Chamath on why young people need more agency, risk, and adventure

Summary

In this TWiST All-Star Summer episode, Jason Calacanis sits down with his All-In bestie Chamath Palihapitiya to trace his shift from “founder-adjacent” capital allocator to full-time founder CEO. Chamath opens by explaining how he productized two of his passions — Learn With Me, a ~$1,000/year research community that turned a multi-million-dollar McKinsey research bill into a subscription business, and Drink With Me, a wine venture built to collapse the “middleman renter economy” that marks wine up and squeezes the artisans who make it. His framing throughout is that capital is more than money: it’s time, reputation, influence, and human capital, and the best returns come from aligning those with what you actually love.

The heart of the conversation is 8090 and its flagship product, Software Factory. Chamath argues the world spends roughly $5 trillion a year on software — $1 trillion in licenses (Workday, ServiceNow, SAP, Oracle) and $4 trillion in maintenance, migration, and services that is largely “pure waste.” His lightbulb was that the best companies — Facebook, Google, Tesla — had an “allergic reaction” to that standard stack and built custom. AI now drives the unit cost of software production toward zero, so Software Factory acts as a “control plane”: intent comes in the front, gets shaped into a PRD, then an engineering plan (blueprint), then work orders sent to any coding agent via MCP — and everything stays “bound” and in sync forward and backward, giving regulated enterprises the governance and auditability that “vibe coding” can’t. On the back of this, 8090 raised a Series A (~$100M) led by Marc Benioff’s Salesforce Ventures.

Chamath then unpacks his “System on a Chip” org model — treating each department like a chip on a circuit board with defined inputs, outputs, and interconnects (marketing takes money + content, outputs only leads; sales outputs only TCV), inspired by Jack Dorsey’s memo and Elon’s “machine that makes the machine.” The episode closes on more personal ground: how a violent, alcoholic childhood trained him to absorb chaos, why the founders who make the money are the “uncoachable” diamonds, and his advice for the next generation — not a rigid plan, but an adventure full of agency, risk, and problem-solving, because millions of years of hardwired physiology won’t change just because AI makes food and shelter abundant.

Highlights

”A co-founder for every human” — the flower shop that spawns 19 agents

“I want to open a flower shop… your co-founder says, great, I’m going to spawn these 19 different processes. One is going to do a market analysis of where in our city is the best traffic patterns for demand… And then you can imagine if instead of saying that, instead you said I want to build an airplane company… Maybe it’s not 10 agents, maybe it’s 10,000.” — Chamath Palihapitiya, 21:27

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The $5 trillion software market — and where $4 trillion is waste

“That 5 trillion can be further subcategorized into a trillion dollars of licensing revenue. So this is what you would pay Workday or ServiceNow or Jira or Linear, GitHub, whatever… And then $4 trillion of maintenance, migration, and services.” — Chamath Palihapitiya, 25:54

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”They’re not here to fuck around with some stupid vibe coding tool”

“Everything is linked together, we call that binding, everything is bound together so that everything is in sync… when you go to the big guys and you talk about what they’re dealing with, they’re not here to fuck around with some stupid vibe coding tool like this. This is the level of governance and auditability that they need.” — Chamath Palihapitiya, 39:21

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The “System on a Chip” org model

“This is not how it should work in a world of AI. And so instead, I came with a framework, and I call it system on a chip… Why aren’t we organized like a circuit board? Why aren’t we a set of chips and a set of interconnects?” — Chamath Palihapitiya, 55:12

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”They’re supposed to be sharp — they’re fucking diamonds, folks”

“Throws them in the refuse pile because they’re a little sharp. They’re supposed to be sharp, they’re fucking diamonds, folks. Go back into the garbage and find me the diamonds you threw away. I want the uncoachable, difficult people. Those are the ones we make the money off of.” — Chamath Palihapitiya, 1:00:00

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”You got one trip around the sun — just never stop”

“The problem with defining your life in terms of external measure is at some point you’ll hit it… and then you kind of stop. And instead, I think you have to be deeply selfish about this, which is you got one trip around the sun, just never stop.” — Chamath Palihapitiya, 1:09:41

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Key Points

• Many forms of capital (3:58) - Chamath frames his job as allocating five kinds of capital — time, reputation, social capital/influence, human capital, and money — not just money.
• The $4M research bill that became a business (5:20) - He hired the McKinsey team that “teaches Bill Gates” for millions, then turned it into Learn With Me, a ~$1,000/year research subscription with thousands of members.
• Churn as the truth signal (6:46) - The single best indicator that his research content is timely and accurate is subscriber churn; growth means it’s working.
• Tom Sawyer entrepreneurship (7:13) - Jason praises turning a cost center into a community-validated, profitable product; Chamath lets the team keep the profit.
• Drink With Me and wine’s rigged middle (9:09) - Wine is roughly 2x marked up by a “middleman renter economy”; Chamath got his own liquor license to collapse it and help winemakers with succession.
• Riding waves and sitting out SaaS (17:47) - He rode the internet (Winamp, AOL) and mobile/social (Facebook growth) waves, sat out SaaS, and saw AI as the next wave to “paddle out” for.
• Co-founder for every human (19:36) - The original spec was “Co-founder”: a decentralized vision of 10 billion companies enabling economic mobility — but the market was ~30-40 years out.
• Software eats $100T of GDP (25:00) - ~90% of the ~$130T world GDP requires software; software extracts a ~5% take rate ($5T) to enable ~$100T.
• The best companies refuse the standard stack (27:00) - Facebook, Google, and Tesla had an “allergic reaction” to traditional software and built custom — the burger analogy for differentiation.
• AI drives unit cost to zero (28:44) - No task too menial or too difficult; the cost curve of production approaching zero is what changed his mind on custom software.
• Vibe coding: possible but trash (30:11) - He saw vibe coding as a way to see “the art of the possible” but end up with proof-of-concept trash — hence a disciplined factory.
• PDLC/SDLC lost its way (33:58) - “Move fast, break things” was born of Facebook being the 35th social network with no money; startups wrongly adopted “don’t document” as dogma.
• Software Factory’s assembly line (32:30) - Like a Tesla Gigafactory: raw intention in the front → PRD → engineering plan/blueprint → work orders → coding agent, with stations in between.
• More input = more precise (36:39) - Counterintuitively, dumping a large, rambling set of feedback makes the models more precise, not more chaotic.
• Model-agnostic via MCP (37:52) - Work orders route to any coding agent (Cognition, Codex, Claude, Cursor); vertical coding tools will converge, so the skill is keeping the system in sync.
• Binding and reverse-propagation (39:21) - A 3am PagerDuty patch auto-propagates back into work orders, engineering plan, and PRD so nothing drifts out of sync.
• Regulated industries are the beachhead (40:21) - Finance, healthcare, pharma, and defense have huge upside and huge blast-radius risk, so they need the control plane’s governance.
• You can’t pick one model provider (45:08) - Firms tying themselves to one lab lose optionality amid leapfrogging; a control plane stays model-agnostic (praise for EY and Deloitte).
• The $100M Series A (50:21) - After a ~$20M seed from the besties two years ago, 8090 raised ~$100M in the A led by Marc Benioff/Salesforce Ventures, with Coatue, Yuri Milner and others.
• Founder-led sales (51:07) - Chamath now literally “sells enterprise software”; Jason notes distribution “gets you the meeting, it doesn’t close the deal.”
• Childhood as chaos training (53:00) - An alcoholic, violent father made him able to absorb the “omnipresent anxiety” of leadership — “the pressure that makes the diamond.”
• System on a Chip org design (55:33) - Departments as chips: marketing takes money + content and outputs only leads; sales outputs only TCV; agents sit at the interconnects.
• A DSP at the chip boundary (58:56) - Instead of humans arguing “the lead sucks,” a signal-qualifying DSP scores leads so decisions are about numbers, not personalities.
• Credit to Jack Dorsey and Elon (1:00:36) - The SOC model came from Dorsey’s memo and Elon’s “this is the machine that makes the machine” line at the first Gigafactory.
• Raise your kids for adventure (1:03:59) - He has no fixed plan for his kids beyond wanting them to have “their own adventure” — wins, losses, agency, and risk in an age of abundance.
• Never stop (1:09:02) - Being around Buffett and Thomas Keller shows a “core group of maniacs” who play an internal game and never stop.

Mentions

Companies

• 8090 (17:24) - Chamath’s AI software company, maker of Software Factory; raised ~$100M Series A.
• Social Capital (3:06) - Chamath’s investment firm; “founder adjacent.”
• McKinsey (4:00) - A senior partner introduced him to the research service behind Learn With Me.
• Workday / ServiceNow / Jira / Linear / GitHub (25:54) - Examples of the ~$1T/year software licensing layer.
• SAP / Oracle (28:08) - Cited as vendors that standardized “at scale the only solution is their solution.”
• Facebook / Meta (27:00) - Built most software internally; Chamath’s Growth Circle produced current CXOs.
• Google / Tesla (27:00) - Other examples of top companies that refused the standard software stack.
• Slack (41:19) - Chamath led the Series A and wrote an “intercompany edge effects” network-effects memo for Stewart Butterfield.
• Ernst & Young / Deloitte (45:00) - Consulting partners he believes will thrive with a model-agnostic control plane.
• PwC / Accenture (45:08) - Cited as having risked optionality by picking a single model provider.
• Anthropic / OpenAI (45:34) - Frontier labs starting consulting JVs to sell ROI on token spend to Fortune 500 CEOs.
• Salesforce Ventures (50:29) - Marc Benioff’s fund led 8090’s Series A.
• Coatue (50:29) - Thomas Lafont joined the Series A, alongside Yuri Milner and Xander Lurie.
• Palo Alto Networks / Quora / Meta (49:14) - Companies tied to angel investors Nikesh Arora and Adam D’Angelo.
• AOL / Winamp (17:47) - Where Chamath (and Jason) rode the first internet wave and learned network effects.

