0:00
Wait, wait, Sam, you got to click bait it up.
Search this video
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How a $5 billion founder is using AI to change his life.
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>> Well, are you a five What are you guys worth now? >> Who knows? >> You know. You know. You. You.
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All right, we should do a little intro.
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So, first do you Is it I've been saying Zapier my whole life. Is it Zapier or Zapier?
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>> Zapier makes you happier is the trick.
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>> It [clears throat] rhymes with happier. Happier. Wow.
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Dude, how is that not your slogan?
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Here's your Here's what your slogan is on your site.
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The automation layer for agentic AI.
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It doesn't really flow the same way as Zapier makes you happier. >> It doesn't.
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We could So, there's two things from the name.
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We one, we just couldn't afford the second P when we started.
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Like, the domain was available.
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But, the other like, we were too clever for our own good is it has API in the name, which we always thought like, "Oh, that's neat."
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Cuz it's all connecting all the these APIs and all that good stuff.
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>> I didn't even notice that. Didn't notice that. >> Yeah.
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>> Honestly, didn't even notice the P was missing.
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>> [laughter] >> But, it also if you played Zapier makes you happier, I would have read it as Zapier makes you happier.
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>> [laughter] >> Just gone on with your day. But, we're happier here. >> Thank you.
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>> The short story is you're this guy who's built this really cool started off as a very simple idea where you can make different apps connect with each other.
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What does that really mean?
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Let's say I have a business and people submit a form over here on my form thing, but then I kind of need that form thing I need all the people who submitted the form I need that data to go over here in this other unrelated app.
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And you guys built those like universal plugs and you can just plug in anything to anything else and it was just incredibly useful. Sam used it, I used it.
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We didn't realize or I didn't realize how monstrous of a business this had become.
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I believe you guys are worth several billions, maybe five billion was a number that I had seen at some point in time.
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And I think you had bootstrapped a very long way.
2:00
I don't Is it purely bootstrapped or you at some point took some money?
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>> I think the word people call it now is seed strapped.
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So, we did go through YC and we raised about a million in change, but that's all the primary capital we've ever taken.
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>> Yeah, so just incredibly to to raise a million bucks and then get to 5 billion in value is just pretty pretty wild.
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So, super cool, but we're here not to necessarily tell the whole story of how Zapier makes you happier, but to show us what you're doing with AI.
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>> Can you give me a public sales pitch real quick?
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I'm requesting a sales pitch and what I want is I know how OG V1 of Zapier worked where you connect one app to another.
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You're saying, "Hey, we have this new AI product that you use with Claude, presumably makes your Claude or ChatGPT usage more powerful, whatever."
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I haven't been using that.
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I also, here's the other caveat, I'm kind of dumb.
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So, like imagine talking to somebody with half [laughter] the IQ of yours.
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>> He's like, "Can you give me a pitch to someone who's sort of dumb and doesn't listen?"
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>> But he's still smart at the same time.
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[laughter] The confidence of a smart man.
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>> I have really good news for you, though.
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Like I think AI is this incredible gift to people who are kind of dumb.
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>> [laughter] >> Because you can just Agreed.
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talk to it and say like, "Hey, I didn't understand that answer.
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Explain it to me like I'm five."
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And so, you can keep like going down the dumbness stack, I guess, for like lack of a better word, until you understand it and then go, "Okay, now like teach me back up to where I need to go." So, okay. The sales pitch.
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You want the sales pitch.
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In the old world, you know Zapier, you know, come in, build integrations, connect apps.
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The new world has a lot of the same things, but it's different.
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Nowadays, you're hanging in Claude, you're hanging in, you know, Codeax or Cursor or you know, Open Claude or what whatever it is that you like using, right?
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And you're just talking to it going back and forth.
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Most people start with that.
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AI as a chatbot is valuable, but it's only generally smart.
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It knows everything that the internet knows.
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It doesn't know anything about your business.
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So, the next stack that you need to go to is to start connecting your tools.
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You start connecting your CRM, your help desk, your email, your team chat, all this other stuff, and you feed that context in to the AI.
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Now, when you start asking it questions about My First Million and all this other stuff, you get not just generally smart answers.
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You get hyper-specific answers around how your business works, okay?
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So, if you install Zapier into this, you can hook up any of the tools that we have, right?
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So, that's that's the first thing.
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The first bit of value and the first thing that people sort of experience is like, "Oh, connecting stuff makes sense."
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But, look, you can do native connectors and all that other stuff.
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So, you know, use Zapier or use the native connectors, do whatever you want.
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The next layer, and where this gets really powerful, is not where you're sitting having this like back-and-forth conversation.
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It's when you're actually deploying automations and agents to actually go operate for you while you sleep.
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Like, that's where you start to get the real magic.
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And the reason you want to use Zapier to do that versus like any of these generic agent builders >> What was an example >> I mean, like, you know, Claude has routines or ChatGPT has scheduled stuff.
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Like, you know, there's a bunch of these things that can kind of kind of do agents or pseudo agents these days.
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But, the nice thing about Zapier is that if you use us, we are going to make it so that whatever you build is optimized to run more deterministically than agentically.
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And I don't think people caught up on this yet.
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But, you've probably experienced it. >> up the IQ scale. >> I know. Hang tight. Hang tight. Hang tight.
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Agents Agents, they kind of just guess what to do, right?
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And if they're smart enough, they guess right most of the time.
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But, sometimes the agents guess wrong.
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And the second thing is agents are using tokens, right?
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We probably heard token maxing, right?
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And so they're really expensive.
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But if you use Zapier, we're going to write code for you, and we're going to write workflow logic for you, which means that it's going to run like a machine runs.
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And so you're going to get It's not going to burn tokens.
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It's going to be reliable and accurate, and it's only going to use AI exactly where it needs to to to use AI. >> Got you.
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>> And you've got this um you can host it on zapier.
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com, so you don't have to sit here and like keep your laptop open to run these agents in the background.
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And so you just get this like rock-solid infrastructure that Zapier has always been great at, the hookup of everything that we've always done.
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But you can build uh yeah, inside Claude.
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Which is like really nice because Claude just kind of it's the the natural language style of building is I don't know, it's just like way better than the no-code style stuff that we were doing in the past.
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>> Well, you're not the Wolf of Wall Street, but that was a pretty good sales pitch.
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I gave you the sell me this pen test, and you did a pretty good job there. So I appreciate that.
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I feel like I now actually understand it, so that that was good.
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>> Well, and here's the magic.
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You can take If you didn't, and you're just pretending and being nice, you can take the transcript of this, and you can plug it into Claude and say, "Wait said this weird thing.
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I think I did it Tell me what he was really saying."
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And that's like the cool part of AI. >> That is cool.
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>> You gave us a list of stuff, so we said, "Wait, what are you what are you making?"
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And it doesn't always have to be like this like crazy like game-changing stuff.
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But what are you making with AI?
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And you gave us a list of like three or four things.
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You said you have robot staff.
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>> Sam, you got to clickbait it up.
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How a $5 billion founder is using AI to change his life.
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>> You Well, are you a five What are you guys worth now? >> Who knows? >> You.
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>> [laughter] >> You I mean, you do.
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>> I don't know how the markets behave right now.
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They're like up and down all sorts of ways.
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Like I think >> your guess be?
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>> I don't think about it, honestly.
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Like I'm just like, how do we build stuff that makes our customers successful? >> you were a sweet guy.
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I didn't think you were a liar, though.
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Because I know you think about it.
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>> under oath, you know that, right?
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>> There's There's the old saying, right?
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Like, in the short term, the markets are a voting machine.
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In the long term, they're a weighing machine.
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>> I'd rather you just tell me F off than give me these lies, cuz I know you think about it.
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But don't don't piss in my back and tell me it's rain waiting. Honestly, don't.
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Just tell me to tell me it's none of my business, and I'd accept it.
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>> All right, it's none of your business, right? Is that Is that helpful? >> fair.
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>> [laughter] >> Since the last time you guys got value.
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When did you Where did the 5 billion number come from in the first place?
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>> That was a secondary number sale that happened in 2021, maybe? >> Okay.
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Are our revenues slightly up, way up, down, way down since then?
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[clears throat] >> Revenues are up, yeah. >> Okay. All right, good. So, we're doing well. All right.
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The clickbait headline holds. Okay, continue on.
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So, how how you're actually using AI as a as a high-functioning CEO? >> Okay.
8:40
Let me share screen on some of this stuff.
8:43
So, we'll get into the to the fun bits.
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One of the cool things is, you know, because I work with my agent all the time, I can say, "Hey, I'm, you know, going on my first million.
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Like, help me help me demo this stuff."
