How to Tailor pm-product-discovery for Different Product Types (SaaS, Mobile Apps)

You can tailor pm-product-discovery for SaaS, mobile apps, or other product platforms by injecting specific product-type context into the agnostic discovery workflow, steering assumptions, metrics, and experiments toward platform-specific constraints.

The pm-product-discovery module in the phuryn/pm-skills repository provides a domain-agnostic framework for product discovery. Because the underlying skills request context rather than enforcing rigid domain rules, you can tailor pm-product-discovery for different product types by strategically supplying platform-specific signals at each stage of the process.

Understanding the Product-Agnostic Architecture

The discovery workflow is built from reusable skills and commands that guide you from idea generation to experiment design. The core command /discover (defined in pm-product-discovery/commands/discover.md) initiates the workflow by asking whether you are exploring an existing product (continuous discovery) or a new product (initial market validation).

Rather than hardcoding logic for specific platforms, the skills in pm-product-discovery/skills/ accept contextual prompts. This architecture allows you to use the same brainstorm-ideas-new, identify-assumptions-new, and prioritize-assumptions components across different product types by simply adjusting the input context.

Tailoring Discovery for SaaS Products

When working with SaaS web applications, you typically have access to usage analytics, subscription data, and defined onboarding funnels. You can inject these signals to steer the discovery process toward multi-tenant architecture, API integrations, and pricing validation.

Setting the Discovery Context for Existing SaaS

For existing SaaS products, begin the /discover command by specifying continuous discovery signals. The skill will route you through the existing-product branch, utilizing pm-product-discovery/skills/brainstorm-ideas-existing/SKILL.md and pm-product-discovery/skills/identify-assumptions-existing/SKILL.md.

Input contextual details that emphasize:

• Multi-tenant architecture constraints
• Integration APIs and third-party dependencies
• Pricing tier limitations and upgrade paths
• Data-export compliance requirements

Identifying SaaS-Specific Assumptions

The identify-assumptions-existing skill categorizes risks into Value, Usability, Feasibility, and Viability. For SaaS, frame assumptions around enterprise adoption patterns, such as: "Will mid-market customers adopt a usage-based API pricing model?" This falls under Viability and Value categories.

When using prioritize-assumptions (defined in pm-product-discovery/skills/prioritize-assumptions/SKILL.md), map assumptions to ARR growth, churn reduction, or average revenue per user (ARPU). These metrics align with the Impact × Risk matrix used to highlight "leap-of-faith" assumptions specific to subscription business models.

Designing SaaS Experiments

Invoke brainstorm-experiments-existing (from pm-product-discovery/skills/brainstorm-experiments-existing/SKILL.md) with prompts that reference billing validation or integration testing. For example:

"Design an experiment to test whether adding a self-service data export feature reduces churn for enterprise SaaS customers."

The skill will suggest appropriate validation methods—such as A/B testing or concierge MVPs—that respect SaaS deployment constraints.

Tailoring Discovery for Mobile Apps

Mobile applications introduce distinct constraints including platform-specific distribution (App Store, Play Store), offline functionality requirements, and battery consumption concerns. You can tailor the same discovery skills by injecting mobile-specific context signals.

Mobile Context Signals and Discovery Stage

When initiating /discover for mobile, specify new product or existing product boundaries while emphasizing:

• App-store review cycles and approval risks
• Push-notification limits and permissions
• Install-to-signup conversion metrics
• Platform-specific iOS/Android constraints

These signals direct the workflow in pm-product-discovery/skills/identify-assumptions-new/SKILL.md or pm-product-discovery/skills/identify-assumptions-existing/SKILL.md to surface mobile-centric risks.

Mobile-First Ideation Techniques

Use brainstorm-ideas-new or brainstorm-ideas-existing (from pm-product-discovery/skills/brainstorm-ideas-new/SKILL.md and pm-product-discovery/skills/brainstorm-ideas-existing/SKILL.md) with explicit mobile framing:

"Generate ideas for a mobile-first habit tracking app that must support offline mode and native iOS gestures."

The skill generates ideas from PM, Designer, and Engineer perspectives while respecting the mobile constraints, surfacing concepts around offline support, native UI gestures, and battery optimization.

Platform-Specific Risk Categories

Mobile assumptions often involve Go-to-Market risks (for new products) or Usability challenges (for existing products). Frame assumptions such as: "Will users enable push notifications during the first 7 days on iOS?" This maps to Usability and Value (retention) categories.

When calling prioritize-assumptions, use mobile-specific impact metrics like DAU/MAU, 30-day retention, or lifetime value (LTV) instead of SaaS revenue metrics.