Products & Technologies

• Software Factory (32:06) - 8090’s flagship: an assembly line from raw intention to PRD to engineering plan to work orders to shipped, maintained code.
• Refinery (37:14) - The front-of-factory module: dump Zoom meetings and docs, get a PRD spec in collaborative multiplayer mode.
• Control plane (41:00) - The layer that sits above the model chaos, staying model-agnostic and providing governance/auditability.
• MCP + coding agents (Cognition, Codex, Claude, Cursor) (37:52) - Work orders route to any agent via MCP because vertical tools will converge.
• Knowledge graph / network effects (41:19) - Software Factory sits on a knowledge graph so the n+1th piece of software improves from building the prior n.
• Learn With Me (3:58) - A ~$1,000/year research community that frames Chamath’s point of view.
• Drink With Me (9:09) - A wine venture with its own liquor license, built to collapse middleman markups and help winemaker succession.
• Plaud NotePin (1:03) - Sponsor; AI recording pin Jason wears to capture and analyze the interview.
• Mermaid diagrams (35:05) - Used to represent the system in the engineering-plan step.
• iPhone camera / power-management chips (55:33) - The circuit-board analogy behind the System on a Chip org model.

People

• Chamath Palihapitiya (1:45) - Guest; founder/CEO of 8090, chairman/CEO of Social Capital, All-In co-host.
• Jason Calacanis (0:33) - Host of This Week in Startups and All-In co-host; seed investor in 8090.
• Bill Gates (4:00) - The research service was pitched as “the team that teaches Bill Gates.”
• Marc Andreessen (25:30) - “Software is eating the world” referenced re: 90% of GDP needing software.
• Elon Musk (27:00) - Taught Chamath about Tesla’s custom stack and “the machine that makes the machine.”
• Jack Dorsey (1:00:36) - His “From Hierarchy to Intelligence” memo seeded the System on a Chip model.
• Cena (1:00:36) - Chamath’s co-founder with whom he sketched the SOC org model.
• Marc Benioff (50:21) - Led the Series A via Salesforce Ventures.
• Nikesh Arora (49:14) - Palo Alto Networks chairman/CEO, angel in the seed.
• Adam D’Angelo (49:14) - Quora founder, ex-Meta CTO, OpenAI board member, angel investor.
• David Friedberg / David Sacks (49:14) - All-In besties and 8090 seed investors.
• Warren Buffett / Thomas Keller (1:09:02) - Cited as “maniacs who never stop”; the crew visited Keller’s French Laundry (TFL).

Surprising Quotes

“I could sleep separated from my wife in a bed at 68 degrees and maybe live an extra six months, but I’m not sure it’s worth it for me.” — Chamath Palihapitiya, 9:09

“Why can’t everybody in the world have an incredibly capable co-founder? And why couldn’t there be as many or more companies as there are people?” — Chamath Palihapitiya, 19:36

“This idea of enabling economic mobility, giving every single human on earth the ability to be economically independent… It’s an extremely decentralized view of capitalism and democracy at scale.” — Chamath Palihapitiya, 22:54

“It’s this constant state of worry to be honest… I don’t want to let my friends down. I don’t want to let my investors down. I don’t want to let my employees down.” — Chamath Palihapitiya, 52:32

“My dad was an alcoholic, my dad didn’t really think twice at times just to beat the shit out of me… it’s really made me able to absorb chaos, I guess.” — Chamath Palihapitiya, 53:00

“It’s not about making the machine, it’s about designing the system that then enables the machine to be made.” — Chamath Palihapitiya, 1:01:29

Transcript

Chamath Palihapitiya: 0:00 I think you have to have a prepared mind. There are many forms of capital. If you’re lucky enough, you can be in a position to allocate time, reputation, influence, human capital. If you can productize your passion, you can have such great joy in your life.

Jason Calacanis: 0:13 And somebody had put into the weighting that the founders were coachable.

Chamath Palihapitiya: 0:16 All our money’s made with the uncoachable ones.

Jason Calacanis: 0:19 Exactly. They’re supposed to be sharp. They’re diamonds, folks.

Chamath Palihapitiya: 0:22 You can be as successful as you want, but then there’s just a lot of people that stop, and then there’s a certain core group of maniacs that never stop. You got one trip around the sun, just never stop. Do all the things you want to do, just never stop.

Jason Calacanis: 0:33 All right, everybody. Welcome back to this week in startups. It’s the summer. And what do we do in the summer? We do the next unicorns, we think about who are those next companies, and we do the twist all-stars. Why do we do the twist all-stars? Because there are some people that share three qualities. One, deep, deep knowledge, experience, they got nuggets of gold. Number two, they’re willing to share them. They’re iconoclastic, they’re outspoken, they will tell you everything. And then number three, they vibe with your boy J-Cal. They got a vibe. So you’re going to get ten of those this summer.

Jason Calacanis: 1:03 (Plaud ad read) And the first one is my guy Chamath Palihapitiya. I don’t want to lose a single gem, a diamond he’s going to drop today. So what do I do? I got my Plaud pin on. Look, it’s on my t-shirt, no problem. Press the button, I get the haptic, it’s recording, organized in my Plaud, using AI… Take Chamath’s knowledge and analyze my businesses with every drop of knowledge he dumps… It’s like getting Chamath as a consultant. And that’s all enabled by Plaud. You have to applaud Plaud for making such a world-class device.

Jason Calacanis: 1:45 There’s some folks who you just love as the Twist audience, as founders. They typically have three things in common. One, deep expertise, two, willingness to share it candidly, and third, they vibe with the host. We get, you know, the vibes are immaculate. Top of that list is my bestie, Chamath Palihapitiya, who’s making his fourth or fifth appearance here on This Week in Startups and my lord, we’ve done 260 episodes of All-In as well. It’s crazy, huh? What’s up, bestie? So to kick us off, one of the great jokes I would have to tweak Chamath, one of the few things I could tweak him about. No, not his fashion and no, not his shirtless selfies.

Chamath Palihapitiya: 2:08 Not my swole body and rock hard abs.

Jason Calacanis: 2:11 None of that. It was the fact that, hey… Decade ago, he was one of the few of us who hadn’t started a company. Well now, that’s changed dramatically.

Chamath Palihapitiya: 3:06 But wait, what do you consider Social Capital? That was a company.

Jason Calacanis: 3:09 I mean starting a firm is very close to starting a company, but slightly different. A firm is slightly different than a company because you don’t have exactly customers, products in the same way, you’re managing assets. I consider it adjacent, right? I don’t know how you feel.

Chamath Palihapitiya: 3:24 Yeah, yeah. Founder adjacent. I was founder adjacent.

Jason Calacanis: 3:27 It’s founder adjacent. I mean you could be the founder of a fund but really, making a product or service is hard. Since that time, I was just thinking about it before I got on air here and I was walking down the road at the ranch. You’ve been in a flurry. People don’t know, but you have two wonderful products that I love the branding on. Drink With Me, or us? It’s Drink With Me. And then Learn With Me. What I love about those two products is your passion, learning and wine, and number two, the branding. I’ve never heard anybody do blank with me. Where did that come from?

Chamath Palihapitiya: 3:58 They are things that are omnipresent in my life. I just thought that there was a clever way to make a business out of it. And maybe you would say why? Like what is Learn With Me? Learn With Me is just a research community. So part of my job at Social Capital and part of my job in general is to be a very thoughtful allocator of capital and we’ll talk about this when we get to 80-90, but there are many forms of capital that if you’re lucky enough you can be in a position to allocate. One is time, another is reputation, another is social capital, so influence, another is human capital, influencing what other people work on, and then the last is capital capital, just money. But in order to do that job, and I think it’s an important job to be a capital allocator, I think you have to have a prepared mind. In the late teens and early 2020s, I was introduced by a friend of mine who was a senior partner at McKinsey at the time, now he works for Google, to this service that they had for certain people and at the time, how he sold it to me was this is the team that teaches Bill Gates about things when Bill Gates wants to learn about something.

Jason Calacanis: 5:18 Ooh.

Chamath Palihapitiya: 5:20 And so I hired them and I said, ‘Okay, teach me all things energy’ because I wanted to understand climate change, but I really just wanted to understand energy production. And that was year five of Grok, so I could kind of see the forest from the trees on AI silicon and what was happening in power and I just felt I didn’t know anything about it. They did an incredible job, but they also charged me four million dollars for three months or two million, three million dollars, I don’t know, something, it was a lot of money. It was many millions.

Jason Calacanis: 5:51 Right.

Chamath Palihapitiya: 5:52 And so I just created a team for myself and I said, ‘I want you guys to create a calendar and create first…’ principles materials that I can use to learn about what I need to know about in the current moment. While they were able to do it, the biggest thing that I struggled with was what if their content is wrong and or not good?

Jason Calacanis: 6:13 Right.

