The AI Tutor That Makes Kids Actually Think | E2298

Summary

Jason welcomes back Brilliant CEO and co-founder Sue Khim (five-timer club member) to demo Koji, Brilliant’s new AI tutor that launched the previous week and immediately went viral. Sue walks through how Koji uses the Socratic Method rather than just delivering answers — the LLM operates within tight constraints while Brilliant’s deterministic pedagogy (years of curriculum work since GPT-2) does the heavy lifting. The conversation covers Brilliant’s evolution from AllTuition (a student-loan startup pitched at TechCrunch 50/Launch a decade ago) to a consumer education product, why they price against tutors ($10K/year) rather than apps, and why Sue says people aren’t anti-AI, they’re “anti-being-replaced and anti-slop.”

The second half is Jason’s monologue on the viral wave of “VCs behaving badly” stories trending on X — Greg Isenberg’s pitch where a GP fell asleep, Travis Kalanick’s tale of a VC trying to escape his own meeting, Matthew Prince’s stories. Jason responds with two of his own: John Doerr making it to a meeting straight from the ER after flipping his bicycle (still the greatest compliment of Jason’s career), and a Mohr Davidow partner who flew Jason up from LA at 5 AM only to bail with a pre-decided “no” in the lobby. Jason uses both to lay out his Launch firm’s countermeasures: NPS-scored first meetings, a 20-minute structure, “may I repeat your vision back to you?”, and founder feedback tomatoes.

Highlights

”Why is this so cheap?” — Pricing Against Tutors, Not Apps

“We don’t benchmark to games. I think that it’s very telling that the main pricing question from our customers is not ‘why is this so expensive?’, it’s ‘why is this so cheap?’ We are benchmarked to tutors. And people understand a tutor for a kid is $10,000 a year.” — Sue Khim, 21:10

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Frontier Models Haven’t Gotten Better At Tutoring Since O1

“Brilliant’s fairly model-agnostic. And the thing that we have versus frontier models is frontier models don’t have verifiable reward signals for tutoring, and we do. If you look at frontier models — and we benchmark this very carefully — their ability to tutor well hasn’t improved much since like O1.” — Sue Khim, 31:52

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John Doerr Came Straight From the ER to Pitch Jason

“He was out biking this morning, he flipped his bike in Woodside, went flying over the handlebars, went to the emergency room, came directly here from the emergency room… Let that sink in. John fucking Doerr flipped his bicycle, dipshit Jason Calacanis with one or two wins under his belt is at the office, easy ability to say ‘I’m not going to make the meeting.’ He made the meeting.” — Jason Calacanis, 49:41

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Mohr Davidow Bailed in the Lobby After Flying Jason Up

“I said, ‘You realize I got up at 5 in the effing morning for this meeting? I came up from LA. You begged my friend to give you the meeting. You’re telling me you’ve already decided no without pitching me?’ And I said, ‘I’m going to tell everybody this story.’ And I did. For 10 years, this is all I talked about with Mohr Davidow.” — Jason Calacanis, 52:27

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”May I repeat your vision back to you?” — Launch’s First-Meeting Fix

“So what I did was I added to every time I meet with a founder, the final question I ask after they’re done is, ‘May I repeat your vision back to you so that I can make sure I understand it perfectly?’ … That changed everything. And then I made everybody who works for me answer every single first meeting with that.” — Jason Calacanis, 56:35

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Key Points

• Cold open: VCs behaving badly (0:00) - A montage of stories about VCs falling asleep, canceling meetings on flying founders
• AllTuition origin story (3:21) - Three nerdy kids out of Chicago trying to fix private student loans
• Brilliant’s mission (6:20) - “Putting a world-class tutor in every home”
• Why people aren’t anti-AI (7:14) - AI that challenges you, AI as a coach versus AI as a slop generator
• Premium consumer pricing decision (15:08) - Why Brilliant went direct-to-consumer instead of B2B2C
• App Store reviews as gold (17:33) - Multiple humans read every review; parents make extremely detailed feature requests
• Tutoring cost reality (20:22) - $80/session in Middle America, $150-$300 for high-end; aiming for 95% cost reduction
• Koji demo (26:31) - Live walkthrough of the Socratic quadratics tutor
• LLMs in a constrained role (23:11) - Years of deterministic pedagogy work since GPT-2 powers the system
• Verifiable reward signals (31:52) - Why Brilliant’s domain data beats frontier models for tutoring
• Teaching the model methodology (33:04) - Expert teachers instructed the model on which tool calls to make per concept
• International expansion (34:43) - 60% of users outside US; voices are localized employee voices
• The unique dataset (36:29) - Real tutoring sessions at scale with real students
• Why VC has changed (42:39) - From founder-replacement era to founder-friendly era
• Greg Isenberg’s GP-asleep tweet (45:34) - $15M Series A pitch, GP fully out cold for 30+ minutes
• John Doerr emails back the same day (48:13) - How Jason raised from Sequoia and Kleiner with two-sentence emails
• Travis Kalanick’s escape-from-VC story (54:21) - Intercepting a partner trying to flee his own meeting at Red Swoosh
• NPS scoring on first meetings (55:05) - 100+ first meetings/week at Launch, kudos and “founder feedback tomatoes”
• 20-minute structured first meetings (57:07) - 10 min pitch, asks, decision in 24-48 hours