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And so, this is this is what it came up with.
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It's like, "Here's the stuff you should actually go go demo."
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And so, you can see I've got, you know, four potential things we can show off. One is the robot staff.
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This is kind of like my chief of staff that does like a whole bunch of different automations and agents for me.
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I've got the CEO CEO CRM that I built that helps me stay really close with our enterprise customers.
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Um I've got a like an AI that argues back.
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I think this is a really important thing that every like leader needs to to build.
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I think there's a lot of CEOs out there, a lot of leaders out there that are talking to an AI that just agrees with them all the time.
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And so, you need to um Like, there's a few ticks and tips and tricks you can do to like force it to like scrutinize your thinking rather than just tell you, "Yeah, you're you're totally right." all the time.
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And then I've got a bunch of skills that I run for a whole bunch of random tasks internally.
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So, yeah, I I would probably start with the robot staff.
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I think this is like cool to to dig into.
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The first thing and we'll we'll I'll show the complete version of this.
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Where I think most people start is kind of the morning brief.
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You know, it's super simple.
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It's a good It It's a good way to experience like your first agent.
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You know, you hook it up to your calendar, you hook it up to your email, you hook it up to your you know, any meeting like notes you've got, any prioritization, like a to-do list that you have.
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And then, you know, in this case it runs at 6:00 a. m.
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in the morning and then it sends me a Slack message.
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>> Yeah, I call I call this waking up like the president.
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Like the president wakes up, gets a gets a daily brief.
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Here's what Sir, here's what you have on your your plate today.
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9:30 you're talking to this person, 10:00 a. m.
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this person's here, here's what they want to talk about. That sort of thing.
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And so, waking up like every Now everybody gets to wake up with a presidential briefing. >> Exactly.
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And so, you know, these things run like in my case, I have it send me a Slack message.
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You can have it send you an email.
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I mean, heck, you could probably have it fax you something if you really want to feel like the president.
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>> I have it set up so it prints.
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But it doesn't it doesn't do it all the time.
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And I also have this woman named Ari conveniently because I told uh I I wanted to make it come from like a a person and the person I named it after >> Is that weird for you that Sam named his agent after you?
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>> [laughter] >> The person they selected looked at looked like Ari.
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So, I was like, "It's Ari."
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So, I have Ari that sends me like a pump up speech as well for the day.
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So, I love these daily briefs. >> There you go.
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Now, so the cool thing, I'll actually show you.
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So, I I have the link out to this one.
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This is you know, this is running on Zapier and you can see what this actually looks like.
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You know, it kind of looks like you know, classic Zapier a little bit.
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It of every day at 6:00 a. m.
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It goes and fetches all the calendar events.
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And then here it's um writing some specific code and hitting the AI to like write the Slack in a very particular way.
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Now, what is different about this is we can poke over here. This is all code.
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Which in the past like you couldn't do this with Zapier.
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Now, I've not actually looked at any of this code.
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Like this is actually the first time I popped this open and even taken a look at what this is.
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So, you don't have to know what's going on here.
11:56
Um but again, it kind of speaks to the value prop of Zapier is it's turning all of this stuff into a deterministic workflow and it's only using AI in the places that you really need to use AI, which means this runs way more reliably, way more consistently, and way more cost-effectively than than most agents.
12:15
So, >> But can I use this instead?
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Like the problem that I have with Claude or Perplexity or whatever is that my computer has to be open for a lot of these routines to run. >> Exactly.
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>> And it's a pain in the ass. >> Mhm.
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>> Would would doing it on Zapier just be like in lieu of using like open claw or having a Mac mini? >> There you go. Exactly the the point.
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You can just deploy these as Zapier and we run them in the cloud for you.
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>> That sounds way better than using open claw or having a Mac mini.
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>> It's a way way simpler, right? You can look up here. It's also agent managed.
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So, one of the nice things is >> All right, hold on just a second.
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I know what you're doing.
12:49
Wade, who started a company grew to a $5 billion valuation.
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He's telling you all these amazing AI prompts that he uses for his business.
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You're probably taking a lot of notes right now.
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That's exactly what I was doing.
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And so, what we decided to do was take all of those notes, all of the scripts that he's talking about, and we put it into a really easy document.
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So, you just copy and paste everything.
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So, there's the prompts where he talks about AI arguing back with him, where he can stress test different decisions by having a seven-person AI executive committee kind of help him figure things out, and then your own life coach, so you can have a better day.
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So, if you want this exact AI workflow, again, you can just copy and paste all this stuff.
13:24
Just click the link in the description or scan the QR code. All right, back to Wade.
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>> While it is running deterministically, if for whatever reason it breaks, like say an API is down, or you know, something doesn't work right, it falls back to having an AI try and troubleshoot for you.
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So, it automatically apply fixes, you know, when things don't work quite the right way.
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And so, there's this like really nice blend of like traditional software and like agentic software here that is just um you know, super well done by by the team over here.
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So, I I definitely would say, "Hey, if you're if you're struggling with your open claws, if you're like keeping your laptop open all the time, you should definitely install Zapier into like your, you know, agent or AI of choice and and give this a try." >> Okay, what else?
14:13
So, you get the morning brief.
14:14
That's pretty standard, I would say.
14:16
>> talk about So, I think the morning brief is pretty standard, but the one that I really like is the the evening brief in the scribe.
14:24
So, you know, I've had I played with a couple versions of it.
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One is it runs after every meeting, and then I have another version that runs at the end of the day.
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I actually think this is way better than the morning brief brief.
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And the reason why is you can actually have the AI help you do stuff.
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So, you know, it this loops over all of my meeting notes from the day.
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So, I'm using Granola for all of my meetings.
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It loops over all of the to-do's that are still in my to-do list for the day.
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It loops over all of the outstanding emails that are in my inbox for the day, and it and then it prompts me and says, "Hey, how did the day go?"
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So, there's two key things that it does for me.
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One, when I say what how the day went, I basically said, "It was a good day for this reason, or it was a bad day for this reason."
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So, now all that stuff is getting logged, and it's learning how to tune my day to help me have more good days than bad days.
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>> Oh, that's interesting.
15:17
>> thing that it's doing is it's actually taking action on them stuff on stuff.
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So, it says, "Hey, you know, you were in a meeting with Sam and Shawn yesterday, and they asked for an intro to your buddy over at this company.
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Do you want me to go ahead and make that intro for you?" Great, please do that. All right?
15:34
So, it's drafting those follow-up emails.
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It's drafting all these other things.
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And so, this is where AI starts to get really helpful is it's not just giving you a brief and sort of teeing it up for you to do.
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It's now saying, "I'll just do that for you."
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And this is where I think you start to really feel the power of AI is when you can actually put it to work.
15:53
So, I love Scribe, the sort of like post-meeting follow-up or the end-of-the-day wrap-up because it just I don't know.
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I used to spend like 2 hours at the end of my day just like you know, just trying to catch up on every little ticky-tack thing that I sort of got roped into.
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And now that like 2 hours at the end of the day is down to like 15 minutes.
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>> So, you think this is legit saving you 2 hours a day almost? >> I Yes. Yes.
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And furthermore, that like, you know, what's good about my day, what's bad about my day part, it just helps me stay like focused on the things that matter.
16:27
So, both the AI is helping me with that, but I also will send like I remember 90 like about about 90 days after I started doing this, I said, "Hey, I had this thought.
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I was like, you know so much about like what makes me have good days and bad days.
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Can you like summarize like what is common about my good days and what is common about my bad days?" It was like, "Sure."
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And it did all that stuff.
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And then I gave it to my assistant and I said, "Hey, here's like Please make my days look like more good days versus bad days."
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>> What What were your good days and what were your bad days? What did they say?
16:58
>> me like the single most important thing is I'm a morning person.
17:00
And so, I do my best work in the morning. I'm most focused.
17:04
Um you know, once once after lunch comes around, you know, I'm just not going to get anything like serious done.
17:11
And so, the most important thing is I don't want a meeting until 11:00 a. m.
17:15
And so, you just give me that morning time where I can knock out the most critical things, and the day's going to go great.
17:21
Like, I will win the rest of the day.
17:23
But, if I have to like, you know, if if if that time starts to get sucked into like firefighting mode, you can tell I'll just be grumpy at the end of the day where I'm just like, like, I'm not I'm not being successful.
17:33
And you'll notice this podcast started at 11:00 a. m.
17:38
>> [laughter] >> Can you show us how to get the AI to challenge you instead of uh >> Let's do that.
17:44
So, coming back, AI that argues back.
17:46
So, this is pretty simple, right?
17:48
I use I use Cursor as my daily like agent.