Chamath Palihapitiya: 6:14 And the solution that we both came up with was okay let’s make it a subscription service and let’s make the cost meaningful enough that it’s a real signal. So there’s a community now of many thousands of people, the cost is about a thousand bucks a year, but it’s all the content that my research team produces that I use to frame my point of view. One day it’ll be lab grown meat, the next day it’ll be about China, the next day it’s about religion, the next day it’s about semiconductors, the next day it’s about AI models, the next day it’s about attention mechanisms, the next day it’s about mining. But if you start to consume it on a regular basis you really do start to develop a prepared mind. And because there’s so many thousands of people now that consume this service, the single biggest indicator of value is churn.

Jason Calacanis: 6:58 Yes.

Chamath Palihapitiya: 6:59 When people are churning it just means the content sucks and so I know that something’s wrong. And when the service is growing it’s the most simple way of me being able to judge whether the content is timely and accurate. That was ‘Learn With Me’ and that’s available to anybody who wants to sign up.

Jason Calacanis: 7:13 I tell you what’s so brilliant about it is you learned a really great, what I call like a Tom Sawyer version of entrepreneurship, which is you had to paint the fence or was it Huck Finn? It was one of the two. And he said hey painting the fence is a lot of fun, if you guys give me an apple I’ll let you paint the fence. And people would come and paint the fence with him. You took something that was a cost center, yeah it was Tom Sawyer. You took something that was a cost center, you then brought a community into it so they act in two ways: they validate, they make sure the information’s correct. But you took something that’s a 4 million dollar money pit and now you own this, you get to direct it, you get to have those employees and it makes a couple of million or who knows what the break even point is based on the number of people working on it.

Chamath Palihapitiya: 7:43 And the team actually makes profit from it so meaning it’s not where I’m going to sort of define my upside but it’s great that the team has the ability to actually build a business and a community around something that I really value. And it seems like many thousands of other people also value. How big could it be? I don’t know, it’s probably in the grand scheme of things probably a reasonable thing for tens of thousands of people to sign up for, maybe a hundred thousand people.

Jason Calacanis: 8:04 Tens of thousands of people signing up for a data product would put you in the most elite circles of data products. Like ‘The Information’ broke ten thousand at some point right? And it’s a third of the price and it’s more journalist than analysis but you know there are corollaries to that. And if you can take something you’re doing anyway and Tom Sawyer it… I did that with podcasting. I was going and having lunch with you and having a great conversation for two or three hours and it was like ‘Hey turn the cameras on, why don’t we share this with people?’ That’s what drew me to podcasting and then all of a sudden it was profitable. Oh my God, this opens up so many doors. And you get that correcting mechanism, you’re bringing a bunch of folks. We’ll get to 8090 in just a minute, big announcement coming up.

Chamath Palihapitiya: 9:09 Yeah, then ‘Drink with Me’ is completely different. So look, I guess you can read all the health stuff you want and I just think at the end of the day, people have to decide what quality of life do they want? And the years that I have on this earth, I want them to be enjoyable in a way that matters to me. I could sleep separated from my wife in a bed at 68 degrees and maybe live an extra six months, but I’m not sure it’s worth it for me. That’s just my own personal trade-off. Similarly, I could live calorie restricted and probably be a little bit fitter, but then I would have to say no or disappoint my children when they say, ‘let’s go to the ice cream parlor, let’s walk down the street, hey dad, try this, I just made this.’ No. So similarly, wine for me, I drink it once a week, but it’s a very special social thing in many people’s lives.

Jason Calacanis: 10:12 And it’s rich culturally, you get it—

Chamath Palihapitiya: 10:14 Culturally super rich. And listen—

Jason Calacanis: 10:17 And also socially, right? Like I know when I’ve opened bottles with you, it’s like so much fun to learn about the wine together.

Chamath Palihapitiya: 10:23 I— and I’ve— I’ve gotten you to drink white burgundy—

Jason Calacanis: 10:26 Yeah, love it. You know, I’ve never been a big alcohol guy, but I love having a couple of ounces with you. It’s fun.

Chamath Palihapitiya: 10:32 So what I noticed about the alcohol business is that wine is incredibly marked up. And the reason is from the winery. So the wineries, by the way, there are two properties of wineries that everybody should know. The first is that they are incredible artisans. These are farmers and scientists.

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Chamath Palihapitiya: 11:54 They slave away, quite honestly, to make something by hand. You can’t— you can’t automate it, you can’t AI this. And I think that that’s beautiful, that that property is beautiful. And the second is you will never find a winery in an ugly part of the world. They are in the most beautiful parts of the world. So you have these people that get the benefit of working in these incredible places making something with their hands. But the minute that that product is done, it enters this middle man renter economy that marks things up and so by the time it gets to you it’s typically twice the price. And there’s a lot of gatekeeping that happens. And that gatekeeping creates artificial scarcity when it shouldn’t and it allows certain people with certain kinds of wines to make a killing. And that annoys me because I don’t want, I’m happy to stand in line, but I don’t like being part of like some rigged game.

Jason Calacanis: 12:54 I hate it. It’s the worst feeling ever. When I tried to buy, like when I first sold Weblogs Inc to AOL, when we were at AOL, I wanted to go buy a Ferrari. And the amount of torture they wanted to put me through: you gotta buy a used one for 100k over sticker, you gotta buy the one you don’t want and that’s a dog, you buy two of those, then you can buy the one you want. It’s just annoying. And I just ran into the same thing with the watches, just looking at watches, they’re like ‘oh boy, here you go, you gotta find a middle man and there are these three watches that sell direct but most don’t,’ so you find this annoying, irritating sand in the oyster and then the pearl comes out, yeah?

Chamath Palihapitiya: 13:28 I think so. I just think the people that make the wine get a bit of a raw deal. And at the end of it, there’s a lot of generational transition that’s happening where most wine makers are hitting the end of the road where their children do not really want to take over these things and so what happens is they sell to a corporation and then the product goes to complete and total shit. So I said I can do one of two things which is I can go and just get my own liquor license so I can collapse the middle man renter economics of the business and I can create a community so that other people who would like to buy it can also buy using the same discount that I can now get, which is upwards of 40% sometimes. But the real goal is to build enough relationships and trust with these wine makers so that when they sell, they don’t just sell to some nameless, faceless organization, but they could theoretically go to us and a community of people that love what they do, sell a portion to us, be able to do some estate planning, find great other people who are young and up and coming to help take over their winery and keep these things going. And look, again, like learn with me, neither of these were meant to be billion dollar businesses, they’re just meant to be parts of my life that give me tremendous ROI and I think that there’s probably many other people for whom that is the same where you can kind of create a perpetual…

Chamath Palihapitiya: 15:00 Kind of a flywheel out of these things going so that again it’s not just all corporations that just kind of treat everything like a number and a cell in a spreadsheet.

Jason Calacanis: 15:11 Yeah, I mean this is one of the great lessons. If you can productize your passion is what I tell founders, you can have such great joy in your life because you’re gonna look at something that was a cost center and you had to go make money doing something you hated to fund the passion. But if you can align that and you’ve productized your passion in some way and then you get this ROI, okay sure maybe it makes a little money on the side it’s not comparable to what we do in day jobs, but it’s nice. And the same thing with the podcast, All In has a nice events business now and we’ll talk about that in a minute because that’s the third business that you famously started, give you a lot of credit for that, you call me after coming out of CNBC one time, you’re like one, I miss you, COVID, two, I can’t do these three minute hits and not get my point across, why don’t the two of us just chew the fat? And I was like, oh come on this week in startups, he’s like no, I want to do something different, and that was the origin story and then we of course got the two Davids in there and got those two nerds nerding it out to counter-balance our…

Chamath Palihapitiya: 16:05 And we made and I made this key decision, no ads ever.

Jason Calacanis: 16:09 No ads ever, another great one.

Chamath Palihapitiya: 16:10 Of which was very smart because it pulled us into other businesses. But yeah, so look, there was a period after COVID if I look back on it, I’m quite proud of the three businesses that I’ve helped co-found.

Jason Calacanis: 16:23 Hmm.

Chamath Palihapitiya: 16:24 And it was a moment in my life in my late 40s where I was honing in on, you know, what am I? You know, what am I?

Jason Calacanis: 16:32 Yeah, who am I, what am I? The big question when you’re successful, right? Yeah.

Chamath Palihapitiya: 16:34 And it’s like, you know, like I know like what drives me, it’s like I have relative mistrust of institutions, I have relative mistrust of experts, I really like to do my own diligence, I think from first principles, I’m not afraid to be wrong. And that’s when I honed in on, I’m this allocator of capital.

Jason Calacanis: 16:52 Mm-hm.

Chamath Palihapitiya: 16:53 But the thing that I had never done in all of this journey since Facebook was really allocate my time to one thing. I’d allocate money, I’d allocate reputation, I’d allocate social capital and influence, I’d convince people to go and work at companies on behalf of my friends or on behalf of the things that I was an investor in, but I’ve never put all of that together into one thing.

Jason Calacanis: 17:23 Yes.

Chamath Palihapitiya: 17:24 And that’s sort of where 80/90 came from. Because I kind of felt at the tail end of COVID like, okay, this AI thing, I would tell my friends and my family it’s like I’m out there waiting to ride a wave.

Jason Calacanis: 17:46 Hmm.

Chamath Palihapitiya: 17:47 And I’ve been lucky in that I’ve ridden two huge waves in my career. Wave one was the beginning of the internet, you rode it with me, I was at Winamp and then I was at AOL and,

Jason Calacanis: 17:55 Yeah, Winamp and AOL.

