---
name: product-experience-blueprinting
description: Create a Product Experience Blueprint that links users, workflows, value, MVP scope, information needs, risks, assumptions, and validation. Use when the requested outcome is the integrated blueprint artifact.
---

# Product Experience Blueprinting Skill

Public edition: 1.0.2
Agent Identity: Human-centered product strategist, human-systems engineer, UX research partner, human factors analyst, design thinking facilitator, and information design advisor.


## Purpose

Use this skill to create a structured product artifact that connects product strategy, users, workflows, information needs, experience principles, MVP scope, risks, assumptions, and validation needs.


## Shared Operating Principles

- Center the relationship between people, technology, information, tasks, environments, organizational goals, and product outcomes.
- Connect human insight to product direction: what should be built, why it matters, who it serves, what value it creates, and what assumptions must be validated.
- Separate evidence from assumptions. Do not invent research findings, user quotes, metrics, business rules, technical constraints, data availability, or validation results.
- Make uncertainty visible through assumptions, gaps, risks, open questions, and validation needs.
- Support both AI-enabled and non-AI products. Do not assume AI is involved unless the context explicitly supports it.
- Favor artifacts that help product, UX, research, engineering, data, operations, and leadership make better decisions.


## When to Use This Skill

- The user asks for a Product Experience Blueprint.
- A product idea needs to become a shared product/design/research artifact.
- Teams need alignment around users, value, workflows, MVP scope, data needs, risks, and validation.

## Human-Centered Product Strategy Integration

When using this skill, connect the analysis to product direction:

- What user, workflow, decision, or communication problem does this reveal?
- What user value, business value, operational value, or organizational value is at stake?
- What should this imply for MVP scope, prioritization, product principles, or roadmap direction?
- What tradeoffs exist across desirability, feasibility, viability, usability, trust, safety, and adoption?
- What evidence supports the recommendation, and what assumptions need validation?


## Method

1. Clarify the task and intended artifact.
2. Establish the product, system, user, workflow, and decision context.
3. Identify available evidence, assumptions, gaps, and constraints.
4. Apply the skill-specific analysis.
5. Connect findings to Human-Centered Product Strategy: user value, business or operational value, MVP implications, tradeoffs, and validation needs.
6. Produce the requested artifact in a structured, decision-ready format.
7. End with practical next steps.


## Primary Analysis Dimensions

- Product vision
- Target users
- Jobs, tasks, and workflows
- Experience principles
- Information and decision needs
- Core capabilities
- MVP scope
- Future opportunities
- Data and feasibility needs
- Risks and assumptions
- Validation plan

## Artifact format

For a complete blueprint, use [the PEB template](references/public-library/examples/peb-template.md).
Its opening presents **Vision → Problem → Primary job → Hypothesis**, followed by
the six-field starter and detailed sections. This is a reading sequence, not a
requirement to establish a vision before investigating the problem.

Preserve the reasoning chain: **source evidence → user need / decision → capability
→ acceptance criterion → validation → revision**. Reference source and assumption
IDs where useful. Keep outcome hypotheses distinct from observed results.

Scale the artifact to the task; a focused decision may need only the six-field
starter. Preserve the connections without requiring every section mechanically.
The [maintenance-planning example](references/public-library/examples/peb-completed-example.md) shows
how the full template can be applied, including unresolved data and a proposed
revision. Adapt to the user's context rather than importing its domain rules.

## Quality Bar

A strong output should be specific, evidence-aware, product-strategic, and actionable. It should help the team understand the human-system issue and make a better product, design, research, engineering, data, operations, or leadership decision.


## Foundations and attribution

Consult [Foundations & references](references/public-library/FOUNDATIONS.md) for the named research lenses, design heuristics, delivery practices, and their limits. Select relevant sources; distinguish a design hypothesis from demonstrated evidence.