Mentions

Companies

• Brilliant (2:31) - Sue Khim’s consumer education company; just launched Koji
• AllTuition (3:21) - Brilliant’s predecessor; private student loan rate comparison
• Cloudflare (0:04) - Matthew Prince’s VC behavior tweets kicked off the trend
• Sequoia (47:46) - Jason raised early as a Sequoia scout 12 years ago
• Kleiner Perkins (48:13) - John Doerr forwarded Jason’s email, partners meeting that same week
• Mohr Davidow Ventures (50:30) - “I don’t think they even exist anymore” — the VC who bailed in the lobby
• Weblogs Inc. (48:02) - Jason’s company sold to AOL for $30M in 18 months
• Micro1 (36:00) - Launch portfolio company doing LLM training/fine-tuning
• LinkedIn (18:46) - Hiring Pro sponsor read
• Shopify (29:44) - Dropshipping sponsor read
• Plaud (1:03) - Plaud NotePin sponsor read
• Northwest Registered Agent (10:09) - Business formation sponsor read

Products & Technologies

• Koji (24:50) - Brilliant’s new AI tutor, Socratic Method, model-agnostic
• GPT-2 (23:11) - Brilliant has been working on AI-assisted learning since 2019
• O1 (31:52) - Frontier model tutoring quality plateau benchmark
• App Store reviews (17:33) - Brilliant’s #1 source of granular product feedback
• GLP-1s (14:22) - Jason’s weight loss aside (lost 43 lbs)

People

• Sue Khim (2:31) - CEO/co-founder of Brilliant
• Chamath Palihapitiya (4:36) - Judge at AllTuition’s pitch event; credited with the pivot
• John Doerr (43:55) - Kleiner Perkins partner; the ER-bicycle story
• Michael Moritz (48:13) - Sequoia partner; called Jason within one hour
• Roelof Botha (48:39) - Sequoia partner; partners meeting with Moritz
• Travis Kalanick (54:21) - Uber CEO; the “intercept the VC escaping his office” story
• Matthew Prince (0:04) - Cloudflare CEO whose tweets kicked off the trend
• Greg Isenberg (45:34) - The viral sleeping-GP $15M Series A tweet
• Mark Cuban (50:14) - One of Jason’s three committed investors at the time

Surprising Quotes

“People aren’t anti-AI. They’re anti-being-replaced and anti-slop.” — Sue Khim (paraphrased thesis, 22:21)

“I think that it’s very telling that the main pricing question from our customers is not ‘why is this so expensive?’, it’s ‘why is this so cheap?’” — Sue Khim, 21:10

“Their ability to tutor well hasn’t improved much since like O1.” — Sue Khim, 31:52

“Let that sink in. John fucking Doerr flipped his bicycle, dipshit Jason Calacanis with one or two wins under his belt is at the office, easy ability to say ‘I’m not going to make the meeting.’ He made the meeting.” — Jason Calacanis, 49:41

“For 10 years, this is all I talked about with Mohr Davidow. I would never recommend that firm.” — Jason Calacanis, 53:02

Transcript

Sue Khim: 0:00 A lot of VCs behaving badly stories trending all week.

Jason Calacanis: 0:04 Matthew Prince from Cloudflare I think started this all off.

Lon Harris: 0:12 I keep presenting my series A slides to an unconscious man in a Herman Miller chair.

Jason Calacanis: 0:14 Oh, I was on the other side of the table raising money myself. I’ll give you a couple stories.

