Agentic UX Design Patterns: Plans, Approvals and Undo

Chat interfaces ask one question: did the answer help? Agents raise harder ones: what is it about to do, can I stop it, and what did it change? The patterns below answer those questions. They complement our posts on generative UI and hybrid UI with a predictable shell.

What is agentic UX?

Agentic UX covers interfaces where software plans and executes multi-step tasks on the user’s behalf: booking, sending, editing records, writing code. The design challenge shifts from presenting output to giving people control, consent and accountability over actions.

1. Intent preview: show the plan before acting

Before a significant action, show a plain-language summary of what the agent will do, step by step, and let the user approve, edit or reject it. Write “Cancel flight AA123 to San Francisco”, not an API call (Smashing Magazine). For actions with an outside effect, preview the exact content: the message text, recipients, amount or files.

2. Risk-based approvals

If every step asks for confirmation, people approve by reflex. Sort actions by risk and only interrupt for irreversible, costly or outward-facing ones. Each approval should say what will happen, to whom, and whether it can be undone (UX Pickle agentic AI checklist).

Some frameworks formalize this as three verdicts per action: allow, deny or require approval, with the policy checked on the server, not only in the browser (CopilotKit).

3. Pause and redirect, not just stop

Users hesitate to press Stop when they expect to lose work. A better control pauses at a safe step, keeps completed steps, asks what should change, and shows the revised plan before resuming. Label it Pause if that is what it does (Setproduct).

4. Clarify instead of guessing

When an instruction is ambiguous (which John? which account?), the agent should ask. Microsoft’s Guidelines for Human-AI Interaction include scoping services when in doubt and making clear why the system did what it did (Microsoft Research).

5. Activity log and undo

• Keep a persistent, readable log of every action with its time, target and result.

• Link each entry to the instruction or trigger that caused it.

• Offer undo per action, not only a global restore point.

• Be honest about limits: if undo expires or an action is permanent, say so before the user approves.

6. Permissions in plain language

Ask for the narrowest access that does the job, explain why the agent needs it, and prefer one-time or task-scoped access over broad, lasting grants. When an agent sends messages or edits shared records, make it clear to other people that an agent did it for the user.

Agentic UX checklist

• Does the user see the plan before anything irreversible happens?

• Are approvals limited to risky actions?

• Can the user pause, edit and resume?

• Is there a log, and can each action be undone or is it marked permanent?

• Are permissions scoped and explained?

• Does the agent ask when the instruction is ambiguous?

Agentic UX FAQ

What is the difference between generative UI and agentic UX?

Generative UI is about the interface itself being generated or adapted by AI. Agentic UX is about an AI taking actions for the user. A product can use either or both.

Do agents need a confirmation for every action?

No. Confirming everything trains people to click through. Confirm actions that are irreversible, cost money or affect other people, and make the rest reversible.

What is human-in-the-loop design?

It means designing checkpoints where a person reviews, approves or corrects the AI before or after it acts, so responsibility stays with the user for decisions that matter.

Designing an AI agent or copilot? Our AI product UX team designs the plans, approvals and controls that make users trust it. See also dashboard design in the AI era.