Ai agent ux

AI Agent UX

Design experiences for AI that doesn't just suggest - it acts. Booking flights, sending emails, executing code, making purchases. The AUTONOMY framework ensures users stay in control while AI operates at machine speed.

Core Principle

Agentic AI inverts the traditional UX model. In classical UX, users take actions and the system responds. In agentic UX, the system takes actions and users supervise. This requires an entirely new design vocabulary: previews instead of forms, audit trails instead of history, interrupts instead of navigation.

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The AUTONOMY Framework

Letter	Principle	Design Question
A	Action Preview	Can the user see exactly what the agent will do before it does it?
U	User Override	Can the user stop, modify, or redirect the agent at any point during execution?
T	Tiered Authority	Does the agent's freedom scale appropriately with risk level?
O	Observable State	Can the user see what the agent is doing right now, in real time?
N	Narrated Reasoning	Does the agent explain why it chose this action over alternatives?
O	Outcome Verification	Can the user verify that the action completed correctly?
M	Memory of Actions	Is there a complete, searchable log of everything the agent did?
Y	Yield to Humans	Does the agent know when to stop and ask for help?

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The Autonomy Dial

Not all actions require the same level of human oversight. Design a graduated control system:

Level	Name	Agent Behavior	User Involvement	Example
1	Suggest	Recommends action, takes none	User must initiate	"I recommend replying with: [draft]. Send?"
2	Draft & Wait	Prepares the action, pauses for approval	User reviews and approves	Agent drafts email, shows preview, waits for "Send"
3	Act & Notify	Executes immediately, sends notification	User reviews after the fact	Agent files expense report, sends summary
4	Act Silently	Executes without notification	User can check audit log	Agent auto-categorizes emails
5	Full Autonomy	Executes complex multi-step tasks independently	User sets goals, agent reports outcomes	Agent manages a full sales outreach sequence

Setting the Default Level

Risk Factor	Default Autonomy Level
Action is reversible + low cost	Level 3-4 (Act & Notify or Silent)
Action is irreversible OR high cost	Level 1-2 (Suggest or Draft & Wait)
Action involves external parties (sends emails, makes payments)	Level 2 maximum until trust is established
Action involves sensitive data	Level 1-2 with audit logging
User has explicitly granted higher autonomy	Respect the setting, but cap at the risk level

Design rule: The Autonomy Dial should be a user-facing control, not a hidden system setting. Let users tune their own comfort level.

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Pre-Action Design

Before the agent acts, users need to understand what's about to happen.

The Action Preview Card

Every consequential agent action should display a preview card with:

Element	Content	Required?
Action summary	One sentence: what the agent will do	Always
Targets affected	Who or what is impacted (people, systems, data)	Always for external actions
Estimated impact	What changes as a result	For non-trivial actions
Alternatives considered	What else the agent could have done	When multiple valid options exist
Reversibility indicator	Can this be undone? How?	Always
Confidence level	How sure is the agent this is the right action?	When confidence varies

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During-Action Design

While the agent is executing, users need visibility and control.

The Agent Activity Feed

A real-time, scrollable feed showing:

Component	Purpose	Update Frequency
Current step indicator	"Step 3 of 7: Sending confirmation email"	Per step
Progress visualization	Linear or branching progress bar	Continuous
Decision log	"Chose option A because [reason]"	Per decision point
Pause/stop controls	Always visible, always responsive	Permanent
Skip/redirect	"Skip this step" or "Do X instead"	Per step

Critical rule: The stop button must work instantly. If the agent can't be stopped mid-action, the UI must make this clear BEFORE the action begins.

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Post-Action Design

The Action Receipt

After every consequential action, provide an action receipt:

Element	Content
What was done	Plain-language summary of completed actions
What changed	Before/after diff of affected data
Undo option	One-click reversal if action is reversible
Time-limited undo	For partially reversible actions: "You have 30 seconds to undo the email send"
Audit link	"View full activity log"

The Undo Architecture

Action Type	Undo Pattern	Time Window
Data modification	Full revert to previous state	Unlimited
Message sent	Recall + replacement option	30 seconds to 5 minutes
File deletion	Soft delete → permanent after 30 days	30 days
Purchase/payment	Cancellation request + refund flow	Varies by provider
Multi-step sequence	Step-by-step rollback with checkpoint selection	Per step
Irreversible action	Prevention-only (no undo, must block before execution)	N/A

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Trust Ramp: Progressive Autonomy

New agents should not start at Level 5. Build trust incrementally.

The Trust Ramp Pattern

Phase	Duration	Autonomy Level	Unlock Condition
Onboarding	First 5 interactions	Level 1 (Suggest only)	User completes first review cycle
Building	Next 20 interactions	Level 2 (Draft & Wait)	>80% approval rate on previews
Established	Ongoing	Level 3 (Act & Notify)	User explicitly opts in
Trusted	After sustained use	Level 4 (Act Silently)	User configures specific action types
Delegated	Expert users only	Level 5 (Full Autonomy)	User sets goals + boundary conditions

The cardinal rule: Users can always dial DOWN autonomy instantly. Dialing UP requires confirmation.

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Multi-Agent Coordination UX

When multiple agents work together:

Challenge	Design Solution
Which agent did what?	Color-coded agent identity in the activity feed
Agents disagree on approach	Surface the disagreement to the user with each agent's reasoning
Agent A's output feeds Agent B	Show the handoff explicitly: "Research Agent found 5 candidates → Outreach Agent will draft emails for your review"
Cascading failures	If Agent A fails, halt Agent B and notify user before damage propagates

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Anti-Patterns

Pattern	Why It Fails
"The AI will handle everything" messaging	Sets unrealistic expectations; users feel betrayed at first failure
Burying the stop button	Users feel trapped. Panic → permanent distrust
Asking permission for every micro-action	Decision fatigue. Users disable the agent entirely
No audit trail	"What did it do while I was asleep?" Users can't trust what they can't verify
Irreversible actions without explicit consent	One wrong autonomous action and the user never delegates again
Showing agent "thinking" animation without substance	A spinner is not transparency. Show what the agent is actually evaluating

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Quick Reference

Task	Framework Element	Key Deliverable
Design a new AI agent product	Full AUTONOMY framework	Autonomy Dial settings + Pre/During/Post action flows
Add agent capabilities to existing product	Trust Ramp Pattern	Phased rollout plan with unlock conditions
Audit agent UX for safety	Undo Architecture + Action Receipt	Gap analysis: which actions lack undo, preview, or audit?
Design multi-agent coordination	Multi-Agent Coordination table	Agent identity system + handoff visualization
Set autonomy defaults	Setting the Default Level table	Risk-matched autonomy levels per action type

Integration

Works with: ai-trust-transparency (explaining agent decisions), ai-error-resilience (agent failure recovery), ai-safety-guardrails (agent action boundaries), ai-feedback-loops (rating agent performance).