Airbnb CEO Brian Chesky on early rejection, customer focus & AI’s future in hospitality

00:00:00.000 | Now, at the time, Jason, we were trying to raise $150,000 at a $1.5 million post-money

00:00:07.240 | valuation.

00:00:08.240 | So, for $150,000, you could have owned 10% of Airbnb.

00:00:12.240 | And the majority of them didn't even reply to the email.

00:00:14.800 | I actually ended up publishing a bunch of the rejection emails, but many people said

00:00:18.000 | like, "This isn't a good idea."

00:00:21.040 | Many people said like, "Travel, we're not like excited about travel."

00:00:24.540 | I remember one investor said, "We love everything but you and your idea."

00:00:27.780 | In other words, I'm like, "Well, everything else is good."

00:00:31.000 | Unfortunately, I thought to myself, "Wait, what else is there?

00:00:34.440 | There's me, there's the idea."

00:00:35.440 | The logo.

00:00:36.440 | Yeah.

00:00:37.440 | I guess there's the name.

00:00:38.440 | They didn't like the name either.

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00:01:28.240 | All right, everybody.

00:01:30.000 | We've had all the legendary startup CEOs on This Week in Startups over the past decade.

00:01:35.400 | Daniel from Spotify, Travis from Uber, Toby from Shopify, Brian from Coinbase, Tony from

00:01:41.040 | DoorDash, Melanie from Canva, Slootman from Snowflake.

00:01:44.440 | But man, I have been wanting to interview the founders of Airbnb, which is just one

00:01:50.780 | of the great companies of all time, and certainly in the last two decades of startup companies.

00:01:56.560 | And I've been able to have both founders now on the program.

00:01:59.880 | We had Joe Jebbia on episode 1675, and today his co-founder and the CEO of Airbnb, Brian

00:02:06.840 | Chesky, is with us.

00:02:07.840 | How are you doing, Brian?

00:02:08.840 | Hey, good.

00:02:09.840 | Great to finally be on, Jason.

00:02:10.840 | Good to see you.

00:02:11.840 | Yes.

00:02:12.840 | We've been trying to get this on for a while, and we finally did it.

00:02:14.920 | Congrats on the great performance.

00:02:18.100 | Thank you.

00:02:19.100 | So, last quarter, things have been going great.

00:02:21.660 | I think big picture, when you look back on the last decade of running this company, there

00:02:26.680 | were really two meaningful companies that came out of this last cycle.

00:02:30.260 | After Facebook and Twitter, you had Airbnb and Uber.

00:02:34.900 | And I'm curious, I know the Uber story, obviously, up close and personal, how that was accepted

00:02:41.360 | by the investment community and the hurdles they had to get over to want to be in that

00:02:45.420 | business.

00:02:46.420 | Uber, famously, had a lot of resistance to the concept of Airbnb, and now massive consumer

00:02:51.540 | acceptance.

00:02:52.540 | So, when you look back on your journey, everybody telling you, "This is crazy.

00:02:56.700 | It's never going to work."

00:02:58.360 | And then everybody, when they see you, saying, "Oh my God, I love Airbnb."

00:03:03.380 | How do you reconcile that as an entrepreneur?

00:03:05.380 | We came up...

00:03:06.380 | Obviously, I know Joe told the founding story, but I'll tell a little bit of the...

00:03:11.940 | There's a founding story, and then, Jason, there's a story of all the rejection.

00:03:14.980 | The first time we came up with the idea, it was October 2007.

00:03:18.320 | It was for a design conference that was coming to San Francisco.

00:03:22.080 | There was an after-party at the Fairmont Hotel.

00:03:24.820 | We went to the Fairmont Hotel.

00:03:26.280 | The first person I told about the idea, he looks at me with a straight face.

00:03:29.260 | He said, "Brian?"

00:03:30.260 | I said, "Yes."

00:03:31.260 | He goes, "I hope that's not the only idea you're working on."

00:03:34.420 | That's what he said to me.

00:03:35.420 | And this was like a design luminaire in our industry.

00:03:38.620 | And that was kind of the general sentiment.

00:03:40.780 | I remember in January, February 2008, Joe and I were living in San Francisco, it was

00:03:48.140 | an apartment.

00:03:49.140 | And we had a roommate named Phil.

00:03:51.560 | And Phil worked for this company called Justin.tv.

00:03:55.780 | Justin.tv was a precursor to Twitch, and it was funded by this program called Y Combinator.

00:04:00.180 | Now, I didn't know anything about Y Combinator.

00:04:02.260 | I didn't know anything about Silicon Valley.

00:04:03.820 | I didn't even know what angels were.

00:04:05.380 | Somebody once told me there are these people called angels.

00:04:07.660 | And I said, "Oh my God, this person believes in angels."

00:04:09.860 | So, I was really naive.

00:04:11.300 | I didn't know anything about Silicon Valley.

00:04:12.460 | I was a designer by training.

00:04:14.140 | And Michael said, "I can introduce you to these angel investors."

00:04:18.540 | And so, Michael introduced us to 10 to 20 angel investors.

00:04:22.660 | Now, at the time, Jason, we were trying to raise $150,000 at a $1.5 million post-money

00:04:29.860 | valuation.

00:04:30.860 | So, for $150,000, you could have owned 10% of Airbnb.

00:04:34.860 | And the majority of them didn't even reply to the email.

00:04:37.420 | I actually ended up publishing a bunch of the rejection emails.

00:04:39.940 | But many people said, "This isn't a good idea."

00:04:43.660 | Many people said, "Travel, we're not excited about travel."

00:04:46.900 | I remember one investor said, "We love everything but you and your idea."

00:04:50.540 | In other words, I'm like, "Well, everything else is good."

00:04:53.820 | So, I thought to myself, "Wait, what else is there?

00:04:57.060 | There's me.

00:04:58.060 | There's the idea."

00:04:59.060 | The logo.

00:05:00.060 | Yeah.

00:05:01.060 | I guess there's the name, but they didn't like the name either.

00:05:02.060 | And what they meant by they liked everything but us and the idea was, it was three founders,

00:05:06.940 | one software engineer, and two designers.

00:05:08.740 | And they thought, "Well, you have too many designers in your founding team."

00:05:12.700 | People just associated designers as non-technical, and therefore, maybe not adding value.

00:05:18.140 | And I always felt like Joe and I, our ability as being designers, was actually part of the

00:05:22.420 | secret sauce of Airbnb because it was not a pure technology problem.

00:05:26.900 | And also, people said, "This is crazy.

00:05:28.620 | Strangers never say they're strangers."

00:05:30.260 | So, basically, no investors will invest in this company.

00:05:33.860 | Everyone rejects us.

00:05:34.940 | It's now the fall 2008.

00:05:38.900 | We had just provided housing for the Democratic and Republican National Conventions.

00:05:42.640 | You know, Barack Obama and John McCain were running for president.

00:05:45.900 | The airbeds weren't working.

00:05:47.300 | We were renting out airbeds.

00:05:48.460 | They weren't selling.

00:05:49.460 | So, we thought, "Let's go with breakfast.

00:05:51.940 | We're airbed and breakfast."

00:05:52.940 | And so, Joe and I ended up creating this collectible breakfast cereal.

00:05:57.580 | These boxes of Cheerios that we called Obama-Os, the breakfast of change.

00:06:03.360 | And then we bought Cap'n Crunch.

00:06:05.480 | And we read that John McCain was a captain of the Navy and we called it Cap'n McCain's,

00:06:09.020 | a maverick in every bite.

00:06:10.520 | And it seemed kind of crazy.

00:06:12.300 | We made these cereal boxes and we actually printed and like made $30,000 worth of cereal

00:06:18.160 | boxes that we sold.

00:06:19.780 | And you know those baseball card binders that kids put, those binders that kids put?

00:06:23.360 | We used to put credit cards in them.

00:06:24.620 | In other words, we funded this company with tens of thousands of dollars of credit card

00:06:27.460 | debt.

00:06:28.460 | We used the cereal boxes to get us out of debt.

00:06:31.380 | But now, it's like October 2008.

00:06:34.740 | We've been working on this idea for like a year.

00:06:36.940 | At some point, my mom said, "Are you a cereal company?"

00:06:39.900 | And technically, I think we were.

00:06:42.400 | I didn't want to admit it.

00:06:43.460 | I guess we were cereal entrepreneurs, but not the right kind of cereal entrepreneurs.

00:06:47.380 | And I remember I was with, out of desperation, Joe and I went to dinner with Michael Seibel.

00:06:54.540 | And Michael Seibel, he had co-founders Justin Kahn, Emmett Shear, and Kyle Voight.

00:07:00.460 | Emmett runs Twitch, Kyle Voight runs Cruise.

00:07:04.420 | And we went to like a Thai restaurant in San Francisco.

00:07:06.940 | And it was like towards the end of the year.

00:07:09.100 | And we're like brainstorming what to do.

00:07:10.540 | We were kind of screwed.

00:07:11.540 | We're like, everyone said no to us.

00:07:12.760 | We have no traction.

00:07:13.760 | We're selling collectible breakfast cereal.

00:07:15.820 | Everyone thinks this idea is no good.

00:07:17.060 | No one wants to fund like two designers and an engineer.

00:07:19.580 | What do we do?

00:07:20.580 | And then Justin says, "I have an idea.

00:07:22.820 | Why don't you apply to Y Combinator?"

00:07:24.860 | And we're like, "But we already launched.

00:07:27.140 | Why would we apply to Y Combinator?"

00:07:28.900 | And they're like, "Because you're dying.

00:07:29.940 | You have no like growth."

00:07:32.580 | And so, we go on the Y Combinator website and we realize that the deadline was the night

00:07:37.820 | before.

00:07:38.820 | In other words, it had just expired.

00:07:39.820 | We couldn't wait for another batch.

00:07:41.340 | Oh, by the way, Jason, the financial crisis you remember had just happened.

00:07:44.900 | - Sure.

00:07:45.900 | - One investor, I'm not going to lie, one investor told me, he said, "The economy is

00:07:52.220 | so bad, we won't even invest in good companies.

00:07:54.900 | You think we're going to invest in air bed and breakfast and unproven concept people

00:07:58.020 | stand with each other?"

00:07:59.020 | Oh, and one other story is that Joe and I went to University Avenue.

00:08:02.880 | We met an investor who I won't name.

00:08:05.540 | He orders a strawberry smoothie.

00:08:07.900 | He then sits down drinking the strawberry smoothie.

00:08:10.740 | Never picked his head up.

00:08:11.740 | In my first interaction with an investor, I'm like, "Maybe this is what they all do."

00:08:14.940 | He goes, "Uh-huh, uh-huh, uh-huh, uh-huh, uh-huh."

00:08:17.740 | And then within 10 minutes, he like leaves and I thought like he had to park his car.

00:08:21.780 | We haven't seen him since though.

00:08:23.140 | - That's hilarious.

00:08:24.140 | - So, at this point, at this point, we're like these bad news bears of Silicon Valley.

00:08:31.300 | We were like rejects and Justin Conn, we're at dinner and they're like, "Oh my God, you're

00:08:36.860 | totally going to die now because like you can't get into Y Combinator."

00:08:40.380 | And then Justin Conn says, "I'm going to email Paul Graham."

00:08:43.980 | And he ends up emailing Paul Graham and he goes, "Is this deadline definitely, definitely

00:08:48.020 | over?"

