Granola Co-Founder Sam Stephenson Unveils AI-Native Meeting Workflow
Peter Yang
Granola achieves high enterprise adoption and daily user retention by aggressively hiding raw transcripts and prioritizing human presence over real-time text walls.
Granola deliberately conceals live transcription behind a minimal control despite persistent user complaints, prioritizing conversational eye contact and reduced anxiety over real-time text walls. (3:45)
Sam Stephenson's Figma usage dropped from 80% to roughly 20% over the past year, shifting product iteration directly into Cursor and an agent-ready design system documented with markdown files. (21:12)
Granola's internal operations rely on Nacho, an unowned, team-maintained agent hooked into Slack, logs, analytics, and GitHub that investigates incidents and directly spins up Cursor to open pull requests. (26:14)
Stephenson warns that because AI makes building trivial, most founders stop iterating too early at version one rather than refining products until they deliver verified daily value. (31:58)
Detailed notes
## Background
Published on YouTube by Peter Yang on October 4, 2026, this video features an interview with Sam Stephenson, co-founder of the AI meeting notes app Granola. According to the show notes, the discussion explores how to show up prepared for meetings using AI, what design means when agents bypass application interfaces, and how Granola builds an AI-native company without falling into the 996 grind.
## TL;DR
Sam Stephenson details Granola's philosophy of designing a calming 'handrail' experience for meetings, explaining opinionated trade-offs like deliberately concealing live transcripts to preserve human eye contact and presence. He explores key product utilities—including pre-meeting briefs and the popular 'What did I miss?' recipe—and outlines how meeting context feeds into organizational wikis and external agents via MCP and APIs. Internally, Granola maintains product craft and avoids AI 'slop' through an agent-ready design system that dropped Sam's Figma usage from 80% to 20%, alongside heavy internal dogfooding and an organic Slack assistant named Nacho that investigates bugs and generates pull requests. Rejecting intense startup overwork, Stephenson argues that because AI makes building trivial, true product excellence requires stepping away from the screen to cultivate taste and relentlessly iterating until software delivers clear daily value.
## Atmosphere & style
The dialogue feels like an intimate, candid debrief between two reflective product practitioners rather than a typical AI hype show. Peter acts as an engaged peer who frequently validates concepts with his own interview workflows, while Sam speaks with a relaxed, self-deprecating warmth—candidly admitting his addiction to coding agent 'slot machines' and the designer's sadness when agents skip user interfaces. The mood shifts effortlessly from philosophical discussions about user anxiety into pragmatic operational walkthroughs, offering a grounded and balanced perspective on modern software craft.
## Bulletin
- [03:45](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=225s) Granola deliberately conceals live transcription behind a minimal control despite persistent user complaints, prioritizing conversational eye contact and reduced anxiety over real-time text walls.
- [21:12](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1272s) Sam Stephenson's Figma usage dropped from 80% to roughly 20% over the past year, shifting product iteration directly into Cursor and an agent-ready design system documented with markdown files.
- [26:14](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1574s) Granola's internal operations rely on Nacho, an unowned, team-maintained agent hooked into Slack, logs, analytics, and GitHub that investigates incidents and directly spins up Cursor to open pull requests.
- [31:58](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1918s) Stephenson warns that because AI makes building trivial, most founders stop iterating too early at version one rather than refining products until they deliver verified daily value.
## Key takeaways
- [00:00](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=0s) Pre-meeting briefs act as an indispensable cognitive buffer, getting executives and interviewers up to speed seconds before jumping into high-stakes calls.
- [01:27](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=87s) 'What did I miss?' is Granola's most utilized recipe, highlighting the demand for discreet recovery tools when users multitask or zone out mid-conversation.
- [03:45](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=225s) Granola intentionally hides scrolling transcripts to protect human presence, accepting user confusion to prevent attendees from reading subtitles instead of making eye contact.
- [05:36](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=336s) The app is architected around a 'handrail' metaphor: remaining an ambient, humble support structure rather than demanding attention as the hero of the workflow.
- [07:47](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=467s) Because spoken meetings contain an organization's freshest, highest-fidelity context, meeting assistants are naturally evolving into living organizational wikis and context engines.
- [10:32](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=632s) Cross-meeting team intelligence requires a strict privacy boundary, relying on dedicated shared folders rather than indexing private 1-on-1s.
- [13:54](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=834s) Enterprise adoption inevitably requires design teams to accept AI agents bypassing custom graphical interfaces via APIs and Model Context Protocol (MCP) servers.
- [17:09](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1029s) Granola rejects the '996' grind because relentless execution drains the mental clarity needed to make high-conviction product decisions.
- [17:09](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1029s) The primary product bottleneck around meetings is managing the compounding stack of 15 to 20 daily follow-up tasks without overwhelming the user.
- [19:30](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1170s) To prevent AI-generated code 'slop' across production, Granola embedded markdown instruction files throughout the codebase to teach coding agents how to apply design tokens and components.
- [23:54](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1434s) Static mockups fail for AI interfaces because the emotional utility of generated text can only be judged using real, live personal data under actual workplace stress.
- [23:54](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1434s) Granola deploys deliberately unpolished version-one prototypes internally within days so engineers directly feel the pain of a bad implementation and iterate with urgency.
- [26:14](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1574s) An embedded 'Edit with Cursor' button on internal dashboards allows non-engineers to point-and-click on UI elements and dispatch background agents to modify tooling.
- [26:14](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1574s) Homegrown internal agents like Nacho deliver high ROI by autonomously cross-referencing system logs against codebases to diagnose bugs and draft pull requests.
- [31:58](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1918s) In an era of frictionless software development, competitive advantage belongs to teams that sweat subtle execution details until users experience genuine daily value.
## Detailed walkthrough
### [00:00](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=0s) The Pre-Meeting Brief and the "First Line of Defense"
Granola's design philosophy begins with addressing the frantic chaos of knowledge work. The app is crafted for the messy, high-friction moments between back-to-back meetings, when someone is rushing between rooms or frantically switching browser windows, running late, and realizing they have completely forgotten who they are about to speak with. In these high-stress transitions, the overarching goal of the product is to provide a calming presence. Peter Yang jokes that his ultimate feature request would be an autonomous agent layer—a "Peter agent" meeting a "Sammy agent" ahead of time to align on topics, calling the humans in only if they fail to reach consensus. Sam Stephenson notes that founders and CEOs frequently ask for Granola to act as exactly that: an intelligent "first line of defense" shielding them from the relentless barrage of incoming questions.
```mermaid
flowchart LR
accTitle: Pre-Meeting to Post-Meeting Granola Workflow
accDescr: A flow illustrating Granola preparing users with pre-meeting briefs, providing calm support during calls, and analyzing discussions afterward.
subgraph Prep ["Preparation"]
A["Pre-Meeting Brief<br/>(Candidate / Context)"]
end
subgraph Live ["In-Meeting Experience"]
B["Clean Note Canvas<br/>(Hidden Transcript)"]
C["'What did I miss?'<br/>(Instant Catch-Up)"]
end
Beyond standard automated note-taking, Sam shares his own indispensable workflow: pre-meeting briefs. Conducting frequent cultural interviews during the hiring process, Sam relies heavily on these concise automated dossiers to summarize the candidate's background and critical details right before a call starts. Having tuned the feature so it delivers just the essential facts without cognitive overload, he admits that he now feels "kind of naked without them," crediting the briefs with repeatedly saving him from embarrassment when context switching on short notice.
- **The Founder's Safety Net**: Sam uses pre-meeting briefs primarily for hiring and cultural interviews when he is under-prepared, getting caught up to speed seconds before jumping onto the call.
- **The Executive Defense Mechanism**: CEOs regularly ask Granola to act as a triage layer or buffer against recurring questions.
---
[01:27](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=87s) "What Did I Miss?" and Post-Meeting Analysis Recipes
Peter brings up the potential for meeting assistants to actively detect hidden tensions or unspoken disagreements in real time, prodding participants with prompts like, *"Do you guys actually agree on this thing?"* While real-time intervention is delicate, Sam highlights how Granola's "recipes" (specialized post-meeting prompt templates) already serve as analytical coaches. One of Granola's investors frequently runs a post-match breakdown recipe after conversations to evaluate his own performance: questioning what was missed, identifying which inquiries should have been pressed further, and discovering where the discussion could have gone deeper. Sales teams at Granola run similar retrospectives against historical calls to critique their pitch technique and refine future objections handling.
While Granola's automatic notes satisfy Sam's requirements 95% of the time, his most frequently used utility is the "What did I miss?" recipe. Whenever he zones out, gets distracted, or multitasks during a call, he relies on this recipe to bring him back up to speed immediately. Because it is by far the single most popular recipe across all users, Granola's team has been exploring making it a permanent, native interaction—such as hovering directly over the live transcript icon to view a quick catch-up summary. Peter confesses to a parallel habit: using Granola during product management interviews by feeding it the evaluation rubric in advance to objectively benchmark a candidate's answer against the grading criteria on the fly.
- **Post-Match Analysis**: Investors and sales representatives run dedicated recipes immediately after meetings to conduct rigorous self-critiques and identify missed opportunities.
- **The Most Popular Recipe**: "What did I miss?" is the app's most heavily triggered command, rescuing users who multitask or lose focus mid-call.
- **Interview Rubric Benchmarking**: Granola accepts pre-set evaluation rubrics to assess candidate answers against structured competency scorecards in real time.
---
[03:45](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=225s) Design Philosophy: Lowering Blood Pressure and Hiding the Transcript
As a designer by trade, Sam codified three core product and design principles alongside his team to align newly hired engineers around the company's ethos. The foremost emotional benchmark is tranquility: "the number one feeling we want people to feel is calm when they use Granola." Granola is tailored around the frantic moments when someone is running behind schedule, managing scattered windows, or rushing between conference rooms. In such chaotic contexts, Granola refuses to compete for attention or flood the screen with notifications; the interface is treated as a clean canvas designed so that simply glancing at it should "lower your blood pressure."
To achieve this radical simplicity, the team committed to aggressive, opinionated product trade-offs. The most controversial decision was deliberately burying the live transcript. Despite receiving a continuous stream of user complaints from people who assume the app lacks real-time transcription entirely, Granola intentionally tucks it away into a tiny control. Sam explains that the cognitive cost of a live scrolling text wall is toxic to human connection: when people see raw text scrolling across the screen, they watch the words instead of making eye contact and listening to the other person. Granola willingly pays the price of user confusion to preserve presence and focus.
- **Core Metric of Design**: The product must actively reduce user anxiety, targeting the chaotic minutes between consecutive calendar events.
- **Aggressive Minimalist Trade-offs**: The live transcription feed is intentionally minimized into an inconspicuous element, filtering out distractions even though some users complain they cannot find it.
- **Preserving Presence**: By stripping away non-essential UI elements, the software ensures attendees remain fully engaged with their counterpart rather than reading real-time subtitles.