Chamath Palihapitiya: 17:58 You know, I had the luck of learning about network effects at AOL and then I accidentally swam into a second huge wave, which was mobile and social. And my real chops were made creating growth as a craft and then just automating and instrumenting and machine learning the shit out of it. That was a huge success for Facebook, but then I kind of sat out the SaaS wave.

Jason Calacanis: 18:18 Extremely tactical, extremely strategic. And this is I think what really made you dangerous, is that you added that tactical, strategic, and team-building philosophy and skill set to your skill stack.

Chamath Palihapitiya: 18:34 You know, the thing that I’m most proud of at Facebook is I recruited a team of seven people. It was called Growth Circle. Three of those people are still there and they’re CXOs of the business. They’re the COO, the CMO. I did a good job of managing people and recruiting them and mentoring them, but I’d never had the itch to do it since then. And part of it was I think my intuition that the waves weren’t big enough. And then this AI wave started to build and I was like, this is it. I just gotta paddle out, get on the board, and just rip it.

Jason Calacanis: 19:09 Yep. Figure it out. And that’s 8090. What was the origin story there? Because I think most people know what you’re doing if they’re fans of All-In and they’ve heard us chit-chat about it on the side, but let’s start from basics. What does the company do? How does it make money? And what’s the origin story here?

Chamath Palihapitiya: 19:29 I like to write things down because I think it’s like, it keeps everybody honest.

Jason Calacanis: 19:31 Writing is clarity of thought. Like that’s what writing is. It just clarifies your thought perfectly.

Chamath Palihapitiya: 19:36 I wrote a product spec for something that I called Co-founder. And the idea is, why can’t everybody in the world have an incredibly capable co-founder? And why couldn’t there be as many or more companies as there are people? Now, bear with me for a second. If you go all the way back to let’s just say the 15 or 1600s, there was hundreds of companies. And I’m sure if you go back many hundreds of years before that, there was probably the one moment where the first company in the entire world was created. But from that one, ultimately grew to hundreds, which ultimately now I’m going to assume there are tens of millions of companies in the world. Maybe hundreds of millions of companies.

Jason Calacanis: 20:26 Yes. Definitely tens of millions, for sure.

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Chamath Palihapitiya: 21:27 So the trend is inexorably in one direction. But in order for you to go from a hundred million companies to say ten billion companies, what you needed and what you will need is something that helps you fill in for all the weaknesses that you have, and I called that co-founder. And so the idea was, what if your co-founder could, I’ll just use a very simple example, I want to open a flower shop. It’s very legitimate business. And your co-founder says, great, I’m going to spawn these 19 different processes. One is going to do a market analysis of where in our city is the best traffic patterns for demand. Another agent will then ping all the commercial real estate agents and ask it, what are the available spots in all of these different geographic corridors that the first agent identified. The third will go and do a crawl of the internet and give me back a market summary of the kinds of flowers that one would need. The fourth will go and ping Stripe and activate a Stripe merchant account. The fifth will go and work with Spot On to get a terminal delivered to my storefront. The sixth will engage a construction crew to do the kit out of my store. The seventh will be a supply chain agent. So you can go on and on down the line. And then you can imagine if instead of saying that, instead you said I want to build an airplane company.

Jason Calacanis: 22:53 Mm.

Chamath Palihapitiya: 22:54 Maybe it’s not 10 agents, maybe it’s 10,000. But the point is that there can be a conductor, an orchestrator at the absolute top level who can help you execute on all of those things. That’s where I originally started and the spec that I wrote. The problem was that the market was not ready for something like that. And my best guess, when I read it over and over again, is that’s a 30-year or 40-year journey. So then I had to wind it all the way back and say, what is a logical starting point today that over time can earn our way into being that omnipotent co-founder for every human on earth. And maybe just to double click on that, why that? Because I think for me, this idea of enabling economic mobility, giving every single human on earth the ability to be economically independent, self-sufficient, take care of themselves, take care of their family, have money to spend on the things that they want. That to me is a very powerful idea. It’s an extremely decentralized view of capitalism and democracy at scale.

Jason Calacanis: 24:00 Yeah.

Chamath Palihapitiya: 24:00 So it just seemed like I had a lot of passion for it.

Jason Calacanis: 24:01 Big audacious mission, right? Yeah, and if you look at what’s wrong with America today, in our great journey as a capitalist society, is self-reliance has been replaced in some ways with victimization and handouts have replaced pulling you up by your bootstraps and agency and what you’re talking about is basically reconnecting people with that.

Chamath Palihapitiya: 24:27 Yeah.

Jason Calacanis: 24:29 What the pioneer spirit of this country and as an immigrant to the country and somebody who had to fight for tooth and nail for everything you got, which people take for granted when they meet Chamath circa 2020s. You know, I know the story. You had to fight every inch. So if you have to fight for everything, you really want to see other people have that opportunity. It’s the clearest path to fixing this K-shaped recovery, the issues we have that we talk about on All In every week is just to empower people to start their own companies.

Chamath Palihapitiya: 24:55 Yeah. Then I had to kind of say, okay, if that’s where I want to be, where do we start? And I learned two really incredible facts. The first is that if you look at the world’s GDP, call it, for the purposes of this conversation, $130 trillion. I would say 90% of it requires some sort of technology to make it come to life. Some sort of software of some kind. There’s a certain percentage of the GDP that does not require that.

Jason Calacanis: 25:25 Yeah. Increasingly smaller and smaller.

Chamath Palihapitiya: 25:30 Yeah, increasingly smaller and smaller. So it’s kind of what Marc Andreessen said. Software really is eating the world. So that was one interesting factoid. And the second is when you look at software, what I learned was software can be bucketed into two categories. It costs around $5 trillion a year. So think about it as $5 trillion enables call it $100 trillion, okay? So there’s a 5% take rate that software extracts to enable most of the GDP of the world. And that 5 trillion can be further subcategorized into a trillion dollars of licensing revenue. So this is what you would pay Workday or ServiceNow or Jira or Linear, GitHub, whatever, right? A trillion dollars of those licenses. And then $4 trillion of maintenance, migration, and services. So meaning, once you implement Workday, you typically bring in a suite of consultants to just help you make sure it doesn’t break all the time.

Jason Calacanis: 26:38 Yeah, and that you get your value from it because somebody’s got to make sure the distance between this huge contract that was signed by management, some CTO somewhere, actually gets implemented and it’s worth the money you spent on it or else somebody loses their job eventually. Might take five years, but I remember when I was in IT, this was an acute thing. Like some top-down person was like, ‘Hey, we’re going with Lotus Notes,’ and then it was up to us.

Chamath Palihapitiya: 27:00 As to make sure Lotus Notes actually delivered the value, not Lotus Corporation. So, but it occurred to me when I looked at that because I had not really looked at that very carefully. I have this kind of like lightbulb moment, which is I contrasted that to what we had done and what a lot of what my team had built at Facebook. And I thought to myself, well, hold on a second. Why is it that Facebook, which is an exceptional business, only uses an extremely small amount of that five trillion dollars, and most of it was built internally. And then I remember what I had learned from my friends at Google, and it was the same thing inside of Google. And then I remember what Elon had taught me about Tesla, same thing at Tesla. You had all these examples where at the extreme end of success, all the best companies almost had an allergic reaction to that traditional software stack. They refused to use it. And so the lightbulb moment for me was, oh, I understand. Like imagine, Jason, you and I both want to start a restaurant. And we’re given ingredients. We both get sesame seed buns, we both get three burger patties, we both get tartar sauce, we both get the same pickles. At some point, you’re going to start to wonder to yourself, how do I differentiate myself from Chamath’s burger company?

Jason Calacanis: 28:05 Yeah, source better meat.

Chamath Palihapitiya: 28:08 And you’re going to say, I’m going to source my own ingredients. I’m going to make these things myself and I’m going to take the risk because I think there’s better margins and better success in doing it my way. But for most companies, even though they say that on the surface, underneath with respect to the software that they use to run themselves, it is exactly the same. That is why companies like SAP and Oracle can be as big as they are. They’ve structured and standardized this idea that at a certain level of scale, the only solution is their solution.

Jason Calacanis: 28:21 Mm-hmm.

Chamath Palihapitiya: 28:22 But I had seen firsthand and I had enough friends and examples of other great companies that took a different route. Now normally you would say, okay, but that means nothing. Nobody’s going to, how do you go to a defense contractor and all of a sudden convince them to make custom software? They can’t do that.

Jason Calacanis: 28:39 No. They’ve got other things on their plate, yeah.

Chamath Palihapitiya: 28:41 Yeah, I would have agreed with you until AI.

Jason Calacanis: 28:44 Right.

Chamath Palihapitiya: 28:44 And the reason is you saw, I saw this cost curve where the unit cost of production was going to approach zero. So there was no task that was either too menial, too manual, too repetitive, or too difficult. So both ends of the spectrum that couldn’t be accomplished at some point by these models based on how fast they were accelerating their learning.

Jason Calacanis: 28:57 Right. That was what you saw just around the corner was, hey, this vibe coding stuff, which people were dismissing.

Chamath Palihapitiya: 30:00 Thing is this is bullshit, it’s just stupid, it actually was if you tracked it and you used it every month, you could see every two or three months that it made some significant leap forward. My thought was that vibe coding was going to be a great way to realize what the art of the possible was, but end up with a bunch of trash.

