Tony Xu of DoorDash: Surviving 1,000 Days of Startup Hell

0:02 So I want to start with the the fact

0:04 So I want to start with the the fact

0:04 So I want to start with the the fact that you said that Paulo Alto

0:05 that you said that Paulo Alto

0:05 that you said that Paulo Alto Delivery.com which was Door Dash and

0:07 Delivery.com which was Door Dash and

0:07 Delivery.com which was Door Dash and Ford Door Dash was the most minimal

0:09 Ford Door Dash was the most minimal

0:10 Ford Door Dash was the most minimal version of a minimal viable product. Can

0:12 version of a minimal viable product. Can

0:12 version of a minimal viable product. Can you explain how you built it?

0:14 you explain how you built it?

0:14 you explain how you built it? >> Well, whenever you can ship something in

0:15 >> Well, whenever you can ship something in

0:16 >> Well, whenever you can ship something in 43 minutes to test your idea,

0:18 43 minutes to test your idea,

0:18 43 minutes to test your idea, >> I think that's pretty good. And

0:19 >> I think that's pretty good. And

0:19 >> I think that's pretty good. And certainly this is, you know, 12 13 years

0:21 certainly this is, you know, 12 13 years

0:22 certainly this is, you know, 12 13 years before the rise of LLMs and AI tools to

0:24 before the rise of LLMs and AI tools to

0:24 before the rise of LLMs and AI tools to make it so easy to do that. But

0:26 make it so easy to do that. But

0:26 make it so easy to do that. But basically, the four of us wanted to test

0:28 basically, the four of us wanted to test

0:28 basically, the four of us wanted to test this idea that if you wanted to offer

0:31 this idea that if you wanted to offer

0:31 this idea that if you wanted to offer delivery from places that never offered

0:33 delivery from places that never offered

0:33 delivery from places that never offered delivery before, what is the fastest way

0:34 delivery before, what is the fastest way

0:34 delivery before, what is the fastest way to see whether or not consumers would

0:36 to see whether or not consumers would

0:36 to see whether or not consumers would care? I mean, at the end of the day,

0:37 care? I mean, at the end of the day,

0:37 care? I mean, at the end of the day, delivery is not a new idea. And so, we

0:39 delivery is not a new idea. And so, we

0:39 delivery is not a new idea. And so, we thought actually one of the reasons why

0:41 thought actually one of the reasons why

0:41 thought actually one of the reasons why maybe delivery in 2013 hadn't been

0:43 maybe delivery in 2013 hadn't been

0:43 maybe delivery in 2013 hadn't been around yet was just because nobody

0:45 around yet was just because nobody

0:45 around yet was just because nobody wanted it. So, we shipped

0:46 wanted it. So, we shipped

0:46 wanted it. So, we shipped powaltodely.com that alias was available

0:49 powaltodely.com that alias was available

0:49 powaltodely.com that alias was available for $9. And so, that's why we got it.

0:53 for $9. And so, that's why we got it.

0:53 for $9. And so, that's why we got it. not a super scalable URL, but we were

0:56 not a super scalable URL, but we were

0:56 not a super scalable URL, but we were able to get it. Um, it was a static page

1:00 able to get it. Um, it was a static page

1:00 able to get it. Um, it was a static page um where you saw eight PDF menus of

1:03 um where you saw eight PDF menus of

1:03 um where you saw eight PDF menus of restaurants that we frequented in Palo

1:05 restaurants that we frequented in Palo

1:05 restaurants that we frequented in Palo Alto. And the only way you can in which

1:08 Alto. And the only way you can in which

1:08 Alto. And the only way you can in which you can order is you can read through

1:11 you can order is you can read through

1:11 you can order is you can read through the menus. You can call a Google voice

1:13 the menus. You can call a Google voice

1:13 the menus. You can call a Google voice number that would ring the cell phones

1:15 number that would ring the cell phones

1:15 number that would ring the cell phones of the four founders and one of us would

1:17 of the four founders and one of us would

1:17 of the four founders and one of us would pick up. We would take your order, place

1:19 pick up. We would take your order, place

1:19 pick up. We would take your order, place the order on your behalf, go and get the

1:21 the order on your behalf, go and get the

1:21 the order on your behalf, go and get the order, deliver it to you. And I used to

1:23 order, deliver it to you. And I used to

1:23 order, deliver it to you. And I used to be an internet square and so I had these

1:26 be an internet square and so I had these

1:26 be an internet square and so I had these card readers which was one of their

1:27 card readers which was one of their

1:27 card readers which was one of their earliest products. These wide dongles

1:29 earliest products. These wide dongles

1:29 earliest products. These wide dongles that you could stick into the audio

1:30 that you could stick into the audio

1:30 that you could stick into the audio jacks of iPhones and that's how we would

1:32 jacks of iPhones and that's how we would

1:32 jacks of iPhones and that's how we would collect payment. Something I didn't

1:34 collect payment. Something I didn't

1:34 collect payment. Something I didn't remember until cuz it feels like Door

1:36 remember until cuz it feels like Door

1:36 remember until cuz it feels like Door Dash and and Uber Eats and everything

1:37 Dash and and Uber Eats and everything

1:37 Dash and and Uber Eats and everything else has been around forever but there

1:39 else has been around forever but there

1:40 else has been around forever but there wasn't what was the state of there was

1:41 wasn't what was the state of there was

1:41 wasn't what was the state of there was other delivery companies but you

1:43 other delivery companies but you

1:43 other delivery companies but you essentially created the market for this.