---
[05:36](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=336s) The "Handrail" Metaphor and the Evolution into an Organizational Context Engine
To maintain product discipline, the team relies on an internal guiding metaphor: Granola must act like a "handrail." It is never intended to be the center of attention or the hero of the interaction. The human user remains the main character, responsible for steering the conversation, evaluating nuance, and making critical decisions. Granola simply sits quietly on the periphery—a sturdy handrail offering steady support whenever needed, a posture Sam notes "keeps you humble" as a software creator. Peter echoes how exhausting the standard meeting cycle can be: frantically scrambling to jot notes during the final five minutes of a call, rushing to blast out takeaways on Slack, and jumping immediately into the next meeting without time to process what happened.
Following a brief demonstration by Peter highlighting how developers use Google AI Studio to spin up rapid prototypes (such as generating multiple distinct landing page concepts for a bakery using Google's Nano Banana model and sharing them via custom URLs), the conversation pivots to Granola's long-term trajectory. While the tool originated as a personal meeting scratchpad, conversations inside meetings represent the single most current, high-fidelity context a company possesses. Peter points out that Granola is positioned to transcend individual note-taking and transform into a living organizational wiki and context platform for entire companies, an evolution Sam and his team are actively pursuing.
- **The Handrail Metaphor**: Granola is engineered as ambient support rather than the main character; it exists purely to assist the human worker in being more present.
- **Meetings as Core Context**: Spoken workplace interactions contain the freshest operational knowledge in an organization, opening the path for Granola to expand from a meeting recorder into a unified company-wide knowledge graph.
[07:47](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=467s) Context Accumulation and Custom Meeting Recipes
When Granola is used day in and day out across every meeting, it quietly accumulates a massive repository of personal and company context: who the key people in your life are, what active projects are underway, and what is happening across the entire organization. Sam notes that this context goes far beyond high-level summary bullets. Because Granola retains nuanced, nitty-gritty details in the transcripts, it can surface smart insights—such as alerting you to which projects are likely to go off the rails soon or highlighting initiatives that have not been receiving enough leadership attention.
Beyond pre-meeting and post-meeting routines, Sam frequently deploys specific prompts and recipes to transform meeting context into deliverables. He uses the app's conversational companion as a sounding board:
- Generating slide deck outlines for internal presentations (such as outlining company design principles).
- Drafting job descriptions for newly opened roles directly after scoping discussions.
- Drafting announcement blog posts and feature launches; rather than facing a blank page, the team holds a meeting to discuss what needs to go into the post, and Granola drafts it while pulling from the entire historical context of the project.
Looking through shared recipes created by the Granola team, Peter points out an internal review recipe—essentially a "What would Sam or Chris think?" prompt used for brainstorming product ideas. Sam laughs at how accurate it is, noting the prompt's sharp evaluative criteria: "It's a simple suggestion we can share. How do you measure it's working? What's the two way to do it?" Peter jokingly urges him to open-source the prompt for other founders.
---
[10:32](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=632s) Team Spaces, Privacy, and Cross-Meeting Insights
The discussion turns to how meeting intelligence scales from individual self-awareness to team-wide collaboration. When asked whether a manager or colleague could use Granola to analyze how coworkers or direct reports operate in meetings, Sam emphasizes the delicate balance between collaboration and strict privacy. Granola intentionally draws a hard boundary: it cannot look into private meetings or spy on reports' 1-on-1s.
Instead, collaborative intelligence relies on explicit sharing inside Granola's team space:
- **Shared Folders:** Teams organize shared notes into dedicated folders for standups, design crits, design weekly syncs, and customer calls.
- **High-Volume Sales Repositories:** The sales folder receives many calls a day, turning customer conversations into a searchable knowledge base.
- **Global Cross-Meeting Search:** Rather than navigating individual folder trees, users can use Granola's chat assistant to query across all team-shared meetings at once (for example, asking "what things customers say" to identify recurring feature requests, trends, or customer pain points across all recent calls).
---
[12:43](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=763s) Automating Workflows via API and MCP
Peter asks whether Granola will introduce scheduled automations—such as automatically running a synthesis search every Monday morning. Sam explains that while they have prototyped these capabilities, there is a distinct gap between an "average" implementation and a truly great out-of-the-box user experience. While native scheduled automations are still being refined for the core app, advanced users are already assembling their own systems through Granola's API and MCP (Model Context Protocol) integration.
```mermaid
flowchart TD
accTitle: Granola Data Flow via MCP and API
accDescr: Diagram showing how meeting context feeds into internal team spaces and external agents via MCP.
subgraph Capture["Context Ingestion"]
A["Granola Meetings & Transcripts"]
B["Team Space Folders (Sales, Standups)"]
end
subgraph Integration["Access Layer"]
C["Granola API & MCP Server"]
end
A --> B
A --> C
B --> C
C --> D
C --> E
D --> F
E --> F
```
Peter shares that he runs a personal workflow using the Granola MCP server: it combines meeting insights from Granola with external context from sources like Google Docs, automatically emailing him a comprehensive weekly summary. Sam points out that monitoring how power users utilize the MCP allows the Granola team to identify high-value workflows and productize them back into the native app.
---
[13:54](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=834s) When AI Agents Skip the UI: The Designer's Dilemma and Enterprise Reality
As users increasingly point external AI agents directly at APIs and MCP endpoints, Peter raises an existential question for product designers: how does a designer feel when end users never actually see the interface they worked hard to craft?
Sam admits there is "definitely a pang of sadness in there in the UI designer part of me." Granola initially resisted this trend, trying to keep every workflow contained inside the Granola UI. However, as the product pushed into larger enterprise environments, they realized enterprise adoption depends entirely on integrating with existing internal stacks:
> "It's been really interesting working with bigger and bigger enterprise customers, because I think just as soon as you become a big enough company... it's inevitable you have all of this internal tooling. And if Granola doesn't play nice with that internal tooling, like, you're a non-starter."
Sam and the team have made peace with Granola serving as the context engine of a company. While regular consumers continue to use the primary desktop UI, enterprise workflows may treat Granola as the ingestion layer during meetings while passing the enriched context downstream into internal corporate agents, ChatGPT, or bespoke enterprise dashboards.
Building the infrastructure for pre-meeting briefs forced Granola to master sifting through email threads. Looking ahead, Sam sees an enormous opportunity to expand that connective tissue to internal systems across Slack, CRMs, and company wikis to feed meeting intelligence from every corner of an organization's knowledge base.
[16:12](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=972s) Pre-Meeting Briefs and the "Peter Agent vs. Sam Agent" Feature Request
Sam notes that pre-meeting briefs are the "obvious first use case" for AI tools, though there is a risk for early adopters who try out every AI tool: they end up drafting briefs from everyone "left, right, and center." He acknowledges that this isn't really a "regular person's problem."
Before moving on from the product discussion, Peter laughs and pitches his "ultimate feature request," admitting that "this is probably bad." He proposes a world where he has a "Peter agent" and Sam has a "Sammy agent," and before they ever meet, they send their agents to have a meeting first to align—only bringing the humans in if the agents can't reach an alignment. Sam laughs and reveals that this is actually a major recurring theme: Granola gets a lot of CEOs asking for that exact capability, phrasing it as, "Can you make Granola be my first line of defense from all the questions I get?" Both agree there is genuinely something compelling there.
[17:09](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1029s) Rejecting the 996 Grind, the Coding Agent "Slot Machine," and Post-Meeting Overload
Shifting gears to how Granola operates internally, Peter admits he feels a bit pessimistic about the current AI cycle, observing that many AI-native companies seem to be working a "996" schedule and grinding non-stop. As a parent, he questions whether anybody really wants that lifestyle, noting that Granola seems to have a different philosophy. Sam credits his perspective to "being a Londoner." While the Granola team works very hard and pours a lot of themselves into the product, Sam firmly believes people should have a life outside of work: "There's just so much more to life than writing code or writing software... the work you do is better when you have some balance."
At the same time, Sam confesses that he is personally "fully like addicted to the slot machine of the coding agents," finding himself on his laptop every night telling himself, "Oh, one more problem. One more problem. One more problem." Peter agrees, pointing out an irony: while Granola helps users with context switching between meetings, context switching between different coding agent threads is even harder—forcing you to context switch literally every five minutes, which quickly becomes exhausting.
This ties directly into a core design challenge Granola is currently grappling with: helping users *outside* of meetings. While chat is a small hint of that, the bigger problem is managing the follow-up work that surrounds meetings once Granola is connected to a user's tools. Sam breaks down the math of why post-meeting tasks quickly become overwhelming:
- If an average meeting generates **3 things** you need to go do or think about, and you have **5 meetings** during the day, it rapidly turns into a massive stack of **15 to 20 takeaways** by the end of the day.
- The hard design problem is figuring out how to present and help users get through that stack in a way that makes their life nicer, better, and more calming, rather than piling on stress and pressure. As Sam sums it up: "We want to be a calming presence in your life, not the opposite."
[19:30](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1170s) Preventing AI "Slop" with an Agent-Ready Design System
Peter brings up a modern product development dilemma: now that shipping code is easier than ever, almost anyone in a company can ship. As a designer, how does Sam maintain craft and quality and avoid "just like a bunch of slop going to prod all the time?" Sam acknowledges the tension, explaining that everyone at Granola writes and ships code in one way or another—much of it for internal tooling, though a surprising amount goes into production. He wants to encourage that empowerment without making design a bottleneck.
The key to maintaining quality came out of Granola's February rebrand. Alongside overhauling the look and feel of the app to match the new brand, the team rebuilt the app on a brand-new design system:
- Everything behind the scenes is built on reusable tokens and components.
- Crucially, the system was built not just for humans, but for agents: they placed `.md` (markdown) files all over the codebase to teach coding agents how to properly use the design system.
- For features that aren't super design-heavy—such as building enterprise features in the settings menu—someone can simply ask the coding agent to "add a new page in settings that does X, Y, and Z, and when this toggle's turned off, this happens," and the agent automatically uses the right components and outputs something that looks decent right out of the box.
[21:12](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1272s) Why Sam's Figma Usage Dropped from 80% to 20%
Reflecting on how the role of designers is changing, Sam remarks that Figma used to have a complete hold on the design industry for good reason. Previously, Sam spent **80% of his day** in Figma—catching ideas, iterating on approaches, refining, and handing off designs. Over the last year, that workflow has been "thrown apart," and Sam estimates his Figma usage is now down to about **20%**, though it varies across the team and depends heavily on the type of project.
Because Granola is an in-person company, the team does a lot of initial thinking together on physical whiteboards. Today, a simple whiteboard sketch is often enough to hand directly to an engineer, because the coding agent can combine that sketch with the design system to build the right thing.
