agentic-product-designer-2026

name	agentic-product-designer-2026
description	Designs production-grade AI agent experiences. Use for PRDs, user journeys, interaction models, trust and approval UX, failure handling, provenance, and measurable acceptance criteria for agentic products.
argument-hint	[feature or workflow]
allowed-tools	Read Write Edit Grep Glob

Design agentic user experiences as state machines with trust, not as chat transcripts with decoration.

The user must always be able to answer:

• what the agent believes the goal is
• what it is doing now
• what evidence it is using
• what it plans to do next
• what actions need approval
• how to stop, edit, or recover

Use this skill when

• the user asks for a PRD or UX design for an AI agent
• a workflow needs planning, execution, approvals, and result review
• trust, provenance, or failure handling is central to product quality
• the product currently feels like a chatbot rather than a dependable operator

First principles

1. Legibility beats magic

Invisible autonomy creates fear and error. Show plan, progress, and receipts.

2. Control is a feature

Users must be able to:

• edit the plan
• approve or deny risky actions
• pause or cancel execution
• retry safely
• inspect what changed

3. Provenance is mandatory

Separate:

• model inference
• retrieved knowledge
• tool-observed facts
• actual side effects

4. Failure is a designed state

Do not only design the happy path. Failure, ambiguity, and handoff need explicit UX.

5. Agent UX is a product system

The UX includes:

• onboarding
• plan authoring
• execution timeline
• approvals
• receipts and diffs
• recovery and handoff

Design procedure

1. Define the operating model

State:

• what the user asks for
• what the agent can infer
• what the agent must confirm
• what the system will do automatically
• what requires explicit approval

2. Define core user journeys

At minimum produce:

• one happy path
• one ambiguity path where the agent needs clarification
• one failure path where a tool or policy blocks progress
• one approval path for side effects

For each journey, specify:

• trigger
• user-visible states
• system actions
• user decisions
• completion criteria

3. Define the state model

Minimum UI states:

• idle
• drafting
• planning
• waiting_for_user_input
• executing
• waiting_for_approval
• retrying
• completed
• failed-recoverable
• failed-terminal

For each state, specify:

• entry condition
• visible UI
• available actions
• exit transitions

4. Define trust surfaces

Every agentic UI should expose:

• plan view
• timeline of steps
• tool receipts
• approval UI
• artifact/output panel
• error and retry controls

5. Define approval UX

Approval requests must include:

• what action will happen
• why it is needed
• what inputs will be used
• what may change
• scope and expiry of approval
• deny and edit alternatives

Never present an approval CTA without consequences and scope.

6. Define provenance UX

For every important answer or action, make clear:

• which parts are from tool output
• which parts are model synthesis
• whether the information is current or cached
• where the user can inspect supporting evidence

7. Define recovery UX

For failures, specify:

• user-friendly error text
• what was attempted
• whether side effects occurred
• safe retry path
• escalation path

8. Define telemetry

Track:

• plan accepted or edited
• approval shown / approved / denied
• tool step success or failure
• retry count
• final task success
• user intervention rate

PRD template

Return a PRD with:

1. Problem
2. Primary user
3. Goals
4. Non-goals
5. Operating model
6. User journeys
7. State model
8. Trust and approval model
9. Provenance model
10. Failure and recovery
11. Telemetry
12. Acceptance criteria

Preferred patterns

• plan-first before execution
• editable plan before risky work
• step receipts instead of hidden work
• previews or dry-runs before production changes
• explicit handoff when confidence collapses

Anti-patterns

Avoid:

• single chat stream hiding planning and execution state
• approval dialogs that do not explain consequences
• answers that mix tool facts with unstated model guesses
• "spinner UX" with no progress semantics
• error states with only "try again"

Output contract

Return:

1. PRD
2. Journey map
3. ASCII state diagram
4. Trust surfaces
5. Acceptance checklist

Done criteria

This skill is done only when:

• the UI can be implemented as a state machine
• trust, provenance, and approvals are explicit
• at least one failure path is designed as thoroughly as the happy path
• the acceptance criteria are testable