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Granola (Granola) is awesome because it doesn't simply outsource your thinking to an AI meeting bot (like all of those weird apps that sit in your Zoom calls). Instead, it merges your actual, human-written notes with the AI transcript to generate something that's accurate, actionable, and actually useful. CEO... show more

Michael Mignano

89,360 subscribers

17,001 views • 2 years ago •via X (Twitter)

Education Science & Technology

Anya Rossi• Live Now

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4 Comments

Michael Mignano2 years ago

Here are the links for my conversation with Chris Pedregal (@cjpedregal), CEO of Granola (@meetgranola): YouTube: Spotify: Apple Podcasts:

Charlie Revett2 years ago

@meetgranola "We don't want to take away note-taking from you, we want to augment your abilities." This will define standout #AI products; those that feel like normal tools with superpowers, not replacements.

Ansh Vashistha2 years ago

@meetgranola interesting! this episode is on my watch list

Dipesh Gaurav1 year ago

@JulieKainz @meetgranola Awesome

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Say hello to Granola for iOS. When we launched Granola, we wanted to bring the magic of AI notetaking to your Zoom calls. Today, we're bringing that magic to your in-person conversations. Give it a try and let us know what you think!

Say hello to Granola for iOS. When we launched Granola, we wanted to bring the magic of AI notetaking to your Zoom calls. Today, we're bringing that magic to your in-person conversations. Give it a try and let us know what you think!

Chris Pedregal

300,310 views • 1 year ago

Even when things are going great, running a $1.5 billion AI startup is a knife fight. Granola was one of the first AI apps of this generation to achieve near-ubiquitous adoption. But meeting notes are not the company’s be-all and end-all. The real battle is over owning the interface that everyone uses to get their work done in an AI-native world. I had Chris Pedregal (Chris Pedregal), cofounder and CEO of Granola, back on Every 📧’s AI & I to talk about the current state of the application layer, AI’s frontier, and the future of work. We get into: - Why meeting notes clones don’t matter. Three big companies cloned Granola’s core feature. To him, meeting notes were never the real prize. “Easy come, easy go” is his view of anyone’s lead, including his own. - How he thinks about building proactive features in AI. Granola pre-generates millions of pre-meeting briefs, which include context on the nature of the meeting and people participating, that most people never open. But when they do, they have a magical experience. - Why Granola is betting on “bring your own agent.” Chris says the API and MCP will get “a lot better” over the next few months, and we talk about their agent-native strategy and why they’ve pushed the product that way. This is a must-watch for anyone building at the application layer. Watch the episode! Timestamps Introduction: 00:00:59 Why running a company is a knife fight even when it’s working: 00:01:57 Granola’s counterintuitive view on competition: 00:04:33 Dan’s “pirate and architect” model for early-stage product teams: 00:10:44 Granola’s “shaping” and “validation” phases for building features: 00:13:09 Why Dan lives almost entirely inside Codex: 00:18:17 The case for “Codex-native apps”: 00:24:40 Granola’s “handrail” philosophy: 00:35:37 Why Granola is going all in on winning meeting-adjacent context: 00:38:12 What a transcript alone can never capture: 00:44:19

Even when things are going great, running a $1.5 billion AI startup is a knife fight. Granola was one of the first AI apps of this generation to achieve near-ubiquitous adoption. But meeting notes are not the company’s be-all and end-all. The real battle is over owning the interface that everyone uses to get their work done in an AI-native world. I had Chris Pedregal (Chris Pedregal), cofounder and CEO of Granola, back on Every 📧’s AI & I to talk about the current state of the application layer, AI’s frontier, and the future of work. We get into: - Why meeting notes clones don’t matter. Three big companies cloned Granola’s core feature. To him, meeting notes were never the real prize. “Easy come, easy go” is his view of anyone’s lead, including his own. - How he thinks about building proactive features in AI. Granola pre-generates millions of pre-meeting briefs, which include context on the nature of the meeting and people participating, that most people never open. But when they do, they have a magical experience. - Why Granola is betting on “bring your own agent.” Chris says the API and MCP will get “a lot better” over the next few months, and we talk about their agent-native strategy and why they’ve pushed the product that way. This is a must-watch for anyone building at the application layer. Watch the episode! Timestamps Introduction: 00:00:59 Why running a company is a knife fight even when it’s working: 00:01:57 Granola’s counterintuitive view on competition: 00:04:33 Dan’s “pirate and architect” model for early-stage product teams: 00:10:44 Granola’s “shaping” and “validation” phases for building features: 00:13:09 Why Dan lives almost entirely inside Codex: 00:18:17 The case for “Codex-native apps”: 00:24:40 Granola’s “handrail” philosophy: 00:35:37 Why Granola is going all in on winning meeting-adjacent context: 00:38:12 What a transcript alone can never capture: 00:44:19