```mermaid
flowchart LR
accTitle: Granola's Modern Design-to-Code Workflows
accDescr: Comparison of when the Granola team uses Figma versus direct code prototyping with Cursor and their design system.
subgraph Ideation["1. Initial Ideation"]
WB["In-person whiteboard sketch"]
end
subgraph Paths["2. Iteration Path (By Project Type)"]
direction TB
Figma["Figma Canvas (20% of Sam's time)<br/>Linear flows & copywriting<br/>e.g., Paywall & business tier upsells"]
Code["Code Prototyping in Cursor<br/>Interactive, core-flow features<br/>e.g., Pre-meeting briefs"]
end
subgraph System["3. Execution"]
DS["Agent-ready Design System<br/>Tokens, components &.md files"]
UI["Live UI placements<br/>Top-right notification, bottom bar,<br/>or side transcription indicator"]
end
Sam contrasts two recent projects led by designer Tanya to illustrate when Figma still shines versus when prototyping in code wins:
- **Paywall and Subscription Flows (Heavy Figma):** When Tanya worked on the paywall and upselling users to the business tier, the hardest design challenge was making sure the linear flow made sense and that the copywriting planted the right ideas in the user's head at the right moments. Because there weren't many complex interaction states, iterating on copywriting side-by-side on a Figma canvas was far faster.
- **Pre-Meeting Briefs (Heavy Code Prototyping):** In contrast, designing pre-meeting briefs was much more interactive and tightly integrated into the core app flow. It only involved a couple of bullet points, so the real question was *where* to show them in the app and how they felt in context.
Walking through Tanya's early explorations for the pre-meeting briefs, Sam explains how they went straight from chatting around a whiteboard to a rough mock, and immediately into **Cursor**. With a single prompt, a designer can tell Cursor: *"Hey, I have this brief to test these texts. Can you go put this in the notification that appears in the top right of the screen before a meeting? And can you also please go and put it in the bottom of the screen? Can you also go put it in the floating transcription indicator on the side of the screen? Do all three of those things now."* By testing all three placements live in code simultaneously, the team gets instant signal on whether an interaction actually feels good.
[23:54](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1434s) Prototyping with Real Data and Dogfooding Ugly V1s
Sam explains that the design process for the meeting brief feature was "not at all linear," flip-flopping repeatedly between interactive code prototypes and Figma—a back-and-forth workflow that is becoming increasingly normal. Peter points out that interactive prototypes get you much closer to the actual end-user experience than static mocks. Sam agrees, pulling up the brief for their current conversation to illustrate why static mocks fall short for AI products. On the surface, a meeting brief is simple—"it's just a bunch of text"—with standard UI nuances around visual hierarchy and screen placement. However, the core design challenge is emotional and situational: "how does it feel when you're stressed and you're late and you're arriving to this meeting and you've forgotten who the person is to like receive these words in this way." You simply cannot judge whether the feature works by looking at a mock-up with made-up text or someone else's brief; you have to evaluate it using your own live data, especially since the quality of the underlying AI-generated text matters just as much as the UI.
Peter asks if Granola relies heavily on internal dogfooding and beta user feedback before general availability (GA) to allow the team to ship fast while maintaining a high quality bar. Sam confirms that whenever a new project starts, they push to get a "shitty end-to-end working version of it in the app as quickly as possible." For the meeting brief feature, they had a live version running inside the app within a week to a week and a half of kicking off the project. It was "incredibly ugly"—just a big box sitting at the top of the notes with poorly written output—but shipping it internally served a vital psychological purpose. Sam believes you want the team "feeling the pain of this thing not being good like day in day out," which is a remarkably effective way of "making you give a shit about it being good," backed by active internal Slack channels where teammates constantly drop feedback.
[26:14](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1574s) Nacho: The Internal Agent Every Granola Employee Asks First
Peter notes the broader industry shift from working in IDEs and apps to commanding agents directly inside Slack, and asks Sam to show off Granola's internal agents, specifically mentioning "Nacho" and "Honeybot." Sam shares his screen to reveal Granola's internal dashboard, a central hub housing all of their internal tools that everyone on the team actively builds and contributes to. To lower the barrier to improving internal tooling, they built an "Edit with Cursor" button directly into the dashboard's UI: anyone can toggle it on, point and click on an element, type a prompt like "make this red," and spin up a background Cursor agent to modify the internal tool on the spot.
Within this ecosystem, Nacho is by far their most-used internal tool. Accessible both via a web chatbot interface and primarily inside Slack, Nacho is hooked up to as many company data sources as possible, including Slack, Granola, Amplitude, system logs, website analytics, and the codebase. It acts as the universal "first port of call" whenever a question or issue arises. Sam walks through a real example in Slack where summary generation experienced a minor dip: brought into the channel, Nacho immediately inspected the system logs to see where errors were popping up, cross-referenced those findings against the codebase to diagnose why the error was happening, and reported back—an investigation that would take a human engineer much longer to piece together manually. It is also highly reliable at writing SQL queries to pull data far faster than a human navigating dashboards.
```mermaid
flowchart LR
accTitle: Nacho Internal Agent Architecture and Workflow
subgraph Sources["Connected Data Sources"]
S1["Slack & Granola"]
S2["Amplitude & Web Analytics"]
S3["System Logs & Codebase"]
end
subgraph Agent["Nacho (Slack & Web)"]
N["First-Pass Investigation & SQL Queries"]
end
subgraph Action["Automated Resolution"]
C["Spins up Cursor Agent"]
PR["Writes Pull Request (PR) to Fix"]
end
Sources --> N
N --> C
C --> PR
```
When Peter asks if a dedicated internal tools team maintains Nacho, Sam reveals that "nobody owns it." An engineer named JK originally built it as a weekend or evening project, and since then, the whole team contributes to it organically. Because Nacho is so popular across the company, "if you make Nacho better, you'll be everybody's best friend," creating a strong social incentive for engineers with 10 spare minutes to add new capabilities. Peter praises this homegrown approach over buying off-the-shelf integrations, noting that building an internal wrapper isn't too difficult and gives a company the flexibility to swap underlying models if a better or cheaper one comes along. Better yet, Sam explains that rather than keeping Nacho and Cursor as two separate tools, they gave Nacho the ability to spin up Cursor agents directly—meaning an automated incident investigation in Slack frequently flows straight into Nacho writing a pull request (PR) to fix the bug.
- **Internal Dashboard ("Edit with Cursor"):** Allows any team member to point-and-click on internal tool UI elements and dispatch a Cursor agent to modify the tool.
- **Nacho's Integrations:** Slack, Granola, Amplitude, system logs, website analytics, SQL databases, and the codebase.
- **Origin & Ownership:** Started by engineer JK as an evening/weekend project; maintained collectively by the team with zero dedicated ownership.
[30:18](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1818s) Why Knowing What to Build Requires Stepping Away from the Grind
Recapping the philosophy of how to build an AI-native company while still giving employees a life outside of work, Peter summarizes Granola's two-pronged operational model: empowering anyone to build via a strong design system and pre-built UI components so engineer-built interfaces still look great, paired with deeply integrated internal agents like Nacho to handle questions and investigations. Sam agrees and adds a crucial cultural pillar: trusting people to manage their own time and judging them by their output rather than counting hours worked per day or week.
In an era where AI makes execution effortless, Sam argues that relentless grinding is actually counterproductive to great product work: "It's a cliche now, but like it's so easy to make stuff. The hard thing is knowing what to make." That kind of product clarity doesn't come from "grinding as hard as you can the whole time"; instead, the truly interesting ideas come from going for a walk, taking time off, and having the mental space to think deeply. Peter strongly agrees, noting that deciding what to build remains a distinctly human strength. Whenever he tries to brainstorm product ideas with AI tools like Claude or Codex, he finds that "the AI is still too agreeable, man"—enthusiastically validating mediocre ideas with "this is a great idea" rather than offering the critical pushback you get from talking to another human. As Peter transitions to wrapping up the interview, he asks Sam for his closing advice for AI builders.
[31:58](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1918s) Why Most Builders Stop Too Early—and Holding a High Bar for Daily Value
Sam credits his co-founder, Chris, with instilling a crucial mindset across the entire company about what it takes to build great products today. Because it has become so easy to build things nowadays, two principles stand out: first, you have to figure out how to build something genuinely interesting; second, "most people stop way too early" when building. Many builders reach a version one, push it out the door, and consider it shipped. Sam argues that the easier it becomes to build software, the more it matters to "really sweat the details and go the extra mile to make something that's actually going to be really useful to somebody." Rather than treating the act of shipping as the finish line, teams must hold themselves accountable to whether a user actually gets "daily value" out of the product—and refuse to stop iterating until they achieve that goal.
Peter agrees with the nuance here, noting that while you don't want to plan forever in a vacuum and need to ship to get market feedback, there is a difference between testing and declaring something done. Sam clarifies how Granola balances speed with quality: the team ships internally as quickly as possible and pushes features out to small groups of friends and beta users very early on, but they maintain a "very high bar for like is this thing actually working for people" before releasing it broadly.
```mermaid
flowchart LR
accTitle: Granola's Iteration vs. Shipping Philosophy
accDescr: Contrasts stopping at version 1 with Granola's approach of rapid internal and beta releases followed by relentless iteration until users get daily value.
subgraph Typical["Typical Builder Path"]
A["Build Version 1"] --> B["Ship to Public & Stop"]
end
subgraph Granola["Granola's Approach"]
C["Ship Internally Fast"] --> D["Test with Friends & Beta Users"]
D --> E["Sweat Details for Daily Value"]
E --> F["Broad Release"]
end
```
As they wrap up the conversation, Peter laughs that the public product is almost *too* polished right now and jokes, "add me to the janky and the mobile builds, man." Sam laughs along and agrees, and the two thank each other for a fun, insightful chat.
- **Co-founder credited for this product philosophy:** Chris.
- **Granola's release tiers:** Rapid internal shipping first, followed by very early access for small groups of friends and beta users, and finally a public release only once the feature proves it delivers daily value.
## Notable quotes
> [00:00](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=0s) kind of naked without them — Sam Stephenson
> [03:45](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=225s) the number one feeling we want people to feel is calm when they use Granola. — Sam Stephenson
> [03:45](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=225s) lower your blood pressure. — Sam Stephenson
> [05:36](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=336s) keeps you humble — Sam Stephenson
> [13:54](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=834s) definitely a pang of sadness in there in the UI designer part of me. — Sam Stephenson
> [13:54](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=834s) It's been really interesting working with bigger and bigger enterprise customers, because I think just as soon as you become a big enough company... it's inevitable you have all of this internal tooling. And if Granola doesn't play nice with that internal tooling, like, you're a non-starter. — Sam Stephenson
> [17:09](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1029s) There's just so much more to life than writing code or writing software... the work you do is better when you have some balance. — Sam Stephenson
> [17:09](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1029s) fully like addicted to the slot machine of the coding agents — Sam Stephenson
> [17:09](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1029s) We want to be a calming presence in your life, not the opposite. — Sam Stephenson
> [23:54](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1434s) feeling the pain of this thing not being good like day in day out — Sam Stephenson
> [26:14](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1574s) if you make Nacho better, you'll be everybody's best friend — Sam Stephenson
> [30:18](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1818s) It's a cliche now, but like it's so easy to make stuff. The hard thing is knowing what to make. — Sam Stephenson
> [30:18](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1818s) the AI is still too agreeable, man — Peter Yang
> [31:58](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1918s) most people stop way too early — Sam Stephenson
> [31:58](https://www.youtube.com/watch?v=3IF3H5dxU3U&t=1918s) really sweat the details and go the extra mile to make something that's actually going to be really useful to somebody. — Sam Stephenson
## Mentioned
Sam Stephenson, Peter Yang, Chris, Tanya, JK, Granola, Google AI Studio, Nano Banana, Claude, ChatGPT, Codex, Cursor, Figma, Nacho, Honeybot, Amplitude, Slack, Model Context Protocol (MCP), Linear, Riverside
## Video description
Sam is the co-founder of Granola, the AI meeting notes app now valued at $1.5B. Granola has helped me survive (and even enjoy) countless meetings, so I was excited to learn how Sam uses AI to show up prepared. We also talked about building an AI-native company without the 996 grind and what design means when agents skip your app entirely.