1:45 essentially created the market for this.

1:45 essentially created the market for this. Can you explain like when I was telling

1:47 Can you explain like when I was telling

1:47 Can you explain like when I was telling people I'm coming I'm really excited.

1:48 people I'm coming I'm really excited.

1:48 people I'm coming I'm really excited. I'm going to go speak Tony for Door

1:49 I'm going to go speak Tony for Door

1:49 I'm going to go speak Tony for Door Dash. They were like, I can't believe he

1:51 Dash. They were like, I can't believe he

1:51 Dash. They were like, I can't believe he survived in this like competitive

1:52 survived in this like competitive

1:52 survived in this like competitive market, but they just assumed that all

1:54 market, but they just assumed that all

1:54 market, but they just assumed that all like there was other apps out there that

1:56 like there was other apps out there that

1:56 like there was other apps out there that were already delivering for for

1:58 were already delivering for for

1:58 were already delivering for for restaurants that didn't have a delivery

1:59 restaurants that didn't have a delivery

1:59 restaurants that didn't have a delivery fleet that didn't exist then.

2:01 fleet that didn't exist then.

2:01 fleet that didn't exist then. >> No, actually, yeah. I I think one of the

2:03 >> No, actually, yeah. I I think one of the

2:03 >> No, actually, yeah. I I think one of the biggest misconceptions when we were

2:04 biggest misconceptions when we were

2:04 biggest misconceptions when we were founded was just how wide open the space

2:06 founded was just how wide open the space

2:06 founded was just how wide open the space was where there were about a million

2:08 was where there were about a million

2:08 was where there were about a million restaurants in the states and maybe 20

2:11 restaurants in the states and maybe 20

2:11 restaurants in the states and maybe 20 to 25,000 of them offered deliveries.

2:13 to 25,000 of them offered deliveries.

2:13 to 25,000 of them offered deliveries. Most of them were pizza shops, places in

2:15 Most of them were pizza shops, places in

2:15 Most of them were pizza shops, places in New York City, some in, you know,

2:17 New York City, some in, you know,

2:17 New York City, some in, you know, Chicago, some in, you know, big city

2:19 Chicago, some in, you know, big city

2:19 Chicago, some in, you know, big city centers. But outside of pizza places,

2:21 centers. But outside of pizza places,

2:21 centers. But outside of pizza places, maybe a few Chinese restaurants, nobody

2:23 maybe a few Chinese restaurants, nobody

2:23 maybe a few Chinese restaurants, nobody offered delivery. And so the real grand

2:25 offered delivery. And so the real grand

2:26 offered delivery. And so the real grand question or experiment of Door Dash,

2:27 question or experiment of Door Dash,

2:27 question or experiment of Door Dash, Palto Delivery.com was, okay, what about

2:30 Palto Delivery.com was, okay, what about

2:30 Palto Delivery.com was, okay, what about everyone else? What if you can enable

2:32 everyone else? What if you can enable

2:32 everyone else? What if you can enable everyone to actually offer delivery?

2:34 everyone to actually offer delivery?

2:34 everyone to actually offer delivery? What would that take? Um, and first of

2:37 What would that take? Um, and first of

2:37 What would that take? Um, and first of all, would people care? And that's

2:38 all, would people care? And that's

2:38 all, would people care? And that's really why we ship something so quickly,

2:39 really why we ship something so quickly,

2:40 really why we ship something so quickly, just to see if people would actually

2:41 just to see if people would actually

2:41 just to see if people would actually come and place orders.

2:42 come and place orders.

2:42 come and place orders. >> So what were the existing companies

2:44 >> So what were the existing companies

2:44 >> So what were the existing companies doing then?

2:44 doing then?

2:44 doing then? >> They were mostly um honestly faxing

2:47 >> They were mostly um honestly faxing

2:47 >> They were mostly um honestly faxing orders, believe it or not. So they would

2:49 orders, believe it or not. So they would

2:49 orders, believe it or not. So they would be a website that would receive orders,

2:50 be a website that would receive orders,

2:50 be a website that would receive orders, if you can believe it. They would fax

2:52 if you can believe it. They would fax

2:52 if you can believe it. They would fax the orders literally um into machines

2:55 the orders literally um into machines

2:55 the orders literally um into machines that would sit near the kitchen or the

2:57 that would sit near the kitchen or the

2:58 that would sit near the kitchen or the payment systems inside these

2:59 payment systems inside these

2:59 payment systems inside these restaurants. Then the restaurants would

3:01 restaurants. Then the restaurants would

3:01 restaurants. Then the restaurants would actually go out and do the deliveries

3:02 actually go out and do the deliveries

3:02 actually go out and do the deliveries themselves. So they were lead gen

3:04 themselves. So they were lead gen

3:04 themselves. So they were lead gen companies at the time. I've heard you

3:06 companies at the time. I've heard you

3:06 companies at the time. I've heard you talk about de developing this like last

3:08 talk about de developing this like last

3:08 talk about de developing this like last mile logistics network. Did you think

3:10 mile logistics network. Did you think

3:10 mile logistics network. Did you think about that back then or you were just

3:12 about that back then or you were just

3:12 about that back then or you were just like, "Hey, I'm just going to try to

3:14 like, "Hey, I'm just going to try to

3:14 like, "Hey, I'm just going to try to expand the market for food delivery."

3:16 expand the market for food delivery."