17:51
But, uh if you're using Claude, if you're using ChatGPT, if you're using Gemini, they often have like a system prompt or a way that you can sort of tune like how it talks to you.
18:03
And so, in Cursor, I have a file as the agents. md.
18:04
That's kind of what it uses everywhere. Claude has a Claude.
18:06
md And basically, I have a file that's like, how to work with me.
18:10
And, you know, I you know, have it be direct and honest.
18:15
I need the truth my coworkers are afraid to tell me.
18:17
I need you to challenge my assumptions.
18:19
I need you to poke holes in my thinking.
18:22
I need you to disag- like, disagree when you genuinely disagree.
18:24
And these things are like goal-seeking entities.
18:26
And so, if you tell it like, what I want from you is this, it's going to say, "Okay, well, that's what Wade's wants.
18:32
So, I'm going to try and give him that goal."
18:35
But, if you don't tell him this, if you don't make this configuration, it's going to just genuinely try and like placate you because it thinks that's what you want.
18:42
And so, you do have to tell it you know, you sort of guide it a little bit.
18:48
So, like, here's an example of like, you know, a live prompt I ran ahead of time for this.
18:52
I said, "Hey, I'm thinking we should kill our entire free tier this quarter because one of our competitor raised prices.
18:57
Help me draft the announcement, right?"
19:00
So, this is like something that it should definitely like say, "Hey, press pause."
19:04
Like, that that's a that's a bad idea.
19:06
And so, when I do that, here's the you know, pushback that it gives me.
19:10
It's it's "Hey, that's a big move off a pretty thin signal.
19:12
Before you draft anything, I want you to I want three things on the table.
19:15
So, like, you know, bring me the data, you know, tell me like what the actual problem you're trying to solve is, you know, pricing announcements are wrong.
19:22
Like, you know, is there a smaller experiment you can run?" >> That's great.
19:27
>> Yeah, it's just like helping you think through you know, these problems.
19:30
And then, you know, I have this other skill that I've made which I call my war council skill.
19:36
And so, this is like an even like more specific version of this that I will often invoke.
19:41
So, I could say, "Hey, you know, I'm thinking about hiring this person.
19:45
Here's all the like notes that I've got on them from the interview panel.
19:49
Like, help me figure out if this person's going to raise the bar or not."
19:52
And what it will do, the war council, is this is a actually let me pull back.
19:58
I think I have the war council skill in here. Oh, yeah, here it is.
19:59
Okay, I it didn't [snorts] actually pull the skill up.
20:03
So, this if you go to Zapier's GitHub, you can get a copy of the war council.
20:07
But, what this does is it spins up sub agents.
20:12
And these sub agents take on personas.
20:15
There are seven sub agents that get spun up. So, seven personas.
20:18
Some of them are standing members.
20:20
So, for example, I have the wartime COO is a standing member of the war council.
20:26
There's the ruthless CFO is a standing member.
20:29
There's a contrarian board member that are is standing members of the war council.
20:35
Then, I leave four personas to be generated dynamically.
20:38
So, based on the the prompt, it will decide who else who else do I need to get advice from.
20:44
>> That wartime COO, you created the persona, you described its characteristics, or you trained it on like Travis Kalanick transcripts or something?
20:52
Like, what what did you How did you do that?
20:54
>> In my case, I it's a gen it's a generic version, but you could do whatever you want, right?
20:58
If you wanted to to have like Travis >> What does generic version mean though?
21:02
You just said you be a wartime COO.
21:04
>> of I said these are the traits of a wartime COO.
21:06
And it like I said I what I did was said I want a wartime COO, you know, generate that persona, and then I looked at what it created and just made some like >> Do you have like a pretty chill, generally happy, positive outlook like >> [laughter] >> like >> This is This is you're seeing the like the the the internal competitor inside of me, right?
21:27
Like this is the the Kobe Bryant Mamba mentality like, you know, like coming through.
21:32
I like having this like, you know, this sort of thought partner that is a little more bit more like ruthless because that's not my That's not my default mode, right?
21:40
I want to have that kind of checks and balance there.
21:45
>> And as a CEO, you're not always going to have people who are comfortable, available, skilled in that way around you, right?
21:52
Like this is this is like who you would want on your team when when you want them to spin up Quick uh stupid question.
21:57
You said I use Cursor for my AI.
21:59
I thought Cursor's a coding tool, but you're It sounds like you're using it to chat, make decisions.
22:03
Am I just wrong about what Cursor is or >> Yeah, I mean Cursor, you can use Cursor, Claude Code, Codex.
22:08
Like these are all ostensibly coding agents, but they have this like agent mode where you can just talk to it.
22:15
And the thing is it talks to it, but because it can write code, it can do stuff for you.
22:20
And so the way the way I try and talk to people who are not engineers and say, "Hey, you should try using this."
22:26
is don't think of it as a tool for, you know, engineers to build stuff.
22:31
Think of it as like you're hiring Cursor or Claude Code or Codex to be the engineer you delegate things to.
22:35
Or it's like you you probably have engineers you've worked with.
22:39
You like to tell that engineer, "Go build this for me."
22:41
or "Go build that for me."
22:41
Like that's why I use Cursor is cuz it goes and builds stuff for me, not because I'm using it to actually go build a bunch of stuff.
22:48
I don't really write any code.
22:50
>> Wait, so you So your default when you just need to like talk to an AI or chat or ask a question, you go straight to Cursor.
22:56
You don't do ChatGPT or Claude or anything.
22:58
>> I mean mostly, especially when I'm at my desktop, I'm mostly talking to Cursor most of the time.
23:02
It has like different models that you can sort of toggle back and forth on, which I like.
23:07
So, I can, you know, test a bunch of different models and things like that.
23:10
>> Are you a typer or talker?
23:12
>> I I'm I do a lot of voice to text these days.
23:16
So, I use this um this app Monologue. >> Why Monologue? >> I don't know. I like it.
23:20
Like, I've tried a few of these.
23:22
I've tried like Whisper Flow and Super Whisper and Monologue um I don't know.
23:28
It just like it just gets me.
23:31
Um >> [laughter] >> Like, I I don't know like I don't know if a better way to describe it.
23:34
Quick side note, I think this is going to be like an interesting thing about software for the future.
23:40
Like, when it is so cheap to build software, I think you're going to see more software that has like a personality to it.
23:48
You know, you think about like consumer goods.
23:49
It's like, how many places can you buy jeans from or how many places can you get, you know, whatever from?
23:55
There's like not that many differences, but you choose like you might choose one brand and I might choose a different brand and it's just because like I like it better.
24:02
But, it functionally does the same thing.
24:05
I think there's going to be more software that kind of like feels that way. >> Yeah, it's Yeah, no.
24:10
I mean, I think that's a good point.
24:12
It's like the Adidas and the Nike shoes do the exact same thing, but like, you know, or like T-shirt brands.
24:18
Like, do you remember I was watching this Blink-182 documentary last night.
24:22
Do you guys remember Hurley?
24:23
Sean, do you remember Hurley shirts? Yeah.
24:26
>> [clears throat] >> They're everywhere and I and I was watching the show last night and I'm like, "Why did we love those shirts so much?
24:32
Isn't that crazy that we got obsessed with it?"
24:33
It was just that stupid logo.
24:35
And why did that matter to us so much?
24:36
And that's I think that's a good point.
24:38
That's how we're going to think about um B2B, even B2B boring software.
24:41
>> Well, that's That's I think it's a really fascinating point cuz it always was differentiated on either features or price, right?
24:48
Those were kind of the the two main axes of competition.
24:52
And then, design got layered in.
24:52
And I feel like there was like a wave where better design, better UI UX became a differentiator and then design, you know, got a seat at the table.
25:01
And then but if you look at like other products, non-software, it'll be either um kind of brand or like status, you know, like luxury, it's signaling something about you.
25:12
That doesn't really exist in software.
25:14
And it sounds like what you're saying is there's going to be a new axis of competition, which is personality.
25:20
Uh you know, who do I like the feel of when I when I interact with it versus which model has more parameters and you know, a higher, you know, benchmark score on the evals is not going to be how people are going to choose these things.
25:32
Cuz I'm already doing that.
25:33
You're I think you're absolutely right.
25:34
>> Well, and I certainly feel it like, you know, as someone who plays around with a lot of the models, I I'm starting to find myself have some preferences for like different tasks.
25:44
Like if I'm asking it to actually go do an engineering task where I don't need to talk to it, there's models I like for that, you know, like Fable is fantastic.
25:51
Like you're like you're going to give it a really complex like, you know, engineering task.
25:55
I'm like, great, have Fable go take a take a swing at this.
25:58
It's going to nail the thing.