Lon Harris: 0:16 This other motherfucker begs a friend of mine to give him the meeting.

Jason Calacanis: 0:19 I’m finding out that the meeting’s been canceled.

Lon Harris: 0:21 That instead of just letting me pitch, you’re so dumb that you would cancel on me when you knew I was flying up from Los Angeles.

Jason Calacanis: 0:29 You’re going to be the worst venture capitalist of all time. Alright everybody, welcome back to TWiST, This Week in Startups, for June 8th, 2026. Got a big docket today, bit in the news, a lot of VCs, uh, behaving badly stories trending all week on Twitter. I’m going to give my reaction at the end of the show. We’re going to have some fun, I’m going to tell some stories. And I can take notes, I can say, hey, action item, catch up with Lon about the launch of this new ‘this week in’ show we’re doing, let’s make a strategy session, blah, blah, blah, ABCD. I do that when… [Plaud NotePin sponsor read]

Jason Calacanis: 2:31 I am so excited to have Sue Khim, the CEO and co-founder of Brilliant, back on the program. She’s been on this program, gosh, she’s got to be in the five-timer club. She’s an incredible founder. I met her originally many, many years ago when she had a different idea.

Sue Khim: 2:57 Hey, Jason. You’re so famous.

Jason Calacanis: 3:00 I know, I was like micro-famous and then now I’m like somewhere between micro and whatever the next level of podcast fame is, but uh, it is true. I go through an airport or I go to a Knicks game and people stop me now.

Sue Khim: 3:12 Yeah, world’s number one podcast.

Jason Calacanis: 3:14 I mean, it’s kind of weird. We’re manifesting here, uh, but you’re on the OG podcast, This Week in Startups. Was it AllTuition? Was that the original name?

Sue Khim: 3:21 Yeah, AllTuition was the original name. Three nerdy kids out of Chicago trying to fix student loans.

Jason Calacanis: 3:27 And that was like 12 years ago, I think. I think I made my first investment as when I was a Sequoia scout, so it’d have to be 12 years ago before I even had a fund. It was a great idea. What was the original idea?

Sue Khim: 3:41 Yeah, so the original idea was a sort of lending tree or bank rate for private student loans. Student loans are the second largest loan that people take out in their lifetimes and there was no way to comparison shop for them. So we took a stab at building one.

Jason Calacanis: 4:36 Yeah, you you found a huge problem, uh, you gave it a shot, you got some level of product-market fit, but you found a better idea. And uh, I remember Chamath was one of the judges, I think, on your panel and uh you wound up in his orbit and he came up with the idea for Brilliant. Tell us a little bit about that pivot.

Sue Khim: 4:58 Yeah, we worked out of that office. I mean, credit to Chamath for for Brilliant becoming what it did. I think that he looked at AllTuition and felt that we were going to end up in the same spot as, you know, a lot of fintech tools at the time. And he sort of pushed us toward, hey, what would you build if you weren’t constrained by what you’re already doing? What would that be? Uh, and then that began the journey of, you know, gracefully helping people manage the loans, but we were already managing on all tuition, but also, you know, starting up a new business.

Jason Calacanis: 6:12 Yeah. And so tell people a little bit about brilliant.org, what the mission is and how it’s evolved over the last decade.

Sue Khim: 6:20 Yeah. So Brilliant is putting a world-class tutor in every home. We launched this product last week. Thank you for helping us amplify it. And, you know, it went incredibly viral.

Jason Calacanis: 7:14 AI that makes you think, that challenges you, the human. AI as a coach, AI as a guide by your side. That AI, people seem to like. Why?

Sue Khim: 7:26 Yeah. Yeah. I think that, you know, everyone’s seen the data, especially American parents see the data that our kids can’t read or do math anymore. AI is making this worse. We are building AI that says, no, you’re going to do this. We’re going to teach you.

Lon Harris: 8:39 It does get painted with one large brush and if it was paper, you’d be like, yeah, some of this paper is really good to, like, write poetry on and, yeah, some of it you can make a flyer, you know, for your business.

Jason Calacanis: 9:00 …write poetry on paper, write a ‘I’m robbing this bank’ on a banknote and you know, rob a bank with it. So yeah, people do paint with a wide brush with it and it’s much more nuanced than that. [Northwest Registered Agent sponsor read]

Lon Harris: 10:09 Okay, so you’ve identified a real problem and you’ve put together a solid solution and a business model that you believe in. So you’re all set to launch your new company, right? Uh, not so fast.