3:16 expand the market for food delivery." >> No, we did. So, the when we started um I

3:20 >> No, we did. So, the when we started um I

3:20 >> No, we did. So, the when we started um I guess to take a step back before we

3:22 guess to take a step back before we

3:22 guess to take a step back before we shipped Paltodely.com or even how we got

3:24 shipped Paltodely.com or even how we got

3:24 shipped Paltodely.com or even how we got there, you know, my co-founders and I

3:26 there, you know, my co-founders and I

3:26 there, you know, my co-founders and I really got connected because of an

3:28 really got connected because of an

3:28 really got connected because of an interest in small businesses. You know,

3:30 interest in small businesses. You know,

3:30 interest in small businesses. You know, I think my story I've told publicly,

3:32 I think my story I've told publicly,

3:32 I think my story I've told publicly, which is really I mean I grew up uh

3:35 which is really I mean I grew up uh

3:35 which is really I mean I grew up uh coming as to the States as an immigrant

3:37 coming as to the States as an immigrant

3:37 coming as to the States as an immigrant from China and my mom um you know, put

3:40 from China and my mom um you know, put

3:40 from China and my mom um you know, put food on the table by working three jobs

3:42 food on the table by working three jobs

3:42 food on the table by working three jobs a day for 12 years. One of those jobs

3:43 a day for 12 years. One of those jobs

3:43 a day for 12 years. One of those jobs happened to be at a Chinese restaurant

3:45 happened to be at a Chinese restaurant

3:45 happened to be at a Chinese restaurant where she was a waitress. I got to hang

3:47 where she was a waitress. I got to hang

3:47 where she was a waitress. I got to hang out with her, wash a few dishes when she

3:49 out with her, wash a few dishes when she

3:49 out with her, wash a few dishes when she allowed me to. That's kind of how I grew

3:51 allowed me to. That's kind of how I grew

3:51 allowed me to. That's kind of how I grew up while my dad was getting his PhD at

3:53 up while my dad was getting his PhD at

3:53 up while my dad was getting his PhD at the University of Illinois. That was,

3:55 the University of Illinois. That was,

3:55 the University of Illinois. That was, you know, the first 10 years or so of

3:57 you know, the first 10 years or so of

3:57 you know, the first 10 years or so of childhood growing up in the states. And

4:01 childhood growing up in the states. And

4:01 childhood growing up in the states. And that moment and experience always just

4:03 that moment and experience always just

4:03 that moment and experience always just gave me a deep appreciation for what

4:05 gave me a deep appreciation for what

4:05 gave me a deep appreciation for what small business owners represent. I mean

4:08 small business owners represent. I mean

4:08 small business owners represent. I mean that to them it there's no such thing as

4:11 that to them it there's no such thing as

4:11 that to them it there's no such thing as work. It it work life it's it's all the

4:13 work. It it work life it's it's all the

4:14 work. It it work life it's it's all the same thing. There's no concept of a

4:15 same thing. There's no concept of a

4:15 same thing. There's no concept of a weekend or a Saturday. It's Saturdays

4:17 weekend or a Saturday. It's Saturdays

4:18 weekend or a Saturday. It's Saturdays and Tuesdays are exactly the same days.

4:20 and Tuesdays are exactly the same days.

4:20 and Tuesdays are exactly the same days. And you just kind of get into this um

4:22 And you just kind of get into this um

4:22 And you just kind of get into this um process where that becomes your

4:24 process where that becomes your

4:24 process where that becomes your identity. And it's actually one of the

4:28 identity. And it's actually one of the

4:28 identity. And it's actually one of the most fascinating things I find about the

4:31 most fascinating things I find about the

4:31 most fascinating things I find about the great experiment that's America where

4:33 great experiment that's America where

4:33 great experiment that's America where you know because it becomes this

4:35 you know because it becomes this

4:35 you know because it becomes this all-consuming thing. One of the nice

4:37 all-consuming thing. One of the nice

4:37 all-consuming thing. One of the nice positive derivatives is actually they

4:39 positive derivatives is actually they

4:39 positive derivatives is actually they don't just create great experiences like

4:41 don't just create great experiences like

4:41 don't just create great experiences like a restaurant or a bar or a furniture

4:43 a restaurant or a bar or a furniture

4:43 a restaurant or a bar or a furniture store or a t-shirt shop. They actually

4:45 store or a t-shirt shop. They actually

4:46 store or a t-shirt shop. They actually create the GDP for all the cities that

4:47 create the GDP for all the cities that

4:47 create the GDP for all the cities that we live in. That GDP is what allows us

4:49 we live in. That GDP is what allows us

4:49 we live in. That GDP is what allows us to have great neighborhoods, schools,

4:51 to have great neighborhoods, schools,

4:51 to have great neighborhoods, schools, all the positive things that happen from

4:53 all the positive things that happen from

4:53 all the positive things that happen from a local community. And that was always

4:57 a local community. And that was always

4:57 a local community. And that was always my fascination with it. We had no idea

4:58 my fascination with it. We had no idea

4:58 my fascination with it. We had no idea though when we're looking at starting

5:00 though when we're looking at starting

5:00 though when we're looking at starting Door Dash about anything related to what

5:04 Door Dash about anything related to what

5:04 Door Dash about anything related to what these business owners problems were. And

5:05 these business owners problems were. And

5:05 these business owners problems were. And so my co-founders and I, we spoke with

5:08 so my co-founders and I, we spoke with

5:08 so my co-founders and I, we spoke with 300 maybe businesses up and down the Bay

5:12 300 maybe businesses up and down the Bay

5:12 300 maybe businesses up and down the Bay Area from San Jose to San Francisco,

5:15 Area from San Jose to San Francisco,

5:15 Area from San Jose to San Francisco, restaurants, retailers, service

5:17 restaurants, retailers, service

5:17 restaurants, retailers, service businesses, and it was actually a baker

5:20 businesses, and it was actually a baker

5:20 businesses, and it was actually a baker who showed us a booklet, a 3-in binder

5:23 who showed us a booklet, a 3-in binder

5:23 who showed us a booklet, a 3-in binder of delivery orders she had turned down.