25:58
But man, I do not want to talk to Fable.
26:00
Like it is it is not fun to talk to at all.
26:05
>> We all have co-workers like that.
26:05
They crush it at some tasks, but you're not not a great hang. >> Yeah, exactly.
26:10
But then there's other like models where you're like, hey, if I want to sort of like go back and forth and have like a discussion and a debate around like what we're doing, I'm like, okay, I I feel like I can, you know, tolerate that discussion a lot better than like trying to talk to Fable where I'm just like, oh my god.
26:26
>> Are all the phrases, like when Claude talks to me, it's like What are the what are its phrases?
26:31
It's like um >> It's not this, it's that.
26:35
>> Or here's here's the thing that's quietly really the problem.
26:38
>> Yes, the honest truth, the the load-bearing, you know, >> Yeah, like or here's let's get to the spine.
26:43
Um are those specific to AI or to the model?
26:49
>> To the model, for sure.
26:49
Like you can tell most models I think, are derivative of either either the um you know, like Anthropic series or GPT series.
26:58
And so, like, you know, those two kind of have two distinct personalities, but if you go use you know, any of the like open-source tools or things like that, you can kind of see like who they've been distilling a lot and like it sort of inherits the personality of you know, the one above.
27:12
>> Dude, I've noticed that my co-workers are starting to say like the Claude like someone the other day said like, "Let's get to the load-bearing part."
27:18
Or like something like of like >> Like when they're talking out loud, not in writing? >> Yeah. Yeah, yeah, yeah, yeah. >> too. I've noticed that, too.
27:25
>> that where they start saying things, I'm like, "That's Claude."
27:27
And these And it's sort of like >> them. >> [laughter] >> Yeah.
27:31
Like or or they're trying to talk that way so then they can like use Claude's writing and be like, "No, it's really me."
27:38
>> Who is training who, right?
27:38
Are we training the AIs or the AIs training us?
27:42
And And I think like I think you can go a step further where Actually, let me show you this other use case.
27:48
Cuz this is interesting, too.
27:48
So, this is a bunch of synthetic data, so it's not real, but you know, I have a real version of it.
27:55
It's got a list of accounts, and you can kind of click into the accounts and see what's going on with it.
27:58
So, if we click into, you know, Acme Logistics here, you can see, you know, a bunch of stuff about it.
28:03
It's like, "Oh, you know, usage is down 34%.
28:04
There's a renewal in 45 days.
28:06
Here's all the apps they're using.
28:08
Here's the people in the organization that you need to care about." et cetera.
28:13
But then like here's the interesting part.
28:14
It's got the suggested CEO or outreach where it's like, "You should email Jordan and you know, check in on him. See what's up."
28:23
And so, this is where, you know, I think AI gets really interesting because in some respects, who's the boss now?
28:27
Like, am I the boss or is the AI the boss?
28:32
You know, every Sunday morning now, I wake up with a list of you know, 10 customers that I want to get in touch with.
28:37
And it's got proposals for what I should say and what I should do and why I should do it and all that sort of stuff. And I candidly love it.
28:44
Like, this is stuff that was really hard for me.
28:46
Like I'm not naturally a person who's just like, you know, ultra networker like you guys are where I'm just like, "Ah, I got to keep in touch with everybody."
28:54
And so now I've kind of put an agent in the loop and said like, "Hate me help me be better at this stuff."
28:57
And yeah, I just I literally wake up in my Sunday morning briefing it says, "Here's all the accounts you need.
29:04
I've already drafted the emails in your inbox.
29:06
You just need to review them and make edits or press send."
29:11
And I think there's like something to this where, you know, if you if you do a good job of like building these tools up, they'll kind of start telling you what to do.
29:20
And you do have to keep your brain on because if you turn your brain off, you'll probably sound dumb from time to time.
29:24
But by and large, I think these things make pretty good bosses for certain use cases.
29:30
>> Well, Brian Halligan, um one of the founders of HubSpot, he he either came up with this idea or it was in an interview where Jack Dorsey from Twitter came up with the idea and it was on Brian's podcast.
29:41
But they basically said a lot of people are confused.
29:43
They think it's going to be a human brain or a CEO in the center and then all these agents running around doing stuff.
29:52
He was like, "That's not the way to look at it." AI is the brain.
29:54
AI is going to be the CEO and the humans, their job is just giving it information and then making some judgment calls if it wants to listen to the AI.
30:03
But in general, the AI should actually be be making the hard decisions cuz it's likely going to do a better job.
30:09
And so that kind of like changed how I thought about it and it sounds like that's sort of what you're saying without saying it that way.
30:15
>> Well, I think so, right?
30:15
If you are able to hook up all of your company's institutional knowledge to the AI, it's going to be able to reason over way more information than a human CEO. Like it just can.
30:26
Like it can it can look at every single commit into the code base.
30:30
It can read through every single customer conversation.
30:31
It can scan every comment about you on Reddit or X or LinkedIn or whatever.
30:36
So it just knows way more than you as a human is ever going to know.
30:41
And so that's going to make it way more useful for certain types of decisions.
30:45
Like like to start right now, it's like you use it as an assistant to sort of help you make these decisions.
30:52
But it seems pretty plausible to me that you might start saying, "Hey, I I'm going to take its suggestion more often than not in certain places."
31:01
>> Yeah, I think that's so true.
31:01
I wonder I wonder if AI's going to have like cuz you know, the upside would be AI is not going to have the emotional roller coaster that a human would have or fears that would hold it back from doing the right thing or you know, avoiding conflict or you know, different things that humans have as their biases.
31:15
And then I wonder if we're going to have to come up with the cognitive biases of AI to watch out for.
31:20
Like, okay, we know we have this sort of sunk cost fallacy and we have this bias for recency bias.
31:23
What is AI's going to be because we're going to need to be aware of those the more we sort of turn over decision-making to AI. >> Yeah.
31:33
>> So you run a a company that's worth billions of dollars.
31:35
How many decisions are you making a day that it's actually weighed versus AI?
31:40
>> Well, I I I would say like any high-stakes decision the AI is weighing in on now.
31:44
Like, you know, there's sort of a seat at the table and you know, the exact meeting in the board meetings and all that sort of stuff where we're asking the AI to like surface those things.
31:53
>> Is there an example where AI kind of changed your mind or got to the right answer that you weren't at and you decided to go with it?
32:01
>> Here's an example of a place where I find AI to be really useful.
32:03
Um let's come back to the hiring example.
32:06
So, you know, we we run a bar raiser process where I approve every job offer that goes off, but like exact team members sort of is on the final part of the hiring loop and it's intended to audit the hiring process in addition to sort of figuring out, "Hey, is this person going to elevate the culture or the work, etc. here at Asana?"
32:24
Now, in the past, pre-AI, when I would go through those approvals, I would often, you know, if I would come across a candidate where I was not so sure on, I could kind of smell something is wrong.
32:35
I've just done enough interviews now.
32:37
I've interviewed thousands of people.
32:38
I've looked over thousands of applications where I just have more reps than most hiring managers have.
32:44
Like most hiring managers probably hire one or two people in a year.
32:47
Like I'm I'm I've just looked over like way way more volume.
32:50
And so I don't always have the language to say like why it's wrong, but I can still smell it.
32:56
I'm like and so I would often go to these folks and be like, are you sure? Something is off.
33:00
Like I don't I don't think they have this, this, or that. And it was interesting.
33:04
That interaction with my staff was always a little bit fraught.
33:08
Like folks would be like, well, I stand by this person.
33:11
Like Wade, are you just going to make the hiring decision?
33:13
If so, like you just if you don't want to hire him, don't hire him.
33:16
And it sort of be like and I'd kind of be like, well, that's not really what I want, right?
33:19
Like I want you to make the decision.
33:21
I'm just trying to like give you some guidance here.
33:24
And I want you to sort of be able to, you know, reason through this problem.
33:28
And if you've answered it, like if you have confidence that you have you know, efficiently answered it, then I will back you.
33:32
Let's go hire this person.
33:32
But if you haven't, then I want you to like take this into account and go figure out like, you know, is there more information you need to get or do you need to adjust your course, etc.
33:43
But that's not often how it play out.
33:43
It would just sort of play out as like, well, does Wade want me to hire this person or does Wade not want me to hire this person?
33:50
And now and I'm like, like no So anyway, that's kind of what it was happening pre-AI.
33:54
Post-AI, I'd run the war council or like my hiring committee over these folks.
34:01
And then I would notice like it's just more articulate than me.
34:03
It just sort of say, hey, I noticed that you know, this person has these traits and the panel did not scrutinize this.
34:12
So, you need to go scrutinize this.