Sam and I talked about:
(00:00) The AI brief Sam now relies on before every new meeting
(01:27) “What did I miss?”: Granola’s most used recipe
(03:45) Why Granola hides the transcript despite user complaints
(09:37) A Granola recipe to get feedback from founders
(13:54) Why Sam feels a pang of sadness when agents skip your UI
(19:30) Why Sam’s Figma use fell to 20% and how Granola stops slop
(26:14) Nacho: The agent every Granola employee asks first
(30:58) Why most people stop improving their product way too early
Thanks to our sponsors:
Linear: The AI agent platform for modern teams https://linear.app/behind-the-craft
Riverside: All-in-one AI studio for podcasts and video https://creators.riverside.com/PeterYang
📌 Get the takeaways: https://creatoreconomy.so/p/how-to-use-ai-to-survive-meetings-sam-stephenson
Granola co-founder Sam Stephenson argues that AI meeting assistants should act as an ambient, calming 'handrail' that protects human presence rather than demanding attention. As software generation becomes trivial through coding agents, he contends that product defensibility hinges on knowing what to build and refining features until they deliver reliable daily value.
Designing for Calm and Human Presence (3:45)
Granola's design philosophy centers on reducing anxiety during chaotic transitions between back-to-back meetings. Stephenson describes the application as a supportive handrail rather than the hero of an interaction, intentionally keeping the software in the background. To keep users focused on making eye contact and listening to counterparts, the team made the opinionated decision to hide the live transcription feed into a tiny control, accepting frequent user complaints from those who assume transcription is missing.
The interface instead emphasizes lightweight interventions. Stephenson relies on automated pre-meeting dossiers to quickly review candidate backgrounds before hiring calls without cognitive overload. During calls, the platform's most popular utility is the 'What did I miss?' prompt template, which brings users up to speed immediately if they become distracted or need to multitask.
From Personal Scratchpad to Organizational Context Engine (5:36)
While meeting tools often begin as personal note-taking utilities, spoken workplace conversations contain an organization's most timely operational knowledge. Stephenson explains that Granola leverages transcript details to track project trajectory, flag neglected initiatives, and draft deliverables such as slide deck outlines, job descriptions, and launch announcements based on historical context.
To balance shared intelligence with individual confidentiality, Granola enforces boundaries that protect private one-on-one syncs while enabling shared team folders for standups, design critiques, and high-volume sales calls. In enterprise settings, workflows increasingly bypass the visual user interface altogether; external language models query Granola via APIs and the Model Context Protocol (MCP) to route meeting insights directly into internal stacks, bespoke agents, and scheduled weekly syntheses.
Shifting from Figma to Agent-Driven Prototyping (19:30)
The rise of coding agents has reshaped Granola's internal product design workflow. Stephenson estimates his daily time spent in Figma dropped from 80% to roughly 20%, with the team increasingly moving directly from physical whiteboard sketches into code prototyping using Cursor. To maintain design craft without bottlenecking engineering, the company introduced an agent-ready design system populated with markdown instruction files that guide coding agents on proper token and component usage.
Stephenson highlights that static mockups are ineffective for evaluating AI features because UI text must be assessed under real-world emotional conditions. During the development of pre-meeting briefs, the team deployed a crude, functional version into the app within roughly a week. By forcing the internal team to experience the friction of an imperfect prototype on live personal data, Granola accelerated iterative improvements before public release.
Internal Tooling and Rejecting Grind Culture (17:09)
Stephenson rejects the intense '996' work culture prevalent among many AI companies, maintaining that high-quality product judgment requires mental space away from continuous coding. Instead, Granola relies on internal autonomy and custom tooling, most notably an internal agent named Nacho. Hooked into Slack, Granola, Amplitude, system logs, and the codebase, Nacho acts as the primary triage layer by analyzing system errors, writing SQL queries, and dispatching Cursor agents to author pull requests.
Reflecting on product execution, Stephenson notes that his co-founder Chris emphasizes not stopping at an initial version. Because spinning up baseline features has become easy, Stephenson argues that builders must avoid treating an early release as the finish line, instead obsessing over post-launch details until users experience genuine daily utility.
A persistent design hurdle for Granola remains managing the aftermath of meetings, where five daily conversations can generate an overwhelming stack of 15 to 20 action items. At the same time, the transition of meeting intelligence into headless API and MCP workflows leaves product designers with the unresolved challenge of creating value when end users rarely interact with the primary graphical interface.
Source quotes
[0:00] Sam Stephenson: kind of naked without them
[3:45] Sam Stephenson: the number one feeling we want people to feel is calm when they use Granola.
[3:45] Sam Stephenson: lower your blood pressure.
[5:36] Sam Stephenson: keeps you humble
[13:54] Sam Stephenson: definitely a pang of sadness in there in the UI designer part of me.
[13:54] Sam Stephenson: It's been really interesting working with bigger and bigger enterprise customers, because I think just as soon as you become a big enough company... it's inevitable you have all of this internal tooling. And if Granola doesn't play nice with that internal tooling, like, you're a non-starter.
[17:09] Sam Stephenson: There's just so much more to life than writing code or writing software... the work you do is better when you have some balance.
[17:09] Sam Stephenson: fully like addicted to the slot machine of the coding agents
[17:09] Sam Stephenson: We want to be a calming presence in your life, not the opposite.
[23:54] Sam Stephenson: feeling the pain of this thing not being good like day in day out
[26:14] Sam Stephenson: if you make Nacho better, you'll be everybody's best friend
[30:18] Sam Stephenson: It's a cliche now, but like it's so easy to make stuff. The hard thing is knowing what to make.
[30:18] Peter Yang: the AI is still too agreeable, man
[31:58] Sam Stephenson: most people stop way too early
[31:58] Sam Stephenson: really sweat the details and go the extra mile to make something that's actually going to be really useful to somebody.
Original transcript
[0:00] I think the number one feeling we want
[0:01] people to feel is calm when they use
[0:03] Granola. The main time we hold our heads
[0:05] as we're thinking about the product is
[0:06] like the messy [music] in between
[0:07] moments between back-to-back meetings.
[0:09] You're probably running late, probably
[0:10] forgot who you're going to be speaking
[0:11] to. We want to be a calming presence in
[0:13] your life. You know what would be the
[0:14] ultimate feature request from me? I'll
[0:16] have a Peter agent and you have a Sammy
[0:18] agent and then we go send our agents
[0:19] have a meeting first to align. And if
[0:21] they can't align, then we come in. You
[0:22] get a lot of like CEOs asking for that
[0:23] kind of thing. Can you make Granola be
[0:25] my first line of defense from all the
[0:27] questions I get all the time?
[0:31] >> All right, everyone. Today I'm really
[0:32] excited to welcome Sam, the co-founder
[0:34] of Granola. Granola started as an AI
[0:36] meeting notes tool and now they're worth
[0:38] $1.5 billion. So, I actually really want
[0:40] to get Sam to show us how he personally
[0:42] uses Granola beyond meeting notes and
[0:44] also how Granola runs internally using
[0:46] agents. So, welcome Sam.
[0:48] >> Uh thank you, Peter. Nice to be here.
[0:49] I've I've been looking forward to this.
[0:51] >> Why don't we get right into it? I think
[0:52] most people use Granola just to take
[0:53] meetings with AI, but I'm curious how
[0:56] you personally use Granola. Can you show
[0:57] us your personal Granola setup?
[0:59] >> I've become very dependent on these
[1:01] pre-meeting briefs. I find these most
[1:03] useful. I've kind of under-prepared for
[1:05] for a meeting with somebody new, like
[1:06] often like a new candidate. Um if I'm
[1:09] I do a lot of like cultural interviews
[1:11] as part of the um hiring process and if
[1:14] if I'm not up to speed on who the
[1:15] candidate is I'm talking to, this saves
[1:16] my ass and embarrasses me a lot of
[1:17] times.
[1:18] >> Nice.
[1:18] >> And uh yeah, I've I've like it it was a
[1:20] bunch of work to make this like just the
[1:21] right information that you need right as
[1:23] you're going into the meeting, but I
[1:24] feel kind of naked without them. That
[1:26] you know now if I'm meeting somebody
[1:27] new.
[1:27] >> I I think it'd be next level if if like
[1:29] Granola can actually help suss out like
[1:31] disagreements that people are not
[1:33] expressing and then be like, "I actually
[1:35] Sam and Peter, like do you guys actually
[1:37] agree on this thing?" Like during
[1:38] [laughter] the meeting.
[1:39] >> So, there is one of our uh uh investors
[1:42] um has a really good recipe, which
[1:44] designed to run like after the meeting,
[1:46] um
[1:47] not really during the meeting, but like
[1:49] uh he uses this a lot, I think, after
[1:51] meetings to kind of like kind of go back
[1:53] and do like a post-match analysis sort
[1:55] of and figure out like, "Oh, what what
[1:57] did I miss? What should I have asked?
[1:58] How could I have gone deeper during that
[1:59] conversation? Yeah, I I I I think that
[2:02] that kind of thing is really powerful.
[2:04] Like our sales team will do this as well
[2:05] on a on a sales call. You know, the
[2:08] after the meeting they'll be like, "I
[2:09] what what should I have done better that
[2:10] time Granola?" And you know, it has the
[2:12] history of previous uh
[2:14] previous sales calls you've done and so
[2:15] it can sometimes give you a pretty smart
[2:17] answer there.
[2:18] >> Got it. Do you just like uh you know,
[2:20] take take some notes here and then
[2:20] Granola fills in the rest of the notes
[2:22] and then you apply a recipe to it
[2:23] afterwards or like do you apply some
[2:24] sort of template to it afterwards?
[2:26] >> For me like the automatic notes sorts me
[2:28] out like 95% of the time. Um
[2:31] the things I will use like recipes and
[2:32] stuff for is I I'm I use this what did I
[2:34] miss thing um a lot. Like if I'm yeah, I
[2:38] shouldn't be but if I'm end up
[2:39] multitasking during the meeting or
[2:42] start you know, zone out thinking about
[2:43] something else like I go
[2:45] >> [laughter]
[2:45] >> I'll be reaching for this to to get me
[2:47] back on track. We uh yeah, we're talking
[2:49] about adding like making this more of a
[2:51] more of a productized feature like um
[2:53] you have this
[2:55] I'm saying over here which um has a live
[2:58] transcript and I kind of I kind of want
[2:59] to just make it so that you hover over
[3:01] this, we we tell you what you missed
[3:03] like straight away cuz it's um it's it's
[3:05] by far the most used recipe like people
[3:07] click on this thing all the time.