Sue Khim: 11:03 Yeah, totally. And you were saying, you know, you’ve met parents and teachers and people in the wild who use this product. And the real differentiator is that school math, what you’re doing is you’re memorizing formulas. You are learning how to see the structure of problems and, you know, people develop these systems brains, you know, kids can develop these systems brains and that’s what learning math online does.

Jason Calacanis: 13:38 Hmm. Yeah, I’ve learned that. I’ve got three daughters. I have learned that challenging stuff. Uh, I typically do it with a hike in the rain. There’s no bad weather is what I tell my kids. They got GLP-1s. How do I know? Look at me. When Sue met me, I was 40 pounds heavier, 43 to be exact. And now I am svelte. I am back to my running marathon weight. Listen, it might be for you. You should ask your doctor. Visit weight loss with Twist and see if your insurance will cover it. I’m a big fan of being thin and fit.

Lon Harris: 15:08 All right, Sue, when we left you, we were talking a little bit about pricing and who to go after. You went after the consumer and you went with the premium pricing. Tell us about those decisions.

Sue Khim: 15:26 Yeah, I think that we have always at heart wanted to get as close to the metal of solving a problem for the user of the product as we could. And one of the problems with selling to schools is that you have a really long sales cycle and you have to win over administrators.

Lon Harris: 16:43 Yeah, so B2B to C, really big mistake because you distance yourself, you’re putting a B between your business and the consumer.

Jason Calacanis: 16:54 When you have an app in the App Store, you get these like two or three really interesting pieces of granular feedback. Obviously you get like engagement stats, that’s great, they’re very granular, but the App Store reviews are gold.

Sue Khim: 17:33 Yeah, the App Store reviews are gold. We still have multiple humans reading every single App Store review. We, you know, get tons and tons of email from customers, parents, you know, telling us exactly the experience working for my kid. And let me tell you, like parents are very happy to tell us exactly what they want to see in the product. They, you know, make extremely detailed feature requests. We launched this tutor, that positive vision of AI and learning really resonated. And just reinforcing, you know, the cost of tutoring is a huge pain point for students, or for parents.

Lon Harris: 18:46 [LinkedIn Hiring Pro sponsor read]

Jason Calacanis: 19:46 They’ll do anything to help their kids learn. They’ll do anything. And that’s I think the thing we had in earlier discussion. I was like, listen, parents will work an extra shift to pay for a tutor. And I think it’s $150 to $300 per like 90-minute session. We tend to have like two or three of the daughters go to the chess tutor, the math tutor, whatever, music tutor. It’s not cheap. What’s the average?

Sue Khim: 20:22 I think the average tutor, you know, let’s call it 80 bucks in Middle America if you’re not getting a super high-end tutor. But the problem with that is, you know, you need high-dosage tutoring for it to be effective.

Jason Calacanis: 20:44 Yeah, it’s, I mean, I look at it and I’m like, huh, is my tutoring budget exceeding the budget for tuition at, you know, the school? And it’s like, yeah, it is. So that makes pricing easy. You priced it… casual games or, you know, other apps in the App Store that are typically, I think, the going rate is $60 to $100 a year for an app experience.

Sue Khim: 21:09 Oh, yeah. Yeah, we don’t benchmark to games. I think that it’s very telling that the main pricing question from our customers is not ‘why is this so expensive?’, it’s ‘why is this so cheap?’ Like, we are benchmarked to tutors. And people understand a tutor for a kid is $10,000 a year. And, you know, we have been working so hard on this because we wanted to bring that cost down by 95%. Like, we wanted to be able to offer a product for 30 bucks a month that could do most of the things a tutor does.

Jason Calacanis: 21:44 All right. So, AI emerges a couple years ago, everybody’s like, oh my God, it’s the death of everything. Everything’s going to die. I mean, if I had a nickel for every single technology that was going to die…

Sue Khim: 22:21 I think that AI has been a huge tailwind for us. It’s created this divide where AI clearly is going to either make you smarter or it’s going to make you passive and dumb. And everyone’s going to have to choose.

Jason Calacanis: 22:46 Let’s do a demo of the new AI tutor. This is the co-pilot, I guess, is the way to think about it. And I’m curious, am I on the existing Brilliant website and you added the AI to that, or is this all new?