Jason Calacanis: 30:18 Like prototypes, basically.

Chamath Palihapitiya: 30:20 At best, but probably not even that.

Jason Calacanis: 30:22 Proof of concept, yeah, like that.

Chamath Palihapitiya: 30:24 And so in the first instantiation of 80/90, I said we have two goals. Goal number one is let’s help companies get the margin benefits and the upside of the kinds of custom software that companies like Facebook and Tesla and Google benefit from, number one. And number two along the way, how do you create a mechanism of learning, the kind of data that can be collected by that process, by the unbundling of that process, so that incremental runs of software become safer and faster and simpler to build. So first is do a job, second is try to orient and create a network effect and a flywheel inside of doing the job.

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Chamath Palihapitiya: 32:06 What we did was we created a product and we called it Software Factory, because we felt that that was a very honest representation of what this V1 goal is. It’s just to create a factory that makes software. And we thought it could give value in both of those ways to people. So let me explain. So Software Factory is exactly what you think of if you went to a Tesla Gigafactory. Raw material comes in the front, finished Teslas come out the back. And in between there are all these very logical stations, and different tasks are done at these stations. In our case, what comes in at the front is just pure raw intention. And that can be for the kinds of business people and senior leadership of a company. That deals in high-level business requirements, McKinsey decks,

Jason Calacanis: 33:07 Whatever your business is, that whatever your business goals are.

Chamath Palihapitiya: 33:09 Regulations, new laws get passed, maybe say it in a different way, a consent decree that you get from the US government, whatever. The point is that at the senior level, you’re managing risk and you’re allocating capital towards ideas. You want to give a shape to that. And then you want to be able to put that in the front part of the factory and have your colleagues and your teammates and the people that work for you extract from it a pretty detailed PRD, right, a product requirements doc. And what’s great is it’s not just the humans that collaborate on that, now you can add agents working behind the scenes to make that PRD incredibly high fidelity and really represent the business.

Jason Calacanis: 33:49 And those PRDs at AOL was where you learned it, yeah, like they were big on these PRD docs, they were huge.

Chamath Palihapitiya: 33:58 Yeah, and by the way, you’re bringing up a very good point. Like when I talk about the software factory, what it is is an embodiment of what people call the product development life cycle or the software development life cycle. They’re interchangeable terms. The reality is that PDLC and SDLC lost its way. It gave way to a lot of what we created at Facebook in terms of an engineering-driven dev culture, which is move fast, break things, build first, poor documentation. And when we did that, we did that in a very specific moment in time, not because we cared about those words, but we were the 35th social network on the scene.

Jason Calacanis: 34:38 Yeah. People forget. Yeah, there were many before, MySpace, etc.

Chamath Palihapitiya: 34:43 And so we had all these giants above us, including Friendster, including MySpace, we didn’t have money, and so we had to move fast.

Jason Calacanis: 34:54 Right. That was your advantage.

Chamath Palihapitiya: 34:56 But now engineering organizations start up with this idiotic idea that you shouldn’t document, you should just wing it, you should just grip and rip this stuff.

Jason Calacanis: 35:03 And don’t write anything down and yeah, then what happens?

Chamath Palihapitiya: 35:05 You get a lot of crap that gets into prod, you have an enormous amount of tribal knowledge, it’s unfortunately trapped in many humans’ heads, it’s not well documented, you have no SOPs, so when things break, things get really bad. Why not have a system where intent comes in the front, you can shape it, humans, AI, agents, and then when you lock that down, Jason, the next most important step is to extract from it a very detailed what we call an engineering plan or a blueprint. Right, like when you sketch out a house, the next step is you give it to the architect and say, ‘give me the buildable blueprints,’ which give you all of the little technical details so that the house can stand on its own, the foundation is strong, all the wiring makes sense. And so our module, that step in our software factory, allows you to do everything from write, you can upload mermaid diagrams, you can do anything that you need to represent the system. And then when you lock that, only then can you do what most people go right to doing right now. Now look, you can skip these steps, but we don’t recommend it. The third step is you extract work orders. And this is where now vibe coding failed. If you could direct an agent to code with relatively strict guard rails, the agents are excellent.

Jason Calacanis: 36:29 Excellent. You’ve experienced this in some of the projects that you’re doing. But the reason I suspect is because you’ve specked it cleanly and precisely.

Chamath Palihapitiya: 36:39 Yeah, and the more you give it, the more precise it becomes. It’s a very counter-intuitive thing. You would think that a stream of consciousness and rambling and throwing everything at it would create chaos. These machines are very good at taking a large set of feedback and actually making sense of it and making a plan out of it.

Jason Calacanis: 36:54 It’s kind of actually its strongest, its strongest ability right now. And so this is why I have the foot pedal because I just when I do a prompt now, I hit the foot pedal and I just keep talking and talking and talking and talking, let it go, and then it makes sense of everything I said. And then it asks follow-up questions because I ask at the end, ask me any follow-up questions about what’s not clear or things I’m missing and blind spots I might have. When you do that pedal to the metal strategy, boom everything changes, which I think is your Refinery thing, which is hey, we’re just going to pull in all of your stuff. What are you writing?

Chamath Palihapitiya: 37:28 Yeah, Refinery like again, exactly right at the front, our thing is you just dump everything, Zoom meetings, whatever, we’ll sort through it for you and we’ll give you a spec of a PRD. And now you can be there collaboratively in multiplayer mode in one doc, debating, questioning, asking, approving, denying. And then you go to an engineering plan, and then you go to work orders. This is the same as the GitHub issue. And then you can send it to a coding agent, and we support all of them via MCP so you can use Cognition, you could use Codex, you could use Claude…

Jason Calacanis: 38:00 Cursor, whatever.

Chamath Palihapitiya: 38:01 You can use Cursor, you can use whatever you want. Our, and by the way, the reason we support those is our view is all of those vertical tools are going to converge. That’s not where the skill is.

Jason Calacanis: 38:07 It’s all going to reach parity is what you’re saying.

Chamath Palihapitiya: 38:10 Yeah, they’re all going to be the same, plus or minus whatever. The real skill is being able to keep this whole system in sync. Right? Because then when you make the code, how do you generate evals? How do you generate unit tests? How do you wrap those together? And then how do you get it into prod and then maintain it as a system? So for example, you build a product, I’ll give you an example of one of our customers, regulated healthcare company, and with the Triple B, a lot changed. They just feed that into Refinery, we understand the diff between that PRD and what needs to happen to respect the law and once that’s approved it gets auto-propagated into the engineering plan auto-propagated into a set of work orders humans review and approve them and then put into the code because an agent goes and writes it and now this system is completely in sync.

Jason Calacanis: 39:20 Yes.

Chamath Palihapitiya: 39:21 The biggest problem that companies have is the drift that happens right everything gets out of sync by the way it also works in reverse so we built the factory so that it can work in forward or reverse so for example an engineer gets a pagerduty wakes up at 3:00 am in the morning they all of a sudden have to fix a bug or patch something and they put production code in we detect that and now we auto-propagate the work order we auto-make the change in the engineering plan and then we make the change in the PRD so now everything is linked together we call that binding everything is bound together so that everything is in sync now that may seem like overkill for a small product but when you go to the big guys and you talk about what they’re dealing with they’re not here to fuck around with some stupid vibe coding tool like this is the level of governance and auditability that they need why because if you think about the kinds of products that many of our customers make they’re in highly regulated markets they have huge upside for doing it but they have huge risk as well Jace.

Jason Calacanis: 40:21 Yes you have to mitigate like as a finance healthcare education any of these verticals.

Chamath Palihapitiya: 40:32 Pharma pharma defense.

Jason Calacanis: 40:34 You make a mistake the blast radius can be large and can take years look at I mean your time at Facebook I don’t think you were there for all of it but they’ve been under three or four consent decrees for mistakes made speed errors whether it’s fair or not whether it was political or not put it all aside it all speaks to having a tight plan having this harness people are calling it having this software factory allows you to trust the AI more and it allows you to be a lot faster.

Chamath Palihapitiya: 41:00 We call it a control plane.

Jason Calacanis: 41:03 Control plane.

Chamath Palihapitiya: 41:04 The reason we call it a control plane is like it’s a plane that sits above all the fray all the chaos models will come models will go we work with all of them we allow ourselves to be able to take advantage of the best-in-class model for the best task at that time.

Jason Calacanis: 41:18 Yeah.

Chamath Palihapitiya: 41:19 But it mostly is a product that’s about multi-user collaboration control governance and then what I told you is this emergent property where whenever you’re building these products we sit it on top of a knowledge graph and what that is is this is very similar to sort of the architecture that I had in mind at Facebook and the architecture when we led the series A in Slack. You know, I wrote this memo for Stewart, which was called intercompany edge effects. Like, I don’t think I’m head and shoulders better than anybody at most things, which I’ll be total, but there is one thing where I’ve just been in it for a lot longer than most people and I see these patterns, and that is around network effects. And so, this third time around, I wrote the PRD for this network effects and how to build it and how to architect it.

Jason Calacanis: 42:28 At Slack specifically?