[3:08] >> Yeah, I don't know if I should admit
[3:09] this but like sometimes I'm interviewing
[3:11] a candidate for like product too and um
[3:13] they'll give me an answer and and then I
[3:14] I probably should not admit this but
[3:15] like I like to double check with Granola
[3:17] and be like, "Hey, you know, is is this
[3:18] a good answer?
[3:19] Like what what what what do you think?"
[3:21] Yeah. It's especially if you like give
[3:23] it like a pretty good template
[3:24] beforehand. Of the rubric that you're
[3:26] assess.
[3:27] Like it's it's actually pretty pretty
[3:28] good.
[3:30] >> Uh I I think for folks who have more
[3:32] kind of structured types of meetings um
[3:35] they lean on a template a lot for this.
[3:37] Like it's a you know, when you when you
[3:38] know you have the certain questions you
[3:39] want to ask, they'll be like making sure
[3:41] the notes come out in this structured
[3:42] way and
[3:43] >> Yeah.
[3:43] >> Yeah, being able to do repeatable things
[3:45] is important.
[3:45] >> Um can you talk about some of the cu-
[3:47] cu- cuz you're a designer by trade,
[3:49] right? Or
[3:49] am I wrong or Yeah. So, do you guys have
[3:52] some like product principle, design
[3:54] principles when building this app cuz it
[3:56] was like very simple and like there's
[3:58] I'm not sure there's a lot of trade-offs
[3:59] that went into this, right?
[4:00] >> We like I don't know. We We wrote these
[4:02] down like a month ago, so that they're
[4:04] pretty fresh.
[4:04] >> Okay. [clears throat and snorts]
[4:05] >> All right. Codify like
[4:07] you know, when we have new people join,
[4:08] we're trying to codify like what
[4:10] For every new engineer that joins, like
[4:11] what what few things should they have in
[4:13] their head, you know, as we like think
[4:15] about Granola. And then uh these were
[4:16] the three we got to. I think the number
[4:18] one emotion or feeling we want people to
[4:20] feel is calm when when they use Granola.
[4:23] We design Granola's designed for like
[4:24] incredibly busy like moment in your
[4:26] life. I think the main time we hold in
[4:28] our heads is when thinking about the
[4:30] product is like the messy in-between
[4:32] moments between back-to-back meetings,
[4:33] you know, where you're like ready or
[4:34] managing your windows or might even be
[4:36] rushing through rooms.
[4:38] You're probably running late. Probably
[4:39] forgotten who you're you're speaking to.
[4:41] Uh you might also have a couple of like
[4:43] quick things you need to get on top of
[4:45] before you jump into the next meeting.
[4:47] And Granola trying to like insert itself
[4:49] into that moment like really chaotic
[4:50] moment. And so, yeah, we really try to
[4:52] hold ourselves to this idea that like
[4:54] Granola should Looking at Granola should
[4:55] lower your blood pressure. It does not
[4:56] add to this chaos. It should feel like
[4:58] it's a it's helping you there. Yeah, I
[4:59] mean, I think such a blank canvas is
[5:01] like
[5:02] a lot a lot of that. And like as a I
[5:04] think we've we've made quite a few
[5:06] aggressive design decisions here.
[5:08] >> Like the transcript is so hidden. You
[5:10] got a lot of people find kind of
[5:11] ridiculous. And honestly, we get a lot
[5:13] of complaints that people don't even
[5:14] realize the transcript is there. Like we
[5:16] We pay a price for having it
[5:18] be that small. Um but I think uh we
[5:21] really really want to like just strip
[5:22] away everything that's not what you need
[5:24] to have in front of you during a
[5:25] meeting. And
[5:26] yeah, I think that's super important.
[5:28] >> Because when you're having a meeting,
[5:29] you want to focus on the other person,
[5:30] right? You don't want to be looking at
[5:31] like a live transcript, you know? It's
[5:33] like distracting.
[5:36] >> Yeah, we had this
[5:37] metaphor of like
[5:39] Granola should feel like a hand rail.
[5:40] Like that's kind of like one way of
[5:42] talking about Granola's role in your
[5:43] life. Like it's it's Um, it's not the
[5:46] main character, you know? Like you
[5:47] you're the main character. You're trying
[5:48] to get your work done and
[5:50] being present in this meeting, you know,
[5:52] the deciding the things you need to
[5:53] decide or talking about the things you
[5:55] need to talk about. And Grainer's really
[5:56] just going to be there on the side and
[5:58] support you and
[6:00] help you be better, you know? Um
[6:03] And uh
[6:04] yeah, I really I really like this
[6:05] metaphor. It It's
[6:07] >> [snorts]
[6:07] >> keeps you humble.
[6:08] >> [laughter]
[6:09] >> Yeah. Yeah, no, it's it's it's
[6:10] fantastic. And um I I totally agree.
[6:12] Like back-to-back meetings you're trying
[6:13] to like jot down notes in the last 5
[6:15] minutes, trying to send some takeaways
[6:16] on Slack. And it it it's just like a mad
[6:18] rush, right? Then you have then you have
[6:19] to contact switch to the other meeting.
[6:21] So, like yeah, so the some reason the
[6:23] pre-meeting briefings are super helpful
[6:25] for for that.
[6:27] >> Yeah. Yeah. Yeah. Yeah.
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[7:22] >> Another thing I think is very
[7:23] interesting is when you guys started, it
[7:25] was just like kind of taking meeting
[7:26] notes, right? But now, and I think Chris
[7:28] said this before, meetings are the most
[7:30] useful and up-to-date context that a
[7:31] company has in in some shapes, right?
[7:33] So, now I feel like there's a big
[7:34] opportunity here to just evolve into a
[7:36] whole, I don't know, like like a wiki or
[7:39] like a contextual platform for the whole
[7:41] com- com- company.
[7:42] >> Yeah. [snorts] Yeah.
[7:43] >> Yeah.
[7:43] >> Yeah. And that that like the direction
[7:44] that you guys are going down, right? Or
[7:45] or like can you talk more about that?
[7:47] >> Yeah. Yeah. Sure. Yeah. I think
[7:49] this is a bit of a I think we kind of we
[7:51] feel this could be
[7:53] an opportunity for us, but I don't think
[7:54] we realized how big of a thing it would
[7:56] be, but um
[7:57] uh I think so much of
[8:00] when you use Grain of like day in day
[8:02] out
[8:03] for all your meetings like just
[8:04] accumulates so much context about who
[8:07] you are, who you who are the people in
[8:08] your life, what projects you're working
[8:09] on, what's happening in your company. Um
[8:12] yeah, you know, like like and and not
[8:14] just at like high-level bullet points,
[8:16] but like real nitty-gritty details and
[8:18] you know, Grain of can tell me like what
[8:21] projects are likely to be going off the
[8:22] rails soon or like what things am I not
[8:24] giving enough attention to, you know,
[8:25] and and and it
[8:26] >> Yeah.
[8:27] >> has enough nuance detail in the
[8:28] transcripts to be able to give smart
[8:29] answers to that.
[8:30] >> I also love like just like the
[8:31] pre-meeting meeting and post-meeting. Do
[8:33] you run some recipes like on a regular
[8:34] basis or like what what what are some
[8:36] stuff that you kind of like, you know,
[8:37] check with all this context?
[8:39] >> Uh I I do like I will use things recipes
[8:42] for quite specific things. So, like
[8:45] um I don't know if I'm going to be able
[8:46] to get get a good example now, but like
[8:48] uh
[8:49] let's say if I just enhanced the notes.
[8:52] I'm to make a presentation
[8:55] internally about our
[8:58] um design principles. Can you make a
[9:02] slide deck outline for me?
[9:04] Um
[9:06] I'll often like use the conversation
[9:08] buddy as a way to Yeah, as draw things.
[9:11] Um I've been doing this with a
[9:13] like job description just earlier today
[9:15] for a for a new role we're looking for.
[9:17] I've used this
[9:20] one of the ways. A blog post like blog
[9:22] posts and new feature announcements have
[9:24] been written by us all having a meeting
[9:26] about what we think needs to go in the
[9:27] blog post and then
[9:28] >> Okay. Grain of has that, but it also has
[9:30] like the whole history of project, you
[9:31] know, so it's like the real [laughter]
[9:32] problem is that zero.
[9:34] >> Um yeah, and so it's I I find it very
[9:36] useful that kind of
[9:37] >> I see. And and and like uh if if I want
[9:39] to write a blog post in my format, like
[9:42] I I can make my own recipe or like save
[9:44] some prompt somewhere.
[9:46] >> Um
[9:48] I
[9:48] >> a recipe on here, yeah.
[9:50] >> You [laughter] do?
[9:51] >> I don't see it.
[9:53] >> Uh let's see. Let's see what Let's see
[9:55] what other folks on the team have done.
[9:56] Um
[9:57] >> Oh, this is this is the from from the
[9:58] team. Nice. Just that was advocated.
[10:00] >> Yeah, these are work with so these are
[10:02] from folks on the team. Yeah. Um
[10:04] >> Is there like a Sam review recipe or
[10:06] like what would Sam think or or Chris
[10:08] think?
[10:10] Oh, it's more like brainstorming product
[10:11] ideas. Got it.
[10:13] >> Yeah.
[10:13] >> Very interesting.
[10:14] >> is funny. This is This is pretty
[10:15] accurate.
[10:16] >> [laughter]
[10:18] >> It's a simple [snorts] suggestion we can
[10:19] share. How do you measure it's working?
[10:21] What's the two way to do it?
[10:23] >> Yeah. Nice.
[10:24] >> Nice. Yeah, yeah. You got it.
[10:25] >> You got to open source this.
[10:27] >> Yeah, you got to open source this.
[10:28] >> Yeah, yeah.
[10:30] >> Got it.
[10:31] Um
[10:32] But what do you think about like okay,
[10:33] so Granola is for like it's really good
[10:35] for me to be a little bit more
[10:37] self-aware about like how I show up in
[10:38] meetings and stuff, right?
[10:40] But like how do you think about like for
[10:41] the team? Like like you know, like like
[10:43] I guess it's just kind of like privacy
[10:44] issue, but like
[10:46] like how how do I know like how like if
[10:48] you and I were on a team and we have a
[10:49] bunch of meetings together or or like
[10:51] you have meetings with other people,
[10:52] like how do I know how Sam op- operates
[10:54] or or maybe like I'm your report and you
[10:56] want to know how I show up in meetings.
[10:59] Is there like an opportunity there?
[11:01] Or something?
[11:01] >> Yeah.
[11:02] >> Yeah, there's um we obviously like I
[11:04] think one of the one of the like
[11:06] surprisingly hard things about Granola
[11:07] is like preserving your privacy at every
[11:10] at every moment. So like um yeah, in the
[11:12] appropriate way. So like Granola
[11:13] definitely can't like go and look into
[11:15] the meetings of my reports and tell me
[11:18] what's going on in them, you know, like
[11:19] how they should be.
[11:20] >> Yeah, that would not be good. Yeah.