5:25 of delivery orders she had turned down.

5:25 of delivery orders she had turned down. She was a oneperson shop who had no

5:28 She was a oneperson shop who had no

5:28 She was a oneperson shop who had no ability to fulfill or desire, frankly,

5:30 ability to fulfill or desire, frankly,

5:30 ability to fulfill or desire, frankly, to fulfill all those orders. And that

5:32 to fulfill all those orders. And that

5:32 to fulfill all those orders. And that was just a very strange moment for us

5:34 was just a very strange moment for us

5:34 was just a very strange moment for us where I said delivery is not a new idea.

5:37 where I said delivery is not a new idea.

5:37 where I said delivery is not a new idea. It's 2013. No one offers delivery.

5:41 It's 2013. No one offers delivery.

5:41 It's 2013. No one offers delivery. Why? And that's really what prompted us

5:44 Why? And that's really what prompted us

5:44 Why? And that's really what prompted us to think about, you know, launching Palo

5:46 to think about, you know, launching Palo

5:46 to think about, you know, launching Palo Alto Delivery.com to see if people

5:48 Alto Delivery.com to see if people

5:48 Alto Delivery.com to see if people cared. But to your question on logistics

5:50 cared. But to your question on logistics

5:50 cared. But to your question on logistics networks, you know, we said, okay, well,

5:52 networks, you know, we said, okay, well,

5:52 networks, you know, we said, okay, well, if the first place in which we can help

5:53 if the first place in which we can help

5:53 if the first place in which we can help local businesses is by building a

5:55 local businesses is by building a

5:55 local businesses is by building a logistics network, we have to pick a

5:58 logistics network, we have to pick a

5:58 logistics network, we have to pick a place to start. And and this is where I

6:02 place to start. And and this is where I

6:02 place to start. And and this is where I guess the math brain, you know, comes in

6:03 guess the math brain, you know, comes in

6:04 guess the math brain, you know, comes in for me where when we studied every

6:06 for me where when we studied every

6:06 for me where when we studied every category of local retail of where we

6:07 category of local retail of where we

6:07 category of local retail of where we would start, whether it was deliveries

6:09 would start, whether it was deliveries

6:09 would start, whether it was deliveries for restaurants, grocery stores,

6:11 for restaurants, grocery stores,

6:11 for restaurants, grocery stores, convenience stores, retail shops,

6:13 convenience stores, retail shops,

6:13 convenience stores, retail shops, >> oh, those are all options.

6:14 >> oh, those are all options.

6:14 >> oh, those are all options. >> We looked at all of them. And we had

6:16 >> We looked at all of them. And we had

6:16 >> We looked at all of them. And we had this hypothesis that if you wanted a

6:18 this hypothesis that if you wanted a

6:18 this hypothesis that if you wanted a chance of creating a logistics network

6:20 chance of creating a logistics network

6:20 chance of creating a logistics network that could actually be successful that

6:24 that could actually be successful that

6:24 that could actually be successful that can be very fast that can you know be

6:27 can be very fast that can you know be

6:27 can be very fast that can you know be very flexible meaning it can you know

6:30 very flexible meaning it can you know

6:30 very flexible meaning it can you know deliver in 30 minutes or it can deliver

6:32 deliver in 30 minutes or it can deliver

6:32 deliver in 30 minutes or it can deliver you know uh longer than that. Um you

6:36 you know uh longer than that. Um you

6:36 you know uh longer than that. Um you needed network density. You needed um

6:39 needed network density. You needed um

6:39 needed network density. You needed um the most number of connections between

6:41 the most number of connections between

6:41 the most number of connections between consumers and stores. We kind of

6:43 consumers and stores. We kind of

6:43 consumers and stores. We kind of targeted restaurants because there were

6:45 targeted restaurants because there were

6:45 targeted restaurants because there were a million restaurants. You know, if you

6:46 a million restaurants. You know, if you

6:46 a million restaurants. You know, if you compare that to the number of grocery

6:48 compare that to the number of grocery

6:48 compare that to the number of grocery stores, there was maybe a couple hundred

6:49 stores, there was maybe a couple hundred

6:49 stores, there was maybe a couple hundred thousand grocery stores. Um, and you

6:52 thousand grocery stores. Um, and you

6:52 thousand grocery stores. Um, and you looked at other categories of retail,

6:53 looked at other categories of retail,

6:53 looked at other categories of retail, restaurants had the highest count of

6:55 restaurants had the highest count of

6:55 restaurants had the highest count of stores. And so very quickly um you know

7:00 stores. And so very quickly um you know

7:00 stores. And so very quickly um you know we made the assumption that if there's

7:03 we made the assumption that if there's

7:03 we made the assumption that if there's any vertical to get started in doing

7:06 any vertical to get started in doing

7:06 any vertical to get started in doing deliveries it would be restaurants and

7:09 deliveries it would be restaurants and

7:09 deliveries it would be restaurants and prepared meals to give us a chance to

