Help users identify unique distribution advantages and master the lifecycle of acquisition channels to build a sustainable engine for growth and retention.
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Help users conduct high-impact customer interviews that move beyond surface-level feature requests to identify root emotional frustrations and specific causal triggers.
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Uncover deep user pain and behavioral triggers to build products people actually need.
Help the user with mastering customer interviews using insights from 11 guests and posts across Lenny's Podcast and Newsletter.
Bob Moesta: "And so the real heart of the method of Jobs to Be Done is understanding the causation of what pushes people to say, 'Today's the day I got to do something different.'"
Interviews should uncover the specific events and context that led to a change in behavior. Understanding the struggling moment makes seemingly irrational user choices appear rational.
Jag Duggal: "You make sure that you focus on customer discovery before you start building. You make sure that that discovery is focused not simply on asking the customer, but on innovating on their behalf."
Effective research goes beyond listening to explicit requests by observing users in their natural environment. This reveals friction points that users may not be able to describe.
Shaun Clowes: "Avoid availability or confirmation bias. Most of the time people go talk to the people they always talk to and they learn nothing particularly new. They don't synthesize the results that they got from that conversation. They don't seek out the counterfactual, they don't seek out the proof that they're wrong."
To avoid confirmation bias, you must intentionally seek out data points that disprove your current assumptions. Learning is maximized when you find counterfactual perspectives.
From "How to develop product sense": "Don’t just read reports from researchers on your team; instead attend user research sessions to get firsthand exposure to user experiences and reactions. What’s important is to pay attention to micro details and ask yourself why people react to your product the way they do."
Directly observing user behavior provides a firsthand understanding of emotional and functional needs. Research reports often overlook the nuance found in live reactions.
From "Startup to exit: Lessons from a first-time founder": "However, we realized our first several “interviews” were actually sales pitches (e.g. “here’s this cool new thing, what do you think?”). Far too biased to get any real signal."
Running discovery calls as sales pitches prevents honest signals. Use an unbiased script that avoids mentioning your specific solution to see if the customer brings up the problem organically.
From "What to do if your product isn’t taking off": "When talking to people, look for two things: pain and pull. Pain tells you there’s an opportunity to solve a problem. Pull tells you that you’re actually solving the problem."
Ignore polite encouragement and look for signs of intense pain. Real pull is evidenced by people paying money or continuing to use a bad prototype despite its flaws.
See references/artifacts.md for the full list with details.
For all 14 sourced insights from 11 guests, see references/guest-insights.md
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概要と使いどころ
Help users identify unique distribution advantages and master the lifecycle of acquisition channels to build a sustainable engine for growth and retention.
日本語の概要は準備中です。原文の説明を表示しています。
Help users build functional product prototypes from natural language or visual mocks using AI coding tools. This skill enables product leaders to bypass engineering bottlenecks and validate ideas through hands-on building.
日本語の概要は準備中です。原文の説明を表示しています。
Help users build robust infrastructure for measuring, monitoring, and iterating on AI product performance using human, code-based, and LLM-as-a-judge methodologies.
日本語の概要は準備中です。原文の説明を表示しています。
Help users interact with probabilistic models by designing interfaces that manage fluidity, intent, and agency while maintaining trust and control.
日本語の概要は準備中です。原文の説明を表示しています。
Help users decide where to apply AI effectively, manage the transition from deterministic to probabilistic software, and build long-term defensibility through verticalization and proprietary data.
日本語の概要は準備中です。原文の説明を表示しています。
Help users convert massive volumes of qualitative and quantitative feedback into high-confidence product decisions through rigorous synthesis and internal immersion.
日本語の概要は準備中です。原文の説明を表示しています。