Sue Khim: 23:11 Yeah, so, you know, the thing that you’re going to see is that LLMs have a very constrained role in this product. Koji’s designed around what LLMs do well, but all of the, you know, pedagogy, the which is more deterministic and we’ve been working on that for years and years. And, you know, part of what makes this product sing with AI is that, you know, since 2019, literally since GPT-2, we have been working on this.

Jason Calacanis: 24:45 Mm. Okay. And the name of the tutor on brilliant.org is…

Sue Khim: 24:50 This is Koji.

Jason Calacanis: 24:51 Koji. Koji, made up word, sounds Japanese, maybe, or Korean. What’s the background here?

Sue Khim: 25:11 Yeah, we have a lot of international usage. So about 40% of our users in the US but 60% are all around the world. And so it was important for us to pick a name that feels accessible to everybody.

Jason Calacanis: 25:41 Love it. K-O-J-I?

Sue Khim: 25:44 K-O-J-I, yeah.

Jason Calacanis: 25:46 Koji. I love it. Is it- does it mean anything? You just found a word, does it have a meaning in a language?

Sue Khim: 25:51 It does have a meaning and a backstory, you know, maybe not worth getting into. But, you know, sort of- we liked the sort of scientific backstory of Koji the fungus, which we can talk about some other time.

Lon Harris: 26:01 Awesome. Listen, you are definitely living up to your nerd credentials here if you named it after a deep pull of fungus, who aren’t completely underrated. All right, let’s see show and tell here.

Sue Khim: 26:31 Yeah, so Koji is Socratic. This is, you know, somewhere in the middle of a quadratics lesson so I’ve been learning with Koji, so let’s start this lesson. Let’s keep going with filling in both terms of the product. But this time, let’s add a coefficient to the mix. Complete the expression.

Sue Khim: 26:51 Okay, so here I am, and I see, oh man, there’s y squares here, so I see three…

Lon Harris: 27:00 3y squared and then I’m supposed to fill in these two blanks. All right, so let me, let me try this. Oops, let me try that.

Sue Khim: 27:12 I see three y’s here, is that correct? I see those three y tiles in the bottom left. If you look at the whole rectangle, how many separate regions contain y tiles?

Lon Harris: 27:24 I’m not really sure what you mean by regions.

Sue Khim: 27:27 Let’s start with what we know. The 3y squared term comes from multiplying 3y and y. Can you fill in the two linear terms?

Lon Harris: 27:39 Ah, okay. So, there’s, there’s two of these. I’m going to put 3y there, and 2y there, and two, and then combine those. Okay.

Sue Khim: 27:55 Exactly. Let’s remove the tile labels this time.

Lon Harris: 28:00 Okay, so now it’s a little bit harder because it’s not telling me what the tiles are, but I just did a problem like this. We got the 15z squared, I’ll count these, so there’s seven of these, seven of those.

Sue Khim: 28:21 Here’s what I want you to notice. We’re multiplying two binomials using the distributive property and then combining the like terms. Neat, right?

Lon Harris: 28:31 I don’t really get it. Can you explain that again? I don’t see how the graphic actually corresponds to the stuff below, the equations.

Sue Khim: 28:41 The main idea is that the area model and the algebra show the same thing. Notice how we have two separate regions with v tiles? In algebra, we combine those like terms into a single 7z.

Jason Calacanis: 28:52 And so, you know, a few things to notice here. Again, Coji is going to guide you to understanding. The responses are tailored so that he’s not just throwing very, very long explanations at you. [Shopify sponsor read]

Jason Calacanis: 30:48 And there’s obvious advantages here. The tutor is available anytime the student has energy or a window. That is key when you start having kids.

Lon Harris: 30:58 Yeah, scheduling. The tutor’s coming at 4:00 PM. The kid didn’t sleep well last night, whatever it is, they’re in a bad mood, their friend is — all their friends are going for ice cream, they’re not. The question I think a lot of people are going to have is: is this like just throwing Claude or OpenAI or Grok or Gemini against Brilliant, or what did you have to do to that AI?

Sue Khim: 31:52 Yeah, so it’s fairly — Brilliant’s fairly model-agnostic. And the thing that we have versus frontier models is frontier models don’t have verifiable reward signals for tutoring, and we do. If you look at frontier models — and we benchmark this very carefully — their ability to tutor well hasn’t improved much since like O1. These models are much better at following instructions and using actions.