7:10 prepared meals to give us a chance to

7:10 prepared meals to give us a chance to build to build the highest density

7:13 build to build the highest density

7:13 build to build the highest density network so that one day we can deliver

7:14 network so that one day we can deliver

7:14 network so that one day we can deliver everything else. I want to tell you

7:17 everything else. I want to tell you

7:17 everything else. I want to tell you about the presenting sponsor of this

7:18 about the presenting sponsor of this

7:18 about the presenting sponsor of this podcast ramp. I have been reading a lot

7:20 podcast ramp. I have been reading a lot

7:20 podcast ramp. I have been reading a lot about SpaceX lately. SpaceX is one of

7:22 about SpaceX lately. SpaceX is one of

7:22 about SpaceX lately. SpaceX is one of the most valuable private businesses in

7:24 the most valuable private businesses in

7:24 the most valuable private businesses in the world and there's an idea from their

7:25 the world and there's an idea from their

7:26 the world and there's an idea from their history that more companies should use.

7:28 history that more companies should use.

7:28 history that more companies should use. From the very beginning, SpaceX was

7:30 From the very beginning, SpaceX was

7:30 From the very beginning, SpaceX was constantly attacking and questioning

7:32 constantly attacking and questioning

7:32 constantly attacking and questioning their costs. RAMP helps many of the most

7:35 their costs. RAMP helps many of the most

7:35 their costs. RAMP helps many of the most innovative businesses in the world do

7:36 innovative businesses in the world do

7:36 innovative businesses in the world do exactly that. The median company running

7:38 exactly that. The median company running

7:38 exactly that. The median company running on RAMP cuts their expenses by 5%. And

7:41 on RAMP cuts their expenses by 5%. And

7:41 on RAMP cuts their expenses by 5%. And the important idea that I found by

7:43 the important idea that I found by

7:43 the important idea that I found by reading about SpaceX is that a religious

7:45 reading about SpaceX is that a religious

7:45 reading about SpaceX is that a religious dedication to controlling costs helps

7:47 dedication to controlling costs helps

7:47 dedication to controlling costs helps increase revenue because you can pursue

7:49 increase revenue because you can pursue

7:49 increase revenue because you can pursue opportunities you couldn't otherwise. We

7:52 opportunities you couldn't otherwise. We

7:52 opportunities you couldn't otherwise. We see that in the RAMP data, too. The

7:54 see that in the RAMP data, too. The

7:54 see that in the RAMP data, too. The median company running on RAMP also

7:56 median company running on RAMP also

7:56 median company running on RAMP also grows their revenue by 16%. So, when

7:58 grows their revenue by 16%. So, when

7:58 grows their revenue by 16%. So, when you're running your business on RAMP and

8:00 you're running your business on RAMP and

8:00 you're running your business on RAMP and your competitors are not, you have a

8:01 your competitors are not, you have a

8:01 your competitors are not, you have a massive competitive advantage that

8:03 massive competitive advantage that

8:03 massive competitive advantage that compounds over time. Ramp is the only

8:06 compounds over time. Ramp is the only

8:06 compounds over time. Ramp is the only platform designed to make your finance

8:08 platform designed to make your finance

8:08 platform designed to make your finance team faster and happier. Many of the top

8:11 team faster and happier. Many of the top

8:11 team faster and happier. Many of the top founders and CEOs that I know run their

8:13 founders and CEOs that I know run their

8:13 founders and CEOs that I know run their business on ramp. I run my business on

8:14 business on ramp. I run my business on

8:14 business on ramp. I run my business on ramp and you should too. Go to ramp.com

8:17 ramp and you should too. Go to ramp.com

8:17 ramp and you should too. Go to ramp.com today to learn how they can help your

8:18 today to learn how they can help your

8:18 today to learn how they can help your business save time, save money, and grow

8:21 business save time, save money, and grow

8:21 business save time, save money, and grow revenue. That is ramp.com.

8:24 revenue. That is ramp.com.

8:24 revenue. That is ramp.com. There was other people that had maybe a

8:25 There was other people that had maybe a

8:25 There was other people that had maybe a similar idea, but I heard you tell the

8:27 similar idea, but I heard you tell the

8:27 similar idea, but I heard you tell the story one time where you're like, well,

8:28 story one time where you're like, well,

8:28 story one time where you're like, well, they actually went into like city

8:29 they actually went into like city

8:30 they actually went into like city centers

8:31 centers

8:31 centers >> and one advantage you I I don't even

8:34 >> and one advantage you I I don't even

8:34 >> and one advantage you I I don't even think this might have been an accidental

8:35 think this might have been an accidental

8:35 think this might have been an accidental you started in Palo Alto instead of like

8:37 you started in Palo Alto instead of like

8:37 you started in Palo Alto instead of like New York City. Can you talk about why

8:38 New York City. Can you talk about why

8:38 New York City. Can you talk about why that was important?

8:39 that was important?

8:39 that was important? >> Yeah. Well, starting in Palo Alto was um

8:42 >> Yeah. Well, starting in Palo Alto was um

8:42 >> Yeah. Well, starting in Palo Alto was um I mean not a conscious choice. I it was

8:44 I mean not a conscious choice. I it was

8:44 I mean not a conscious choice. I it was just where we were students at the time.

8:45 just where we were students at the time.