Dan Shipper 📧

13,146 views • 2 months ago

You meet on Zoom, take notes with Granola, then work in isolation to make your changes. That is so... ...2025 😅 Introducing Pactto: present, review & approve creative work., the single place to meet, build context, and act on feedback. Agents listen, take notes, suggest changes, and make the changes, live, before the discussion ends. Better than talking about it, see it in action.

You meet on Zoom, take notes with Granola, then work in isolation to make your changes. That is so... ...2025 😅 Introducing Pactto: present, review & approve creative work., the single place to meet, build context, and act on feedback. Agents listen, take notes, suggest changes, and make the changes, live, before the discussion ends. Better than talking about it, see it in action.

Demian Borba

49,032 views • 3 months ago

Demo alert: What if your company wiki was automatically written and updated by LLMs? Jim Fisher built a demo of this for Granola using all the meetings we've shared internally. Observations so far: it's incredibly up to date (no more stale docs!) and it requires zero effort. Not having a human author feels... different. When it's missing context on something (ie when something happens but we don't talk about it in a meeting) I want to add it manually to the wiki, but then that'll disappear the next time the page gets regenerated... Generally, makes me bullish on workflows where humans feed tons of unstructured data (easiest of which to create is conversations) to an AI, and then AI organizes + structures it on the fly.

Demo alert: What if your company wiki was automatically written and updated by LLMs? Jim Fisher built a demo of this for Granola using all the meetings we've shared internally. Observations so far: it's incredibly up to date (no more stale docs!) and it requires zero effort. Not having a human author feels... different. When it's missing context on something (ie when something happens but we don't talk about it in a meeting) I want to add it manually to the wiki, but then that'll disappear the next time the page gets regenerated... Generally, makes me bullish on workflows where humans feed tons of unstructured data (easiest of which to create is conversations) to an AI, and then AI organizes + structures it on the fly.

Chris Pedregal

15,213 views • 1 year ago

How to build a beloved AI product, with Granola CEO Chris Pedregal Granola is the rare AI startup that slipped into a very crowded niche — meeting notes — and still managed to become the product founders (and VCs!) rave about. Plenty of product lessons in this episode. 00:00 - Introduction: The Granola Story 01:41 - Building a "Life-Changing" Product 04:31 - The "Second Brain" Vision 06:28 - Augmentation Philosophy (Engelbart), Tools That Shape Us 09:02 - Late to a Crowded Market: Why it Worked 13:43 - Two Product Founders, Zero ML PhDs 16:01 - London vs. SF: Building Outside the Valley 19:51 - One Year in Stealth: Learning Before Launch 22:40 - "Building For Us" & Finding First Users 25:41 - Key Design Choices: No Meeting Bot, No Stored Audio 29:24 - Simplicity is Hard: Cutting 50% of Features 32:54 - Intuition vs. Data in Making Product Decisions 36:25 - Continuous User Conversations: 4-6 Calls/Week 38:06 - Prioritizing the Future: Build for Tomorrow's Workflows 40:17 - Tech Stack Tour: Model Routing & Evals 42:29 - Context Windows, Costs & Inference Economics 45:03 - Audio Stack: Transcription, Noise Cancellation & Diarization Limits 48:27 - Guardrails & Citations: Building Trust in AI 50:00 - Growth Loops Without Virality Hacks 54:54 - Enterprise Compliance, Data Footprint & Liability Risk 57:07 - Retention & Habit Formation: The "500 Millisecond Window" 58:43 - Competing with OpenAI and Legacy Suites 1:01:27 - The Future: Deep Research Across Meetings & Roadmap 1:04:41 - Granola as Career Coach?