Chamath Palihapitiya: 42:30 No, no, here at 8090, yeah. But I’m saying it’s built on the experience of Slack and it’s built on the experience of Facebook. And what I see is this ability to use the nature of these models to help improve the n plus first piece of software based on its experience building the n pieces before it. I don’t want to give too much of that away, but that’s working too. So basically what we have, Jason, I guess in a nutshell is, we’ve created a factory. It gives companies a lot of control. It allows them to document things, it allows them to take out of tribal knowledge what is in humans’ heads and document it for the first time in a long time. It allows these systems to stay complete and in sync. It allows them to unbundle a lot of that five trillion they’re spending, and slowly but surely how do you eat the elephant? One bite at a time. It’s like, okay, I’m gonna take a shot at this specific workload. Oh, great. So for example, like today, there was a guy that tweeted, this is a third party, and he said we’ve used software factory now to unbundle five billion dollars of ISV licenses. Five billion dollars. And I saw that and I was like, man, this product works, this is great.

Jason Calacanis: 43:52 Yeah, I mean, you have product mark— you’ve got the signs of early product market fit, which means you’ll get to pull eventually where people will just be like, I need this. And what people don’t realize is in those large companies, there’s a long list of projects they would like to work on. They have two choices generally. They can hire IBM, they can hire a software company, then they have the implementers they can hire alongside them, McKinsey or Ernst & Young, whoever it is. And now you’re giving them a third way, which is, hey, are you smart enough to use these new tools to control your destiny and then take those middlemen, we talked about the middlemen in wine, and those folks, like, are they actually adding value or are they damaging the core brand? And you could argue and, for every time one of these implementations happens and we saw it up close and personal, it was a waste of money and didn’t get used and got thrown away or it’s just years of frustration and you lose anyway. Here at least you’re getting closer to the craft, yeah?

Chamath Palihapitiya: 44:49 Well look, here’s what I’ll say about that. I mean, I think that there are some phenomenal organizations that I think have the potential to really thrive. I think the big consulting firms— so take— I’ll take two— Specifically, that I’m relatively close to Ernst & Young and then Deloitte as an example.

Jason Calacanis: 45:07 Yeah.

Chamath Palihapitiya: 45:08 I think that these guys can thrive in the world of AI. Then you look at companies like PwC or Accenture and it’s like, it’s very crystal to me, but it’s like they picked a model provider. And it’s like, how can you pick one of Anthropic and OpenAI? Not because they’re not good, these models are incredible. But two reasons. One is, you’re then tying yourself to only one technological roadmap, and you see the leapfrogging that’s happening.

Jason Calacanis: 45:31 You have no optionality. Yeah.

Chamath Palihapitiya: 45:34 And then two is, I think Anthropic and OpenAI have realized what we’ve realized, which is the end boss of tokens. So if you want to generate ROI, you must be able to sell ROI, meaning return on investment on token spend, to corporate Fortune 2000, Fortune 500 CEOs. CEOs who can see a line of sight to making more money than they’re spending. The thing that we all can see is that they are the most important customer. Why do you think Anthropic and OpenAI have started consulting JVs?

Jason Calacanis: 46:12 Yeah.

Chamath Palihapitiya: 46:13 So, for Ernst & Young and Deloitte, what I’ve told them is like, wow, you guys have made the best decision. Now, obviously I’m biased because they picked us, but when you have a control plane, you can now be model agnostic, you can solve your clients’ problems, you can actually work together, we work together really closely with them, they’re incredible partners. It’s incredible because now we get the benefit of decades of relationships, right, and trust that they’ve built and independence and auditability, and now we can work together to actually solve people’s problems.

Jason Calacanis: 46:46 Yeah, that’s great.

Chamath Palihapitiya: 46:49 So step one for like the next few years, we’re going to be doing a lot of this, which is selling these big transformations into large corporate enterprises and then doing the methodical work of implementing it and making it successful. I think if we can do that, Jason, in three or four years from now, we move into phase two, which is how do you take Software Factory and then slowly submerge it under the waterline.

Jason Calacanis: 47:07 Mm-hmm.

Chamath Palihapitiya: 47:08 And that’s the setup for phase three, which is how then do you have this just little, maybe it’s a foot pedal called co-founder that exists. But what will co-founder sit on top of? Co-founder will sit on top of an extremely robust software factory, right, ultimately. And the understanding of how to get work done and how do you tie it to actual GDP and outcomes.

Jason Calacanis: 47:28 Yeah, and if you think about it in terms of infrastructure, we turn a faucet on, water comes out. We don’t even see all of that underpinning, and we take it for granted, right? And we’re kind of moving towards that with the solutions you’re building and intelligence as a service in general. But there’s a lot of things that happen before that water comes out of your spigot and what we saw… With Uber and some other folks were, you give people unlimited water, they’re just going to let it run, man. They’re just going to be like a golf course, they’d be like making almonds, and—

Chamath Palihapitiya: 48:10 In the bathtub because there’s a valve where the water just runs out so you can just let it run. Who cares? Like, I forgot I put the bath on, and this is what happened with token maxing, I think. And also, it’s got a like slot machine type addiction to it, which is you give it a job, it comes back, oh, the job’s almost correct, and you’re like, “Ooh, I almost hit my flush,” you know, if you’re playing cards, “Let me see another flop, let me see another flop, give me two flops.” And you get this like incredible rush, but more often than not, it’s 60 or 70% of the way there, so you gotta pull the slot machine again, which means you gotta put another hundred-dollar bill in for tokens, right? Pretty funny.

Jason Calacanis: 48:48 Big announcement today. You’ve done your, I believe, is it the series A and the other one’s considered seed or series B?

Chamath Palihapitiya: 48:56 Series A. I mean, you technically are the seed, although we’re calling you the preferred A1, and then but yeah, you’re the— you guys— so yeah, we raised $20 million when we started two years ago. Literally almost two years ago to the day. And it was great. It was all the besties: you and—

Jason Calacanis: 49:13 Fun.

Chamath Palihapitiya: 49:14 Friedberg and Sacks. And then some incredible angels: Nikesh Arora, who’s the chairman and CEO of Palo Alto Networks; Adam D’Angelo, who I worked with, he was the CTO of Meta and founder of Quora, on the board of OpenAI.

Jason Calacanis: 49:30 He is podcast-shy. I tried to get him on this podcast for a decade. He’s just so podcast-shy, he just loves his work, huh? What’s Adam like?

Chamath Palihapitiya: 49:37 He’s great. He seems very smart, very thoughtful. And then, like a bunch of our friends from the group chat, like Andrew Bogut, David Lee, Sky Dayton, Diego Berdakin. It was—

Jason Calacanis: 49:48 Love it. Isn’t it nice to pass the hat with your friends for that first round? It’s just a really great feeling. And we’ve seen it now with our friend Sunny Madra pass the hat twice for us, and we had two nice outcomes there. It’s just a nice feeling if you can get there with your friends.

Chamath Palihapitiya: 50:04 That’s what we raised. We raised 20 million in the seed two years ago. And then, yeah, very excited. We raised about a hundred in the A—

Jason Calacanis: 50:20 Wow.

Chamath Palihapitiya: 50:21 Which was great. And we had an incredible lead, Marc Benioff and Salesforce Ventures—

Jason Calacanis: 50:28 Amazing.

Chamath Palihapitiya: 50:29 And then we had an incredible new group of folks also join, Thomas Lafont at Coatue, Yuri Milner, Xander Lurie—

Jason Calacanis: 50:40 Oh, wow. Just great people. Great humans. Now, this is the largest you’ve raised for a startup, obviously. What’s it like? What are you learning as a CEO versus a capital allocator? Because I went to see the office, and sometimes I call you, you’re like, “Hey, let’s get lunch,” or “Can you come to this event or do something?” You’re like, “I have a sales call,” which, by the way, I—

Chamath Palihapitiya: 51:00 I tell everybody that’s what I do. It’s I sell enterprise software now. That’s what I do.

Jason Calacanis: 51:03 You’re an enter… you’re doing the founder-led sales. Which is always the best way to do it because then there’s nothing between you and the truth and you can then have this clarity of vision. And that’s why founder-led sales for the first couple of years is so important. Because your sales team will massage you, massage the client. The truth gets kind of obscured 20% on either side… and now you’re living in a house of mirrors. Like, your sales team’s making you feel 12 feet tall, while they’re doing the same thing to the client and reality is just distorted. But talk a little bit about what you’re learning being a CEO versus a capital allocator or working being somebody top of funnel.

Chamath Palihapitiya: 51:43 I think it’s the same job. I mean, the difference between being an investor is I was only investing one of those five units. But being a founder CEO, you are allocating all five of those units. Now, I benefit definitely from having distribution that most founders don’t start with, right? A large Twitter following, obviously being able to do the podcast with you. That definitely has helped me and it’s given me an advantage.

Jason Calacanis: 52:14 It gets you to… what I tell people is, it gets you the meeting. It doesn’t close the deal, right? Doesn’t close the deal. It will get you the meeting. People ask you for a selfie in the lobby. But you’re not closing the LP unless your returns are there… you’re not closing the client unless the value is there, so you can’t overestimate it.

Chamath Palihapitiya: 52:30 Yeah. Where do I spend my time now? It’s like, it’s this constant state of worry to be honest. Like, it’s…

Jason Calacanis: 52:38 Existential dread.

Chamath Palihapitiya: 52:39 I don’t want to let my friends down. I don’t want to let my investors down. I don’t want to let my employees down.

Jason Calacanis: 52:44 Yeah.

Chamath Palihapitiya: 52:46 In terms of the actual… so that creates this kind of like omnipresent anxiety that I think I’m actually pretty good at absorbing like… in many ways, Jason, like I grew up in a pretty complicated household. I’ve been pretty open about that.