Jason Calacanis: 32:47 And is that how you trained it? Is you said, “Hey look, here’s a bunch of data for this problem, here’s a bunch of data for this problem, these are the questions we typically get, this is where people get stuck”… methodology or did you have to teach it a certain methodology?

Sue Khim: 33:04 We had to teach it a certain methodology and it was a huge schlep. You know, literally for every concept we had expert teachers in that concept essentially instruct the model on which tool calls to make.

Jason Calacanis: 34:03 Yeah, that makes complete sense to me. How has it been received by users and does this change your business model in any way?

Sue Khim: 34:31 Oh yeah. Yeah, our vision is a tutor in every home, in every language, in every subject. And that means you have to have a tutor that works, it has to be at a price point that everyone can afford or essentially free.

Lon Harris: 34:43 And how is it? Is it localization accurate enough to feel confident selling it to other regions?

Sue Khim: 34:46 The localization is astonishingly good. And actually, you know, some of these voices are employee voices, the tutor voices, and it is uncanny to hear, you know, people that I work with every day teach in another language.

Jason Calacanis: 35:59 We have a portfolio company Micro1, that does this learning for language model companies. How do you think about, you know, having the learning occur inside of Brilliant or working with those vendors who are currently helping people?

Sue Khim: 36:29 Certainly, I think there is deep recognition that we have a really unique dataset. Uh, you know, we are — we have scale — we have tutoring sessions at scale with real students.

Jason Calacanis: 37:10 What I love about what you’re doing at brilliant.org, Sue, is you are taking a very world-positive view of AI. I believe the reason people booed AI during this recent graduation season — and it wasn’t one… is because they were the first generation to use AI in school. And I think they have some resentment for it in some ways.

Sue Khim: 38:34 Thanks, JCal.

Jason Calacanis: 38:36 That was my — I sometimes have to give my little soliloquy and my little speech at the end so I can feed the shorts algorithm. Pretty big team, yeah?

Sue Khim: 39:02 Yeah, about 70.

Jason Calacanis: 39:04 70’s great! I mean for the amount you… you don’t release your revenue numbers or membership numbers, I take it?

Sue Khim: 39:10 No, I mean, we may hit some major milestones here soon and where we do that, but so far hasn’t been public.

Jason Calacanis: 39:17 Got it. So yeah, I would man — I would love to see some nine — I would love to see a figure with nine in it. I don’t know like if that would be a revenue number or users or whatever, but I love when companies have nine zeros.

Sue Khim: 39:32 Well, hang tight.

Jason Calacanis: 39:35 It’s great to be on the cap table all these years and just to know you and watch the team crush it like this. And this is a true accelerant for the business. And my lord, if you can figure out how to teach philosophy or writing or other subjects… instead of it taking 10 years to build a vertical, it takes you two years or 10 months, this business is going to scale.

Sue Khim: 40:22 Absolutely.

Lon Harris: 40:24 A lot of lessons there from today’s interviews for founders. Number one, really understanding your customer and finding spaces where maybe it’s not clearly defined, which means idiot VCs — and we’re not naming names — won’t necessarily be able to recognize what you’re doing. The issue with venture capitalists in a lot of cases, not all… there is a valid criticism that if it doesn’t fit into an existing TAM, very hard for I think some young, inexperienced VCs to understand this.

Lon Harris: 41:23 When you look at these two companies like online tutor doesn’t exist, digital board game — that doesn’t exist and the people who like the existing board games hate this. You have to ignore all that and you have to ignore people who are trying to create a TAM for something that doesn’t exist in the world. The TAM for Airbnb was basically zero, they induced a market.

Jason Calacanis: 42:00 …markets because it was global. All of this is to say, listen to your customers and build a product that delights them and everything will be fine. High order lessons here.

Jason Calacanis: 42:12 All right, let’s get into bad VC behavior. For every story of bad VC behavior, you’re going to find an equal number of entrepreneurs doing crazy stuff. I’ve invested in 700 companies, I’m sure I’ve made everybody on the planet mad at me at one point. But VC has changed over the years. It went from the VCs replacing founders, putting in professional management, like they did to Google. They were like, ‘Hey, Larry and Sergey can’t run this company. We need an adult here. We need Eric Schmidt.’

Jason Calacanis: 43:06 Listen, anybody who’s in the company building business is going to have sharp elbows at times. There’s a lot of money at stake, it’s a trust-based system. VCs, when you think about it, give millions of dollars to founders for shares.

