How to Create a Value Proposition Using the 6-Part JTBD Template

The 6-part JTBD template generates customer-centric value propositions by structuring product narratives around Who, Why, What Before, How, What After, and Alternatives, implemented in the pm-product-strategy plugin as a declarative AI skill.

The phuryn/pm-skills repository provides a structured approach to product strategy through AI-assisted workflows. Creating a value proposition using the 6-part JTBD template allows product teams to move beyond feature lists and articulate genuine customer value through a causal narrative framework. This methodology is embedded in the pm-product-strategy plugin, which exposes the functionality through a simple slash command.

Architecture of the Value Proposition Skill

The value-proposition capability follows a clear, layered architecture that separates definition from execution. Understanding these layers helps teams customize or extend the workflow.

Skill Definition Layer

The core template logic resides in pm-product-strategy/skills/value-proposition/SKILL.md. This file defines the 6-part JTBD structure:

• Who: The target user segment
• Why: The job to be done or underlying motivation
• What Before: The current state or existing pain points
• How: The mechanism or solution approach
• What After: The desired outcome or transformation
• Alternatives: Competing solutions or workarounds

This declarative definition includes metadata, input requirements, and a step-by-step workflow that AI assistants follow when generating propositions.

Command Wrapper Layer

The pm-product-strategy/commands/value-proposition.md file exposes the skill via the /value-proposition slash command. When invoked, this wrapper gathers contextual inputs—such as product descriptions and uploaded documents—and formats the final structured output.

Plugin Registration

The skill is declared in the main repository README.md under the Value-Proposition section, enabling automatic discovery by AI assistants including Claude Code, Claude Cowork, and OpenCode.

Executing the Value Proposition Workflow

The execution flow is fully declarative and requires no additional code execution beyond standard AI tooling.

Interactive Command Usage

Invoke the workflow in any compatible AI chat interface:

/value-proposition

The assistant prompts for required context:

What does the product do?
Who is the target user segment?
What alternatives do they currently use?

Programmatic Invocation

For automated documentation pipelines, use the Claude CLI:

# Assuming the Claude CLI is installed and the plugin is added

claude ask "/value-proposition" "AI writing assistant for non-native speakers"

The CLI returns a structured markdown block ready for inclusion in README.md files or internal wikis.

Anatomy of the 6-Part Template

Each component serves a specific narrative function that forces customer-centric thinking.

Who and Why: Customer-First Orientation

Unlike traditional frameworks that start with features, the JTBD template begins with the user and their motivation. This anchoring prevents solution-first bias and ensures the proposition addresses real needs.

What Before → How → What After: Narrative Continuity

This sequence creates a causal story that is easy to communicate to stakeholders:

1. What Before: Manual editing, costly freelance writers, or generic translation tools that produce awkward phrasing
2. How: An AI-powered editor that suggests tone-appropriate phrasing and corrects grammar
3. What After: Users publish polished copy in minutes and improve conversion rates

Alternatives: Explicit Competitive Context

The template forces explicit naming of competitors or workarounds—a step often omitted in other frameworks. This appears in lines 78-85 of the SKILL file, which includes comparative notes against traditional canvases.

Sample Output Structure

When executed, the skill produces structured markdown like this:

## Value Proposition: AI Writing Assistant

### For non-native English speakers who need professional-grade copy:

1. **Who**: Language learners & small-business owners with limited editing budgets.
2. **Why**: They need clear, persuasive content quickly, but lack native fluency.
3. **What Before**: Manual editing, costly freelance writers, or generic translation tools.
4. **How**: An AI-powered editor that suggests tone-appropriate phrasing and corrects grammar.
5. **What After**: Users publish polished copy in minutes and reduce reliance on external writers.
6. **Alternatives**: Traditional copy-editing services (expensive), generic grammar checkers (limited context).

**Value Proposition Statement**
*For non-native English speakers who need professional copy, the AI Writing Assistant is an intelligent editor that delivers native-level language in seconds. Unlike expensive copy-editing services, it provides instant, affordable output.*

This output can be copied directly into product briefs, marketing collateral, or pitch decks.

JTBD vs. Traditional Value Proposition Canvases

According to the source code analysis in SKILL.md, the 6-part JTBD template offers distinct advantages over frameworks like Strategyzer's Value Proposition Canvas:

• Explicit alternatives: Forces acknowledgment of competition rather than ignoring market context
• Temporal narrative: The Before/How/After sequence creates a transformation story rather than a static mapping
• Job-centered: Focuses on the progress the customer wants to make, not just pain/gain points

Summary

• The 6-part JTBD template structures value propositions around Who, Why, What Before, How, What After, and Alternatives
• Implementation resides in pm-product-strategy/skills/value-proposition/SKILL.md with command wrappers in pm-product-strategy/commands/value-proposition.md
• Execute via /value-proposition in AI assistants or programmatically through CLI tools
• Output generates structured markdown suitable for immediate use in product documentation
• The framework emphasizes customer jobs and explicit competitive alternatives over feature-centric descriptions

Frequently Asked Questions

What are the six components of the JTBD value proposition template?

The six components are: Who (target segment), Why (job to be done), What Before (current state), How (solution mechanism), What After (desired outcome), and Alternatives (competing solutions). This structure ensures the proposition is anchored in real user needs rather than product features.

How do I access the value proposition skill in my AI assistant?

Add the pm-product-strategy plugin from the phuryn/pm-skills repository to your AI assistant's configuration. Once loaded, type /value-proposition in the chat interface. The assistant will request product context and generate the structured template automatically.

How does the 6-part JTBD template differ from Strategyzer's Value Proposition Canvas?

Unlike Strategyzer's canvas, the JTBD template explicitly requires documenting Alternatives (lines 78-85 in SKILL.md) and follows a temporal narrative (Before → How → After) rather than a static mapping of pains and gains. This forces teams to articulate competitive positioning and transformation stories.

Can I automate value proposition generation in my documentation pipeline?

Yes. Use the Claude CLI or compatible API clients to invoke /value-proposition programmatically. The skill returns structured markdown that can be piped into documentation generators, wikis, or version-controlled product briefs without manual intervention.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}