Jason Calacanis: 52:59 Sure.

Chamath Palihapitiya: 53:00 That was incredible training for this moment specifically. My dad was an alcoholic, my dad didn’t really think twice at times just to beat the shit out of me.

Jason Calacanis: 53:09 Yeah.

Chamath Palihapitiya: 53:10 Which it was what it was. Like, I don’t have no grudge, but it’s really made me able to absorb chaos, I guess.

Jason Calacanis: 53:19 I mean, if you look at all the great founders, you’re going to find this like dysfunctional childhood on the margins or at the core of it and… you know, it’s the pressure that makes the diamond, right? And then you get into a business situation and you’re like, this is nothing… compared to getting the shit beat out of me or living in terror or, you know, whatever it was.

Chamath Palihapitiya: 53:41 Yeah. I just want to do right… yeah. I just want to do right by the people that have taken that put their faith in me.

Jason Calacanis: 53:47 Yeah.

Chamath Palihapitiya: 53:48 And so where do I spend my time maybe? So I spend a bunch of time obviously kind of like in the machinery of getting more business because I think that that’s… Very crucial. I spend a bunch of my time as a product manager of our network effects business. So there’s the principal engineer and I, he sits side by side and we’re like little buddies pairing on this thing. I spend a bunch of time there. And I’ve been spending a lot of time right now in the organizational design of 80/90. So meaning, we don’t have an org chart and we don’t have a hierarchy. And so you may say, well, how does a company, and look, last year we did 17 and a half million of bookings. This year if we execute, maybe we get, we should have a decent chance of getting to 100. Next year, I’ve already told them what the plan is, which is 500. I have no idea whether they’re going to get there or not. But my point is, I wanted to take all the drama off the table. And we’re making a lot of progress, but the default Jason was to create an org chart. People would ask to hire people, then it’s like who should report to who.

Jason Calacanis: 55:06 Yeah, then you get Game of Thrones starting, fiefdoms, it’s not the way to succeed.

Chamath Palihapitiya: 55:12 This is not how it should work in a world of AI. And so instead, I came with a framework, and I call it system on a chip. And so what does that mean? When you look at the iPhone, the iPhone’s an incredibly beautiful product, it clearly works, it’s incredibly successful.

Jason Calacanis: 55:28 I would some say the most successful product of all time in terms of profits and distribution, yeah.

Chamath Palihapitiya: 55:33 Let’s take two examples inside the iPhone. Let’s take the camera chip and the power management chip. What’s so interesting to me is if you break open the iPhone, what you see is a circuit board, and what you see are a bunch of chips with a bunch of interconnects. So in the case of power management and the camera, the camera has no idea what the power management function does except that it gets a signal. That signal is very specific, you know exactly what it is and it can act on it.

Jason Calacanis: 55:57 Hmm.

Chamath Palihapitiya: 55:58 And I tried to take that analogy and I said, why aren’t we organized like a circuit board? Why aren’t we a set of chips and a set of interconnects? And what that does is it reduces each function into understanding what are the inputs and outputs of that function. I’ll give you one example. So I went to marketing and I said, okay, don’t ask me who reports to who, none of this stuff. You have two inputs. One is money, and the second is all the content that you may need. And the only output that you can generate are leads. Now those leads can be enterprise leads, they could be leads for people who want to buy subscriptions to Software Factory, the leads could be job applicants. But your chip takes in these two inputs, generates one output. Now draw your internals for me and let’s go debate the internals.

Jason Calacanis: 56:49 That’s where you start to get into tactics and strategies and how the loops, yeah.

Chamath Palihapitiya: 56:56 And loops, yes, process. And so what you start to see are like people designing cores, right? To use chip architecture language, cores, and chiplets, and we debate the interconnects. And then the leads now feed into sales, right? And then I go to sales and I’m like, ‘All right, let’s design your chip.’

Jason Calacanis: 57:08 Hmm. Sales to demo…

Chamath Palihapitiya: 57:11 No.

Jason Calacanis: 57:12 …and a customer client comes out the end. Yeah.

Chamath Palihapitiya: 57:13 No, they get just TCVs is all we allowed to come out the end. That’s all they’re allowed to exude- to… their exhaust is TCV. And so then TCV goes into the 80/90 enterprise…

Jason Calacanis: 57:29 …team to then build the stuff, it goes into finance to account and—

Chamath Palihapitiya: 57:34 So my point is we’ve been playing this game essentially of reimagining the company as a circuit board and reimagining everything as a chip, and the chip is comprised of these cores and chiplets, and everything has interconnects. And now you get to like a place, Jason, in a world of AI where agents can sit at these boundaries, measure everything. And I’m not saying that we’ve eliminated politics at all, but I’m saying it could be a path to it. So I’ve spent a lot of time trying to structure the mechanism of our company so that we can scale without the typical failure modes.

Jason Calacanis: 58:05 Yeah, it’s— I mean, I think your customers are also going to go through this kind of change. We’re seeing it when we debate, oh, these job losses, these layoffs, is it AI window dressing or is it actual reality? And then we debate it in a very granular way. It’s obviously both, which makes the debate great. But the interesting thing about this moment in time, those middle managers who were responsible for massaging this chip and getting things in and out, and then what happens between the chips, there were humans there. And those humans would bring their biases, they would bring their—

Chamath Palihapitiya: 58:43 Okay, so this is a great example. This is a great example. So let’s just say that marketing generates leads.

Jason Calacanis: 58:48 Yeah.

Chamath Palihapitiya: 58:49 Well, what happens at scale is they’ll generate a lead and sales will say the lead sucks.

Jason Calacanis: 58:54 Yeah, the lead is weak.

Chamath Palihapitiya: 58:56 And instead what should happen is at the boundary of those chips, there should be a DSP, right? Something that qualifies the signal as high or low, what scores it on a spectrum. And now we know what the leads are, we know how they convert. And to your point, there’s nobody debating and arguing and it’s not about personalities and emotions. It’s about what does the number say?

Jason Calacanis: 59:08 It’s a much simpler process. And it’s so great to hear you doing this because I’m also learning, learning with you. And did a similar process where I took all the applications we have and we started scoring the applications for year zero, year one startups. And then we just have this great Socratic debate. The humans are in the loop. ‘Hey, what should we weight the scores?’ And somebody had put into the weighting that the founders were coachable. And I was like, ‘Wait a second. How did that get in here?’ And they’re like, ‘Well, we have these problems with these people who are hard to deal with as founders, and then we have these ones who are coachable.’ I said, ‘By the way, all of our money is made with the uncoachable ones.’

Chamath Palihapitiya: 59:59 Yeah, yeah, yeah.

Jason Calacanis: 1:00:00 So you just put into the system something that takes the diamonds and—

Chamath Palihapitiya: 1:00:00 throws them in the refuse pile because they’re a little sharp. They’re supposed to be sharp, they’re fucking diamonds, folks. Go back into the garbage and find me the diamonds you threw away. I want the uncoachable, difficult people. Those are the ones we make the money off of.

Jason Calacanis: 1:00:17 This is one of the great aspects of systems thinking, and I kind of feel like the future is people who can think in systems. Whether it’s first principles, second-order effects, and just understand the, I guess some people call it the idea maze in business thinking, but the more you can understand the entire playing field, each of the chips, the more you can make that incredible brand product, right?

Chamath Palihapitiya: 1:00:36 Well, look, I want to give credit to two people. This system-on-a-chip org model for me was the output of reading Jack Dorsey’s memo and to be honest, I couldn’t understand it and I thought I was dumb. And I was like, Jack was talking about building a world model and a sales model, and I really couldn’t get to the level of detail to understand what he meant and what he was doing. And so I was just kind of churning in my head, churning in my head, churning in my head. And I had an important meeting internally where I was talking to my co-founder Cena, and it kind of pop, out popped this idea. I was like, Cena, I just want a bunch of SOCs. I want to just be able to see I/O and then I want to debate the pinout and the interconnects. And then he and I kind of sketched it together. And the second was Elon. I don’t know if you remember, Jason, when Elon opened Tesla’s first gigafactory, when we went to that party in Nevada.

Jason Calacanis: 1:01:28 In Nevada, we went there.

Chamath Palihapitiya: 1:01:29 Yeah. He showed me the layout of the factory and I said, “Oh, what is this? Is this a chip?” And he was like, “No, dummy, this is the machine that makes the machine. This is the factory.” And that has stuck with me to this day and the reason is because, to your point about abstracting one level up, it’s not about making the machine, it’s about designing the system that then enables the machine to be made. So when I’m sitting there designing the org, I’m trying to think through, like, what is the repeatable system that makes it like an iPhone and less like a brittle org chart, right? Or when we’re designing software factory, what is the network effect that allows this thing to just spin faster and faster every single piece of software that we see? And I think if we get these things right, we have the chance to build something quite interesting.

Jason Calacanis: 1:02:22 Yeah. And it’s great you’re in the arena, trying things, running a company, all of those things.

Chamath Palihapitiya: 1:02:26 All of those things.

Jason Calacanis: 1:02:27 The haters are going to be so mad, Jason. I mean, you’re going to pull it off too, and they’re going to be like, “Oh, he can actually build a company too, in addition to a podcast.” I took a couple pictures when I was there because I got to visit.

Chamath Palihapitiya: 1:02:39 Oh you did?