8:46 just where we were students at the time. But one of the earliest experiments we

8:47 But one of the earliest experiments we

8:47 But one of the earliest experiments we ran at Door Dash was doing deliveries in

8:49 ran at Door Dash was doing deliveries in

8:49 ran at Door Dash was doing deliveries in Palo Alto versus doing deliveries in San

8:50 Palo Alto versus doing deliveries in San

8:50 Palo Alto versus doing deliveries in San Francisco. So a city center if you will.

8:53 Francisco. So a city center if you will.

8:53 Francisco. So a city center if you will. That was close to where we started the

8:54 That was close to where we started the

8:54 That was close to where we started the company. And one of the fascinating

8:56 company. And one of the fascinating

8:56 company. And one of the fascinating things we found out um and we didn't

8:58 things we found out um and we didn't

8:58 things we found out um and we didn't understand why initially was we were

9:00 understand why initially was we were

9:00 understand why initially was we were actually completing deliveries faster um

9:03 actually completing deliveries faster um

9:03 actually completing deliveries faster um inside Palo Alto than we were inside San

9:06 inside Palo Alto than we were inside San

9:06 inside Palo Alto than we were inside San Francisco. Obviously San Francisco is a

9:08 Francisco. Obviously San Francisco is a

9:08 Francisco. Obviously San Francisco is a more dense place. But one of the things

9:10 more dense place. But one of the things

9:10 more dense place. But one of the things we learned early on though was that

9:12 we learned early on though was that

9:12 we learned early on though was that obviously, you know, in Palo Alto, you

9:14 obviously, you know, in Palo Alto, you

9:14 obviously, you know, in Palo Alto, you had much easier parking. You had a lot

9:17 had much easier parking. You had a lot

9:17 had much easier parking. You had a lot um fewer apartment complexes where you

9:20 um fewer apartment complexes where you

9:20 um fewer apartment complexes where you had to go up and down the stairs and

9:21 had to go up and down the stairs and

9:21 had to go up and down the stairs and figure out where the lobby was or the

9:23 figure out where the lobby was or the

9:23 figure out where the lobby was or the right elevator entrance, things like

9:24 right elevator entrance, things like

9:24 right elevator entrance, things like that. Palo Alto had the following which

9:27 that. Palo Alto had the following which

9:27 that. Palo Alto had the following which is if you looked at places like Palo

9:29 is if you looked at places like Palo

9:29 is if you looked at places like Palo Alto it's really um it you know

9:34 Alto it's really um it you know

9:34 Alto it's really um it you know represents I think most cities in the US

9:36 represents I think most cities in the US

9:36 represents I think most cities in the US or a lot of the world where you have

9:38 or a lot of the world where you have

9:38 or a lot of the world where you have main streets and then you kind of have

9:41 main streets and then you kind of have

9:41 main streets and then you kind of have you know in the spokes um outside of

9:43 you know in the spokes um outside of

9:43 you know in the spokes um outside of this main street hub of commerce you

9:46 this main street hub of commerce you

9:46 this main street hub of commerce you have where the people live and if you

9:48 have where the people live and if you

9:48 have where the people live and if you actually thought intelligently about

9:51 actually thought intelligently about

9:51 actually thought intelligently about what that really told you you can

9:52 what that really told you you can

9:52 what that really told you you can actually build a very efficient

9:53 actually build a very efficient

9:53 actually build a very efficient logistics system if you just you know

9:56 logistics system if you just you know

9:56 logistics system if you just you know understood how to you know manipulate

9:58 understood how to you know manipulate

9:58 understood how to you know manipulate some of these hubs and spokes. And so

10:01 some of these hubs and spokes. And so

10:01 some of these hubs and spokes. And so this was one of the earliest you know

10:02 this was one of the earliest you know

10:02 this was one of the earliest you know hypotheses we had that you can actually

10:05 hypotheses we had that you can actually

10:05 hypotheses we had that you can actually make a logistics business as efficient

10:08 make a logistics business as efficient

10:08 make a logistics business as efficient you know in a place like a Palo Alto

10:09 you know in a place like a Palo Alto

10:09 you know in a place like a Palo Alto versus San Francisco that was you know

10:11 versus San Francisco that was you know

10:11 versus San Francisco that was you know guided by that experiment. But the

10:12 guided by that experiment. But the

10:12 guided by that experiment. But the second thing was actually just in

10:14 second thing was actually just in

10:14 second thing was actually just in talking to customers. What customers

10:15 talking to customers. What customers

10:16 talking to customers. What customers told us was they said, "Look, in San

10:17 told us was they said, "Look, in San

10:17 told us was they said, "Look, in San Francisco, I can just walk down, you

10:19 Francisco, I can just walk down, you

10:19 Francisco, I can just walk down, you know, the the the the elevator from and

10:22 know, the the the the elevator from and

10:22 know, the the the the elevator from and head out the lobby and we could probably

10:24 head out the lobby and we could probably

10:24 head out the lobby and we could probably find a few places to go and eat." In

10:26 find a few places to go and eat." In

10:26 find a few places to go and eat." In Palo Alto, you'd be walking for miles

10:28 Palo Alto, you'd be walking for miles

10:28 Palo Alto, you'd be walking for miles before you could achieve something like

10:29 before you could achieve something like

10:29 before you could achieve something like that. You know, the closest, you know,

10:31 that. You know, the closest, you know,

10:31 that. You know, the closest, you know, set of restaurants near Stanford

10:32 set of restaurants near Stanford

10:32 set of restaurants near Stanford University where we started this was 2

10:34 University where we started this was 2

10:34 University where we started this was 2 miles away on University Avenue, as an