00:08:49.020 | And Paul Graham says, "I will extend it to midnight tonight."

00:08:51.940 | It's like 9 p.m., okay?

00:08:53.580 | - Yeah.

00:08:54.580 | - But they have to apply by midnight.

00:08:55.780 | Now, Joe and I are in San Francisco.

00:08:58.340 | We have a co-founder named Nate who's an engineer.

00:09:00.500 | He's in Boston.

00:09:01.500 | Now, it's like midnight and Nate kind of doesn't sleep past, I think he went to bed.

00:09:07.180 | So, I told Joe, I said, "Okay, we'll divide and conquer.

00:09:09.740 | I will fill out the application and you will convince Nate, you're going to wake his ass

00:09:13.300 | up in Boston and convince him to do Y Combinator if we get in."

00:09:18.340 | So, he calls Nate, apparently, he goes, "Nate's in," I'm like, "Great."

00:09:22.980 | We fill out the application, we submit it.

00:09:25.380 | Then a week later or whatever, we get an interview and then we tell Nate and I think Nate's like,

00:09:31.020 | "Wait, what?

00:09:32.020 | What did I agree to?

00:09:33.020 | I agreed to like move to San Francisco?"

00:09:35.220 | So, you know that movie "8 Mile" where like Eminem, he's like, "You got like one shot?"

00:09:39.460 | - Yeah.

00:09:40.460 | - This was kind of it.

00:09:41.460 | This is like our one shot, right?

00:09:42.460 | - Yeah.

00:09:43.460 | - So, we like prepared for this interview like crazy and we were warned, this is going to

00:09:46.580 | be like a 15-minute interview and they're going to ask you four questions at the same

00:09:50.700 | time.

00:09:51.700 | And you better know every answer.

00:09:52.700 | And Justin and Michael and Emmitt said like, "Just know your numbers inside and out."

00:09:56.660 | So, we basically did like rehearsals.

00:09:58.860 | We almost recreated like NYPD Blue or like we throw a phone book in each other's faces.

00:10:03.220 | - Yeah.

00:10:04.220 | - And we were just like, "We better get this sh*t right."

00:10:06.580 | So, we go to Y Combinator, we go to the interview, it's exactly what I expected.

00:10:11.580 | It's Paul, it's Jessica, it's Trevor Brackwell and it's I think Robert Morris.

00:10:15.540 | And they're all like basically, they all ask us questions at the same time.

00:10:19.220 | Like all four of them.

00:10:20.220 | And I was like totally bewildered.

00:10:21.780 | And the first question Paul Graham asked me is, "People are actually doing this?"

00:10:25.740 | And I said, "Yes."

00:10:27.020 | His second question was, "What's wrong with them?"

00:10:30.340 | And the interview at that point went downhill from there.

00:10:32.940 | He, midway through the interview, he basically tried to get us to create Stripe.

00:10:37.700 | He's like, "You should create this like payments company or like an online bank or something."

00:10:42.380 | And we're like, "That seems like a really good idea."

00:10:43.700 | But like, we have an idea.

00:10:45.700 | And we're about to leave the interview.

00:10:48.100 | It doesn't seem like it's going well.

00:10:49.980 | And Joe takes out a box of Obama O's and he hands it to Paul Graham.

00:10:54.460 | And Paul Graham's like, looks like he just got a novelty gift.

00:10:57.460 | He's like, "All right.

00:10:58.460 | Thank you."

00:10:59.460 | - Yeah.

00:11:00.460 | - And Joe goes, "What's the story?"

00:11:01.460 | He goes, "This is how we funded the company."

00:11:03.060 | And he goes, "What do you mean?"

00:11:05.300 | He said, "Well, we told him the story, how we like made the cereal boxes.

00:11:08.500 | And then the way we sold the cereal boxes, we mailed them to reporters and they put them

00:11:12.060 | in their newsroom desk and everyone would buy them."

00:11:14.120 | And he said something like, "I guess if you can convince people to pay $40 for a $4 box

00:11:19.540 | of cereal, then maybe you can convince at least some people to stay in each other's

00:11:22.940 | homes."

00:11:23.940 | And he ended up admitting us to Y Combinator.

00:11:26.140 | And I guess we've never looked back since.

00:11:28.580 | I also want to give credit to Jessica, because I think Jessica thought, I remember Paul and

00:11:33.180 | Jessica said later, they thought we were like cockroaches.

00:11:36.140 | And I think they mean it in a good way, that it was like an investment nuclear winter.

00:11:39.980 | And in a nuclear holocaust, the only thing that survives are cockroaches.

00:11:43.220 | And the only thing that would survive an investment nuclear winter would be the founders of Airbnb.

00:11:47.700 | We said, "We won't die no matter what happens."

00:11:50.460 | And so they basically funded us because we seem Brazilian, unkillable.

00:11:55.060 | And like, even if the fundraising market was dried up, we would just go on.

00:11:58.860 | So it was definitely not a story to glory in the beginning.

00:12:02.340 | And I like to remind founders of this, because then when we got product market fit three

00:12:06.440 | months later, we got funded by Sequoia.

00:12:09.420 | And so in a three-month period, we went from like, kind of like this untouchable company

00:12:14.180 | to Sequoia.

00:12:15.180 | And if you were a part of Sequoia, so you'll remember 2009, I would say it was like, it's

00:12:20.580 | I don't know, it's like going to like an Ivy League school or something.

00:12:22.980 | But it meant something, it was a real seal of approval and it was crazy.

00:12:27.540 | And you were anointed basically, if Sequoia invested in you, that was like, okay, seal

00:12:31.180 | of approval.

00:12:32.220 | This is a legit company.

00:12:33.720 | And I think it meant even more than not because Sequoia was more prestigious than but because

00:12:37.740 | there wasn't a much capital than like, I just, you know, I don't, you know, this industry

00:12:41.940 | better than I do.

00:12:42.940 | But I don't remember hundreds of people I could contact to get money.

00:12:45.580 | They're really angel list.

00:12:46.860 | I don't think existed.

00:12:47.860 | Or I just get it was venture list at the time.

00:12:50.980 | I always do it like my open angel forum, they were like, maybe you could make a list of

00:12:55.120 | maybe 25 angel investors in the valley.

00:12:57.580 | And half of them said no to us already.

00:12:59.020 | So clearly, and we raise money, Jason, our first actual round, which is a series A was

00:13:06.940 | and this is when we had product market fit, we were voted by Y Combinator.

00:13:10.900 | So each batch, they rate like the best company like halfway through and at the end, and we

00:13:15.420 | were rated the best.

00:13:16.420 | We had the most traction.

00:13:18.220 | And then then we raised $615,000 at a $3 million post money valuation, credible with product

00:13:26.220 | market fit $3 million post money.

00:13:28.820 | It's crazy.

00:13:29.820 | And you just like look at the signaling at that time.

00:13:32.140 | Yeah.

00:13:33.140 | It's so weird.

00:13:34.140 | Like people had these ideas like, oh, well, the only way it's going to work is if you're

00:13:36.980 | from Stanford, you're from RISD.

00:13:38.700 | Like what is that like?

00:13:39.980 | Yeah.

00:13:40.980 | And one developer and two designers?

00:13:41.980 | Yeah.

00:13:42.980 | makes a difference between two developers and one designer?

00:13:44.900 | Yeah.

00:13:45.900 | Obviously, these are not the material things.

00:13:46.900 | All that matters is the customers.

00:13:48.400 | And do they engage with the product and actually get some value.

00:13:51.140 | And that's what you figured out was, you don't need to appeal to everybody.

00:13:54.740 | There just has to be somebody who gets value from this.

00:13:57.340 | Exactly.

00:13:58.340 | And there's a group of people.

00:13:59.340 | Yeah.

00:14:00.340 | That's a great lesson.

00:14:01.340 | Michael Sabe used to tell us to me, I used to tell Jason, Michael, I said, my sister

00:14:04.780 | won't stay in Airbnb because initially, when I first came to the idea, she said she wouldn't

00:14:08.820 | do it.

00:14:09.820 | And he said, you don't do cares about your sister.

00:14:11.580 | She's not the early adopter.

00:14:13.060 | You need the early adopters.

00:14:14.340 | You just need enough people to get the flywheel going.

00:14:17.580 | Everyone else will come later.

00:14:18.580 | So focus on those people.

00:14:19.580 | Yeah.

00:14:20.580 | And you think about his first hand experience with Justin TV was like, Justin TV was called

00:14:23.700 | Justin TV because there was one person who was insane enough to record their life.

00:14:27.380 | Yes.

00:14:28.380 | Exactly.

00:14:29.380 | Yes.

00:14:30.380 | Then it became Twitch.

00:14:31.380 | And now here we are, there's 10 million people streaming and like you turn on TikTok and there

00:14:33.980 | are people who are working in China, like cooking and they're on a live streaming like

00:14:38.780 | what is happening in the world like people are making a living just live streaming themselves

00:14:42.100 | cooking in a restaurant halfway around the world.

00:14:44.620 | And it really is about those early adopters.

00:14:48.980 | Imagine this, you've got the greatest idea ever for a tech startup, and it's going to

00:14:53.300 | change the world.

00:14:54.540 | But you got a problem.

00:14:56.320 | You don't have the engineers you need to make this a reality.

00:15:00.100 | Why?

00:15:01.100 | It's hard to find engineers, right?

00:15:02.980 | Everybody's in competition for those great engineers.

00:15:05.340 | And you've got to manage your burn rate, you don't have unlimited resources like those

00:15:08.780 | big slow incumbents, you've got to be efficient.

00:15:11.360 | So now imagine you had a partner who could provide you with more than 1000 on demand

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00:16:05.880 | I was really impressed today and I've always been impressed with you and Joe and then the

00:16:09.800 | team of this like relentless focus on the customer experience.

00:16:14.840 | Yes.

00:16:15.840 | And now becoming a public company, growing at the pace you did having to deal with regulation

00:16:20.960 | and there's a lot of blocking and talking and tackling and operational stuff.

00:16:25.080 | I'm curious how you spend your time today as CEO of the company.

00:16:29.800 | Because in just over the last decade, every time I talked to you about Airbnb on Twitter,

00:16:34.240 | or I mentioned Airbnb or something I like about it, you're instantly in there responding

00:16:38.200 | and thinking about product.

00:16:39.620 | And so I'm curious, how much of your day are you on product over time?

00:16:47.320 | How is that change?

00:16:48.320 | And how do you stay so focused on product versus doing your chores, which as a public

00:16:53.040 | company, there's a lot of chores that come up?

00:16:55.560 | Yeah, it's a great question.

00:16:57.160 | I would say I spend almost all my time on product, marketing, and hiring, those three

00:17:03.920 | things.

00:17:04.920 | And product and marketing, I also combine, like a lot of companies, they think of marketing

00:17:09.320 | as like advertising and product as product development.

00:17:11.760 | We actually have a function, we took it from Apple, product marketing, where we tie, we

00:17:16.360 | basically try to make sure product and marketing are joint the hip.

00:17:19.080 | Think of product as the chefs, marketers the waiters, and a lot of companies like the waiters

00:17:23.400 | can't go in the kitchen, they get yelled at.

00:17:25.280 | So we really try to make them integrated.

00:17:27.100 | So here's how we run the company.

00:17:28.280 | The entire company is a functional organization.

00:17:30.520 | So we have an engineering group, a product marketing group, a design group, like ops,

00:17:34.960 | you know, legal, HR.

