tests

Common Pitfalls & Debugging

Pitfall Symptom Fix
Vague confidence labels user confusion define confidence bands with plain-language meaning
Hidden rollback controls trapped users surface undo near side effects
No correction telemetry blind UX iteration track correction and abandonment events

Interview Questions They’ll Ask

  1. What is trust calibration in agent UX?
  2. How do you communicate uncertainty effectively?
  3. What makes a strong human-override pattern?
  4. Which telemetry indicates UX trust is improving?

Hints in Layers

  • Hint 1: Use three confidence bands, not raw probabilities.
  • Hint 2: Keep explanation one click away.
  • Hint 3: Make rollback available at action boundary.
  • Hint 4: Compare pre/post confusion event rates.

Submission / Completion Criteria

Minimum Completion

  • Confidence + provenance + override UI flow

Full Completion

  • Context repair and escalation UX implemented

Excellence

  • Measurable trust improvements from telemetry