Jason Calacanis: 1:02:40 Yeah, yeah, here’s the first picture. This is you working in the factory. Oh, wait, there we go. Oh, no, this is you on the sales. There’s Chamath, and there you are, look at that.

Chamath Palihapitiya: 1:02:49 Wow, there I am in the factory. Yes.

Jason Calacanis: 1:02:51 Getting dirty, rolling up your sleeves, getting dirty, sweating. So you really can do both. You can do both. We have photographic evidence, you’re able to hit the… Road in that… Let me see that suit again you’re wearing. Woo, this is the JC Penney suit.

Chamath Palihapitiya: 1:03:02 Yeah, rugged. Look at that with the buttons. Burn that suit.

Jason Calacanis: 1:03:06 I mean listen, you gotta go knock on some doors. The young folks love to hear from you, love to hear for… oh, and there you are in the drink with me.

Chamath Palihapitiya: 1:03:13 And that one looks actually… the way these Chinese… these are Chinese models by the way that we’ve been playing with internally. Oh, there, you didn’t like that one.

Jason Calacanis: 1:03:23 Oh.

Chamath Palihapitiya: 1:03:24 That one… that bottle went bed. This is what the idiots who work for me and I do. We’re like producing a podcast and they just make images to try to get me to break up on air so they’re showing me these as we talk.

Jason Calacanis: 1:03:30 We’re image maxing. We’re image maxing. We’re meme maxing.

Chamath Palihapitiya: 1:03:32 It’s pretty funny. It’s pretty funny. But let’s look back and young people coming out of school now. Whether they’ve, let’s put aside like how in depth they are. We all agree you shouldn’t go in debt. That’s kind of a settled issue. We understand the future is AI.

Jason Calacanis: 1:03:43 So for our kids… we have kids of similar ages, we have teenagers and some younger kids… over the next decade or two, they’re going to be going through college, they’re going to be into the workforce. What are you raising them… how are you raising them in terms of skills, hard skills, soft skills, whatever in between, but how are you thinking about getting them ready to take on the world and be productive in it and then what’s your advice to people who are in college? You got a lot of Waterloo alumni. What are you thinking now in just stream of consciousness because this is a dynamic field here?

Chamath Palihapitiya: 1:03:59 I don’t have a good answer. I have not tried to answer this for my kids because I feel like I ask this question more than I answer it. And I don’t really know. And the only thing that I’ve concluded is that I think it’s very important for my kids to have their own adventure. I want them to do something interesting and have some wins, have some losses. But beyond that, I don’t really have much of a… I don’t have a plan. I just hope that they find an adventure and if I can be a part of helping them find that, that I think is going to be the whole challenge because like… and why do I say adventure? Because I think it’s kind of like all-encapsulating. Like if you think that the food, the shelter, your basic necessities are essentially covered for you in this next iteration where most things are abundant.

Jason Calacanis: 1:04:26 Yeah, modern society… a society evolved…

Chamath Palihapitiya: 1:04:28 Modern society evolves, abundance, yeah. It’s still not going to change millions of years of hardwired physiology. So, how your brain has evolved, that’s not going to change in one generation.

Jason Calacanis: 1:04:38 No.

Chamath Palihapitiya: 1:04:39 And so I think if you understand that, humans’ desire for agency and for risk…

Jason Calacanis: 1:04:50 Problem solving, socialization, there’s some core things that are just inherent in who we are. We’re going to want to play games, we’re going to solve problems, we’re going to want to socialize. And if you don’t do those things, by the way… You’re going to all of a sudden have people telling you you got to put your kids on SSRIs or speed to get them to have those things and it’s like—

Chamath Palihapitiya: 1:06:08 Yeah, that’s why I think the best word that I have come up with is adventure.

Jason Calacanis: 1:06:12 Hmm, I love it.

Chamath Palihapitiya: 1:06:13 And I would like my kids to have a chance to have an adventure. I mean I’ve had a great adventure, and it’s still only half done.

Jason Calacanis: 1:06:23 Hmm.

Chamath Palihapitiya: 1:06:24 And you’ve had a great adventure. Like, it’s like this is what you want for your kids.

Jason Calacanis: 1:06:26 Well I mean the kid from Toron- I mean you were Toronto originally? Where?

Chamath Palihapitiya: 1:06:30 Ottawa.

Jason Calacanis: 1:06:30 Ottawa. Kid from Ottawa, kid from Brooklyn and now look like, it’s— and we still have 20, 30 great years, who knows if they’re gonna solve some life extension, God forbid we’ll be doing episode 2,000 of All-In from somewhere.

Chamath Palihapitiya: 1:06:43 Great.

Jason Calacanis: 1:06:43 But yeah, I’ve been thinking about a lot too. I don’t have the easy answers, but the one I came up with is very similar to your adventure, which is exposure. Exposing them to possibilities. Exposing them to high agency people. And I think if you can expose them to these things, then it’s enough because young people have that energy, they’ll find something that’ll pull them to it. But I wish somebody had exposed me earlier to entrepreneurship, a little earlier to risk taking. You had to find that yourself, right? You had to find it yourself eventually. And that’s like… I’m taking them to Tokyo with me for Founder University and I’m going to let them sit in on it. And it’s like, I just thought to myself, man, if a 10 or 16-year-old J-Cal had experienced Tokyo… My first time on an airplane was when I was 15, 16 years old, I went to Florida. Like, we didn’t have the money for airline tickets, that was out of the question. Our vacation was how far can we drive the van before it reasonably breaks down.

Chamath Palihapitiya: 1:07:46 Were you upset when your dad had only bought you a one-way ticket and left you there?

Jason Calacanis: 1:07:52 Yeah, it was just like ‘Good luck getting back, son!’ It’s always great to catch up. Congratulations 80/90. I think I gotta talk to you about branding. You’re getting very good at branding. I love the ‘With Me’ branding. Great on that job. On 80/90 and Software Factory, both of them are interesting names. 80/90, hey, 80% of the cost for 90 or… 80% of the features for 90% less.

Chamath Palihapitiya: 1:08:18 80% of the features at 90% less is how it started. I’m not sure if we’ll deliver that, but that’s what it started.

Jason Calacanis: 1:08:22 Well, still great as an idea. But Software Factory is iconic. So I think we could retire 80/90 at somewhere and just call it TSF. Like there’s TFL, the French Laundry we went to. This is like TSF. And people will start referring to it, ‘Hey, did you talk to TSF? Hey, what did TSF say? Or have you tried TSF to solve that problem?’ You can just TSF it or whatever. Cause when we were up at the French Laundry, which was— how great of an experience was two days at French Laundry? I mean, just give people a little sample of how crazy our lives are now, and just getting to… go hang out with TK up there.

Chamath Palihapitiya: 1:09:02 I mean, I think being around these kinds of people is very inspiring for me. It’s like, you can be as successful as you want, but then there’s just a lot of people that stop. And then there’s a certain core group of maniacs that never stop. And I admire that, Buffett, Thomas Keller, these guys could have stopped a long time ago, they keep going and I just find it deeply impressive.

Jason Calacanis: 1:09:28 And the intentionality.

Chamath Palihapitiya: 1:09:29 And why is that? I think it’s because they’re playing their own internal game. The problem with defining your life in terms of external measure is at some point you’ll hit it

Jason Calacanis: 1:09:40 Yep. Then what?

Chamath Palihapitiya: 1:09:41 and then you’ll think, oh, I guess that’s it and then you kind of stop. And instead, I think you have to be deeply selfish about this, which is you got one trip around the sun, just never stop.

Jason Calacanis: 1:09:51 Yeah, just keep why not keep why not keep at it.

Chamath Palihapitiya: 1:09:54 All the things you want to do, just never stop.

Jason Calacanis: 1:09:56 Yeah. Be relentless. That’s another thing for these kids. I’m big on the you know how some things take like four days or five days to get good at, some take five hours. So if you look at skiing, right? Like, gosh, when you started skiing, man, it was like watching Big Bird coming down the hill blindfolded. And now you’re like, whoa, cutting S-turns, you can do a diamond but you stay on the blues, like you can ski, you can ski. Five years later you can actually ski.

Chamath Palihapitiya: 1:10:21 Ish. You’re like the Sri Lankan skier, it’s like unbelievable. You could be on the Sri Lankan Olympic team, I don’t know if there’s anyone. The only person more awkward than me is Friedberg, which gives me some solace.

Jason Calacanis: 1:10:36 I mean, Friedberg coming down a diamond, woof. Every time he comes down, it’s a knee injury. He’s I’m like, are you coming out tomorrow? He’s like, no, my knee, my hip, my this, my that. Poor guy. He’s just not built for it. But what I did with my daughter, my 16 year old specifically, was I was like what are things we can do together, daddy daughter date, that take like that third or fourth time to have the unlock where you go ooh, I like this. So pickleball, skiing, anything like that that takes like three or four times to get good at, it just builds that resiliency and once they’ve done the third or fourth one, they’re like what’s next? What’s next? What skill can I learn that’s kind of hard? There’s your hour plus with my bestie Chamath Palihapitiya. Love you, bro.

Chamath Palihapitiya: 1:11:14 I really appreciate you, Jason. Thank you for having me.

Jason Calacanis: 1:11:16 Appreciate you too, bro. Yeah. Oh, thanks for coming back on the show as one of the Twist All Stars for summer of 2026. Nine more to go folks, it’s going to be a great summer. Keep tuned in to the podcast feed. Bye-bye.