00:17:37.340 | So most every other company is divisional or subdivisional.

00:17:40.400 | The entire company is on one single roadmap.

00:17:43.120 | So I mean, yeah, there's accounting systems that maybe aren't, but basically anything

00:17:46.560 | you ever see is on one roadmap.

00:17:48.160 | Most companies have separate roadmaps.

00:17:49.600 | And then we do these release cycles.

00:17:51.480 | And we basically do a giant release in May and a giant release in November.

00:17:54.760 | So basically, the idea is that we try to basically take the best of software development, and

00:17:59.140 | the best in hardware development, and put it onto one practice.

00:18:02.740 | And the reason why is I found that the way people develop software, which is great for

00:18:06.280 | 10 people, where you basically democratize data, you decentralize, and anyone can ship

00:18:10.540 | anything and it feels very empowering, and it feels it can go really fast.

00:18:13.840 | That's great until you're like 1000s of people.

00:18:16.340 | And then everyone is basically a free for all.

00:18:19.780 | They're all hitting the payments platform.

00:18:21.480 | There's no cohesive roadmap.

00:18:23.280 | As you subdivide the company, ideas get smaller, you don't even know what to market.

00:18:27.380 | And then you can't keep track of everything, then there's like no accountability.

00:18:30.900 | And so and then lack of accountability becomes politics and bureaucracy, all this weird stuff.

00:18:35.900 | So when the pandemic occurred, out of basically Jason's survival, we lost 80% of our business

00:18:41.740 | in eight weeks.

00:18:43.240 | And Joe and I and Nate, we were like, what the hell do we do?

00:18:46.380 | And we were like staring into the abyss.

00:18:48.060 | I mean, you might remember people were making predictions like is this the end of Airbnb?

00:18:52.300 | Will Airbnb exist?

00:18:54.020 | And one of the people I was talking to a lot back then was Johnny Ive.

00:18:58.540 | He now works with me.

00:18:59.540 | But he told me the stories of Steve Jobs going back to Apple.

00:19:02.920 | And when Steve Jobs went back to Apple, you know, they were like 90 days from bankruptcy.

00:19:06.120 | And I'm like, well, that seems kind of like, you know, Airbnb is in a very precarious situation.

00:19:10.760 | And Johnny Ive said, you know, you can cut but you can't cut your way to the growth.

00:19:14.620 | Steve, you have to build product, you need to stay in the product.

00:19:17.680 | And I hired a guy named Hiroki Asai from Apple, he was also instrumental.

00:19:21.680 | And so I totally changed how I ran the company.

00:19:23.760 | So what I used to do is I was very hands off, I democratize data, I was very much reactive,

00:19:28.860 | I thought my job was like strategy and capital allocation.

00:19:32.600 | And here's the weird thing, the less hands on I was, the more I got sucked into problems.

00:19:37.480 | And when I by the time I got sucked into a problem, it was like 10 times as much work.

00:19:41.160 | So then I decided I'm going to do something different.

00:19:43.560 | We're going to be totally integrated, one roadmap, I'm going to do very few things,

00:19:47.160 | and I'm going to be involved in every single detail.

00:19:49.600 | And Airbnb is not going to do anything more than I can personally focus on.

00:19:54.560 | And that what became the governor.

00:19:55.940 | And this is what Steve said at Apple, he said, well, we want to do more things than I can

00:19:58.400 | focus on.

00:19:59.400 | Now, this sounds like it would slow us down.

00:20:01.400 | And initially, it did slow us down.

00:20:03.520 | Because I would review everything.

00:20:04.960 | So I had these things called CEO reviews.

00:20:07.440 | And every single project in the company, I had a program management function.

00:20:11.640 | And I would review everything either every week, every two weeks, every four weeks or

00:20:14.760 | every quarter.

00:20:15.800 | And then we track the progress.

00:20:17.720 | And then you know, then everything would ship on a single deadline.

00:20:20.720 | Initially, people hated this, no one wanted to collaborate, people didn't want to have

00:20:24.880 | imposed deadlines on them.

00:20:26.480 | They were wondering, why are you meddling?

00:20:28.320 | Like, why are you reviewing all the work, but eventually, it created a culture.

00:20:32.400 | And I was trying to teach a sense of quality, I was trying to be like the editor or the

00:20:36.240 | orchestra conductor.

00:20:37.680 | And eventually, what ended up happening was, we were able to like start shipping faster.

00:20:43.520 | And in the last three years, we've shipped 340 upgrades and innovations.

00:20:47.840 | And we obsess.

00:20:48.840 | I mean, a lot of companies, they're just trying to grow.

00:20:50.760 | And they look at their dashboard, they have these sub teams looking at growth, they're

00:20:53.640 | doing A/B tests.

00:20:55.320 | And I don't like that process, the process of just chasing growth.

00:20:59.680 | Because first of all, you're not really solving customer problems.

00:21:02.860 | And if you're over reliant on A/B testing, and you choose B, do you know why B worked?

00:21:08.320 | Because if you don't know why B worked, you're stuck with B. And you can never redesign B

00:21:12.000 | because you don't even know why B was better than A. And so, we decided, if you're going

00:21:15.720 | to do ERF experimentation, you better know why B worked better than A. We're going to

00:21:20.520 | be qualitative and quantitatively driven.

00:21:23.760 | And so, what I do is, I spend most of my time just reviewing work and hiring people.

00:21:28.120 | So, I review all these different things.

00:21:30.880 | And I don't really spend a lot of time on corporate matters anymore.

00:21:35.160 | And the reason why is because once we designed the company, like, it became very efficient.

00:21:40.840 | We also don't have a lot of employees.

00:21:42.120 | We have like 5,300 employees.

00:21:45.520 | And we did three and a half billion dollars in free cash flow last year.

00:21:48.560 | So, you can just think about that.

00:21:50.040 | - That's incredible.

00:21:51.040 | - For every dollar, we do 40, 42% of 42 cents in free cash flow, which I believe is higher

00:21:57.040 | than Google or Apple.

00:21:58.040 | Now, obviously, we're not nearly as profitable at absolute dollars, but it's very efficient.

00:22:02.680 | So, we try to be like the Navy SEALs around the Navy.

00:22:06.040 | It's a small, lean, elite group.

00:22:08.440 | It's super intense.

00:22:09.680 | It's kind of day and night, to be honest.

00:22:11.720 | But I'm honest about it.

00:22:13.000 | And when people come to join, I probably try to talk people out of joining more talking

00:22:17.120 | them in.

00:22:18.120 | I'm kind of like, "Are you crazy?

00:22:19.120 | Like, why do you want to put up with all this?"

00:22:20.880 | And it really tries to set a mindset that when you come here, this is a really intense

00:22:25.240 | place, but hopefully, it's going to be really gratifying.

00:22:27.800 | And we're really connected, the top 30, 40 people in the company.

00:22:31.360 | And I think of it as like one shared consciousness.

00:22:33.720 | Does that make sense?

00:22:34.720 | - Yeah.

00:22:35.720 | - So, it's one shared consciousness.

00:22:37.280 | I don't push decision-making down.

00:22:39.000 | I pull it in.

00:22:40.160 | I don't make the decisions on my own.

00:22:41.960 | There's like a group of us, a concentric circle that like kind of just are in constant conversation.

00:22:48.000 | I don't do strategy reviews.

00:22:50.120 | I do this thing called living with the strategy.

00:22:52.520 | Instead of doing like a three-hour, that's like what boards do.

00:22:54.600 | They get like a deep dive.

00:22:56.240 | I talk about it every week until we resolve it.

00:22:58.600 | So, every week, we'll have like, "What are we going to do about this topic?

00:23:00.960 | What are we going to do about this topic?"

00:23:02.160 | Until the answer reveals itself.

00:23:04.400 | And I think this way of working is trial and error.

00:23:07.760 | I've tried all the other ways of working and they didn't work.

00:23:10.880 | And I think this like bottoms up, like giving tons of people a lot of discretion.

00:23:15.080 | It does work when you're small.

00:23:16.480 | When you get big, it becomes a free-for-all.

00:23:18.000 | And I think a lot of big companies are paying the price.

00:23:21.080 | - Yeah.

00:23:22.080 | And the prioritization gets lost.

00:23:23.440 | What I like about, "Hey, here's what I can keep in my brain," well, that also parallels

00:23:28.840 | what a customer can keep in their brain.

00:23:30.640 | - Exactly.

00:23:31.880 | - They can only handle so many new features at a certain velocity.

00:23:35.720 | And if you give them 20 things, they're going to remember two.

00:23:39.200 | - Exactly.

00:23:40.200 | - And probably not more than that.

00:23:41.200 | - And that's what happened.

00:23:42.200 | Years ago, we had, so we have one marketing department now, and they only market a few

00:23:47.200 | things a year.

00:23:48.200 | And the things we market, you probably know about because we try not to say anything you

00:23:51.200 | don't know about.

00:23:52.200 | - Upfront and clear pricing was the last one.

00:23:54.240 | - Exactly.

00:23:55.240 | Yeah, exactly.

00:23:56.240 | And today, we promoted Airbnb rooms, and we promoted that there are a whole bunch of things

00:24:00.280 | people are angry about, or they don't like about Airbnb, and we've made 50 fixes.

00:24:04.640 | And so we did that.

00:24:05.800 | But I remember-

00:24:06.880 | - And before that was Experiences.

00:24:08.440 | - Yep.

00:24:09.440 | Experiences.

00:24:10.440 | We launched Airbnb Categories a year ago.

00:24:11.440 | - Oh, yeah.

00:24:12.440 | I remember that too.

00:24:13.440 | - And Air Cover, which is this really important thing for hosts and protects them.

00:24:17.240 | But years ago, at one point, we had 10 divisions.

00:24:20.440 | We had 10 marketing departments.

00:24:23.200 | And it was so crazy that one time, I asked the marketing department, "Get a conference

00:24:28.280 | room and put every piece of marketing on the wall."

00:24:31.480 | It took them a week to track down all the marketing because it was 10 different teams.

00:24:34.760 | I'm like, "If you can't track down everything we're saying," and then I went around the

00:24:38.240 | wall and I said, "It feels like I'm looking at 10 different companies."

00:24:41.600 | And I didn't even know 80% of the marketing we were doing.

00:24:44.640 | I mean, we were doing, we had different creative agencies in different countries, and it was

00:24:48.360 | just incoherent.

00:24:50.560 | So what we do now is we just do a few campaigns.

00:24:53.800 | We don't do local campaigns.

00:24:55.280 | We trans-create, but we only do global campaigns because it's a cross-border business.

00:25:00.040 | And we just try to be incredibly simple.

00:25:01.920 | Steve Jobs had a saying, "Marketing is education.

00:25:05.440 | You speak to the customer the way you talk to an eight-year-old."

00:25:08.200 | Not down to them, but they're busy.

00:25:10.520 | You have to explain things simply.

00:25:11.960 | If you can't explain something simply, you don't understand it.

00:25:14.920 | And so every type of communication we try to do, we try to do to somebody who's not

00:25:18.760 | really paying attention, they're busy, and they don't have time and say, "What's the

00:25:22.720 | most basic idea we can communicate?"

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00:26:42.360 | It really is like this modern conundrum that Google finds itself in, not to single out

00:26:47.560 | Google.

00:26:48.560 | I mean, any big company has this.

00:26:49.560 | And I think Doug had it as well, which is, it's just too many people working on too many

00:26:52.680 | different projects.

