product-taste-intuition▌
refoundai/lenny-skills · updated Apr 8, 2026
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Develop product taste and intuition using frameworks from 10 product leaders.
- ›Grounded in core principles: intuition as hypothesis generation, taste as a learnable skill built through exposure hours, and deliberate self-observation of your own product reactions
- ›Guides users to identify gaps in their judgment, suggest targeted practice activities, and know when to trust gut instinct versus data
- ›Includes diagnostic questions to surface what products users analyze regularly, how they no
Product Taste & Intuition
Help the user develop product taste and intuition using frameworks from 10 product leaders.
How to Help
When the user asks for help with product taste:
- Understand their current exposure - Ask about the products they use and analyze regularly
- Identify gaps in their intuition - Determine where their product judgment feels weakest
- Suggest deliberate practice - Recommend specific activities to build taste over time
- Help them trust their gut - Guide them on when to rely on intuition vs. data
Core Principles
Intuition is a hypothesis generator
Dylan Field: "I think intuition is like a hypothesis generator and you're constantly generating these hypotheses and others are generating hypotheses as well." Intuition isn't about being right - it's about generating good hypotheses quickly that you can then validate.
Taste is the differentiator in an AI world
Alex Komoroske: "In this cacophony, how do you stand out? You stand out by having good taste. I think taste is the most important thing." As AI makes production easier, taste becomes the critical differentiator that separates great products from "slop."
Taste is a developable skill
Guillermo Rauch: "Taste, sometimes I think we think of as this inaccessible thing that, 'Oh, that person was born with taste.' I see it as a skill that it can develop." Taste is built through "exposure hours" and deliberately analyzing the best products in the world, not innate talent.
Build taste through self-observation
Julie Zhuo: "The number one advice... is it's just really about observation and it's about curiosity and can start by first observing yourself." Build product sense by noticing your own reactions to products, then validating those observations qualitatively and quantitatively.
Be a voracious user of products
Kayvon Beykpour: "The best cheat codes for getting better at building products is just being a voracious user of products... There's just no replacement for that." Building great consumer products relies on "muscle memory" developed by using many products deeply.
Taste means knowing what to remove
Great taste isn't just about what to add - it's about knowing what to cut. The ability to simplify and focus is a core expression of product taste.
Questions to Help Users
- "What products do you use daily that you think are exceptionally well-designed? What makes them great?"
- "When was the last time you analyzed a competitor's product in detail? What did you learn?"
- "When you use a new app, what do you notice first? What bothers you?"
- "How often do you experiment with products outside your industry or domain?"
- "When your intuition and data conflict, how do you decide what to do?"
Common Mistakes to Flag
- Treating taste as innate - Believing some people just "have it" rather than developing it deliberately
- Not using enough products - Limited exposure leading to limited intuition
- Ignoring your own reactions - Not paying attention to what delights or frustrates you as a user
- Over-relying on data - Never making decisions based on judgment when data is unavailable
- Copying without understanding - Adopting patterns from successful products without understanding why they work
Deep Dive
For all 11 insights from 10 guests, see references/guest-insights.md
Related Skills
- problem-definition
- running-design-reviews
- positioning-messaging
How to use product-taste-intuition 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 development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add product-taste-intuition
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches product-taste-intuition from GitHub repository refoundai/lenny-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate product-taste-intuition. Access the skill through slash commands (e.g., /product-taste-intuition) or your agent's skill management interface.
Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★55 reviews- ★★★★★Chinedu Johnson· Dec 24, 2024
product-taste-intuition reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Yuki Anderson· Dec 20, 2024
I recommend product-taste-intuition for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Tariq Yang· Dec 16, 2024
Registry listing for product-taste-intuition matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Evelyn Zhang· Dec 16, 2024
Solid pick for teams standardizing on skills: product-taste-intuition is focused, and the summary matches what you get after install.
- ★★★★★Diya Patel· Nov 27, 2024
Solid pick for teams standardizing on skills: product-taste-intuition is focused, and the summary matches what you get after install.
- ★★★★★Chinedu Tandon· Nov 19, 2024
product-taste-intuition has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Diya Reddy· Nov 15, 2024
We added product-taste-intuition from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Tariq Chen· Nov 11, 2024
Keeps context tight: product-taste-intuition is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yuki Thomas· Nov 7, 2024
product-taste-intuition fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Diego Farah· Oct 26, 2024
We added product-taste-intuition from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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