10:35 miles away on University Avenue, as an

10:36 miles away on University Avenue, as an example. And that's true in a lot of

10:38 example. And that's true in a lot of

10:38 example. And that's true in a lot of places um in in America. And so if there

10:41 places um in in America. And so if there

10:41 places um in in America. And so if there was any place we thought where there

10:43 was any place we thought where there

10:43 was any place we thought where there would be the highest um interest from

10:47 would be the highest um interest from

10:47 would be the highest um interest from consumers and a possibility where you

10:49 consumers and a possibility where you

10:49 consumers and a possibility where you can actually make the math work, it was

10:51 can actually make the math work, it was

10:51 can actually make the math work, it was places like Palo Alto. And the question,

10:53 places like Palo Alto. And the question,

10:53 places like Palo Alto. And the question, you know, to us was just how many of

10:55 you know, to us was just how many of

10:55 you know, to us was just how many of them are there

10:55 them are there

10:56 them are there >> and the only people doing deliveries at

10:57 >> and the only people doing deliveries at

10:57 >> and the only people doing deliveries at this time are the four founders.

11:00 this time are the four founders.

11:00 this time are the four founders. >> Yeah. In the in the very beginning, it

11:01 >> Yeah. In the in the very beginning, it

11:01 >> Yeah. In the in the very beginning, it was just it was just the four founders.

11:03 was just it was just the four founders.

11:03 was just it was just the four founders. >> Okay. So you had a line about this where

11:04 >> Okay. So you had a line about this where

11:04 >> Okay. So you had a line about this where it said it became obvious that the need

11:06 it said it became obvious that the need

11:06 it said it became obvious that the need was higher outside of the cities. We did

11:08 was higher outside of the cities. We did

11:08 was higher outside of the cities. We did not have the data to prove it at the

11:10 not have the data to prove it at the

11:10 not have the data to prove it at the time. We had the conviction that because

11:12 time. We had the conviction that because

11:12 time. We had the conviction that because we were doing the deliveries ourselves

11:13 we were doing the deliveries ourselves

11:13 we were doing the deliveries ourselves that this could be true.

11:15 that this could be true.

11:15 that this could be true. >> Yeah. I mean we saw I mean when one of

11:17 >> Yeah. I mean we saw I mean when one of

11:17 >> Yeah. I mean we saw I mean when one of the um benefits when you do the

11:19 the um benefits when you do the

11:19 the um benefits when you do the deliveries is well one you see how hard

11:21 deliveries is well one you see how hard

11:21 deliveries is well one you see how hard it is to actually you know bring you a

11:22 it is to actually you know bring you a

11:22 it is to actually you know bring you a burrito on time every time correctly.

11:25 burrito on time every time correctly.

11:25 burrito on time every time correctly. Um, and the second thing is you get to

11:28 Um, and the second thing is you get to

11:28 Um, and the second thing is you get to see who the customer is. And you saw the

11:30 see who the customer is. And you saw the

11:30 see who the customer is. And you saw the customer actually almost always was a

11:31 customer actually almost always was a

11:31 customer actually almost always was a mom, you know, who had young children,

11:34 mom, you know, who had young children,

11:34 mom, you know, who had young children, who had not a lot of time, who didn't

11:37 who had not a lot of time, who didn't

11:37 who had not a lot of time, who didn't want to cook, you know, every single

11:38 want to cook, you know, every single

11:38 want to cook, you know, every single meal, who wanted just looked for any

11:41 meal, who wanted just looked for any

11:42 meal, who wanted just looked for any solution to save her time. And so when

11:44 solution to save her time. And so when

11:44 solution to save her time. And so when we did those deliveries, we just saw,

11:46 we did those deliveries, we just saw,

11:46 we did those deliveries, we just saw, wow, well, there are a lot of young

11:48 wow, well, there are a lot of young

11:48 wow, well, there are a lot of young families out there, and let's go find

11:50 families out there, and let's go find

11:50 families out there, and let's go find out where they hang out. Let's go find

11:52 out where they hang out. Let's go find

11:52 out where they hang out. Let's go find out where they live. And that's why we

11:53 out where they live. And that's why we

11:53 out where they live. And that's why we had that sense that you know we can

11:55 had that sense that you know we can

11:55 had that sense that you know we can build a business you know with this

11:57 build a business you know with this

11:57 build a business you know with this audience to start.

11:58 audience to start.

11:58 audience to start. >> Is that another unexpected benefit of

12:00 >> Is that another unexpected benefit of

12:00 >> Is that another unexpected benefit of starting in these basically the suburbs

12:01 starting in these basically the suburbs

12:01 starting in these basically the suburbs or the cities? Think about like the

12:03 or the cities? Think about like the

12:03 or the cities? Think about like the typical city populations like maybe more

12:05 typical city populations like maybe more

12:05 typical city populations like maybe more single people or maybe like just a

12:06 single people or maybe like just a

12:06 single people or maybe like just a couple but it's not large families

12:09 couple but it's not large families

12:09 couple but it's not large families shoved in these buildings.

12:10 shoved in these buildings.