Jason Calacanis: 43:36 And then founders are taking this other leap of faith that the investors are not going to block a sale down the road or block an investment down the road. And this is why standard documents and standard terms are important.

Jason Calacanis: 44:02 Please do not take money from some high-net-worth individual who then wants the ability to, you know, control the board or get three board seats. Just keep it easy-breezy.

Jason Calacanis: 44:24 If the person invests early, maybe they could get super pro-rata and warrants. ‘Hey, we’re going to give you double pro-rata if you write the first check.’

Jason Calacanis: 45:00 The thing about these pile-ons that happen is they act as a cathartic release for the community. Everybody’s got bad VC stories, everybody’s got bad entrepreneur stories.

Jason Calacanis: 45:34 Okay, Greg Isenberg on the Twitter. ‘I was once pitching in a boardroom at a top three VC firm for a $15 million Series A. 12 people in the meeting, one of the GPs fully fell asleep. Out cold for 30 plus minutes.’

Jason Calacanis: 46:29 Okay. Uh, you have to consider when these tweets came out. VC behavior, like I said earlier, in the 80s and 90s was, hey, we’re going to replace the founder, etc. Then in the 2000s it started to change.

Jason Calacanis: 48:00 I email the top two and see what happens. Short, two sentences. Hi, my name is Jason Calacanis. I sold my last company for 30 million dollars in 18 months to AOL, it was called Weblogs Inc. I’ve got my new idea, I’m looking to raise 3 million dollars, it’s a human-edited search engine.

Jason Calacanis: 48:13 Boom, they both get back to me. Michael Moritz personally calls the phone numbers. John Doerr forwarded it to one of his people and had them call me. I was in his office a week later.

Jason Calacanis: 48:22 Just those two observations. One, the person I emailed called me back on my phone immediately within one hour. The second one was like a day or two delay. Still incredible.

Jason Calacanis: 48:39 So that led me to believe Michael Moritz is on it a little bit more than John Doerr. Then when I went to see Michael Moritz and Roelof, man, it was just very fast. They had me in a partners meeting that week.

Jason Calacanis: 48:49 Low and behold, I go, I get the meeting, and John Doerr is there and two of his other partners. John Doerr falls asleep in the meeting. And I told the story in my book Angel.

Jason Calacanis: 48:59 And he’s wearing a sling, and he’s not like fully knocked out. He’s like a little groggy. And I’m looking at him, and I’m like, ‘I gotta just power through this.’ But he’s got like a scrape on his face. And he’s got his arm in a sling and he can’t move it, and he looks banged up. And so he leaves the meeting, whatever, and one of the guys pulls me over, grabs me by the elbow and says, ‘Listen, I just want to apologize.’

Jason Calacanis: 49:25 ‘He was out biking this morning, he flipped his bike in Woodside, went flying over the handlebars, went to the emergency room, came directly here from the emergency room. He’s on a painkiller. He’s got a torn rotator cuff.’

Jason Calacanis: 49:41 Let that sink in. John fucking Doerr flipped his bicycle, dipshit Jason Calacanis with one or two wins under his belt is at the office, easy ability to say, ‘I’m not going to make the meeting.’ He made the meeting. He didn’t nod off during it. I joked with him about it later. To me, this was the greatest compliment I’ve ever gotten.

Jason Calacanis: 50:00 But I’ll tell you two other stories, since we’re giving stories. This other melon farmer goes to a friend and says, ‘Hey, I hear JCal’s raising from Sequoia and John Doerr. He was on Sand Hill Road. Could you help me get a meeting?’

Jason Calacanis: 50:14 I go, I’m supposed to — I said, ‘Listen, I’m in the final stages here. I had an offer from John Doerr. I had an offer from Sequoia. Mark Cuban had already committed.’ And so I’m three for three.

Jason Calacanis: 50:30 Mohr Davidow Ventures, I’ll say the name of the firm. I don’t think they even exist anymore. Begs a friend of mine to give him the meeting. My friend’s like a consultant to the firm.

Jason Calacanis: 50:44 And they said, ‘Okay, come to the Monday morning meeting.’ I go to the Monday morning meeting. I get off the airplane in San Francisco. There’s no internet on the plane.