00:26:53.680 | There's no cohesiveness.

00:26:55.200 | And then quality goes down.

00:26:56.640 | And then the consumers are like, am I supposed to buy a Pixel or some other Android phone?

00:27:01.200 | Am I supposed to use Chrome operating system or the Android operating system?

00:27:04.520 | Which one is going to win out here?

00:27:06.840 | And then I'm a consumer, I have a Nest, and then I have Google Home.

00:27:10.760 | And just that one cognitive dissonance I have, like where I open up Google Home to see all

00:27:16.960 | of my cameras, and I open up Nest to see the old cameras.

00:27:20.920 | And I like my Nest better, and it's just chaos, right?

00:27:23.800 | And Sundar's got to be in the middle of this, trying to referee it, and if he did the same

00:27:27.880 | approach.

00:27:28.880 | And I don't want that life.

00:27:29.880 | I had that life before the pandemic.

00:27:30.880 | And I said, I don't want that life.

00:27:31.960 | I don't want the life where I have to ask permission to get involved.

00:27:34.480 | I'm adjudicating disagreements, I'm managing bureaucracy and dysfunction.

00:27:38.320 | I want to be in the product with people making the product.

00:27:41.840 | I want to be talking to customers, I want to be communicating with them.

00:27:45.240 | And I want as little bureaucracy as possible.

00:27:48.200 | And that requires us to do as little as possible.

00:27:50.720 | There's an old saying, have few details and perfect every detail.

00:27:54.320 | And that requires focus, it requires you saying no.

00:27:56.760 | So, we probably say no now more than we say yes to things.

00:27:59.600 | And I think that's pretty important.

00:28:01.280 | - Yeah, the second business line really was experiences, am I correct?

00:28:06.600 | - Yes.

00:28:07.600 | - It was stays and then experiences.

00:28:08.600 | - Yes.

00:28:09.600 | - And is there even a third business line?

00:28:10.920 | - No, no.

00:28:11.920 | It's really just, you know, probably broadly like there's stays, 80% of stays are short-term,

00:28:18.040 | 20% are long-term stays defined by longer than 30 days.

00:28:21.400 | So, that's kind of like an in-between, it's an extension of the core.

00:28:25.440 | And then experiences, which has been kind of like in an in-between zone because it was,

00:28:29.840 | we thought it was going to break out before the pandemic and then we had actually shut

00:28:32.440 | it down or pause it.

00:28:33.800 | So, it's, we're in a process of we're going to reboot that and we do, and just to be clear,

00:28:40.560 | we have some big ideas coming.

00:28:42.360 | We have some really huge ideas that I think will expand Airbnb way beyond travel, way

00:28:46.560 | beyond our core.

00:28:48.040 | It's going to launch next year.

00:28:49.600 | But I'll tell one more story, you know, I feel like companies, you know, like there's

00:28:54.920 | certain companies you like root for them, like a lot of people love their Tesla car

00:28:59.200 | and they like want Tesla to come out with a truck.

00:29:01.200 | A lot of people love, in 2006, how many people wanted Apple to come out of the phone?

00:29:05.920 | A lot.

00:29:06.920 | And the reason why is we all loved our iPod.

00:29:09.200 | How many of us love, wanted Gateway to come out with a phone?

00:29:12.040 | Probably not many.

00:29:13.040 | And so, I like to tell people, we have to have permission by the customer to do something

00:29:17.440 | new.

00:29:18.440 | And we only have permission to do something new if they love what we currently do.

00:29:22.120 | And if they're complaining on Twitter about upfront pricing, about having to do chores

00:29:25.720 | and they check out, about customer service taking too long, then we don't have permission.

00:29:29.840 | They don't want to do something new because they're going to think we're going to bring

00:29:31.800 | problems to that category.

00:29:32.800 | So, I told the team, I said, "We have some big ideas, AI is going to unlock so many of

00:29:38.520 | them, but we don't have permission to do new things until people love our core service.

00:29:42.800 | So, we're going to basically create a blueprint of every single thing people are complaining

00:29:46.480 | about."

00:29:47.480 | So, we created this storyboard of the end-to-end experience.

00:29:50.760 | Then I got basically blueprinted out with the team, all 150 screens on the app, every

00:29:56.960 | user policy, all 72 user policies.

00:29:59.640 | Now, each of these user policies are as many as 100 pages long, right?

00:30:03.240 | Like who gets a refund, when.

00:30:05.200 | And imagine, Jason, you're a call center worker, Airbnb just hired you.

00:30:09.080 | Now, like two customers in different languages are in a dispute and you're adjudicating between

00:30:15.280 | 70 policies that are as many as 100 pages long.

00:30:17.840 | That's a perfect example of AI.

00:30:20.040 | Anyway, this is an opportunity where we realized, okay, we created this blueprint and then we

00:30:24.480 | mapped tens of thousands of social media posts, millions of customer calls, and all these

00:30:30.000 | interviews with customers.

00:30:31.000 | And we put them on the blueprint.

00:30:32.240 | We looked at what is everyone upset about?

00:30:34.400 | What do they want fixed?

00:30:35.880 | And based on this blueprint, we were able to go stage by stage in the end-to-end journey

00:30:40.080 | and prioritize the top issues.

00:30:42.080 | And we said, "We're going to get through every one of these issues before we do something

00:30:45.720 | new."

00:30:46.720 | And that was the whole premise of today.

00:30:47.840 | It was basically fixing what people wanted.

00:30:50.240 | And then we had one more thing.

00:30:51.640 | We're like, "We got some unfinished business."

00:30:53.880 | This idea of people staying with each other in their homes, the original idea of Airbnb,

00:30:59.120 | that's kind of like the Volkswagen's Beetle or Nike's running shoes or Apple's iMac or

00:31:04.560 | whatever, the original car, original product.

00:31:07.520 | I said, "We got to revive that.

00:31:08.840 | We can't.

00:31:09.840 | We got to get back on the highway and we got to reinvest in this core idea before we do

00:31:14.840 | new stuff."

00:31:15.840 | And so, that was kind of what today was about.

00:31:17.760 | And hopefully, if we're successful, people feel like we listened.

00:31:21.880 | Let's talk about the user complaints and prioritization of them because how do you know when you're

00:31:28.680 | running something at scale like this, that this is something that's annoying but necessary.

00:31:34.280 | You can't throw a party in an Airbnb.

00:31:37.320 | I had my old home, which I was thinking of keeping, and I had an Airbnb.

00:31:42.360 | And only one time in a year was there a party thrown there.

00:31:45.640 | You guys handled it great.

00:31:47.920 | There was a little bit of damage.

00:31:48.920 | Insurance picked it up.

00:31:51.040 | But over and over again, it has in the documentation, do not throw a party here.

00:31:55.000 | Do not throw a party.

00:31:56.000 | You can't throw parties.

00:31:57.000 | So, how do you know when something is like, you know, just this is a deal breaker for

00:32:03.400 | people who are hosts.

00:32:05.120 | This is a deal breaker for people who are going to choose a hotel or an Airbnb to run

00:32:11.480 | an Airbnb or not run an Airbnb as a host.

00:32:14.600 | And these are like minor annoyances, but they come up frequently.

00:32:17.720 | So, there's like a certain amount of suffering in each thing, right?

00:32:21.600 | And I'm curious how you prioritize the suffering to alleviate it, because you're also mitigating

00:32:27.920 | and arbitrating between these two groups of people, the hosts who can't be burdened so

00:32:33.040 | much that they don't want to be a host because it's arduous.

00:32:36.520 | And then the people who are leaving the home who don't want to have to do an hour of chores

00:32:40.200 | when they leave.

00:32:41.200 | Like, it's reasonable to put the dishes in the sink, but do you have to mop the floor

00:32:44.000 | or take out the garbage?

00:32:45.000 | Okay, maybe taking the garbage out is okay.

00:32:47.280 | How did you prioritize that?

00:32:50.040 | It's both an art and a science.

00:32:51.480 | I think that analyzing it is a science and then prioritization is probably more of an

00:32:56.480 | art.

00:32:57.480 | I can explain.

00:32:58.480 | So, let's start with analyzing.

00:33:00.240 | The first thing we do is we try to just take all the inputs.

00:33:03.320 | So, what are the inputs we get?

00:33:05.520 | Inputs are customer service calls.

00:33:07.640 | Inputs are social media posts.

00:33:09.680 | Inputs are we do like tens of thousands of like, we do listening sessions with guests

00:33:13.480 | and hosts.

00:33:14.480 | And then inputs are like basically user behavior, right?

00:33:16.700 | You can like see what people are clicking.

00:33:18.640 | You can see retention.

00:33:19.720 | You can see when somebody churns.

00:33:21.640 | And then if there's a party, we don't handle it right, they churn, they don't come back.

00:33:25.600 | And then we see people in their network don't list and you can start to measure that.

00:33:28.760 | So, those are your inputs.

00:33:30.520 | Those inputs, you basically now have like an organization of like maybe millions of

00:33:35.960 | issues and you can bucket them to like say 100, 200 types of things.

00:33:40.240 | The next thing you do is you look at the frequency and the severity.

00:33:43.920 | So, severity might be like a safety issue.

00:33:47.080 | Very infrequent, but when it happens, it's really serious.

00:33:49.840 | A frequent issue is like, I'm upset with a refund.

00:33:53.000 | Not as severe, but very frequent.

00:33:55.200 | That happens all the time.

00:33:56.840 | And then you start to look at relationships like, you know, we notice a lot of hosts are

00:34:03.760 | complaining about pricing being confusing.

00:34:06.040 | A lot of guests are complaining that hosts are charging too high fees.

00:34:10.080 | And then we start to realize, wait a second, if we make it easier for hosts to price and

00:34:14.920 | they understand what guests are actually paying, they might actually do a better job pricing

00:34:18.920 | and guests won't complain as much.

00:34:20.600 | So, you start to find like connections.

00:34:23.800 | So, this is where, that's the science part.

00:34:26.280 | Now the art part.

00:34:28.160 | Now it's actually picking stuff because you have a list.

00:34:31.040 | You have some matrix like severity, frequency, this and that.

00:34:35.400 | But the real ability is the art form of a group of us, 10 or 20 of us, deeply understand

00:34:42.200 | the issue so well.

00:34:43.720 | We live the product, we use the product, I host, I've read thousands of things.

00:34:49.280 | You just take thousands of inputs, you put them in your head, and then you just go through

00:34:54.920 | and you can't paint by numbers.

00:34:57.000 | You can't be purely algorithmic is what I would say.

00:34:59.720 | That's why that's the art.

00:35:00.880 | You could, but I think it's never as good as your intuition.

00:35:03.120 | But your intuition is formed of all these data points.

00:35:05.880 | And the intuition might be like, you know, it also might involve like engineering capability.

00:35:10.920 | Like this is going to be a really heavy lift, so we have like t-shirt sizes.

00:35:14.280 | A small lift, medium lift, large lift, extra large lift.

00:35:17.360 | So, we'll prioritize high severity, high frequency, like low engineering lifts, for example, would

00:35:22.560 | be a great candidate.

00:35:23.560 | - Quick wins.

00:35:24.560 | - Quick wins.

00:35:25.560 | - Yeah.

00:35:26.560 | - That with high payoff.

00:35:27.560 | There might be a big lift, but we need to do it to launch this feature later.

00:35:31.000 | So basically, there's like hundreds of inputs.