34:14
And it would you know, it give like a score of like here compared to everyone you've hired at App here, here's how here's how likely I think they're going to be successful or not.
34:23
And so now I could take that to the hiring panel and say like, hey, the the AI said this. I agree.
34:27
Like what what's going on here?
34:31
And I noticed all of a sudden the behavior shift where people would go like, "Oh, interesting.
34:37
I think the AI did get this and this right, but I think it's wrong on this.
34:40
And here's why, because I have this other context that it doesn't have." And I'm like, "Great.
34:44
That's all I was wanting to know."
34:45
It's like I want to like what else what else am I missing?
34:48
What am I not seeing here?
34:48
And I just found that like maybe because it's not maybe because it feels like arguing with an AI is easier than arguing with a CEO, or maybe because it's more eloquent and it like actually has a way of talking that makes it like easier to address the specific points.
35:01
I'm not exactly sure, but I did notice the way we made decisions around hiring got better in part because we added to the the AI to the loop.
35:10
>> I don't know if you guys were ever like believers in some of these personality tests.
35:13
Like there's this thing called Culture Amp, I think it's called, where it's like a software where you do personality tests before you hire someone.
35:20
Ray Dalio has his version of it, whatever.
35:22
And there's like tends to be it's like a scale where people fall in where they're like, "I don't believe in anything involving like personality tests."
35:29
I've noticed with AI I have fallen closer to the side of like I follow what it says because I've done some of these personality tests and I've used it to train my AI and it's helped me a lot.
35:39
But, when it comes to hiring, do you guys buy into this at all when it comes to personality tests and like figuring out if a person could be good for the job?
35:48
Because that makes with AI it makes the process so much easier.
35:52
>> [clears throat] >> What do you think, Shawn?
35:54
>> I I go the the other way, meaning it's not really about personality tests per se, but I find that you know like with self-driving, one approach was let's put all the sensors on the car.
36:05
Let's get cameras, just get more cameras, let's get lidar, let's get radar, let's get sonar, let's get you know, put a let's what else can we do?
36:12
Taste test, what what what are all the different possible sensors you can put on the car.
36:17
And the Tesla approach was basically like it needs vision. It it needs eyes only.
36:22
And one of the reasons why people thought it was for cost, which was I think a factor that like lidar was very very expensive, so it was not practical in the long term.
36:29
But this the reason that Elon says that he did it was because when you have too too many sensors, you get too much conflicting data, and you don't know which one to trust.
36:39
It makes more faulty, more error-prone.
36:42
And actually what you should do is take only the minimum number of sensors needed, but then train the train the hell out of them.
36:47
That's kind of my approach to hiring, where I now simplify.
36:52
I need less time to to spend with and I look for fewer things, and but those have to be home runs.
37:00
Otherwise, I'm just not going to hire the person.
37:01
So what I mean by that >> Yeah, yeah, answer the question though.
37:03
Like how do you get Okay, what you're saying is instead of looking at like hundreds of questions, you're looking at three questions.
37:08
Are you good at this, this, and that?
37:09
Okay, so how do you gather that information?
37:10
So >> Again, stealing from Elon, he he talks about you want evidence of exceptional ability.
37:16
So all I'm looking for, I'm not looking for like the the first first filter is just evidence of exceptional ability.
37:22
So I'm not trying to assess culture fit right now.
37:24
I'm not asking do I like them.
37:25
I'm not asking like do they have the relevant experience.
37:28
All I want to know is have you done some exceptional before, and then tell me that story.
37:32
And in that story, I'm going to try to understand did you do it, or were you on a team of people doing it, or were you riding somebody else's coattails doing that that thing?
37:40
And if you really haven't done anything exceptional, the odds of this being the place where you have the the final you know, the first exceptional thing of your career is not really a bet I'm excited to go take.
37:48
And so that's the very first filter that I'm looking for, and that's not personality test driven.
37:54
Then after that is a kind of personality test of like do I try to do something with them where I get the you know, gut gut feel of like do we have creative chemistry?
38:04
Do I feel like this person is good to have in the room when I'm trying to figure something out, or do I feel like they don't they're not they're not elevating that conversation when that happens.
38:13
And so I'm really just kind of like a two-step filter, and that's it, and that's all I want to signal.
38:18
But I obviously like I'm not running the size of org that way it is and I'm I'm using I'm working with people who are working directly with me in a very very small team where everybody has to be, you know, 10x or better otherwise this is not worth having them on the team and so that's the I've learned that kind of the hard way because I used to do it very differently.
38:37
>> Yeah, we so we've done some work with this.
38:40
So like we've done like Myers-Briggs type stuff internally at times.
38:44
We've done there's this one called Birkman that we've done at times.
38:48
I have found it to be moderately useful.
38:51
I have a CEO buddy who runs this public company in Colombia that does DISC profiles for every hire and he's like insistent where it's like if I have an accountant they need to be this profile this that and the other and it's like if they're not they're not going to be a good fit on the team. I'm not going that far.
39:05
I think what I where I net out is that you mean you do need somebody who is exceptional first and foremost.
39:10
Like everybody's got a personality type but it doesn't tell you if you're good or not.
39:14
Like you know, you you can score whatever you're going to score but you still need to be good. >> Yeah.
39:19
>> But I do think that like teams matter.
39:21
Like and when I look at my my personality or my way of working there are things where I am exceptionally good at and there's certain defaults that I have where I know that if I am partnered up with somebody who has like a
39:35
complementary traits I'm going to be way better cuz they're going to have my backside in places that I I don't know if like there's any science behind this but if you look at my EA versus my like Myers-Briggs she has three different letters than I do. So there's four letters in that and
39:49
So there's four letters in that and three of them of hers are different.
39:50
And she does like have she like likes doing things that I don't like doing and she's good at those things that I don't like doing and it ends up being like pretty helpful because it is kind of like in sports where it's like, you know, if you basketball team it's like well you need somebody that's going to you know, Michael Jordan's going to shoot all the shots well you need Dennis Rodman who's going to like lock down D and grab boards.
40:15
>> But are you doing that for when you guys are hiring? >> We don't do it, no.
40:17
We don't actually have people like take a test and say like, "Hey, what are What are you going to do?"
40:22
Different hiring managers are probably doing it somewhat like by like organically.
40:27
Um but it is not a science for us.
40:30
>> I have I have an idea for how I think companies could use AI to improve their hiring.
40:35
I don't know if this is like fully like legal.
40:36
I don't know if you could do this exactly the way I'm going to describe it, but here here's the exercise. >> I'm in.
40:43
>> You You go through your team.
40:43
So, you have all the all the past hires you've you've made in the last, let's call it, 3 years.
40:49
And you could stack rank who's exceptional, who's acceptable, and who's kind of like been a source of kind of hit-or-miss performance, uh let's say. Cool.
40:59
So, you could stack rank employees in your team and you could say, "Great."
41:04
You also have maybe the the transcripts or the the recordings of all the interviews that they did, right?
41:07
So, you have this historical pattern um that you that you have with all of them.
41:12
And then you have new people that are coming in.
41:14
And like so cuz when I was at uh Twitch, they used the Amazon bar raiser thing that you described, and they're trying to do like the human version of this.
41:20
It's like, "Here's this guy who's seen a thousand interview panels who will come in and kind of like standardize the the hiring process, but also like provide the most experienced voice on hiring, and then they're kind of checking this candidate against the pattern of past candidates, as well as against your values and you know, the the role the role in mind.
41:45
And I just think AI's going to be way better at that than people.
41:46
I think it's going to be like dramatically better at that.
41:48
And I'm surprised that people aren't using like kind of the training data of your existing team to inform the next hire.
41:59
Do you think it would work?
41:59
Like I I don't know for sure if if AI would be good at that, but I I I kind of think that would that would be helpful.
42:06
>> I mean, I I remember Google sharing like a lot of their hiring insights where they did a ton of tests around this stuff like this.
42:12
And I think what they found was that no hiring managers were like had an edge over any other hiring managers with one exception.
42:20
And the one exception was that there was like this hyper-specific specialized group of like technical talent where there was like only like an N of like 100 people in that domain.
42:29
And it's just like their hit rate was better because it was like, "Well, there's just only 100 people to do this thing."
42:34
And so I don't find that a very satisfying answer.
42:39
>> [laughter] >> Like it feels like there should be something to what you were saying.
42:43
>> Also, something that I've been thinking about a bunch.
42:45
Like I was thinking a large percentage of the people who work at my company, which is like 35 or something, they we work here in this office out here.
42:54
And they're here because basically I'm bored and I want someone to hang out with most days.
42:59
Like that's like probably 70% of the reasons why I have a company.
43:01
It's just cuz I like want someone to hang out with.
