Product Management
98 frameworks, rules, and principles from 51 practitioners — ready to drop into any AI agent.
AI Era Startup Approach, Brian Chesky, Alex Komoroske, Ami Vora, Aparna Chennapragada, Asha Sharma, and 46 more
What's in this pack
31
frameworks
12
rules
22
heuristics
25
principles
8
disagreements
Your AI can help you
- Prioritizing features with RICE and ICE frameworks
- Running product discovery interviews
- Deciding pricing and packaging strategies
See the difference
Generic AI gives you a checklist. Gavel gives you named experts who disagree — so you can decide who to follow.
"We have 30 feature requests from customers. How do I decide what to build next?"
Here are some things to consider:
- Categorize requests by frequency and impact
- Align features with your product strategy
- Consider development effort and complexity
- Gather more data through customer interviews
- Use a prioritization framework to rank them
The right choice depends on your specific situation...
"We have 30 feature requests from customers. How do I decide what to build next?"
"Do not build any of them yet. Run each through four risk filters: Will customers buy it (value)? Can they figure it out (usability)? Can you build it (feasibility)? Does it work for the business (viability)? Most of your 30 requests will fail at least one filter. Discovery before delivery."
Christian Idiodi
Four Pillars of Product Discovery"20% of your features drive 80% of willingness to pay. Run a willingness-to-pay study before you prioritize anything. Ask customers which features they would pay more for. The features they request most are often not the features they will pay for."
Madhavan Ramanujam
Monetizing InnovationWhere They Disagree
Idiodi says test for four types of risk before building anything. Ramanujam says follow the money — what customers request and what they will pay for are different lists.
See exactly what you get
Real items from this skill pack. Every item includes expert attribution and source material.
Four Pillars of Product Discovery
Four Pillars of Product Discovery Product teams must address four key risks: value (will people buy/choose it?), usability (can they use it?), feasibility (can we build it?), and viability (will it work for our business?). Product managers are primarily responsible for value and viability. Steps: 1. Assess Value Risk - Will customers buy or choose this product? 2. Assess Usability Risk - Can customers figure out how to use it? 3. Assess Feasibility Risk - Can we build it with current resources and technology? 4. Assess Viability Risk - Does it work for the business (sales, legal, compliance)? Why it works: Ensures product development addresses all critical dimensions before significant investment, reducing costly pivots and failures Common mistakes: - Focusing only on feasibility (can we build it) while ignoring viability - Assuming value because the team loves the idea - Skipping usability assessment for technically complex products
Christian Idiodi (SVPG)
The essence of product management
high consensus20% of features drive 80% of willingness to pay
20% of features drive 80% of willingness to pay Context: Pricing strategy and feature prioritization - this crucial 20% is often the easiest part to build
Madhavan Ramanujam
Pricing your AI product: Lessons from 400+ companies and 50 unicorns
If a product always has limitless opportunities for improvement, the team is thinking correctly; ...
If a product always has limitless opportunities for improvement, the team is thinking correctly; if not, they shouldn't be in charge Context: Mindset for continuous product improvement
Stewart Butterfield
Mental models for building products people love
Frameworks from the people who've done it
Give your AI real expertise in product management
98 expert-sourced frameworks, rules, and principles. One .md file. Drop it in and your AI cites practitioners instead of guessing.
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