Sarah Tavel, a venture partner at Benchmark and former product manager at Pinterest, discusses the need for a social layer in AI tools like ChatGPT. She believes the next wave of consumer AI will harness social interactions to enhance user experiences. Drawing from her Pinterest experience, she emphasizes that product-driven founders will help bridge this gap. Tavel also shares her insights on identifying passionate founders and the importance of community in building successful AI products.
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Tech to Product Genius Shift
Early tech companies like Google succeeded due to deep technical expertise and innovative infrastructure.
As tech matures, leadership shifts towards product geniuses who craft engaging user experiences.
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Lack of Social Layer in ChatGPT
ChatGPT feels "criminal" because it lacks inherent social features that enable prompt sharing.
A community of prompt experts could greatly simplify AI usage for everyone.
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Using Multiple AI Personalities
A film director uses multiple ChatGPT personalities for medical advice, writing support, and emotional boosts.
These AI personas serve different life roles, indicating diverse AI application potential.
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The book explores the pitfalls and challenges that leaders, particularly CEOs, face through a narrative centered around Andrew O’Brien, the CEO of a fictional company. Andrew meets Charlie, a wise former CEO, who introduces him to five temptations: prioritizing personal status over organizational results, valuing popularity over accountability, choosing certainty over clarity in decision-making, preferring harmony over productive conflict, and avoiding vulnerability to maintain an aura of invulnerability. Lencioni emphasizes the importance of humility, accountability, decisiveness, healthy conflict, and trust in leadership.
Thinking in bets
Making Smarter Decisions When You Don't Have All the Facts
Annie Duke
In this book, Annie Duke teaches readers how to make better decisions by treating them as 'bets' on uncertain outcomes. She emphasizes the importance of distinguishing between the quality of a decision and its outcome, acknowledging the role of luck, and avoiding biases such as 'resulting' and hindsight bias. Duke draws on her experiences as a professional poker player and combines these with insights from cognitive psychology and other fields to provide tools for making more objective and thoughtful decisions. The book encourages readers to get comfortable with uncertainty, seek truth through diverse opinions, and learn from outcomes to improve future decision-making[1][3][5].
Sarah Tavel thinks it's criminal that ChatGPT isn’t inherently social.
There’s no easy way to discover great prompts or share the ones that worked. As a venture partner at Benchmark, Sarah believes that the next wave of consumer AI will be built on this missing social layer—by product-driven founders who understand people, not just models.
Sarah has seen this shift before. As one of Pinterest’s first product managers, she saw the company grow from a niche consumer tool to a beloved global community. On this episode of Every's podcast AI & I, we talk about how she’s applying the lessons she learned to AI—and what it takes to build a breakout consumer AI app today.
We get into:
Why product geniuses win as new tech matures. In the early days of a new technology, companies win by wrangling raw innovation into something usable. But as the infrastructure matures, Sarah says the edge shifts to product thinkers—founders who turn new capabilities into delightful user experiences.
The future of prompting is social. When Sarah had to dig through Reddit to find a prompt to help her interpret her blood test results, she saw a gap: The best prompt creators are invisible. Sarah bets that a social AI product that makes them discoverable and followable would gain traction.
Sarah’s method to spot exceptional founders. Sarah backs founders for whom building a company feels like a calling—or even an affliction. These are people who have fallen in love with the process and are obsessed with learning how to grow alongside their companies.
How to tell if your startup really has network effects. Founders raising money love to say that their business has “network effects.” Sarah has learned to look for early signs they’re real—like traction in a small, white-hot segment of the market. If there’s no evidence the flywheel is already starting to spin, it’s probably not a network effect.
How LLMs change the way the best VCs invest. Sarah thinks the future of venture will be shaped by how well VCs can turn the decisions they make into training data. After every pitch, she logs what she liked, what she didn’t, the deal terms, and her reasoning. Over time, she’s building a dataset of her own judgment—one an LLM could help her use to pressure-test decisions and avoid past mistakes.
This is a must-listen for if you’re building a consumer AI product and want to see ahead of the curve.
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