00:35:34.000 | You see how like you're like weighing all these in your head?

00:35:36.480 | And I think there is this, I think developing a product, the best products I feel like are

00:35:41.960 | a group of people that are deeply involved and they can hold a thousand contradictory

00:35:47.200 | things in their head.

00:35:48.600 | And they can make all those different trade-offs.

00:35:51.040 | We call that intuition, but I don't know if I love that because it makes it seem like

00:35:55.080 | it's arbitrary and not systematic.

00:35:57.560 | It actually is very deep and it can actually be very technical.

00:36:01.040 | And so, that's what we do.

00:36:02.040 | I audit all the prioritization and I personally decide on the final prioritization of every

00:36:09.040 | single project and the company that a customer will ever see.

00:36:12.720 | I don't decide, I mean, the final decision, I make the final call.

00:36:16.360 | And I only make a call if I'm informed.

00:36:18.880 | And I only am informed if my team understands.

00:36:21.720 | And so, I make sure that I know the details, my directs know the details, and their directs

00:36:25.840 | directs know the details.

00:36:26.840 | I also have a rule that if I have a direct report in a meeting, they can never call their

00:36:31.040 | direct to answer a question.

00:36:32.800 | If that's the case, they don't know the details and their scope is too big.

00:36:36.600 | So I mean, within reason.

00:36:38.120 | So that's kind of how I do it.

00:36:40.520 | And then we update it twice a year.

00:36:42.600 | So we have this thing called the Roadmap Review where we bring in like top 70 or so product

00:36:46.840 | people in the company or people weighing on the roadmap.

00:36:49.200 | We spend a couple days together.

00:36:50.920 | We debate everything on the roadmap, we adjust it, and then we roll it out.

00:36:54.840 | And then we have an extremely robust program management function.

00:36:58.560 | Most companies ask product management to basically be their program managers.

00:37:02.520 | We separate product management with program management.

00:37:05.480 | And we have a very small product management function.

00:37:07.920 | It's very small.

00:37:09.080 | We have product marketers.

00:37:11.080 | Product marketers are senior product managers.

00:37:13.200 | So we have no outbound people.

00:37:15.100 | You have to know inbound and outbound.

00:37:16.960 | The junior product managers don't need to do outbound.

00:37:20.480 | But then most of what people call product management, we call program management.

00:37:24.200 | And they're the ones keeping the whole thing on trains because everything has to fit together.

00:37:27.840 | And they're doing like really rigorous reporting every week about like where we are at the

00:37:31.880 | project.

00:37:32.880 | So it's all integrated.

00:37:33.880 | And the net result of this, Jason, is I can literally know the performance of an individual

00:37:38.800 | engineer I've never met on a week-to-week basis.

00:37:41.760 | Because imagine if we're all designing a car, I know how good the tire team is doing when

00:37:47.280 | I see the car assembled every week.

00:37:48.960 | And I see, hey, there's something wrong with the tire.

00:37:51.040 | But when there are like 100 different products, I don't have time to value 100 different things.

00:37:56.160 | Yeah.

00:37:57.160 | I mean, this is where constraint comes in.

00:37:58.280 | If you want to make great art, as you learned as an artist at RISD, like if you give some

00:38:02.520 | artist a thousand canvases and buckets and buckets of paint and a million brushes, like

00:38:07.760 | where do you begin?

00:38:08.760 | Right?

00:38:09.760 | And how do you prioritize?

00:38:10.760 | And you just get lost.

00:38:12.480 | Creative people want constraints.

00:38:13.880 | And that's the other thing.

00:38:14.880 | And I think what happened, and maybe this is a burger lesson, Jason, in Silicon Valley

00:38:18.160 | is I think in the last 10 years, we as entrepreneurs in Silicon Valley probably didn't have enough

00:38:23.080 | constraints.

00:38:24.080 | And it's kind of like we didn't ask for constraints, we didn't want constraints, but we probably

00:38:27.120 | needed them.

00:38:28.120 | I think that Airbnb before the pandemic probably raised too much money.

00:38:31.760 | And we didn't raise as much money as others.

00:38:33.680 | And I think that in hindsight, like not having as much money means you have constraints.

00:38:38.600 | Constraints means you have to say no, you have to make hard decisions.

00:38:41.320 | If somebody is not performing, you can't just hire more people, you got to deal with it.

00:38:45.440 | And if a product's not succeeding, you got to actually fix it or sunset it, you know.

00:38:49.760 | So I think the constraints are really critical.

00:38:53.000 | Listen, we work with super early stage companies at my investment firm launch, you know, pre

00:38:59.000 | Series A, maybe got a couple of $1,000 a month in revenue, you've raised a couple $100,000,

00:39:05.760 | maybe $1 million, right?

00:39:06.760 | That's the early days, year one or two of a startup.

00:39:10.100 | And I'll be honest, a lot of times startups, they don't have their insurance.

00:39:14.120 | They haven't set that up yet.

00:39:15.280 | They haven't set up their accounting properly.

00:39:17.320 | They're getting things cleaned up.

00:39:19.320 | In fact, I was recently had a great startup, but they didn't have DNO insurance that basically

00:39:24.040 | protect your directors and officers.

00:39:26.080 | That's the D directors, people on the board, officers, the people who work at the company,

00:39:30.640 | right?

00:39:31.640 | directors and officers insurance is super important.

00:39:33.440 | So what do we do?

00:39:34.440 | We sent them right to in broker or friends over to broker or a business insurance company

00:39:38.340 | that's built specifically for startups.

00:39:40.720 | You just fill out a simple application, right?

00:39:42.880 | And then startups get four quotes for four lines of coverage in 15 minutes, four quotes,

00:39:47.960 | four lines of coverage, 15 minutes, easy breezy lemon, squeezy.

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00:39:58.200 | your policy.

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00:40:22.720 | broker.com/twist.

00:40:26.720 | The zero interest rate policy led to a lack of discipline and maybe you avoid difficult

00:40:35.200 | decisions.

00:40:36.200 | Like, hey, this divisions working out okay, but it's not great.

00:40:39.400 | Yeah, it's never gonna be profitable.

00:40:41.480 | And you watched Uber, you know, you guys had your media stuff you were doing for a little

00:40:45.680 | while, which you were passionate about, I remember, but like, at a certain point, it's

00:40:50.120 | about the guests.

00:40:51.480 | It's about their experience, and how many different projects could Uber do?

00:40:54.600 | They were doing micro mobility.

00:40:56.080 | And that was interesting, but it was just such a minor, unprofitable piece of the business.

00:41:00.800 | They deprecated it, right?

00:41:01.800 | Yeah, exactly.

00:41:02.800 | People really want to get on scooters, like what percentage of people in what percentage

00:41:05.740 | of cities?

00:41:06.740 | When you did this cycle, what do you think are the problems you solved that were the

00:41:11.880 | most rewarding for you?

00:41:13.240 | Because when you solve a problem, you immediately know.

00:41:15.380 | So when you say cycle, you mean which time horizon?

00:41:17.760 | Well, the one you just did, where today at the release, there must be things that you

00:41:23.880 | personally, as you did the prioritization said, hey, these three things, these are the

00:41:28.320 | big wins.

00:41:29.360 | And now you put that tweet storm out with the images in it showing each one, which I

00:41:34.720 | love by the way, when you get it directly from the founder, and it's like, here's the

00:41:38.680 | image, here's what I was thinking.

00:41:41.320 | Let me know.

00:41:42.680 | How did the public's early response, your host's early response, your customer's early

00:41:47.040 | response to what you thought the top three things were versus what they think the three

00:41:51.440 | things are?

00:41:52.720 | Yeah, so the things I prioritized was probably number one, anything around pricing.

00:41:59.440 | The number one complaint at Airbnb is that the prices have gone up.

00:42:02.400 | And we started as an affordable alternative to a hotel, and Airbnbs had become over time

00:42:07.280 | less affordable.

00:42:08.280 | And I think we just like, I mean, that in itself was a potentially zero interest rate

00:42:12.120 | kind of phenomenon.

00:42:13.520 | And so, that was the number one, it was like pricing transparency.

00:42:16.320 | The second one I focused on, because I just was so tired of hearing about it and I didn't

00:42:19.400 | want people to deal with it, was checkout chores.

00:42:21.920 | There was this, you know, turn the lights off and you'll leave is totally reasonable.

00:42:26.200 | Strip the bed and put the sheets in the laundry is not reasonable, you're on vacation, like,

00:42:29.680 | and especially if you pay the cleaning fee.

00:42:31.880 | So, that is not reasonable.

00:42:33.200 | So, that was the second one that I really prioritized.

00:42:35.840 | The third, and this is more on the opportunity, is monthly stays.

00:42:39.880 | That's a growing part of our business.

00:42:41.440 | People think of us as a travel company, but 20% of our business is now housing.

00:42:46.240 | And Airbnb, there's a lot of problems with monthly stays.

00:42:49.160 | For example, you can only pay by credit card.

00:42:52.140 | Paying your rent with credit card means you have to pay a credit card processing fee.

00:42:55.440 | So, we thought, well, what if we allowed an integration where you can pay by bank?

00:42:59.040 | We did integration with Stripe, and now you can save a bunch of money paying by bank.

00:43:03.040 | You can now pay in installments.

00:43:05.000 | We now lower the fees.

00:43:06.520 | We now have this really cool little dial.

00:43:08.520 | We now have really cool pricing discount tools.

00:43:11.240 | So, hosts can be encouraged to charge less and will promote the very best listings.

00:43:15.400 | So, these are maybe some of the ones that I was probably most passionate about.

00:43:19.320 | Anything around pricing, anything around chores, anything around really expanding the definition

00:43:23.560 | of Airbnb.

00:43:24.560 | But yeah, there were 53 upgrades that we made.

00:43:27.360 | So, there were a lot of things.

00:43:28.360 | That's incredible.

00:43:29.360 | Yeah.

00:43:30.360 | And running a remote company, you're so thoughtful about how you're running the company now,

00:43:34.640 | and then you have constraints.

00:43:35.640 | It seems like you've got it really dialed in.

00:43:36.920 | Yeah.

00:43:37.920 | And listen, the stock market is responding to it.

00:43:39.360 | The stock market is looking for discipline.

00:43:41.400 | I think you were the first of the cohort to actually show it.

00:43:45.320 | Uber just showed it.

00:43:46.320 | They started hitting free cash flow.

00:43:48.080 | Dara's done a great job there.

00:43:49.560 | And we're starting to see this discipline.

00:43:51.680 | And Zuck actually got religion.

00:43:54.200 | He cut 20,000 people and got rid of layers of management.

00:43:58.640 | How is, when you are a remote company and you try to institute this, are these things

00:44:04.200 | in sync still?

00:44:05.320 | Or do you miss being in the same place with each other?

00:44:09.240 | Or do these retreats that you're doing and these offsites, whatever you call them now,

00:44:14.840 | are they enough?

00:44:15.840 | Or do you think at some point you want to be in an HQ again?

00:44:19.560 | Yeah.

00:44:20.560 | Actually, yeah.

00:44:21.560 | So, probably, actually even good to clarify, we're not a so-called returned office company

00:44:25.920 | or a remote company.

00:44:26.920 | I would say Shopify and Coinbase are probably remote companies, as far as I can tell, last

00:44:30.760 | I checked.

00:44:31.760 | I go to an office every week.