How to build a beloved AI product, with Granola CEO Chris Pedregal Granola is the rare AI startup that slipped into a very crowded niche — meeting notes — and still managed to become the product founders (and VCs!) rave about. Plenty of product lessons in this episode. 00:00 - Introduction: The Granola Story 01:41 - Building a "Life-Changing" Product 04:31 - The "Second Brain" Vision 06:28 - Augmentation Philosophy (Engelbart), Tools That Shape Us 09:02 - Late to a Crowded Market: Why it Worked 13:43 - Two Product Founders, Zero ML PhDs 16:01 - London vs. SF: Building Outside the Valley 19:51 - One Year in Stealth: Learning Before Launch 22:40 - "Building For Us" & Finding First Users 25:41 - Key Design Choices: No Meeting Bot, No Stored Audio 29:24 - Simplicity is Hard: Cutting 50% of Features 32:54 - Intuition vs. Data in Making Product Decisions 36:25 - Continuous User Conversations: 4-6 Calls/Week 38:06 - Prioritizing the Future: Build for Tomorrow's Workflows 40:17 - Tech Stack Tour: Model Routing & Evals 42:29 - Context Windows, Costs & Inference Economics 45:03 - Audio Stack: Transcription, Noise Cancellation & Diarization Limits 48:27 - Guardrails & Citations: Building Trust in AI 50:00 - Growth Loops Without Virality Hacks 54:54 - Enterprise Compliance, Data Footprint & Liability Risk 57:07 - Retention & Habit Formation: The "500 Millisecond Window" 58:43 - Competing with OpenAI and Legacy Suites 1:01:27 - The Future: Deep Research Across Meetings & Roadmap 1:04:41 - Granola as Career Coach?

Matt Turck

32,002 views • 1 year ago

KYC verifies the human. But your agent? It has no identity. No name. No way to prove who it's acting for. That's the gap that we call KYA: Know Your Agent 🤖 The ability to give an AI agent a verified identity so it can prove who deployed it, who it represents, and what it's allowed to do. Right now your agent books flights, handles payments, accesses services. Flying blind on your behalf. That's not trust. That's assumption. KYA is the infrastructure that changes this. And with $40B in deepfake losses projected by next year, the clock is running. Our CEO & Cofounder Evin evin sat down with amanda.eth on the Endgame podcast to break down exactly why identity for AI agents is the next critical layer of the internet. Full episode 👉

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Billions Network

31,273 views • 7 months ago

👋 Meet the Model Context Protocol (MCP): the open standard allowing apps to feed vital context to LLMs. Why is this protocol so important? Because context is what turns those generic AI replies into relevant, useful assistance tailored to your work. In this video, ☁️ Chris Reddington explains how MCP delivers this crucial info and why it makes such a difference for AI pair programmers like GitHub Copilot. 💡

👋 Meet the Model Context Protocol (MCP): the open standard allowing apps to feed vital context to LLMs. Why is this protocol so important? Because context is what turns those generic AI replies into relevant, useful assistance tailored to your work. In this video, ☁️ Chris Reddington explains how MCP delivers this crucial info and why it makes such a difference for AI pair programmers like GitHub Copilot. 💡

GitHub

35,316 views • 1 year ago

Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO Brian Armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛.

Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO Brian Armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛.

The All-In Podcast

80,524 views • 7 months ago

David Deutsch (David Deutsch) on the poverty of 'P(Doom)': "If you ask somebody, 'What's your subjective probability for AI Doom?', well, if they say anything other than zero or one, then your interlocutor has already won the argument. Because even if you said 'one in a million', they'll say, 'Well, one in a million is much too high a probability for the end of the human race, so you've got to do everything we say now to avoid that at all costs.' And the cost is irrelevant because the utility is infinitely negative. And this argument has all been about nothing, because you're arguing about the content of the other person's brain. Which actually has nothing to do with the real probability – which is unknowable – of a physical event that's going to be subject to unimaginably vast numbers of unknown forces in the future. So, much better to talk about a thing like that by talking about substance. Talking about what the probabilities in somebody's mind are is irrelevant. And it's always irrelevant unless you're talking about an actual random physical process." (Links to the full conversation below.)