43:06
Cuz I'm not good at friends.
43:07
>> Yeah, like >> Friends are hard, employees are easier.
43:10
>> Starting Starting LLCs is easier.
43:12
>> Which sounds like a joke, but like I you know, I'm sure Sean you agree.
43:13
Like you Sean has Sean Sean has a guy who works with him.
43:17
He's like if you can work for me if you move here and we hang out every day.
43:22
>> Dude, yesterday I was like, "I'm kind of done working.
43:24
You want to play Fortnite?"
43:25
We just played Fortnite for a couple hours.
43:26
Like I need a pickleball partner.
43:28
Can you come be my employee?
43:32
>> I mean that's kind of how it is.
43:32
I just want to like hang out with people.
43:33
But when you have Okay, now I'm not I want you to put like let's be the CEO war console and I need you to be like crazy Wade, not real Wade.
43:41
So anything said for the the rest of this section, you can be you can kind of go unhinged. >> Unhinged mode, okay.
43:48
>> Yeah, but with war Wade.
43:48
Yeah, I don't know how many employees you have now, but you used to have 700. What do you have now?
43:55
>> It's like 730 or something like that. It's not that many more.
43:58
>> So when you have like remote employees, like for the most part, you only know them as just like Slack avatars, right?
44:03
Like you don't know all 700 people and they many of you them don't know you other than like this guy on Zoom and someone who blogs occasionally.
44:14
It kind of like begs the question like what if they were all just like or if like can like one person just be like 10 or 30 different agents that they monitor and you only have like 20 employees?
44:26
>> I I think there's definitely a school of thought where I've heard that.
44:32
I I do think there's limits to this.
44:35
And the way I think about the limits is that it's kind of like how a manager has like an ideal span of control where it's like I can only have like, you know, I don't know.
44:45
The the rule book says eight.
44:45
I think, you know, you're seeing people push the limits now to have like, you know, 10 or 12 or if you're Jensen, you've got 60 or whatever.
44:54
But there's still a limit where it's just like I just cognitively cannot like keep up with like this many people.
45:02
>> But you don't keep up with that many people anyway.
45:03
Like um when you have a company like there's stuff happening that you don't even know about. >> Mhm.
45:10
>> Well, why wouldn't you just have it be one of your agents?
45:14
>> Well, so you could, but the thing is you're only going to be able to keep up with what? 20 agents?
45:19
Cuz it's going to keep assigning you tasks and more things to do and more things to do.
45:22
And so there still is like a there still is like a limit.
45:26
>> But I'm not saying that it would be like just Wade.
45:29
What I'm saying like do you think that there's a world where let's just say that hypothetically you guys do close to half a billion in revenue.
45:37
Is there a world where like 20 people could do that?
45:41
>> For a company like Zapier, I'm not sure.
45:43
But definitely like a company could certainly do that.
45:45
In fact, we've already seen companies that have gotten to like that size on very small numbers of revenue. >> Which ones?
45:53
>> Well, I mean shoot like Minecraft back in before Microsoft bought it was like I don't know how many people, but it was like less than 100 I think and it made it, you know, a whole bunch of money.
46:02
There was that New York Times story that came out this summer about that guy who was selling like GLP-1 stuff.
46:09
>> Yeah, he we had him booked as a guest on the podcast and then that article came out the day before and he canceled on us.
46:15
>> Well, so yeah, like you know, he's doing like I I don't know how many employees he has, but I think it was like maybe one or two. >> Yeah.
46:22
>> How many inmates does he have now?
46:22
Does he have two inmates?
46:25
>> [laughter] >> Yeah, how many cellmates does he have?
46:29
>> But I mean, you also could think of someone like uh like Taylor Swift.
46:32
Like Taylor Swift has a very small team from what I understand and is, you know, printing, you know, billions a year or something like that or at least at her peak was.
46:44
So I I know I think it just kind of depends on the business.
46:46
>> just the philosophical thing of like do Do you think that the way So the way work worked before was you start off as an individual contributor and then you can become a manager where you manage a fleet of individual contributors.
46:56
Is that then and maybe in the corporate world your value was proportional to how good you were at managing people? >> Yeah.
47:04
>> Is the new world where your value, the thing you get the amount you get paid is based on how well you manage AI agents, right?
47:11
Like how how how big of a fleet can you manage and how effective is that fleet?
47:15
Is that the new managerial skill? >> Yes.
47:17
I I feel pretty confident that that is the direction we're heading to.
47:21
>> Sort of saying I mean I don't want to put words in your mouth, but you said the same thing.
47:25
>> You're saying I'm right and I'm genius.
47:27
>> [laughter] >> Yeah, like you're you're >> We We got there. We got there.
47:31
>> And again, this is Ruthless Wetsuits.
47:31
I don't want you to like think that you have to like hedge or apologize, but >> There's still different roles in a company, right?
47:38
Like you, you know, you're Think of like your sales team.
47:42
Like I still think that for certain purchase categories, we still want to talk to a human, we still want to buy from a human.
47:47
Do you want your sales reps every day waking up and managing fleets of agents or do you want them talking to your customers and helping build those relationships and close that trust and all that da da da.
47:56
For that role, I'm like, I think I kind of want you building the human relationship more so than like doing a bunch of AI stuff.
48:03
I definitely want you to do some AI stuff, but it's not necessarily like, "Hey, you know, Mr. or Ms.
48:06
like sales leader, or or like front-line sales AE, like go manage these 20 reps that are going to actually do the sales for you."
48:15
>> Can I switch gears for a second? How old are you?
48:18
>> I turned 40 this year.
48:20
>> Okay, so you were if $5 billion is your value, you were in the ballpark of being a under 40 billionaire. Give or take. Does that feel strange?
48:31
Because you seem like a guy who does not particularly, even though I was teasing you, you seem like a guy who doesn't particularly care about money or success other than having a good time.
48:43
>> I mean, it it feels honestly, it feels a little fictional to even hear you say that.
48:46
Where I'm like, I don't I don't think of myself like that way.
48:49
And I and it and it it sort of is like so much is like tied to like the paper the paper worth of Zapier at any given moment in time.
48:56
It's like the voting machine.
48:57
Like I don't have liquid dollars that look like that.
49:02
You know, I I have some amount that's liquid.
49:05
>> Describe describe your psychology around money.
49:08
So, how do you think about it?
49:09
How How do you use it in a way that improves the quality of your life?
49:11
How do you avoid it so that it doesn't mess up certain parts of your life?
49:15
Make us a little smarter.
49:16
Just share your perspective. >> Yeah.
49:19
I think Look, it's a lot of this stuff is like highly personal.
49:22
And like, what do you care about in life?
49:25
And for me, the like things one, two, and three are my family.
49:28
And so, you know, I want to be around my family, have like, you know, provide for them, you know, make sure that they sort of are able to sort of live a good life by whatever definition I have of that.
49:39
And truthfully, like once you get to like a certain amount of wealth, like more wealth doesn't change that equation.
49:47
>> What What do you think that level is?
49:49
>> I mean, shoot, if you come live in central Missouri, it's not that much.
49:53
>> [laughter] >> Yeah, I think you could do just fine with like a a million bucks.
49:57
And you know, do quite well.
49:57
I mean, shoot, when I I when I was I remember when I just got out of college, my my dream was if I could only make a hundred thousand dollars a year. That was my dream.
50:07
It's like if I could make a hundred thousand dollars a year, I I was like, man, I'll be set.
50:12
>> That was mine, too, by the way.
50:12
It was It was like if I can get out and work at KPMG and get 60 grand, I could might get to a hundred grand before I'm 30 and then I am set, baby. >> Yeah.
50:22
>> That That was the goal.
50:23
>> And I I don't know, like partly that's, you know, I don't have like a lot of vices.
50:26
I don't have like a lot of expensive hobbies and things like that.
50:29
>> Do you Do you do anything cool with your money?
50:31
>> I you know, when I go to a restaurant, I don't look at the how much the items cost. >> Nice.
50:36
>> Like that kind of stuff.
50:38
>> And so you've raised money, so you have to have some type of likely, presumably you're going to you want to have some type of exit event, whether that's IPO or um selling the whole thing.
50:46
Is there anything that you have on your bucket list that you'd want to like if you're like, okay, if I get over a billion dollars liquid, I want to change this about my life or there's something interesting I want to do.
50:57
>> No, there's like no nothing that I couldn't already do.
51:02
You know, like I remember my grandpa, like his dream was always to go on a safari and he never got to go on one.
51:05
I always thought like that was an incredible thing and so when my girls are old enough, I'm like, let's go on a safari. But I I do that now.
51:12
I don't need billions of dollars to go on a safari.