[11:22] >> But but I mean I mean not all the
[11:24] private ones at least, but like um
[11:26] you definitely can ask stuff like that
[11:28] of like um the more you know, anything
[11:29] that's been shared. Like we have this um
[11:32] Yeah, we have like we have like our team
[11:33] space and there are
[11:35] I won't open any, but there's like tons
[11:36] and tons of folders in here um of people
[11:39] pouring team notes into here. Um
[11:42] you can see stand-ups, you can
[11:44] uh this is like sales calls and
[11:45] >> so so there's like a team so there's
[11:47] like a de- design notes channel and then
[11:49] people proactively share stuff in here
[11:51] and then and you can look stuff up. Is
[11:53] that kind of
[11:53] >> Yeah, yeah. So, I this one isn't used
[11:55] very much. I guess it's like design crit
[11:57] podcast thing.
[11:58] Uh design team weekly.
[12:00] Um
[12:01] Like, the sales folder has many, many
[12:04] calls a day.
[12:05] Uh yeah.
[12:05] >> Okay, yeah. I can believe it's that.
[12:06] Yeah.
[12:07] >> Yeah.
[12:08] >> Mhm.
[12:08] >> And uh yeah, this I mean this this I use
[12:10] a lot. Like,
[12:11] usually you don't you actually don't
[12:13] really need to go to this folder.
[12:14] Whoever is good at the chat can just
[12:15] access all of it, but um
[12:16] >> Yeah.
[12:17] >> I go to like
[12:20] uh
[12:21] >> Be- Be- Be- because the sales is
[12:22] actually the customer conversations,
[12:23] right? So, you can look for like
[12:24] insights and trends and stuff.
[12:26] >> Yeah, exactly. Yeah, you know like what
[12:28] that's things uh customers
[12:31] say.
[12:34] Um
[12:35] >> Yeah.
[12:36] >> This is going to look across like Yeah,
[12:37] not just my meetings, but across
[12:39] everything that the team you know the
[12:40] team's been having recently.
[12:42] >> Okay, got it.
[12:43] And and and is there a way to or maybe
[12:45] this is coming like at some point like
[12:46] is there a way to set up au- automations
[12:48] so that like you know it does the search
[12:49] every Monday
[12:51] or or something?
[12:51] >> Uh
[12:52] we Yeah, we um
[12:55] I hope so soon. Like, we've prototyped a
[12:56] lot of these things. Um yeah.
[12:58] Uh I think
[12:59] it would be easy for us to do average-ly
[13:02] and like I think quite hard to do to
[13:03] develop. Like, our summary is so far
[13:05] like um just in
[13:06] >> Yeah.
[13:07] >> being able to get out of the box, making
[13:09] the quality of the output very good. Um
[13:11] So, yeah. I would I definitely think
[13:13] we'll we'll get there.
[13:14] We'll get there at some point someday.
[13:15] Yeah. We have um
[13:17] >> Okay.
[13:17] >> Uh because of the API and the MCP I like
[13:20] we have a bunch of users right now using
[13:21] those to create
[13:23] you know like a weekly report of uh
[13:26] uh things like this.
[13:28] Um,
[13:28] >> Yeah. Yeah, I do it for myself actually.
[13:30] I have a I I just go to Granola MCP and
[13:32] then it it's it gets the information
[13:34] from Granola but also from my other
[13:36] sources and it sends me like a email
[13:37] summary of what's going on. Yeah.
[13:39] >> Nice.
[13:39] >> Yeah, super helpful.
[13:40] >> Right.
[13:40] >> Yeah.
[13:41] >> Yeah. Yeah. Uh, like I lots of other
[13:44] people use the MCP and uh,
[13:46] I think like a a bunch of our other
[13:48] members probably just be like figure
[13:50] out, you know, what are people using MCP
[13:52] for the most and productize it back into
[13:54] the app.
[13:54] >> I have a
[13:55] I I actually have a question for you as
[13:56] a designer. Like um,
[13:58] cuz like people are just like using
[13:59] these like people are just getting their
[14:01] agents to use these products, right?
[14:02] Like just use the MCP or use the API.
[14:04] And then and then and then how do you
[14:06] think of that? So then maybe your
[14:08] beautiful UI won't even be shown to
[14:09] people. Like
[14:10] >> [laughter]
[14:11] >> How do you think of that? You know, like
[14:12] as a designer, like do you design APIs
[14:15] instead? Or
[14:16] >> There's definitely a There's a pang of
[14:18] sadness in there.
[14:19] In the UI designer uh, part of me when
[14:22] when I think about that for sure. Yeah.
[14:23] Yeah. I I like
[14:25] We honestly I think because of that
[14:26] reason we fought it for a while. Like we
[14:28] um, we were kind of like no, we we
[14:29] really need to keep everybody in the
[14:31] Granola UI for everything.
[14:33] I think um, it's been really uh, it's
[14:35] been really interesting working with
[14:37] bigger and bigger enterprise customers
[14:39] um, because I think just as soon as you
[14:41] become a big enough company you have
[14:43] it's inevitable you have all of this
[14:44] internal tooling and you if Granola
[14:47] doesn't play nice with that internal
[14:49] tooling, like you kind of you're a
[14:50] non-starter. Like companies like
[14:52] and uh, yeah, I think you know, I think
[14:54] we basically just like I think at this
[14:56] point we're at peace with the fact that
[14:57] like
[14:58] for a bunch of work for best way to use
[15:00] Granola is it to
[15:02] use it to ingest the context, you know,
[15:04] and use it during the meetings but then
[15:06] it's like powering workflows off in all
[15:08] kinds of other apps because it's
[15:09] connected to your internal agent or Ford
[15:11] or ChatGPT or whatever.
[15:12] >> Yeah, exactly. Yeah. I mean there's
[15:14] always going to be like more normal
[15:16] users who just use the UI, right? But
[15:17] like for for even as a solopreneur for
[15:19] me like Granola has super useful context
[15:22] but I have a bunch of contacts in Google
[15:23] Docs and other sources." So, like, the
[15:25] power is combining all that stuff
[15:26] together. Like, helping the AI
[15:27] understand everything.
[15:29] >> Yeah. Yeah. Yeah, it is. It is. Like,
[15:31] as it's um it's as
[15:34] as the context you give it, right? And
[15:35] the amount of connections and stuff you
[15:36] have. Um yeah. Yeah, I'm excited to do a
[15:38] little more of that. Like, with the
[15:40] pre-meeting briefs was great for us
[15:41] because it um I guess it it forced us to
[15:43] build a bunch of infrastructure under
[15:45] the hood to make Gronela good at sifting
[15:47] through emails to find the right thing.
[15:49] Um and uh yeah, I don't I don't know if
[15:51] that's been built in a similar way so
[15:52] that we can make that work for other
[15:54] other tools, too. You know, Slack and
[15:55] and CRMs and everywhere else a company
[15:59] has like a a world of knowledge that we
[16:00] could be looking at.
[16:02] >> Yeah, dude, there's so much opportunity,
[16:03] man. Like, you you can do like a weekly
[16:05] brief, like weekly [snorts] meeting
[16:06] brief, or like you can do like a
[16:08] post-meeting inside brief. There's so
[16:09] much. You can do so much briefs.
[16:11] >> [laughter]
[16:12] >> It'll be amazing.
[16:15] >> The briefs is kind of like the um it's
[16:16] like the obvious first use case or
[16:17] whatever, you know? So, I feel like
[16:18] there's there's a there's a risk of us
[16:20] If you're the kind of person that's
[16:21] going to try out the AI tools that then
[16:22] you can write just draft briefs
[16:24] from everybody left, right, and center.
[16:26] Yeah, yeah.
[16:27] That's not a a regular person's problem.
[16:29] Like, yeah, I think
[16:31] >> But, before we move on the product,
[16:32] like, you you know what would be the
[16:33] ultimate feature? The ultimate feature
[16:35] request from me. You know
[16:36] >> [laughter]
[16:37] >> The ultimate feature request from me is
[16:38] like uh this is probably bad, but like,
[16:40] you know, you and I just make our own
[16:42] like I have a Peter agent and you have a
[16:44] Sammy agent, and then we we go send our
[16:46] agents we go send our agents to have a
[16:47] meeting first to align, and if they
[16:49] can't align, then we come in.
[16:51] >> [laughter]
[16:52] >> That'd be the ultimate feature to do.
[16:53] >> I feel like people are having a major
[16:54] thing a lot. Like, um CEOs we get a lot
[16:56] of like CEOs asking for that kind of
[16:58] thing. Like, you know, can you can you
[16:59] make Gronela be my first line of defense
[17:01] from all the questions I [laughter] get?
[17:04] Yeah, yeah.
[17:05] >> [clears throat]
[17:05] >> I think it's a it's a good idea. Yeah.
[17:07] Yeah.
[17:07] >> Yeah, there's there's something there.
[17:08] Yeah.
[17:09] >> [snorts]
[17:09] >> All right. Well, I mean, now let's let's
[17:11] let's kind of switch switch gears and
[17:13] talk about kind of like how you guys
[17:14] work internally.
[17:15] >> Yeah. I'm kind of like a little bit
[17:16] pessimistic about like this whole AI
[17:18] cycle of thing. Like it feels like a lot
[17:19] of the AI native companies are just
[17:21] like, you know, working 996 and just
[17:22] like
[17:23] >> [laughter]
[17:24] >> working non-stop, dude. And I feel like
[17:25] as a parent, like do I really want that?
[17:28] Uh but like I I I think Granola, maybe
[17:30] you guys have a different philosophy
[17:32] on how this stuff works.
[17:33] >> Yeah.
[17:33] >> Yeah.
[17:34] >> I think on that front I really enjoy
[17:35] being a Londoner, honestly. Like I think
[17:37] um the team works a lot and and very
[17:39] hard. I mean, they pour a lot of
[17:40] themselves into it. But I think I don't
[17:41] know. I
[17:42] I think you should all you should have a
[17:43] life outside of work and you should like
[17:45] you should this just this just so much
[17:46] more to life than than than writing code
[17:49] or writing software. And then I don't
[17:50] know. I think it's so important. Like I
[17:52] think you the work you do is better when
[17:53] you have some balance.
[17:55] >> Mhm.
[17:55] >> Working hard though. Like I feel like
[17:56] that I'm I'm fully like addicted to the
[17:58] slot machine of the coding agents. You
[18:01] know, the
[18:02] I'm like every every night I'm on my
[18:04] laptop like, "Oh, one more problem. One
[18:06] more problem. One more problem. One more
[18:07] problem." So
[18:08] Yeah.
[18:08] >> Yeah.
[18:09] >> Yeah.
[18:09] >> Yeah, it's it's actually it's actually
[18:10] cuz we talk about like Granola helping
[18:12] with context switching with me meetings,
[18:13] but like actually context switching
[18:14] between the different agent threads is
[18:16] even harder. Like you literally context
[18:18] switch like every 5 minutes.
[18:19] >> [laughter]
[18:19] >> Yeah.
[18:20] >> Yeah.
[18:20] >> Yeah.
[18:21] >> So
[18:22] >> Yeah.
[18:22] >> Yeah.
[18:22] >> Yeah.
[18:23] >> It gets pretty exhausting.