Jason Calacanis: 51:00 Plans 20 years ago. I’m driving in my rent-a-car. There’s no Uber, I had to get a rent-a-car. This is like significant expense. I’m driving to Sand Hill Road. They have the office next to Sequoia.

Jason Calacanis: 51:29 Now this is Monday effing morning. I got up at 5:00 AM to take a 6:00 AM flight to land at 7:30 to get a rent-a-car to then get to their office for this 10:00 effing meeting.

Jason Calacanis: 51:59 I walk right into Mohr Davidow, I walk right to the receptionist. I’m Jason Calacanis. I have a meeting at 10:00 AM. And I look and I see the guy in the Monday morning partners meeting. It’s 9:30.

Jason Calacanis: 52:27 He says, “I can’t. You know, I told my partners, they told me the valuation, da da da. It’s not a fit for our firm.” I said, “You realize I got up at 5 in the effing morning for this meeting? I came up from LA. You begged my friend to give you the meeting. You’re telling me you’ve already decided no without pitching me?”

Jason Calacanis: 53:02 And I said, “I’m going to tell everybody this story.” And I did. For 10 years, this is all I talked about with Mohr Davidow. I would never recommend that firm. I don’t think the guy’s there anymore.

Jason Calacanis: 53:24 The guy came up to me two years later at like one of the Recode or D conferences. “Hey, I just want to apologize one more time. I was wondering if I could take you out for sushi.” I said, “I don’t know if I have time for that.”

Jason Calacanis: 53:49 I was just so, I mean, this is a 30-something-year-old J-Cal. It was a little crazy at the time, but I needed that animosity, so I took it out on them.

Jason Calacanis: 54:00 People falling asleep in meetings as a second recurring thing. He had it happen, I had it happen. John Doerr, still greatest venture cap, one of the top greatest venture caps of all time, great human being.

Jason Calacanis: 54:21 Travis, my boy, Kalanick. ‘In 2001, I intercepted a partner at a VC, this is long before Uber, this is during Red Swoosh I’m assuming, a VC who was trying to escape his office before our meeting was supposed to start.’

Jason Calacanis: 54:48 100% true. I saw this actually happen. A friend of mine did this where he just took somebody’s laptop in front of me at one of my events and just started rifling through the slides.

Jason Calacanis: 55:05 And so when I made my firm launch, and I have 11 people on the investment team, we were doing over 100 first meetings. I have every first meeting we do, two or three days after we do the meeting, it automatically goes out for a feedback survey to the founder.

Jason Calacanis: 55:41 So we get scores. If the scores are seven and below, they go into founder feedback tomatoes and if they are seven and above, they go into another room which is like kudos. And we rank everybody in our office.

Jason Calacanis: 56:18 Then when they give that feedback, man, somebody will tell us in that feedback, ‘This person didn’t understand my business.’ That kept happening over and over again. People said that about me!

Jason Calacanis: 56:35 So what I did was I added to every time I meet with a founder, the final question I ask after they’re done is, ‘May I repeat your vision back to you so that I can make sure I understand it perfectly?’

Jason Calacanis: 57:00 Whether it was my brain or their lips, somewhere between those two I didn’t get it, we can work that out.

Jason Calacanis: 57:07 That changed everything. And then I made everybody who works for me answer every single first meeting with that. And we said our first meetings are 20 minutes long. You present for 10 minutes, we ask questions.

Jason Calacanis: 57:29 Why do I frame the first meetings as 20 minutes on Zoom? Because it shows the founders that we respect them. And we make sure we have all the proper information and we make sure they understand how our process works.

Jason Calacanis: 57:46 And then I had hired some people who had experience in venture capital, they brought all these bad habits. They wanted to do one meeting a day instead of doing three, four meetings a day.

Jason Calacanis: 58:17 Okay. I’m Jason Calacanis. Thanks for coming to my TED talk. Bye bye.

Lon Harris: 58:21 Thanks for watching This Week in Startups. If you liked this episode, check out more. If you’re a startup founder, Founder University Cohort 13 kicks off this fall. It’s a 12-week program. Already have traction? The Launch Accelerator invests $125,000. If you’re an accredited investor looking to gain access to quality deal flow, apply for Jason’s Angel Syndicate at thesyndicate.com. And check out This Week in AI, Jason’s experts-only roundtable. Check out the Twist Ticker. Thanks again to our sponsors. This Week in Startups publishes three days a week: Monday, Wednesday, and Friday at 5:00 PM Central Time.