Mobile Experiment Design

For brainstorm-experiments-new or brainstorm-experiments-existing, include mobile-specific constraints in your prompts:

"Design an experiment to test personalized push-notification timing for increasing 30-day retention on iOS."

The skill will suggest experiments such as landing-page pre-launch tests or in-app prototypes that account for App Store approval timelines and platform-specific user behaviors.

Practical Command Examples for Product-Specific Workflows

Below are concrete command sequences demonstrating how to steer the discovery flow for each product type within the pm-skills workspace.

SaaS Existing Feature Expansion

/discover

# Response: Existing product

# Context: "Advanced reporting dashboard for B2B SaaS analytics platform"

/brainstorm-ideas-existing

# Select ideas relevant to API integrations and data visualization

/identify-assumptions-existing

# Focus on assumptions around enterprise adoption and data security

/prioritize-assumptions

# Map to ARR impact and implementation risk

/brainstorm-experiments-existing

# Design A/B test for dashboard UI changes

Mobile New Product Discovery

/discover

# Response: New product

# Context: "On-the-go habit tracking mobile app for iOS and Android"

/brainstorm-ideas-new

# Emphasize offline-first architecture and native gestures

/identify-assumptions-new

# Include Go-to-Market assumptions about App Store optimization

/prioritize-assumptions

# Map to DAU/MAU impact and technical feasibility

/brainstorm-experiments-new

# Design fake-door test and in-app prototype sequence

Both flows generate a markdown Discovery Plan that aggregates ideas, assumptions, experiments, and timelines into a single document defined in pm-product-discovery/commands/discover.md.

Extending the Discovery Plan for Platform Deliverables

The final discovery plan is a plain markdown file that you can customize post-generation to reflect product-type specific deliverables.

For SaaS products, append sections for:

• Integration testing checklists
• Billing validation workflows
• Multi-tenant security audits

For mobile apps, insert:

• Store-listing optimization checklists
• Crash-report monitoring notes
• Platform-specific approval timelines

Because the plan is a standard markdown file, you can version-control it or pipe it into downstream tools in the pm-skills repository, such as the PRD-generator in the pm-product-strategy package, without modifying the underlying skill code.

Summary

• pm-product-discovery uses agnostic skills that accept contextual prompts, allowing you to tailor the workflow for SaaS, mobile, or other product types.
• Provide product-type context at the start of each step (/discover, brainstorm-ideas, identify-assumptions) to steer the outputs toward platform-specific constraints.
• Use SaaS-specific metrics (ARR, churn, ARPU) when prioritizing assumptions, and mobile-specific metrics (DAU/MAU, retention, LTV) for app products.
• Reference the skill files in pm-product-discovery/skills/—including brainstorm-ideas-new/SKILL.md, identify-assumptions-existing/SKILL.md, and prioritize-assumptions/SKILL.md—to understand how context injection modifies the discovery outputs.
• Customize the final markdown Discovery Plan with platform-specific deliverables such as integration testing (SaaS) or store-listing optimization (mobile).

Frequently Asked Questions

Can I use pm-product-discovery for hardware or IoT products?

Yes. The framework is deliberately agnostic. You can tailor pm-product-discovery for hardware or IoT products by supplying appropriate context during the /discover command and subsequent skills. Focus on hardware-specific assumptions around manufacturing feasibility, supply chain risks, and firmware update mechanisms when using identify-assumptions-new or identify-assumptions-existing.

How do I switch between existing and new product discovery modes?

The /discover command (defined in pm-product-discovery/commands/discover.md) prompts you to specify whether you are exploring an existing product or new product at the outset. This selection determines whether the workflow utilizes brainstorm-ideas-existing and identify-assumptions-existing (for continuous discovery) or their *-new counterparts (for initial validation).

What metrics should I use when prioritizing assumptions for marketplace products?

For marketplace products (a hybrid of SaaS and mobile considerations), use prioritize-assumptions with metrics that capture both sides of the market, such as liquidity (successful matches), take rate, and network effects velocity. Include these specific metrics in your context when calling the skill to ensure the Impact × Risk matrix reflects marketplace dynamics rather than single-sided user metrics.

Can I combine multiple product types in one discovery workflow?

While the skills are designed to handle single product-type contexts, you can run parallel discovery tracks by initiating separate /discover sessions for each platform (e.g., one for your SaaS dashboard and one for your companion mobile app). Alternatively, provide hybrid context during brainstorm-ideas-new to generate cross-platform ideas, then use prioritize-assumptions to resolve conflicts between web and mobile constraints.

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