[18:24] >> It's like it's the thing we're grappling
[18:26] with at the moment, I think, is like
[18:27] with designing Granola cuz we we want to
[18:29] help Granola be better for you like
[18:31] outside of meetings for
[18:33] and um
[18:34] the stuff you can use chat for is like a
[18:36] little hint of that, but I think there's
[18:37] a lot more we could do with especially
[18:38] like um when you need to follow work
[18:41] around meetings.
[18:42] Um
[18:43] once Granola is connected to a couple of
[18:44] tools,
[18:45] but really I think there is like if you
[18:47] have like three things that come out of
[18:49] an average meeting that you might need
[18:50] to go away and do or think about and
[18:51] then you have five meetings during the
[18:53] day, it very very quickly becomes a big
[18:55] big stack of things to do.
[18:56] >> Yeah.
[18:56] >> And uh how you like present that to the
[18:59] user or like how Granola can help you
[19:00] get through that stack of things in a
[19:02] way that feels like uh it makes your
[19:03] life nicer and better and and more
[19:06] calming rather than just like adding
[19:08] stress to like uh pressure and more more
[19:11] and more to do on top of you is like a
[19:13] hard thing to figure out.
[19:15] >> Uh yeah, yeah, yeah, that's that's
[19:17] that's right. Cuz yeah, if if you guys
[19:19] if Granola has like three takeaways from
[19:20] each meeting, but at the end of day
[19:22] there'll be like 20 takeaways.
[19:24] It would be too much.
[19:25] Yeah. It would be too interesting.
[19:27] >> We want to be a calming presence in your
[19:28] life, not not the opposite.
[19:30] >> Um and and and like how how do you guys
[19:32] cuz I I feel like nowadays like any
[19:33] engineer can just start shipping like
[19:35] the the shipping stuff is not hard
[19:37] anymore. It's easier than before.
[19:39] Uh so in some ways like almost everyone
[19:40] in the company can ship basically. And
[19:42] and like now like you know as a designer
[19:43] how how do you make the craft and
[19:45] quality still good? Like it doesn't like
[19:47] >> [laughter]
[19:47] >> how do you avoid just like a bunch of
[19:48] slop going to prod all all the time?
[19:50] Yeah.
[19:51] >> Yeah, it's uh it's hard like cuz there's
[19:54] a lot of benefit to letting
[19:55] uh like everybody in Granola is like
[19:57] writing code shipping code in one way or
[19:59] another. Like a lot of it's for internal
[20:01] tooling not not into production, but a
[20:03] surprising amount is in production as
[20:05] well. And um
[20:06] there's like some power in having
[20:08] anybody be able to go and do that. Uh
[20:10] and I want to encourage that and not
[20:11] make design like a bottleneck for that.
[20:14] Yeah, we like I guess um some things I
[20:16] think we've done that I think really
[20:18] helped there that um with the rebrand
[20:21] that we did in in February, we did a
[20:23] bunch of work to
[20:25] overhaul the look and feel of the app,
[20:26] make it feel in line with the brand, but
[20:28] in doing that we also
[20:30] built that out on a new design system.
[20:32] And so there like everything behind the
[20:33] scenes is tokens and components and uh
[20:36] yeah, it's all it's all reusable. Not
[20:38] just the human, but for agents to do it
[20:39] as in B files all over the place to
[20:41] teach the agent how to use the design
[20:43] system. That's I mean that's helped a
[20:44] lot for like stuff that's not super like
[20:46] design heavy or doesn't need thinking
[20:48] about super hard. Like it usually comes
[20:49] out looking decent.
[20:50] >> Uh okay.
[20:52] >> Okay, just from the agent writing the
[20:53] code. A lot of the I don't know, for
[20:55] building enterprise features in the
[20:56] settings menu like you can just ask
[20:59] Granola to you can just ask the coding
[21:01] agent to um
[21:02] you know, add a add a new page in
[21:03] settings that does X Y and Z and when
[21:05] this toggle's turned off this then and
[21:08] uh
[21:08] does all the right things like comes out
[21:09] with the right
[21:10] >> It was the components.
[21:11] >> Yeah.
[21:11] >> Got it.
[21:12] >> Yeah. Yeah. Yeah, for the designers, I
[21:14] don't know. I feel like they're It's an
[21:16] interesting time. I feel like
[21:18] in real Figma had like a complete hold
[21:19] on the whole design industry, you know,
[21:21] for good reasons like it's just a great
[21:23] tool. Um
[21:24] I I don't know. Even for us, 80% of my
[21:27] day was spent in Figma both like
[21:29] catching ideas, iterating on different
[21:31] approaches, and also like refining and
[21:33] handing off designs. And I feel like
[21:35] that's just all been thrown apart like
[21:36] in the last year or something. And it's
[21:38] honestly now like a I don't know all the
[21:40] designers use all kinds of different
[21:42] tools all day long. Like Like um we're
[21:44] an in-person company. We do a lot of
[21:45] like initial thinking on whiteboards
[21:47] together in rooms. I mean sometimes like
[21:48] a whiteboard sketch is enough now to
[21:50] give to an engineer and they're able to
[21:52] like cuz like the coding engine can
[21:54] with the design system go and do the
[21:56] thing. You know, like do the right
[21:57] thing.
[21:57] >> Yeah.
[21:57] >> Yeah, and then and then I don't know
[21:59] like
[21:59] I have I have an example actually. We
[22:00] have like some some mocks and stuff
[22:02] premium briefs I could talk you through.
[22:05] >> Yeah. I mean I mean how how how much do
[22:06] you use Figma now? Is like 10% or you
[22:08] just don't use it anymore?
[22:09] >> Uh
[22:10] 20% maybe yeah, something like that.
[22:13] It varies. Like I I some designers on
[22:15] the team will be a lot more than that
[22:16] and I think it depends on the project
[22:18] too. Like when
[22:19] when Tanya was working on the a paywall,
[22:23] you know, like subscription flows and
[22:25] upselling you to the the business tier
[22:28] and stuff like that. That's all like all
[22:29] of the hard design stuff there is like
[22:31] does this flow
[22:32] make sense and does the copywriting
[22:35] ideas in your head at the right moments?
[22:36] And it's far faster to iterate on that
[22:38] by just looking at it all in Canvas and
[22:41] it's not
[22:42] it's not heavy on like interaction
[22:44] detail or like you know, there's not too
[22:46] many states to have to worry about. It's
[22:47] just like a linear flow with copywriting
[22:49] being the hard thing. Um whereas premium
[22:51] and briefs example is much more
[22:53] interactive and
[22:55] integrated in the core flow. And so it
[22:56] was a lot less Figma and a lot more
[22:58] prototyping in
[22:59] in code for for premium and briefs for
[23:01] example.
[23:02] >> Yeah, makes sense cuz it's just a couple
[23:03] bullet points, right? You got to make
[23:03] sure the bullet points are actually
[23:04] good. Yeah, so.
[23:05] >> Yeah, yeah. And it's like where do you
[23:06] where do you show them in the app and um
[23:08] Yeah, so like this was a this was one of
[23:10] Tanya's early prototyping um
[23:14] explorations. Like I think we basically
[23:16] went from like chatting about where the
[23:18] where the brief could live in a room on
[23:20] a whiteboard or something to this to to
[23:22] her kind of like mocking this up. So
[23:24] this was like
[23:26] what if it's in the notification and uh
[23:29] this, you know, like
[23:30] >> Okay, got it.
[23:31] >> from here. You can ask Cursor to be
[23:33] like, "Hey, I want to I have this brief
[23:35] to test these texts. Um can you go like
[23:38] put this in the notification that
[23:40] appears in the top right of the screen
[23:41] before a meeting?" And can you also
[23:42] please go and put it in the bottom of
[23:44] the screen? Can you also go put it in
[23:45] the floating transcription indicator on
[23:47] the side of the screen? Do all three of
[23:48] those things now, you know? And you get
[23:50] like um instantly
[23:52] get so much more signal on like is this
[23:53] going to feel good or not?
[23:54] >> Yeah, got it.
[23:55] >> And then, you know, like [clears throat]
[23:56] uh I this this pro this whole project
[23:58] like flip-flopped between prototypes
[23:59] like this and then back into Figma and
[24:02] then prototypes again, back into Figma.
[24:03] Yeah, it was really uh not at all
[24:06] linear.
[24:07] And that's more and more okay now.
[24:08] >> Yeah, cuz you want to I guess you want
[24:10] to get as close to the actual end user
[24:11] experience as possible, right? So like
[24:13] this is more it feels more interactive
[24:15] than like static mocks.
[24:16] >> Yeah.
[24:17] Yeah, exactly. And and I think like
[24:19] especially with um uh
[24:22] Well, let's see if I go back to mine to
[24:24] us, for example. Um like with something
[24:26] like this, you know, it's it's pretty
[24:27] simple. It's just it's just a bunch of
[24:28] text. Uh and
[24:30] there's there's a bunch of nuance in
[24:32] like
[24:33] how loud you make it and where do you
[24:34] put it on the screen and whatever, but
[24:36] really the thing you're designing for is
[24:37] like how does it feel when you're
[24:40] stressed and you're late and you're
[24:41] arriving to this meeting and you've
[24:43] forgotten who the person is to to like
[24:45] receive these words in this in this way.
[24:47] And um
[24:49] it's very hard to get a realistic
[24:51] feeling of that from looking at a
[24:52] mock-up of like somebody else's brief,
[24:54] you know, or like a made-up brief. Like
[24:56] it really it really matters that it's
[24:57] your data and that it's your stuff
[25:00] you're looking at to make a judgment
[25:01] call on whether it works or not.
[25:02] >> Yeah, that that that makes a lot of
[25:04] sense. Yeah. Yeah. Yeah, and and also
[25:06] like how how how good the brief is also
[25:08] matters, right? It's not just about the
[25:09] UI. It's like how how good is the brief.
[25:10] >> Yeah.
[25:11] >> Yeah. Yeah, exactly. Yeah. Yeah.
[25:13] Yeah.
[25:13] >> Do Do you guys like like another way I
[25:15] found to just like still let people ship
[25:17] but still have higher quality is like,
[25:19] you know, just like a ton of dog
[25:21] food internally and like, you know,
[25:22] showing to beta users and getting their
[25:24] feedback before you do GA the product,
[25:26] right? Like I I I assume you guys do
[25:27] that, too. Yeah.
[25:28] >> Yeah. Yeah. Yeah. Yeah, we do. We we
[25:30] really like try and push to get like
[25:32] when a project starts to get like a
[25:33] shitty end-to-end working version of it
[25:35] in the app as quickly as possible. Um
[25:37] yeah, like we had brief we had a version
[25:40] of this brief in the app within like a
[25:42] within a week a week and a half of of um
[25:45] starting the project.
[25:46] >> Nice.
[25:47] >> and it was incredibly ugly. Like it was
[25:49] just in a big box at the top of the
[25:51] notes and um
[25:53] >> Yeah.
[25:53] >> you know, the beta wasn't good and the
[25:54] the yeah, it wasn't well written. But
[25:56] like I I think you you want people to be
[25:58] feeling the pain of this thing not being
[26:00] good like day in day out. It's a very
[26:02] It's a very effective way of like of you
[26:04] know, making you give a about about
[26:06] being good.