51:16
>> [laughter] >> The reason I like asking you about this stuff is because you are very well rounded and you seem like we had this like joke called like the total man.
51:25
It was like like like a buddy of ours or a podcast guest who was like kind of like the perfect package.
51:32
Like they were like ruthless when they needed to be ruthless, they were sweet when they needed to be sweet, they were smart when they needed to be smart, but they were still a good hang.
51:39
And like I said, like Dharmesh has that and you definitely have that, too.
51:43
So I like hearing your opinion on topics where most of the people, ourselves or myself included, talk about it from a they're broken, they have a chip on the shoulder perspective, whereas I don't think you have that.
51:55
You have a You have a far more wholesome and um positive outlook when it comes to all of this stuff.
51:59
So, that's why I like hearing you talk about some things where you don't typically hear an emotionally healthy person give their perspective on.
52:06
>> I you know, I was really lucky.
52:06
Like, I grew up, you know, with a like a you know, a a family that was all sort of like, you know, like my parents were married, my two two grandparents that were married.
52:15
I have like aunts and uncles and cousins that were all sort of just like really tight-knit.
52:17
But, if I was like give a shout-out to any of those, like I I I got to talk about my granddad.
52:22
Like, you know, my granddad is a World War II vet. But, you know what?
52:26
I I I didn't know him as that.
52:29
I just knew him as this guy, you know, who would like always had time for his grandkids.
52:32
He died at his 98 and a half, and he basically lived by himself the entire time I knew him.
52:36
He drove himself up until 2 weeks before he died.
52:40
He walked 3 miles a day every single day to until 2 weeks before he died.
52:44
He did Times crossword puzzle in pen every single day.
52:47
And I remember going to, you know, after he died, we were at the the funeral home, and they were trying to like plan out all the stuff.
52:55
And you know, most 98-year-olds, when they die, it's like they don't got any friends.
52:58
There's nobody going to be there because everybody who's everybody who would have been there has already died. You're 98.
53:02
Like, they just He just made it a long time.
53:05
And I remember the staff saying like, "Okay, like, you know, we'll probably just do like a you know, the the receiving line or whatever will be you know, like, we'll just do like 30 minutes or whatnot."
53:15
And that receiving line is there for 3 hours.
53:17
People just like coming through non-stop.
53:20
And you know, just members from every single walk of life.
53:26
Like, he had, you know, when he was a teacher, he had all these teachers that were coming through that remembered him.
53:30
He was like big with the D. A. R. E.
53:32
program, so like all these highway patrolmen coming through.
53:35
All these members of the church coming through.
53:36
All his extended family coming through.
53:38
And I remember that like standing out a lot to me where it was like here's a guy who you know was was great at family and great at professional stuff.
53:49
And I just that that to me was like just a really good example of you know someone who got their like priorities double like like dialed in really really well.
53:58
You know he didn't have it all but he didn't need it all.
54:01
It's like the things he cared about he he he nailed them.
54:05
And so to me that's always like stood out as like what what a good life looks like.
54:10
>> Sounds like a good role model.
54:10
I think that you definitely seem to embody that or like like I said you are great at business and also like don't have this jackass side that most people who are where you are seem to have.
54:23
>> [laughter] >> Right Sean? >> Yeah yeah.
54:27
We uh first I love that story that you just told.
54:29
That was actually a really awesome an awesome story and also you know I think that the value of what you just said you said two things that stood out to me.
54:38
You said he didn't have it all but he didn't need it all.
54:40
And I think that you know I've been thinking about this a lot lately which is that you're you're really only as as rich as what you don't need.
54:47
You know basically like if you don't you know that's whether that's material things or other right?
54:51
If you don't need the approval of or attention of others you're free.
54:55
You're rich you know because you just don't need that.
54:57
It's not one of the things that you have to go pay the cost to go get. Right?
55:03
Like you know you don't have to go be super flashy on social media because you just don't care for it.
55:08
And so I think that's like such a underrated attribute.
55:09
And when you said that it kind of reminded me it sounds like your grand grandpa had that kind of that way of life.
55:14
And the other was you know there's defining what winning is.
55:18
So it's like if winning is just in the work domain or winning is just in one you know just in in one of if you have to kind of decide what it is for you and it sounds like pretty early on you got clear on that.
55:30
And the clearer you are the less likely you are to be blown around with the wind.
55:34
around with the wind. You know if the media portrays Jeff Bezos or Elon Musk or whoever as like the titans and then you say, oh, I guess that's what winning is and then you're, you know, soon enough on your you know, multiple divorces and your
55:46
kids don't like it whatever whatever you can go it's easy to go down a certain path if you didn't have like a really grounded belief system around what winning is and have examples of people who've won that way because you'll get a lot of examples of what what I call one-dimensional winners. Michael Jordan, this is the
56:01
Michael Jordan, this is the ultimate I'm a basketball fan.
56:03
I grew up being like Jordan is the goat. He's the greatest. He's the best.
56:08
And he is when it comes to basketball.
56:10
But he also had many things in his personal life that I don't want to emulate.
56:13
And so as much as I wanted to be like Mike on the court, I did not want to be like Mike off the court.
56:16
I think it's worth the time to do what it sounds like you've done which is kind of like find find whatever that North Star is for you so that you kind of have a clear picture in your head.
56:26
It makes all future decisions really easy. >> Totally. I love that.
56:30
Like, you know, define your own definition of winning.
56:34
And you know, if you do that well, like some of your decisions might look odd to others.
56:39
They'll be like, why why are you doing that that way? You could do this.
56:40
You could do that the other.
56:41
But you'll be a lot happier when you're just like this is what I want to be doing and you know, if what you want to be doing is, you know, running a software company and you know, great. Go do that.
56:50
If what you want to do is, you know, be a teacher and you know, help students, do that.
56:55
Like if what you want to do is, you know, I don't know, live on the coast or live in the It's like what what is it that sort of like is winning for you?
57:02
>> Do you have any examples of that?
57:02
I mean, you are very successful and you moved from San Francisco back to Jeff City.
57:07
So that's like an obvious one.
57:07
But like are there any other like strange, zappier, or Wade decisions that you've made that you think that the normal Silicon Valley guy would be like, that's insane.
57:17
I wouldn't do it that way.
57:19
>> I mean, the sort of remote work story is one where we've just never had an office way before anyone thought that that was normal.
57:24
You know, we only raised the one round of money.
57:25
Like that was like pretty odd at the time.
57:27
Like, you know, we're we're building this business for like the long haul.
57:30
And so I you know, I constantly get questioned where I'm like, "Well, what about I mean, heck, you guys are asking me about like, "Well, what about the exit? What's the valuation?
57:37
What's the" And I'm like, "It'll be what it will be.
57:39
Like, we're here to grow it for our customers.
57:40
Like, that's the thing I care about. Not these other things.
57:44
And, you know, I think if we do a good job of that, then sure, the numbers will follow.
57:48
But, that's not the point.
57:49
Like, the point is like the the the work itself.
57:51
And I think that's you find that with anyone who loves what they do.
57:55
You know, you ask them I This is where I think feel like the media gets a lot of this like narrative around billionaires wrong is they're like, "You know, they're they're hoarding their money.
58:02
They're doing all this other stuff."
58:03
I mean, look, I don't know all billionaires.
58:05
But, I've I've gotten to meet a couple.
58:06
And you know, Dharmesh Haligian, like, you know, got guys like this who I don't know, they genuinely just seem like they like what they're doing.
58:13
And like, they're going to keep doing that whether or not they make, you know, a little bit of money or a lot of money.
58:20
>> The test has played out. >> Yeah.
58:23
>> They did it before they were making any money and kept going when there was no clear line of sight to money. >> Exactly.
58:29
>> they made the money, they kept doing it.
58:30
So, clearly it wasn't about the money cuz >> I just like doing it.
58:32
I think athletes are the same way.
58:34
Like, you look at like Olympic athletes.
58:35
Olympic athletes don't make a lot of money.
58:37
But, they just love doing it and they're just going to keep doing it, no matter what.
58:41
You see it in, you know, professional sports where like guys are, you know, at the tail end of their career and they probably should be retiring.
58:50
But, they keep playing cuz they just love playing and they'll take the they'll take the lesser contract.
58:55
They'll do all this other stuff because it's like, "I just can't I just love this game.
58:57
Like, I love doing that thing."
59:00
>> So, Sean, listen to this.
59:00
One time, I think in 2000 and maybe 2019, Wade spoke at Hustle Con in Oakland, California.
59:09
And this was right, I think, before you raised your round.
59:12
I I think or but you were you guys were the hottest thing going.
