dogfooding
Help teams build cultures of intense internal product usage to uncover real user pain points.
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What it does
Focuses on two core practices: requiring all team members to become active users of their own product, and using it intensely every day for real work rather than demo testing
Provides a four-step implementation framework: assess current usage levels, identify gaps in firsthand experience, design systems that make dogfooding natural and required, and measure impact on product decisions
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Installation Guide
How to use dogfooding on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
dogfooding
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches dogfooding from refoundai/lenny-skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate dogfooding. Access via /dogfooding in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Dogfooding
Help the user implement effective dogfooding practices using frameworks from 2 product leaders who have built cultures of intense internal product usage.
How to Help
When the user asks for help with dogfooding:
- Assess current state - Determine how much the team currently uses their own product
- Identify the gap - Find where team members lack firsthand experience with user pain points
- Design the program - Help create systems that make dogfooding natural and required
- Measure impact - Track how dogfooding improves product decisions
Core Principles
Require team members to become users
Maya Prohovnik: "I am constantly yelling at my product team who do not have podcasts and being like, I really don't think that you can build the right things. If they talk to users all the time, they see the data, but all of them, once they finally start doing their podcast, they're like, I get it." Force the entire team to become creators/users to deeply understand user pain points.
Use the tool intensely every day
Michael Truell: "From the very start, our product development process was really about dogfooding, and using the tool intensely every day. And we never wanted to ship anything that wasn't useful to us." 'Intense' daily use provides the realism needed to build useful features, especially for AI products.
Questions to Help Users
- "How often does each team member actually use the product as a real user?"
- "What's preventing your team from being heavy users of your own product?"
- "What would it take to make internal usage feel natural rather than forced?"
- "Are you learning different things from dogfooding vs. customer feedback?"
- "How quickly do you feel the pain of bugs or friction when using your own product?"
Common Mistakes to Flag
- Superficial testing - Using the product only in demo mode, not for real work
- Delegating to QA - Relying on testers instead of requiring team members to be real users
- Ignoring non-obvious use cases - Only testing the happy path rather than edge cases
- Not acting on findings - Dogfooding without a process to fix discovered issues
- Excluding non-product roles - Only having engineers dogfood when designers and PMs should too
Deep Dive
For all 2 insights from 2 guests, see references/guest-insights.md
Related Skills
- Writing North Star Metrics
- Defining Product Vision
- Prioritizing Roadmap
- Setting OKRs & Goals
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Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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Reviews
- SSakura Torres★★★★★Dec 28, 2024
dogfooding is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- JJin Rahman★★★★★Dec 28, 2024
Registry listing for dogfooding matched our evaluation — installs cleanly and behaves as described in the markdown.
- SSophia Khan★★★★★Dec 8, 2024
Keeps context tight: dogfooding is the kind of skill you can hand to a new teammate without a long onboarding doc.
- SSophia Smith★★★★★Nov 27, 2024
Registry listing for dogfooding matched our evaluation — installs cleanly and behaves as described in the markdown.
- SSofia Iyer★★★★★Nov 23, 2024
dogfooding fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- RRahul Santra★★★★★Nov 19, 2024
We added dogfooding from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- RRen Reddy★★★★★Nov 19, 2024
dogfooding reduced setup friction for our internal harness; good balance of opinion and flexibility.
- HHiroshi Wang★★★★★Oct 18, 2024
dogfooding reduced setup friction for our internal harness; good balance of opinion and flexibility.
- AAva Gill★★★★★Oct 14, 2024
We added dogfooding from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- PPratham Ware★★★★★Oct 10, 2024
dogfooding fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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