[26:06] >> Yeah, you probably have a bunch of like
[26:07] internal Slack channels giving feedback
[26:09] and stuff like that, right? It's like
[26:10] yeah.
[26:10] >> Yeah. Yeah. Yeah. Yeah, it's Yeah.
[26:13] >> [laughter]
[26:14] >> Um
[26:16] cool. Well, I mean, uh I I I guess maybe
[26:17] you can show us one more thing. Like I'm
[26:19] um you know, like uh Cloud Launch Tags
[26:22] recently and people are saying like, oh,
[26:23] you know, moving from the IDE to like
[26:25] the app and now we're moving to just
[26:26] like people giving commands to agents in
[26:28] Slack.
[26:29] And um and like I I think you guys have
[26:31] a bunch of internal agents, right? Like
[26:32] there's like um
[26:34] >> Yeah.
[26:34] >> Na- Na- natural or something or like
[26:36] Honeybot. [snorts]
[26:37] Yeah. Can you show us some of this?
[26:39] >> Yeah. Yeah. Um
[26:41] So,
[26:43] uh
[26:44] yeah, natural So, we have this whole
[26:46] like internal dashboard thing. Um so,
[26:49] this is
[26:50] like all kinds of um features people go.
[26:54] That's for all internal tools
[26:56] all kinds of things. This is I'm I'm I'm
[26:59] like really I'm really proud of
[27:01] this. So, like I think it's
[27:04] everyone on the team is adding stuff in
[27:06] here and building it. And you can see
[27:07] like we have this little edit with
[27:09] cursor data like you can
[27:12] turn this on and I'm like
[27:14] make this red.
[27:16] It like you can basically like point and
[27:19] click be like hey, I need to change the
[27:20] internal tool to go do this thing for
[27:22] me.
[27:23] >> Oh nice. Okay.
[27:24] >> You got to get the spinner up cursor
[27:25] agent to go do it. So, we really tried
[27:26] to like like a bunch of people have put
[27:28] in work to lower the bar to making
[27:30] internal tools. Yeah. Natural is like I
[27:32] think by far and away the most used
[27:33] internal tool thingy we have. Um It's a
[27:37] it's a chatbot here
[27:39] and it's highly up with like connected
[27:41] to
[27:42] as many things as we can give it like
[27:45] Slack, granola, amplitude, all of our
[27:47] logs.
[27:48] >> Okay.
[27:49] >> website [snorts]
[27:50] analytics like as many things as we can
[27:51] as many things as we can. And then
[27:53] people use it. I guess you can use it
[27:55] here. It's it's mostly used in Slack.
[27:57] I'll show some examples that hopefully
[27:58] safe to share like look at the code,
[28:00] figure out how the code works, give a
[28:02] smart answer. Yeah, you know, and then
[28:04] like okay. This this takes so long to go
[28:06] actually takes them to do it yourself.
[28:07] It's like often So, this was a minor I
[28:10] think summary generation had a little
[28:12] dip for a second or something like a
[28:13] minor incident and
[28:16] yeah, so we have like video into the
[28:17] natural channels starts out.
[28:19] Tells me also what's going on. So, this
[28:21] is like what's it doing? This is
[28:24] looking at logs I think to figure out
[28:26] you know, where are these errors popping
[28:27] up? What's going on there? It's then
[28:29] able to then go like sense check that
[28:30] against the code and figure out like why
[28:32] would that error be happening?
[28:33] >> I see.
[28:34] >> Yeah, like this this
[28:37] natural basically gets brought into
[28:38] every like every question that pops up
[28:40] is how many states uh
[28:41] as the first protocol. And
[28:44] yeah, I don't know. We're really
[28:45] extremely mad at this point.
[28:47] >> But [snorts] basically you just linked
[28:49] it up to multiple internal company
[28:50] sources and has a you you can it sounds
[28:52] like it can pick the model they want to
[28:53] use, but then like it it kind of does
[28:55] the first pass response, right? And then
[28:56] you can talk to it properly.
[28:57] >> Yeah. Yeah. Yeah. And then you know,
[28:59] it's it can it's it's really reliable at
[29:01] SQL queries and things like that. So it
[29:02] can pretty Yeah, you can pull data in
[29:04] and it's going to be cheap like just
[29:06] just way way faster than a human being
[29:07] your dashboards would be able to.
[29:09] >> Yeah. And and do you have like some guy
[29:11] or some person work working on that? So
[29:12] like a internal tools team or something?
[29:15] >> Nobody owns it. Like I like um uh JK JK
[29:18] one of our engineers I think started it
[29:20] as a weekend or an evening project. Um
[29:23] >> Yeah.
[29:24] >> And no, people just add things here and
[29:26] there to it like a um yeah, someone
[29:29] like Nacho was incredibly popular and so
[29:31] if you make Nacho better, you'll be
[29:32] everybody's best friend.
[29:34] So uh there's a strong incentive to
[29:37] to
[29:38] you know, if you if you've got 10
[29:39] minutes to try and figure out a way to
[29:41] make Nacho more powerful for everybody.
[29:42] >> Yeah, I I I feel like this is the right
[29:43] way to do things, man, cuz I I feel like
[29:45] um like I guess you can also just bring
[29:47] Claude or you know, like Cursor in here
[29:49] too, but like I I feel like companies
[29:50] should just build their own internal
[29:51] thing for that. It's not too hard to
[29:52] build, I feel like and like you have
[29:54] more flexibility. Like if if if
[29:55] someone's model becomes better or like
[29:57] the price gets too high or something,
[29:58] you can just switch, right?
[30:01] Yeah, it's like a snake.
[30:01] >> And it's I mean we have um we have I
[30:03] think Nacho can create Cursor
[30:06] agents. So like it will often, you know,
[30:08] like in an doing an investigation will
[30:10] often lead into a PR being written to
[30:13] fix the thing. And I think that's just a
[30:14] great way to do lessons we added Cursor
[30:16] and made that not two tool two different
[30:17] tools. Yeah.
[30:18] >> So I guess uh like I I guess just to
[30:20] recap like, you know, how to be AI
[30:21] native and and still give people a life
[30:23] is is like
[30:24] >> [laughter]
[30:25] >> it's kind of like anyone can build, but
[30:26] you have like design system and
[30:28] components to make sure that at least
[30:29] the the UI is like looks good like from
[30:31] any engineer and then also having a
[30:33] bunch of internal agents that's hooked
[30:34] up to internal systems for people to ask
[30:36] questions, right? That that that's kind
[30:37] of
[30:38] >> Yeah, I think so. Yeah. Yeah. And then
[30:40] uh
[30:40] yeah. Yeah, don't don't I don't know
[30:43] and trust people to use their time as
[30:45] they as you know like as they as they
[30:47] wish. Like uh
[30:48] >> Yeah. I mean yeah
[30:50] like you know you're not trying to
[30:51] you're not trying to make sure people
[30:52] are working like you know 8 hours a week
[30:53] or like a day or something. You're just
[30:54] trying to see the output, right?
[30:56] You look at the output.
[30:57] >> Yeah. Yeah.
[30:57] >> Yeah.
[30:58] >> Yeah. Yeah, I really think like
[30:59] especially maybe now like more than more
[31:02] than in the old days like it's so easy
[31:03] to make stuff. You know, it's a cliche
[31:04] now but like it's so easy to make stuff.
[31:07] The hot thing is knowing what to make
[31:08] and like that kind of thinking comes
[31:10] from like doesn't come from just like
[31:12] grinding as hard as you can the whole
[31:13] time. Like the the real interesting
[31:15] stuff comes from I don't know going for
[31:17] a walk or taking your time off or or
[31:19] um
[31:20] you know space to go and think about
[31:21] something. So
[31:23] Yeah.
[31:24] >> That that part is still very human dude
[31:25] because I I I
[31:26] try to brainstorm like what to make with
[31:28] like you know code codex or something
[31:29] and then
[31:31] like the AI is still too agreeable, man.
[31:32] It is like you know, here's some ideas
[31:34] and like this is a great this is a great
[31:35] idea. Is it are you sure it's a great
[31:36] idea? No, it's not a great idea. It is
[31:38] like it's not the same as talking to a
[31:39] human.
[31:40] >> Yeah.
[31:40] >> Yeah, not the same.
[31:41] >> Yeah. Yeah. Yeah.
[31:42] >> Well, well Sam this is this is a
[31:43] pleasure man. Do do you have any like
[31:45] closing words of advice for AI builders
[31:47] or people trying to build just like AI
[31:48] tools or companies? I guess it is about
[31:50] like trying to figure out what you want
[31:51] to build and maybe
[31:53] >> I think I think the I mean yeah, the the
[31:54] thing I the thing I really like
[31:56] appreciate about what we have here which
[31:58] I mostly credit Chris my co-founder with
[31:59] instilling in me and in everyone else in
[32:01] the company is like it's it's just you
[32:04] know, it's so easy to build things
[32:05] nowadays. Like one you got to build
[32:06] something interesting. You know, a lot
[32:07] of
[32:08] I think figuring out what's going to be
[32:09] the interesting thing. But two like most
[32:11] people stop way too early I think when
[32:13] in building stuff. Like they you know,
[32:15] they get to the version one and they
[32:16] have push it out the door and ship it
[32:18] and I think the easier it gets to build
[32:20] stuff the more it matters to like really
[32:22] sweat the details and go the extra mile
[32:23] to make something that's actually going
[32:24] to be really useful to somebody. To hold
[32:26] yourself accountable not just to
[32:27] shipping something but to like does the
[32:29] person actually get like daily value out
[32:32] of it? Um
[32:33] and to not stop until you achieve that
[32:35] that goal rather than just the shipping
[32:37] goal.
[32:37] >> I I see. Yeah, yeah, yeah. Cuz you you
[32:39] want to ship some stuff to get some
[32:41] market feedback. You don't want to just
[32:42] like plan it forever, right? You want to
[32:44] ship.
[32:45] >> Yeah, I know, yeah.
[32:47] We encourage to like ship We ship stuff
[32:48] internally like as quickly as we can,
[32:50] but um we, you know, and and to like
[32:52] small groups of friends and beta users
[32:53] and things like that very very early,
[32:54] but we do like I think we pull the like
[32:57] a a very high bar for like is this thing
[32:59] actually working for people, you know,
[33:00] before we put stuff out often.
[33:01] >> Got it. Well, well,
[33:03] add me to the janky and the mobile
[33:05] builds, man. I I I I think the problem
[33:06] is it's too polished right now. Add me
[33:07] to the janky and the mobile builds.
[33:08] Yeah. We're not in the builds. Yeah.
[33:09] >> [laughter]
[33:10] >> Yeah, I know.
[33:10] >> Yeah.
[33:11] >> It's really fun. Yeah. Yeah.
[33:12] >> Cool. Thanks so much, man. I I feel like
[33:14] I learned a lot from this chat. Thanks.
[33:15] >> This is really fun. Thanks. Thanks a lot
[33:17] for doing it.