00:44:33.480 | And many of my top people go to an office every week.

00:44:35.720 | And we have offices open, and we welcome people back to the office.

00:44:38.800 | But we don't require people.

00:44:40.240 | We say, "You work wherever the hell you want because we're so disciplined, so organized

00:44:43.800 | that we don't think there's going to be a hit to productivity."

00:44:46.320 | I basically came to the conclusion that, especially with the accelerating rate of technological

00:44:50.120 | progress to AI, increasingly, you're going to be able to have more and more of a global

00:44:54.160 | talent pool.

00:44:55.280 | And so then, if you're going to require people to come into an office, you have to believe

00:44:58.720 | that you get a greater productivity gain by having them physically there than the productivity

00:45:03.000 | gain you have being able to hire anyone anywhere in the world.

00:45:06.760 | And for some jobs, like your core team, where it's really creative and you're making stuff,

00:45:11.000 | I think you want to be physically together.

00:45:13.240 | But I do not need our accounting systems to be managed together physically around me.

00:45:17.720 | I don't need thousands of people physically around me.

00:45:19.920 | I can't even talk to them.

00:45:21.120 | After about 1,500 people, I can't remember the conversations.

00:45:26.440 | I can't keep track of those conversations.

00:45:28.080 | So my vision is that we have a small, tight team of some of the most senior people, many

00:45:34.440 | product people.

00:45:35.440 | We built this creative studio, and we're in San Francisco a lot.

00:45:38.920 | And then the rest of the company, they can choose.

00:45:40.840 | Some groups, they do come to the office.

00:45:43.020 | Other groups, people just work totally remotely.

00:45:45.160 | And then once a week, a quarter, we try to bring people together.

00:45:48.760 | Sometimes it might be a week every six months.

00:45:50.800 | And I think that kind of suffices for a lot of people.

00:45:53.360 | In other words, we kind of give teams the option.

00:45:56.160 | But the most senior people, we're pretty much together.

00:45:59.320 | We also travel a lot together.

00:46:01.000 | So I'm here in New York.

00:46:02.840 | We probably had 20 people here with me.

00:46:04.680 | So I was around them.

00:46:06.440 | But I think we're just still learning.

00:46:07.920 | We're still moving.

00:46:08.920 | And I think, Jason, the future is flexibility.

00:46:11.640 | I think that this is the worst technology we'll ever be in our lifetime.

00:46:15.840 | As screens get better, as bandwidth gets stronger, I think people are going to want more flexibility.

00:46:20.360 | And my prediction is even proponents of working in the office, I bet you a lot of those people

00:46:24.720 | are going to be somewhere else over the summer in an Airbnb.

00:46:27.240 | You know?

00:46:28.240 | Yeah.

00:46:29.240 | It's easy for people to be like, "Yeah, we will."

00:46:30.560 | All these rich guys in New York, let's just be honest, all these rich guys in New York

00:46:33.160 | who said they want to call back to the office, they're all going to Hamptons for the summer,

00:46:37.720 | and they're going to Europe in August.

00:46:39.240 | So even the return to office, those aren't 12 months a year.

00:46:42.240 | Those are now nine months a year.

00:46:43.680 | Yeah.

00:46:44.680 | And I mean, Europeans have a better lifestyle and they enjoy it.

00:46:48.240 | So maybe what happened during this pandemic, when we look back on and we do the post-mortem,

00:46:53.040 | it's going to be, "Hey, you know what?

00:46:55.240 | Maybe Americans, we were slaves to the offices a bit too much.

00:46:58.720 | We over-indexed on it."

00:47:00.360 | And maybe there's some balance because when you do take a four-week vacation and you work

00:47:04.400 | half days for two of the weeks, you kind of come back refreshed and you stay with the

00:47:08.000 | company longer.

00:47:09.000 | You don't resent your company and you're not depressed because you feel guilty about not

00:47:13.320 | spending time with your kids or not checking the bucket list items.

00:47:16.520 | And I think you're so right about the speed to hire that talented person versus the annoyance

00:47:23.080 | of somebody quiet quitting, or somebody's phoning it in, or somebody's working two jobs.

00:47:27.480 | Like, of course, you're going to have abuse in every system.

00:47:29.320 | There's abuse in people who come to the office, screwing around with their door closed.

00:47:32.840 | So you're going to deal with some level of, I don't know, bad actors, whatever.

00:47:37.600 | And I kind of feel like if you want people to come to the office, it should be because

00:47:41.280 | of collaboration, it should be for trust building.

00:47:43.880 | It shouldn't be for accountability.

00:47:45.580 | We have enough tools digitally that actually, it's frankly easier to track people when they're

00:47:50.440 | working digitally than they're in the office because you can actually track everything

00:47:54.760 | they're doing and you can just have really good mechanisms like what did you get done

00:47:58.040 | today?

00:47:59.040 | Yes.

00:48:00.040 | Actually, we have a whole program manager operation whose job it is to basically tally

00:48:03.960 | what everyone's doing.

00:48:05.600 | And if we don't know what you're doing, then we're not doing our job.

00:48:08.640 | That's I think, why people are so, some of these managers are so aggressive about this

00:48:14.040 | is because they don't actually know how to manage.

00:48:16.780 | And so since they didn't know how to manage, they were managing by the fear of being in

00:48:20.420 | the office and the punch clock as opposed to, did you assign the right person to work

00:48:24.420 | and did you check the work?

00:48:25.420 | Yeah.

00:48:26.420 | And checking the work and assigning the work is a lot of work and prioritizing, as you

00:48:30.100 | just said, your biggest challenge as the founder is just keeping all this in your head and

00:48:35.060 | trying to make the right decision on behalf of the customers.

00:48:38.260 | And so many managers are phoning it in.

00:48:39.980 | I came up with the simplest system possible for my investment company, which was at the

00:48:43.700 | end of the day, have a cup of coffee and share with the team what you're going to try to

00:48:46.520 | accomplish.

00:48:47.520 | And when you check out for the end of the day, like make it a good checkout so you can

00:48:49.860 | go spend time with your family and just say what you got accomplished, if there are any

00:48:53.540 | blockers.

00:48:54.540 | And when people just started doing that in the slack room, it was such a big difference.

00:48:57.380 | It was such a big difference.

00:48:58.380 | And then when somebody left the company, you know, we did we looked at their end of the

00:49:01.180 | week, and what they said they got accomplished what they were working on.

00:49:03.900 | And we said, Hey, here's the last three into the weeks, we put it into one document, who

00:49:08.020 | should do this job?

00:49:09.420 | Should this job be retired?

00:49:10.420 | Should it be spread across three people?

00:49:11.940 | Should it be outsourced?

00:49:12.940 | You can actually look at the granularity, like you're saying, when they do digital work,

00:49:16.940 | it's all right there.

00:49:17.940 | So then you can say, does this position need to be here?

00:49:20.460 | Or should it be outsourced or automated?

00:49:23.340 | You keep bringing up AI.

00:49:26.140 | And I'm curious, when you start, what are you seeing in AI right now that's getting

00:49:30.780 | you excited, internally running the company, and then externally in terms of opportunities,

00:49:37.500 | because travel is such a rich, textured experience, it's also so customized.

00:49:42.860 | So you know, so much about your customers, you know, when I'm in Japan, you know, my

00:49:47.700 | trip to France, you know, the different places I've Airbnb'd, you know, who came with me.

00:49:54.620 | And, you know, whatever else, you know, about the hosts and everything.

00:49:58.940 | What do you think the opportunity is going to be in travel, specifically for AI?

00:50:02.340 | Yeah, so let me let me, if you may indulge Jason, I'll like zoom out and just give you

00:50:06.860 | like kind of my mental model.

00:50:08.460 | And you can tell me if this maps to yours.

00:50:11.140 | So you have like the base of the foundation, right, the base models, which are basically

00:50:15.620 | the large language model.

00:50:17.500 | So of course, GPT-4 is probably the preeminent base model.

00:50:21.260 | Google has some base models, Anthropic has a base model, Microsoft Research has their

00:50:24.860 | own base model.

00:50:25.860 | So you have like three to five big base models.

00:50:28.100 | I think of those base models as if it's like a highway, they're the highway, they're like

00:50:32.980 | the infrastructure.

00:50:34.100 | And, you know, in another generation, by the way, that probably would have been dealt by

00:50:37.380 | the government, right?

00:50:39.060 | It's almost like the Manhattan Project, these large language models are going to be eventually

00:50:43.020 | about $100 billion supercomputers running these models.

00:50:46.580 | So they're going to be like massive, these are giant infrastructures.

00:50:49.500 | And we're not going to do that.

00:50:50.740 | We don't do infrastructure.

00:50:52.220 | Airbnb, we think of ourselves as designing the cars on the highway.

00:50:55.460 | So on top of the base model, you have the tuning of the model.

00:50:58.860 | And the tuning of the model is going to be as good as your sensibility and your customer

00:51:02.460 | data.

00:51:03.460 | So if you and I both ask Chachi Pitya a question, we mostly get the same answer.

00:51:07.700 | And we mostly get the same answer because it doesn't know who you or I am.

00:51:11.660 | And that's great for some questions, like what was the like, you know, like, how far

00:51:17.340 | is the moon from the sun or whatever?

00:51:19.260 | Like there's one right answer.

00:51:20.900 | But if you ask like, where should I travel?

00:51:22.740 | Your answer and my answer are probably different.

00:51:24.740 | And so some problems are search problems.

00:51:27.260 | Some problems are kind of matching and personalization preferences problems.

00:51:30.780 | And so what we want to do is we want to be one of the best companies for AI personalization.

00:51:36.020 | So we want to develop really good tuned models.

00:51:38.860 | To do that, we have to change our business.

00:51:41.140 | And actually, one of the questions that Johnny Ive told me when we brought him on the team

00:51:44.660 | is he said, you need to switch from beyond, you need to go beyond where and when.

00:51:48.900 | Right now, you ask, where are you going?

00:51:50.460 | And when are you going?

00:51:51.460 | And we need to shift to who and what, who are you and what do you want?

00:51:55.540 | And that's really the vision.

00:51:57.300 | And so what we want to do is we want to build these robust profiles, I want to start to

00:52:01.820 | learn Jason, who you are, build really good, rich customer information.

00:52:06.340 | And then I can understand and personalize, like, where do you want to go?

00:52:09.100 | And also, what do you want in your life?

00:52:10.300 | Like you looking for inspiration, just get out like a, you know, what do you what are

00:52:13.300 | you looking for?

00:52:14.300 | Do you like want to get healthy?

00:52:15.300 | Do you, you know, and you start to learn about people.

00:52:18.300 | And then we're also pretty good interfaces and the application layer.

00:52:22.900 | And I think that Airbnb, that's where we're really, really going to focus, we're going

00:52:26.340 | to focus on the tuning of the models, the most personalized AI interface, and then really

00:52:31.100 | good application interfaces.

00:52:33.100 | Now I think as far as interface, I don't think they're all going to be just text based.

00:52:37.220 | For example, we were working on the open AI plugin, we were one of the first partners

00:52:41.940 | that was working with open AI.

00:52:44.260 | And at the last second, I pulled the plug on the plugin.

00:52:47.260 | Because I just didn't like the interface.

00:52:48.860 | I didn't think that was the right way to interface a travel.

00:52:51.260 | I told Sam, I said, long text outputs are low bandwidth.

