# How to Create a Value Proposition Using the 6-Part JTBD Template > Learn to create effective value propositions with the 6-part JTBD template. Structure your product narrative around Who, Why, What Before, How, What After, and Alternatives for customer-centricity. - Repository: [Pawel Huryn/pm-skills](https://github.com/phuryn/pm-skills) - Tags: how-to-guide - Published: 2026-06-26 --- **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`](https://github.com/phuryn/pm-skills/blob/main/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`](https://github.com/phuryn/pm-skills/blob/main/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`](https://github.com/phuryn/pm-skills/blob/main/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: ```text /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: ```bash # 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`](https://github.com/phuryn/pm-skills/blob/main/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: ```markdown ## 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`](https://github.com/phuryn/pm-skills/blob/main/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`](https://github.com/phuryn/pm-skills/blob/main/pm-product-strategy/skills/value-proposition/SKILL.md) with command wrappers in [`pm-product-strategy/commands/value-proposition.md`](https://github.com/phuryn/pm-skills/blob/main/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`](https://github.com/phuryn/pm-skills/blob/main/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.