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cover of episode Chris Pedregal + Sam Stephenson: Making Meetings More Effective with Granola

Chris Pedregal + Sam Stephenson: Making Meetings More Effective with Granola

2025/5/15
logo of podcast Generative Now | AI Builders on Creating the Future

Generative Now | AI Builders on Creating the Future
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Chris Pedregal
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Sam Stephenson
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Chris Pedregal: 三年前我辞职谷歌，想在伦敦创业，并开始尝试GPT-3。我意识到AI将彻底改变工具的格局，因此我开始寻找合适的联合创始人。我认为技术联合创始人应该懂模型训练和AI原生UI设计。人类是工具制造者，我们的能力受限于我们可用的工具，AI是思考工具的终极加速器。我在网上一个思考工具的聚会群里找到了Sam，并邀请他喝啤酒。 Sam Stephenson: 我们从一开始就认为AI会改变工具的格局，现有的工具需要改变，或者新人会来接管。建立好的产品体验，找到用户痛点并围绕它进行设计非常重要。我们花时间寻找用户痛点，发现围绕会议的工作会产生大量后续工作，而人们普遍讨厌做这些琐事。因此，我们开始研究如何开发一个工具，在会议中帮助人们处理会议相关的琐事。

Deep Dive

Chapters
This chapter details the origin story of Granola, starting from Chris Pedregal's post-Google GPT-3 explorations and his subsequent meeting with Sam Stephenson. It covers their shared vision of AI's impact on tools for thought, the identification of meeting follow-up as a key pain point, and the shift in perception of the AI app layer.
  • Chris Pedregal's post-Google exploration of GPT-3.
  • Meeting follow-up identified as a significant pain point.
  • Shift in perception of the AI app layer.

Shownotes Transcript

How can AI make meetings better? That’s the simple question that inspired Granola, a productivity tool that can tell you what was actually discussed in that meeting last week and what the real next steps are. 

In this episode of Generative Now, host Michael Mignano, partner at Lightspeed, sits down with Granola co-founders Chris Pedregal and Sam Stephenson at their headquarters in London. They talk about how they first met, their early product bets, and how they decided to focus on solving one painful problem: the chaos that follows every meeting. They share the story behind their early experiments with GPT-3 and how that eventually evolved into a tool designed especially for people who find their days filled with back-to-back meetings. 

Chris and Sam explain why they avoided flashy AI features to focus on simplicity and habit-forming design, how they quickly found their product-market fit, and what it means to adapt quickly in the age of LLMs.

Episode Chapters

00:00 Welcome and Introduction

01:15 Finding the Right Co-Founder

01:51 Tools for Thought and AI

03:24 Identifying the Problem

04:38 Building the Solution

05:07 The Evolution of AI and App Layer

07:46 Challenges and Innovations

11:20 Business Model and Future Outlook

14:24 The Launch and Early Success

17:52 Theoretical vs. Practical User Needs

18:17 Stress and Software Design

19:28 Scaling with AI

22:05 Maintaining Quality and Taste

24:10 Building a Silicon Valley Startup in London

28:03 The Future of Granola

30:27 Early Feedback and Iteration

35:09 Privacy and Data Handling

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