00:52:55.380 | And then you give me another text output with widgets at the bottom, I said, I want something

00:52:59.500 | much more multimodal, more visual, richer.

00:53:02.940 | And if you're going to have access to GPT-4, why don't we put it in our app.

00:53:06.740 | So we pulled the plug on the plugin.

00:53:09.340 | And we think eventually, I think our real vision is Airbnb, at the largest sense, isn't

00:53:15.780 | even a product or service.

00:53:17.060 | I hope it's more like a travel community.

00:53:18.780 | We're really building a travel community.

00:53:20.700 | And then the role we have the app in the travel community, is eventually we're like the ultimate

00:53:24.780 | like AI concierge, right?

00:53:26.820 | We're like the ultimate host, like Charles Eames, one of the greatest in our 20th century

00:53:30.700 | said, "The role of the designer is that of a thoughtful host, anticipating the needs

00:53:33.700 | of the guests."

00:53:34.700 | So that's what we should do.

00:53:35.700 | And we understand who are you?

00:53:37.060 | What do you want?

00:53:38.060 | Where do you want to go?

00:53:39.060 | And maybe we could even go beyond travel, if we get there, right?

00:53:42.420 | And the part of that means you have to trust us to give us your personal information.

00:53:46.980 | It means we have to be a marriage of art and science.

00:53:49.700 | It means we have to understand a lot about like human psychology and know what you want.

00:53:53.020 | It's not just a technical problem.

00:53:55.020 | We have to design unique AI interfaces that are probably richer than just text inputs.

00:54:01.180 | Because you know, like, you want to see and feel things, right?

00:54:05.740 | And I think it's much more immersive.

00:54:07.740 | So that's where I think it goes.

00:54:09.860 | That's like the long term vision.

00:54:11.860 | In the interim, and that's probably long term is in three to five years.

00:54:15.260 | I mean, that's not even that long term.

00:54:18.140 | In the next year, what we're going to do is three things.

00:54:20.980 | One, engineer productivity or productivity.

00:54:24.380 | I mean, I think engineers can be 30% more productive in the next three to six months.

00:54:29.820 | - It's exactly the number I can put with.

00:54:32.180 | I'm watching my team interview founders for investment.

00:54:35.660 | I'm looking at due diligence.

00:54:37.380 | And I'm looking at my own behavior.

00:54:38.540 | And it seems like one out of three tasks, I can offload.

00:54:41.900 | And so I'm like, this is like this year, 30% more efficient, which means headcount stays

00:54:45.360 | the same, but we just added a third more people like this is unbelievable.

00:54:50.100 | - It's amazing.

00:54:51.100 | And by the way, it's actually if everyone's 30% more productive, it's actually more productive

00:54:55.500 | than adding 30% more people because you know, the mythical man month, every time you add

00:54:59.180 | somebody they bring up communication and like, like bring attacks with them.

00:55:03.420 | So this is like productivity without the tax of more people.

00:55:07.660 | And I think the productivity doubles, you know, in somewhere between one and two years,

00:55:12.500 | it's a little hard to know, but it will be double.

00:55:14.220 | So we'll have the equivalent of twice the engineers without the productivity tax.

00:55:19.400 | And so that's the first thing is just getting everyone on the tools, give everyone a co-pilot

00:55:23.060 | and getting everyone like just immerse.

00:55:25.060 | And I just bang the drum, like use these tools as much as you can.

00:55:28.660 | I don't want to be like the Luddites or like afraid of a computer in the 1980s, right?

00:55:32.620 | Like we want to be using these tools.

00:55:34.660 | - That is so key.

00:55:35.660 | I told everybody to make chat GPT for their homepage in their browser, so that every time

00:55:40.440 | they open their browser, it just reminds them, hey, use this.

00:55:43.220 | And I said, searches is obvious.

00:55:44.980 | But when I told you they do, they're like, hey, here's what I'm going to accomplish today.

00:55:47.660 | And here's what I'm going to accomplish at the end of the day.

00:55:49.540 | I just told everybody, try that in chat GPT and try a plugin.

00:55:53.700 | And by the way, when you were talking about plugins being like not exactly the right modality,

00:55:58.340 | I've been using OpenTable, Expedia, Kayak the last couple of days for travel, trying

00:56:02.340 | to see if it works.

00:56:03.760 | And it's not as good as using some of the other like native interfaces yet.

00:56:09.020 | I mean, I'm sure it'll get better, but I agree that it needs to be visual and it's got a

00:56:13.520 | long ways to go.

00:56:14.520 | - OpenAI is a choice.

00:56:15.520 | They can either invest a ton on the interface layer, or they can decide that they're the

00:56:20.260 | brain and other people decide the interface.

00:56:22.700 | Either way it can work.

00:56:23.820 | But either way, the interfaces, here's the thing I'd say, do you remember when like the

00:56:28.580 | iPhone launched and Steve said like, the problem with most smartphones is the bottom half of

00:56:32.700 | the screen, the interface doesn't change?

00:56:34.900 | I think that we should think of every task as wanting a distinct interface.

00:56:40.440 | Like you have a hammer to get a nail in, you have a screwdriver for a screw, you have a

00:56:43.940 | spatula to scoop something up.

00:56:46.580 | Every interface should be custom designed exactly for the task.

00:56:49.940 | - Do you think it's voice for travel or do you think it's flipping through videos that

00:56:53.620 | are TikTok style and then understanding which ones people spend more time on?

00:56:57.660 | - I don't think it's voice.

00:56:58.660 | I think voice is for commodities.

00:56:59.980 | So if you basically say I need to go from here to there, and there's no inputs, there's

00:57:05.300 | no decision making or visual discretion in voice.

00:57:08.060 | I think it's more like, I don't want to say like minority report, but I have this image

00:57:12.180 | of like, it's an immersive interface where it's words and images, and it's a conversational

00:57:19.420 | bot, but it's not pure text.

00:57:21.780 | It's got lots of rich visuals, videos, photos.

00:57:25.340 | It's a little hard to describe.

00:57:26.380 | I have to build a prototype.

00:57:27.380 | - I haven't seen Minority Report.

00:57:28.740 | He puts on a pair of gloves, which MIT was working on at the time, and he's just moving

00:57:32.260 | stuff around in a virtual desktop.

00:57:34.340 | - That's conceptually what I'm talking about.

00:57:35.900 | - Yeah, I think it's actually a pretty brilliant one because if you think about the function

00:57:38.820 | of magazines, which is how people did this previously, you flip through a magazine, what

00:57:43.140 | would you see in a magazine?

00:57:44.140 | A subhead, a headline, a table, an infographic, a picture, a two-page spread, a table.

00:57:51.340 | And all of that was evocative and kind of pulled you in, and I actually really think

00:57:56.060 | with this vision of trying to understand me as a person, psychologically and where I'm

00:58:01.460 | going next, oh, Jason's doing more skiing, oh, he's got a bucket list of places he wants

00:58:07.260 | to go skiing, ah, he's really into food, and that trust you've built up is interesting

00:58:12.980 | as well because I would have no problem authenticating with Instagram and giving you all my photos,

00:58:17.620 | and with AI, you could just tell from my photos that I take pictures of a lot of food, and

00:58:23.060 | I take a lot of pictures of skiing.

00:58:25.140 | You now know a lot about me, and I don't have to tell you, you just know my Instagram account.

00:58:29.740 | - And I think the problem is all of us, and Airbnb is part of this problem, you come to

00:58:35.380 | Airbnb and it looks the same as it did the last time you came, and we're like a marketplace,

00:58:39.580 | and everything's a transaction, and we assume you're like, we don't know anything about

00:58:43.100 | you, and you just walked into a store, and we got a bunch of stuff on a shelf.

00:58:46.380 | And I think that's a very 1990s, 2000s Amazon paradigm of commerce, and I think the future

00:58:52.300 | of commerce is more like somebody showing you around, and they understand you deeply,

00:58:57.060 | and you have so much more control, and it's significantly more personalized, and everyone

00:59:00.420 | has a unique experience.

00:59:02.060 | And so that's where I think it goes, and I think that we don't have a search problem

00:59:05.020 | in the future, we have a matching problem.

00:59:06.820 | So we are gonna use AI to match you to whatever you want, and I think that, the other thing

00:59:12.180 | is, I think we're gonna be really good at hopefully identity authentication.

00:59:16.900 | You know, the problem with AI is, what's the first word in AI?

00:59:21.220 | Artificial.

00:59:22.220 | The biggest risk before machines come after us is they become us, and we can't discern

00:59:27.020 | who is a machine and who is not.

00:59:29.180 | And I think that we're already seeing that.

00:59:30.380 | I mean, when that Pope photo circulated, I thought that was a real photo at first.

00:59:33.340 | - I did too, I was like, that's weird, the Pope is going for it.

00:59:36.740 | - Yeah, I was like, pretty awesome, he's got Balenciaga, go for him.

00:59:40.020 | But that's today's technology.

00:59:42.460 | So we're about to live in a world where someone can sound like me, they can behave like me,

00:59:46.860 | and as we spend more and more time online, it's gonna be harder to discern what is real

00:59:50.020 | and what's not real.

00:59:51.020 | So I think in the age of artificial intelligence, the other thing people want is authenticity.

00:59:56.100 | And authenticity is whatever's real, and whatever's authenticated.

00:59:59.500 | So I think our brand is kind of authenticity, like we're not gonna ever be the most digitally

01:00:03.860 | immersive company.

01:00:05.300 | That's gonna be social media or entertainment.

01:00:07.860 | Our value is really the physical world.

01:00:09.700 | We get you online, offline, with people different from you all over the world.

01:00:13.740 | And that comes with starting with knowing who you are, authenticating your identity.

01:00:17.380 | Eventually, we may use biometrics, because right now we use like a government ID.

01:00:21.300 | But I think eventually, I want to do something with biometrics to be much more robust, so

01:00:25.860 | you can't really get around it.

01:00:27.460 | And then we have your identity, you trust us, we build this incredibly robust personal

01:00:31.740 | profile.

01:00:32.740 | And then we can just match you and we are the then and then hopefully, we're really

01:00:35.780 | good interfaces.

01:00:37.460 | And we use the latest, greatest language models.

01:00:40.380 | - Yeah, it's pretty amazing how fast these are working, and what's going to be possible,

01:00:45.860 | because we don't know what it's going to match people with over time.

01:00:50.460 | I don't know necessarily what's going to delight me, but every time I go somewhere in the world

01:00:56.500 | that somebody else introduces me to, like my guide on the side, a friend, if you told

01:01:00.540 | me, "Hey, you gotta try this place in San Francisco, cafe, Okinawa that I've been going

01:01:06.020 | to to get tonkatsu sandwiches."

01:01:08.140 | I told like three people about this, because I love these when I go to Japan, and everybody

01:01:12.740 | goes there and they're like, "Oh yeah, you're right, that was great."

01:01:14.980 | And now they spread to the next person, and that kind of word of mouth, I think like this

01:01:19.540 | AI is going to find little things like that, where it didn't know that this was something

01:01:23.700 | that you would be delighted by.

01:01:25.300 | - Totally.

01:01:26.300 | - And it's such an opportunity.

01:01:27.300 | - I think it's amazing.

01:01:28.300 | And by the way, I think I heard another, one of your podcasts, you said something that

01:01:32.420 | really resonates that I think it's just worth calling out.

01:01:35.220 | The cost to develop software is about to go down, and maybe a good analogy, Jason, would

01:01:39.140 | be like the camera.