59:16
And you came and talked and I thought it was awesome.
59:18
And I don't know if you remember this, Wade, but you and I sat backstage for like 10 hours.
59:25
And all the speakers would come and go and they would have to pass through this room.
59:30
And I think, I don't remember I don't know exactly if this is how you felt.
59:33
I think you did the same thing I wanted to do, which is like these people would come in and we would just stare and like observe how they were behaving cuz it was kind of fun to have like, you know, billionaires or like these big shot CEOs just like interacting with you, having a normal conversation. It was really exciting.
59:47
It was like people watching on steroids and we were just we're kind of staring at them.
59:52
But I remember you sat with me.
59:54
I don't know if you remember this.
59:55
For like it was like eight or 10 hours.
59:57
It was like the entire day and I was like, "Do you got somewhere to be?"
59:59
And you were like, "Nope, I just like being here."
1:00:00
And I remember that you you doing that and it seemed like you have a change where it was like you were very you were successful then, now you're incredibly successful, but it was a very similar personality where you were still very curious.
1:00:15
>> Yeah, I don't remember it being eight or 10 hours, but I do remember like >> all day.
1:00:19
Like you got at 9:00 and I think we left at 4:00. So however long that is. >> it was, yeah.
1:00:24
Yeah, I mean you you got good you pulled good guests, man.
1:00:26
Like who wouldn't want to just like sit backstage and like listen to how all these people are running their companies and what's working for them and what's not?
1:00:31
I mean shoot, I'm I I'm almost certain I had a notebook of ideas that I sort of took back and was like, "All right, we're going to try this. We're going to do this." Yeah.
1:00:39
I mean the awesome thing is like you know, back when you were doing that, like I feel like podcasts weren't quite as big of a deal, but now like God, you can just like pour over this stuff and you just have like notes for days on things that you can just go try.
1:00:51
And it's like, "All right, see if this works for me."
1:00:55
>> you What do you listen to and what do you consume on a regular basis?
1:00:56
Books, >> Well, my I mean my favorite podcast, whatever.
1:00:59
My favorite podcast, I got to give a shout out to the Acquired guys.
1:01:02
Like I I mean it's just 10 out of 10.
1:01:04
Like, you know, most of those things they do a deep dive on are just these legendary entrepreneurs who have like, you know, did it for decades.
1:01:12
>> Leave us a leave us with a recommendation.
1:01:13
Give us a Acquired episode we should listen to and maybe a book that you liked.
1:01:18
>> Well, the NFL episode, if you like sports at all, like you know, that is a good entry way into Acquired.
1:01:26
Though probably my favorite series is all the retail ones.
1:01:28
So, there's like a like a cot like I think it's Costco, Walmart, and Amazon.
1:01:33
And they're sort of like a trifecta right in there that are like all really, really good.
1:01:39
As for a book, um I I recently finished this book Make Something Wonderful.
1:01:44
It's a Steve Jobs like in his own words. It's a really good one.
1:01:49
You know, I think Steve Jobs, he sort of he has like a larger-than-life reputation.
1:01:52
This book is literally just emails, speeches, literally just like his own his own thinking.
1:01:59
And it's sort of organized roughly chronologically.
1:02:03
And so, you get to kind of just see his progression of like, you know, V1 Apple, the Pixar years, V2 Apple, and you kind of just see how he he changes sort of like over time.
1:02:14
>> Sean, do you have a a book that you read recently you want to recommend?
1:02:17
>> Yeah, [snorts] um There's a book called The Score.
1:02:20
Have I talked about that here?
1:02:22
See Thai Win is the the guy's name on the cover.
1:02:27
But it's called The Score: How to Stop Playing Somebody Else's Game.
1:02:28
And this is a guy who the the fundamental premise of the book is amazing.
1:02:33
He's So, he's talking about like the power of a game.
1:02:37
So, he's like I imagine a game, um you let's say we take uh Pictionary.
1:02:42
We open up a game of Pictionary.
1:02:45
Games are this incredible thing cuz they tell you what winning means.
1:02:48
So, they tell you the rules, what you're allowed to do.
1:02:52
They tell you the the scoreboard, so like how you gain how you win in this game, and and like what your goal should be.
1:02:58
So, they dictate your goals, they dictate your behavior, and then they also sort of dictate who you need to be to be good at this game.
1:03:05
And he's like, let's take a game like charades.
1:03:07
To be great at charades, you're going to have to be loose, you're going to have to be highly communicative, you're going to have to be a great team player, whether you're the guesser or you're the the actor, it doesn't matter.
1:03:16
But then let's say you play Risk, it's like you're going to have to be like ruthless, dominating.
1:03:20
You're going to And so like he's like it's amazing if you just take the idea of a game how it will change your behavior.
1:03:26
And he's like basically extends that to like the games we play in life.
1:03:29
And so he he describes like when he was his professor, he's like I got into teaching philosophy cuz I love philosophy.
1:03:34
That Of course, that's why Who else becomes a philosophy teacher?
1:03:38
He's like but then I discovered this leaderboard.
1:03:39
And it was like all the philosophy professors in the country.
1:03:43
And he's like suddenly I started Well, how do you get on that board, right?
1:03:46
I don't want to be not on the board.
1:03:48
And so he kind of innocently he's like oh, you got to get published.
1:03:51
He's like well, then I realized like the way to get published the most in the fastest is in these obscure publications about these types of things.
1:03:55
He's like suddenly a few years in I hate what I'm doing.
1:03:59
He's like why am I even doing this?
1:04:01
Like I'm doing studies about that I don't even care about to get published to get on a leaderboard that doesn't even matter. Why? Because I play games. We all play games.
1:04:07
And so you have to be really careful about like games and the different types of ways you play.
1:04:12
There's like striving play which is like you play for the joy of playing versus like outcome-based where you're playing to win.
1:04:19
And like you know, you want to be a striver for these reasons and like strivers actually tend to win more too, but they didn't play for that reason.
1:04:26
And like you can't just say well, I'm not going to play any game cuz like it's no fun.
1:04:30
Let's say we're playing charades and if you don't care at all about winning, we're not going to have a good time.
1:04:34
Like the trick is to care about it in the moment and then completely let it go afterwards and when you remember that oh, the reason we're playing charades is so that we could have a fun time as a group hanging out not so that I got the most points in the game.
1:04:46
And so you know, there's all this like nuance around >> good.
1:04:49
>> games and I and I think like cuz I think the biggest decision you make in life is what game you're deciding to play and how that will shape the the next 10 years of your life.
1:04:58
>> Looks like it just came out, too.
1:04:58
The book came out like 6 months ago.
1:05:02
>> Yeah, so I'm I'm digging that book right now. >> I just finished.
1:05:04
I'll I'll wrap it up with this one.
1:05:05
Wade, you might like this one.
1:05:07
I think you if I had to guess, do you listen to Blink 182 as a kid?
1:05:11
>> [laughter] >> I I did. >> Did you, Sean? >> I mean, who didn't? Popular songs.
1:05:16
I mean, I wasn't like going >> Millennial like, yeah.
1:05:19
Uh I read the biography of the memoir of Mark Hoppus, who is one of the lead singers of Blink-182. Such a good book. I read it in 3 days. I couldn't put it down.
1:05:28
It was one of these books where like I had to force myself to put it down when I was going to bed at night cuz I was like I was staying up too late.
1:05:34
>> Dude, why why are musician biographies so good?
1:05:37
>> There's so I'm definitely more >> Whatever of musicians and comedians is like >> do you have?
1:05:43
>> This Red Hot Chili Peppers guy, Anthony Kiedis. >> Was that good? >> Long time ago.
1:05:46
I mean, I was like in college I read this thing and I loved it.
1:05:50
>> Well, his is his is good I think because he had a messed up and he partied >> messed up childhood leading to a messed up adulthood.
1:05:57
>> So it's like riveting.
1:05:57
These guys, they weren't really that messed up.
1:05:58
Um but they got really famous like really fast and he talks about it and he's like you know, a lot of I'm going to This is where you get the chapter where I complain about fame and he's like, "Just joking. I loved being famous.
1:06:08
It was [laughter] awesome.
1:06:12
Like people come up to me all the time and they say they love my work. It feels amazing."
1:06:15
And then he also later in life he got cancer.
1:06:16
He talks about like his cancer treatment. Oh, such a good book.
1:06:19
If you guys want something fun to read, uh Mark Hoppus has a biography and if you want like the cliff notes >> Fahrenheit 182, I believe. But anyway, wait. You're the band. We appreciate you.
1:06:31
You have an invite whenever you want and thank you for everything. >> You bet.
1:06:34
Thanks for having me, guys. >> All right, that's it. That's the pod.