David Deutsch (David Deutsch) on the poverty of 'P(Doom)': "If you ask somebody, 'What's your subjective probability for AI Doom?', well, if they say anything other than zero or one, then your interlocutor has already won the argument. Because even if you said 'one in a million', they'll say, 'Well, one in a million is much too high a probability for the end of the human race, so you've got to do everything we say now to avoid that at all costs.' And the cost is irrelevant because the utility is infinitely negative. And this argument has all been about nothing, because you're arguing about the content of the other person's brain. Which actually has nothing to do with the real probability – which is unknowable – of a physical event that's going to be subject to unimaginably vast numbers of unknown forces in the future. So, much better to talk about a thing like that by talking about substance. Talking about what the probabilities in somebody's mind are is irrelevant. And it's always irrelevant unless you're talking about an actual random physical process." (Links to the full conversation below.)

Joseph Noel Walker

371,706 views • 2 years ago

Proof of human in an AI world is one of the world's most urgent issues... so on today's JourneyMan, I sit down with Tiago Sada from to discover what this is all about. As ever, I hope you enjoy and find it useful.

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Raoul Pal

130,137 views • 1 year ago

I spoke with John Arrow of freedomgpt about why he created an AI clone of Scott Adams, creator of Dilbert, after he passed away. John mentions that the AI version of Scott is so realistic that he has to remind listeners that it’s an AI clone. Watch/listen to the full interview with John to learn about AI’s impact on society in the new episode of Deep Dive Podcast!

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Rachel Wolfson

25,587 views • 5 months ago

I recently joined Christopher Lind on the Future-Focused Podcast. The episode is titled "AI, Ethics, and Philosophy: Why We Need to Be Asking The Right Questions Before It’s Too Late." In this conversation, we discuss some of the most profound questions about AI, consciousness, and the future of human communication. Listen to the full episode on Christopher Lind's YouTube page! #lessonsfromleaders #brianbeckcomlawyer #ai #consciousness

I recently joined Christopher Lind on the Future-Focused Podcast. The episode is titled "AI, Ethics, and Philosophy: Why We Need to Be Asking The Right Questions Before It’s Too Late." In this conversation, we discuss some of the most profound questions about AI, consciousness, and the future of human communication. Listen to the full episode on Christopher Lind's YouTube page! #lessonsfromleaders #brianbeckcomlawyer #ai #consciousness

Brian Beckcom | Lawyer

83,624 views • 1 year ago

LinkedIn just started hiding AI-written posts. And their system catches them 94 percent of the time. But the answer is NOT to stop using AI. They announced this in May. If your post sounds like everyone else's, it doesn't get deleted. It just stops spreading. Your followers see it. Nobody new ever does. They're even flagging the way AI writes. Sentences like "it's not this, it's that"? Flagged. But most people missed one line in that announcement: using AI to HELP you write is totally fine. You just have to make it sound like you. Here are 2 things you can do: One, give your AI your own stuff. Upload your old posts, your client results, your stories, your data, your transcripts. Now instead of pulling generic advice off the internet, it's writing from YOUR experience. In your voice. Two, write about what people care about RIGHT NOW. I check AnswerThePublic to see the exact questions my audience is typing in this week then I write about those. The more you sound like yourself and talk about real problems people face, the more people will want to hear what you have to say.

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Neil Patel

12,378 views • 1 month ago

🧠 AI That Boosts, Not Replaces AI shouldn't replace creators — it should elevate them. That’s why World Engine was built with an AI-native approach that enhances your workflow rather than removing your role in it. Whether you're designing environments, generating terrain, or crafting detailed props, the AI does the heavy lifting on the boring and time-consuming parts so you can focus on the actual creative process. Think of it like a co-pilot that understands your vision. Use natural language to describe your idea and generate full 3D scenes instantly. Get context-aware suggestions that adapt to your style. Receive smart asset recommendations that match your world’s mood. World Engine’s AI tools are there to accelerate your vision, not overwrite it. 🖥 Watch the video for the full breakdown!

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NeuralAI

19,803 views • 1 year ago

"There are millions of transactions happening on the x402 protocol between agents and agents" says Chandler Fang of t54.ai Watch/listen to the full interview with Chandler, which covers the agentic economy in-depth in the latest episode of Deep Dive Podcast 🎧Comment below your thoughts!

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Rachel Wolfson

21,306 views • 5 months ago

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

Sophia

45,809 views • 1 year ago