01:01:40.140 | 130 years ago, very few people could operate a camera.

01:01:43.700 | And so, therefore, you had to be a specialist to take a photo, and there weren't a lot of

01:01:47.660 | photos.

01:01:48.660 | Suddenly, computer programming is just basically telling a computer to do something in its

01:01:52.820 | language.

01:01:53.820 | AI means you can now tell a computer to do something in your language.

01:01:56.640 | The moment you don't have to learn a different language, you can use your natural language

01:01:59.820 | to English, suddenly kind of everyone in a way can be a programmer like everyone's a

01:02:04.660 | photographer.

01:02:05.660 | You don't have to actually have a skill.

01:02:06.660 | Now, there will be programming skills, but suddenly anyone can do that.

01:02:10.260 | Now when that's possible, there's going to be so much more software.

01:02:13.100 | We're going to live in an abundance of software.

01:02:15.220 | I think in a podcast, you referenced like a ski instructor or a ski company, like a

01:02:19.620 | niche business that couldn't have developed, hired great software engineers, but now they

01:02:24.220 | can become the best engineer you've ever had developing their app.

01:02:28.500 | And so, suddenly the skills start to be different.

01:02:30.340 | We have to understand skiing, human psychology, taste, design, and how to operate and have

01:02:35.740 | a conversation with that tool, but you don't have to necessarily build the infrastructure.

01:02:39.940 | It's like we never built servers because we had AWS, but if we launched five years earlier,

01:02:45.180 | we would have had to have been really good at like kind of building out servers.

01:02:48.180 | Rack and stacking servers.

01:02:49.180 | I mean, your first half a million would have went towards a co-location facility.

01:02:53.420 | And now it's like, you're just going to talk to this thing and it's going to make your

01:02:56.820 | software for you.

01:02:57.820 | So I think this is going to create, I think this is going to create millions of startups.

01:03:01.860 | I think that like, entrepreneurship is going to be a boon.

01:03:05.420 | I think there's going to be millions more.

01:03:06.820 | I think anyone can essentially do the equivalent of what software engineering only allowed

01:03:10.420 | you to do only five years ago.

01:03:12.380 | It's going to be awesome for many people.

01:03:13.860 | It's going to be wildly disruptive for others.

01:03:16.180 | Albert Einstein used to have a saying, the best way to keep your balance in a bicycle

01:03:19.260 | is to keep moving.

01:03:20.260 | And I think the best way to keep your balance in the world of AI is to keep moving forward

01:03:23.800 | and just adopt the tools.

01:03:25.300 | Don't fight it and see where it takes us.

01:03:27.940 | But it's going to be pretty wild.

01:03:28.940 | So interesting you say that.

01:03:29.940 | I was just looking, the Writer's Guild was going on strike and like on the second page,

01:03:35.460 | the third thing from the bottom was their update on AI.

01:03:39.700 | And they're like, we're seeking a ban of using AI in the writer's room, using AI to ingest

01:03:44.140 | previous scripts, and using AI to generate future scripts and dialogue.

01:03:49.300 | And it said, the most the studios will commit to is doing a yearly review with the union

01:03:55.080 | about technology.

01:03:56.700 | And it's like, don't you realize you could ingest the entirety of the Simpsons or every

01:04:01.180 | late night joke, and then you would start on second or third base with all these incredible

01:04:05.620 | ideas and brainstorms for jokes, and the jokes would get better, and the shows would be more

01:04:10.060 | compelling.

01:04:11.060 | You're totally right.

01:04:12.060 | I think trying to ban AI is like trying to ban electricity.

01:04:14.500 | You're going to be on the wrong side of history.

01:04:16.100 | The genie's out of the bottle, you can't put it back in the bottle.

01:04:18.740 | And I think that, here's the problem, Jason.

01:04:21.800 | I think it's easier to imagine what jobs will be displaced than what jobs will be created.

01:04:26.340 | Because we can imagine everything that now AI can do.

01:04:30.840 | We can't imagine everything it hasn't yet done, because that requires us to conceive

01:04:35.060 | of what doesn't exist.

01:04:36.500 | But if we remember that in all other periods in history, technology created jobs that didn't

01:04:41.860 | exist.

01:04:42.860 | This can do that too.

01:04:43.860 | It doesn't mean we should be blindly ignorant or not be concerned.

01:04:46.620 | There's a lot of concerns I have about AI.

01:04:49.180 | I'm concerned about how fast it's going, and is society prepared for the speed.

01:04:52.860 | But I think from a creative standpoint, as a person who went to Rhode Island School of

01:04:56.460 | Design, I would tell the creative community, you only have to be worried if you don't want

01:05:00.200 | to be a part of it.

01:05:01.200 | Because this is a creative tool for you.

01:05:03.460 | You know, computers are tools.

01:05:06.240 | The reason they put a handle on the back of the iMac was they used to have a saying at

01:05:10.260 | Apple, "Never trust a computer you can't throw out the window."

01:05:13.460 | Computers are tools and AI is a tool.

01:05:15.500 | And I think if we think of it as a tool, then it's a tool for creativity.

01:05:19.280 | And you're right, you start in third base.

01:05:20.820 | Like, I'm already noticing at Chachibit, like, it makes my writing better.

01:05:24.420 | I don't use - I actually don't use most of what Chachibit gives me back, but it gives

01:05:29.380 | me some words.

01:05:30.860 | And I'm like, "Summarize this."

01:05:32.260 | The cold start problem is solved, because you're like, "Hey, I want to write about,

01:05:36.100 | I want to make a marketing plan."

01:05:37.340 | And it's like, "Oh, well, here's what goes in a marketing plan."

01:05:39.220 | You're like, "Oh, yeah, points two and seven, let me double down on those."

01:05:42.260 | Or I can like, I can have a thousand word thing, say, summarizes in four sentences,

01:05:47.060 | and maybe I don't use the four sentences, but it gives me ideas.

01:05:49.860 | By the way, before we go, I want to say, one, I keep discovering new uses for Chachibit.

01:05:55.380 | Here's the coolest use I've discovered.

01:05:57.380 | I asked Chachibit a question, "At the most fundamental level, what business are we in?"

01:06:02.100 | And then it spits out a not super insightful answer, like, "Airbnb is the business of travel

01:06:06.620 | and experiences and blah, blah, blah."

01:06:08.460 | And then I - the cool thing that you should do this, is ask a follow-up, and keep asking

01:06:12.300 | follow-ups until I can't do it anymore.

01:06:14.300 | And so I ask, "What's a more fundamental business?"

01:06:16.660 | And it goes, "Actually, a more fundamental business that Airbnb is in is sharing."

01:06:20.740 | And I go, "Okay, but what's a more fundamental business?"

01:06:23.020 | Then it goes, "A more fundamental business is human connection."

01:06:26.220 | And I go, "What's a more fundamental?"

01:06:27.500 | And it just keeps going.

01:06:28.500 | - Joy!

01:06:29.500 | - And you, but you start to learn, and it teaches you its first principles, right?

01:06:32.980 | - Yes.

01:06:33.980 | It reduces it down.

01:06:34.980 | Yeah.

01:06:35.980 | - And then I did the same thing with AI.

01:06:36.980 | I said, "How can AI transform Airbnb?"

01:06:39.940 | And it has these really small ideas.

01:06:41.700 | And then I go, "How can do it even bigger?"

01:06:43.220 | And you keep doing it.

01:06:44.740 | And so if you keep going, go bigger, or go more fundamental.

01:06:47.660 | Keep going.

01:06:48.660 | - Yeah.

01:06:49.660 | Take more risk.

01:06:50.660 | - AI starts to teach.

01:06:51.660 | It helps you discover the first principles in really interesting ideas, which I think

01:06:57.620 | the follow-up questions with these chatbots are always more important than the first question.

01:07:02.620 | - Yeah.

01:07:03.620 | It really gets interesting the third or fourth time.

01:07:06.220 | And as you said, I think one of the most profound things you've said here is, "We don't know

01:07:09.900 | what jobs can be created because they haven't been created yet."

01:07:12.420 | - Yes.

01:07:13.420 | - And if you look at marketplaces, whether it's eBay, whether it's Etsy, whether it's

01:07:17.900 | Airbnb, whether it's Uber or DoorDash, to different extents, these allowed people to

01:07:23.740 | create new careers for themselves.

01:07:25.380 | - Yeah.

01:07:26.380 | - And how many people do we know now who became real estate magnates and they own 20 properties

01:07:31.580 | because of how well their first two properties did on Airbnb?

01:07:34.580 | Or they have collections on Etsy or Kickstarter.

01:07:38.820 | And who knows what this is gonna lead to, but it's going to...

01:07:42.700 | Unless there's not enough problems and not enough human creativity and energy, then this

01:07:47.340 | is gonna be incredible for society, I believe.

01:07:49.980 | - Exactly.

01:07:50.980 | - I'm an optimist about it, and I'm using it every day for multiple hours a day.

01:07:53.740 | I'm playing with the plugins, the web tools.

01:07:56.420 | And I just started on Repl.it, like, putting up bounties, and I started a Python course

01:08:02.220 | because I'm like, "I just wanna know how to, like, stitch this stuff together," because

01:08:05.460 | the auto-GPTs, to me, are where this gets really wild.

01:08:08.700 | - Oh, yes.

01:08:09.700 | - If you could start putting a couple of the ideas we talked about today on autopilot and

01:08:14.220 | then say, "Hey," and try to make a better result every day, it could just be trying

01:08:19.100 | to make a better result for how Airbnb understands my travel taste.

01:08:23.820 | And you say, "Hey, just keep trying to get information from Jason, ask him some interesting

01:08:27.420 | probing questions, or look at his social media and try to give him better ideas," and then

01:08:31.740 | I give the thumbs up, thumbs down, either implicitly or explicitly, and you just start

01:08:35.620 | understanding me.

01:08:36.620 | Hey, listen, I know you gotta go.

01:08:38.540 | This has been amazing, dude.

01:08:39.580 | I'm so glad we got to finally do this.

01:08:41.260 | - I know.

01:08:42.260 | Thank you for having me.

01:08:43.260 | - We'll talk again soon.

01:08:44.260 | We gotta not wait so long.

01:08:45.260 | - Let's do it, yeah.

01:08:46.260 | Well, you know, the thing is, like, I had all these notes about, like, the blocking

01:08:48.860 | and tackling.

01:08:51.300 | Like all great conversations, I think, and great CEOs, you've got some things on your

01:08:55.260 | mind about how you're architecting the company and then AI that are really profound.

01:08:59.660 | So, if you're an entrepreneur, you're gonna wanna listen to this with your team and probably

01:09:03.220 | don't put it on 2X speed because Brian and I both talk pretty quick.

01:09:08.820 | But a great conversation, bookend it with the Joe interview, and we'll see you all next

01:09:14.100 | time on This Week in Stardust.

01:09:15.100 | Bye-bye.

01:09:15.100 | - Bye-bye.

01:09:15.600 | - Bye-bye.

01:09:16.100 | - Bye-bye.

01:09:16.600 | - Bye-bye.

01:09:17.600 | - Bye-bye.

01:09:18.100 | - Bye-bye.

01:09:19.100 | - Bye-bye.

01:09:19.600 | (upbeat music)

01:09:22.180 | [BLANK_AUDIO]

Airbnb CEO Brian Chesky on early rejection, customer focus & AI’s future in hospitality | E1735

Chapters