12:10 shoved in these buildings. >> Yeah. I mean, I I I think that was

12:12 >> Yeah. I mean, I I I think that was

12:12 >> Yeah. I mean, I I I think that was probably a derivative of the discovery,

12:14 probably a derivative of the discovery,

12:14 probably a derivative of the discovery, but no, I think in the beginning,

12:16 but no, I think in the beginning,

12:16 but no, I think in the beginning, especially when you're looking for

12:17 especially when you're looking for

12:17 especially when you're looking for product market fit as an entrepreneur,

12:18 product market fit as an entrepreneur,

12:18 product market fit as an entrepreneur, you're looking for

12:20 you're looking for

12:20 you're looking for >> someone who actually just wants your

12:22 >> someone who actually just wants your

12:22 >> someone who actually just wants your product organically. And we could tell

12:24 product organically. And we could tell

12:24 product organically. And we could tell very quickly that someone who has young

12:27 very quickly that someone who has young

12:27 very quickly that someone who has young children who maybe doesn't want to take

12:29 children who maybe doesn't want to take

12:29 children who maybe doesn't want to take a stroller, pack it up, pack all the

12:30 a stroller, pack it up, pack all the

12:30 a stroller, pack it up, pack all the things that come with the stroller,

12:32 things that come with the stroller,

12:32 things that come with the stroller, then, you know, put that, you know,

12:34 then, you know, put that, you know,

12:34 then, you know, put that, you know, stroller and the children into the

12:36 stroller and the children into the

12:36 stroller and the children into the vehicle, then get it out and then

12:38 vehicle, then get it out and then

12:38 vehicle, then get it out and then somehow get into inside of a crowded

12:39 somehow get into inside of a crowded

12:39 somehow get into inside of a crowded parking lot or a restaurant. Well, there

12:41 parking lot or a restaurant. Well, there

12:41 parking lot or a restaurant. Well, there are a lot of those people. And if we can

12:43 are a lot of those people. And if we can

12:43 are a lot of those people. And if we can solve it for that group, then we believe

12:46 solve it for that group, then we believe

12:46 solve it for that group, then we believe we could build a business that can

12:47 we could build a business that can

12:47 we could build a business that can easily grow organically. You're right. I

12:49 easily grow organically. You're right. I

12:49 easily grow organically. You're right. I mean, there's a second derivative, which

12:50 mean, there's a second derivative, which

12:50 mean, there's a second derivative, which is there more mouths to feed when you

12:51 is there more mouths to feed when you

12:51 is there more mouths to feed when you have a family than when you have, you

12:53 have a family than when you have, you

12:53 have a family than when you have, you know, one or two people living inside of

12:54 know, one or two people living inside of

12:54 know, one or two people living inside of a city. But that wasn't the first

12:56 a city. But that wasn't the first

12:56 a city. But that wasn't the first thought we had.

12:57 thought we had.

12:57 thought we had. >> But even more than a second derivative,

12:58 >> But even more than a second derivative,

12:58 >> But even more than a second derivative, because you were just explaining like,

12:59 because you were just explaining like,

13:00 because you were just explaining like, okay, well, if I'm delivering to

13:01 okay, well, if I'm delivering to

13:01 okay, well, if I'm delivering to somebody's house, I know where the park

13:02 somebody's house, I know where the park

13:02 somebody's house, I know where the park where to park as opposed if I'm in a

13:04 where to park as opposed if I'm in a

13:04 where to park as opposed if I'm in a city, you have to navigate where's the

13:05 city, you have to navigate where's the

13:05 city, you have to navigate where's the lobby, how do I get in this building,

13:06 lobby, how do I get in this building,

13:06 lobby, how do I get in this building, what floor do I get, how to access the

13:07 what floor do I get, how to access the

13:07 what floor do I get, how to access the elevator, right?

13:08 elevator, right?

13:08 elevator, right? >> Yeah, totally. And the the presence of

13:10 >> Yeah, totally. And the the presence of

13:10 >> Yeah, totally. And the the presence of single family homes made it a lot easier

13:12 single family homes made it a lot easier

13:12 single family homes made it a lot easier for sure. Um that was one of the

13:15 for sure. Um that was one of the

13:15 for sure. Um that was one of the benefits of delivering to places like

13:16 benefits of delivering to places like

13:16 benefits of delivering to places like Palo Alto. But again I think it just

13:18 Palo Alto. But again I think it just

13:18 Palo Alto. But again I think it just came from this very simple experiment

13:20 came from this very simple experiment

13:20 came from this very simple experiment which had an anomalous finding which is

13:23 which had an anomalous finding which is

13:23 which had an anomalous finding which is why is it faster to deliver in Palo Alto

13:25 why is it faster to deliver in Palo Alto

13:25 why is it faster to deliver in Palo Alto than it is in San Francisco? Why is it

13:27 than it is in San Francisco? Why is it

13:27 than it is in San Francisco? Why is it faster to to deliver in a less dense

13:30 faster to to deliver in a less dense

13:30 faster to to deliver in a less dense place in in other words? Exactly. This

13:32 place in in other words? Exactly. This

13:32 place in in other words? Exactly. This is what is interesting to me. It almost

13:34 is what is interesting to me. It almost

13:34 is what is interesting to me. It almost made it sense like your competitors seem

13:36 made it sense like your competitors seem

13:36 made it sense like your competitors seem to do the the most obvious or like the

13:38 to do the the most obvious or like the

13:38 to do the the most obvious or like the the logical thing. It's like no I need

13:40 the logical thing. It's like no I need

13:40 the logical thing. It's like no I need order density. Where are all the people?

13:41 order density. Where are all the people?

13:41 order density. Where are all the people? let me just go to the cities. We chased

13:43 let me just go to the cities. We chased

13:43 let me just go to the cities. We chased where the I think when you're starting

13:45 where the I think when you're starting

13:45 where the I think when you're starting out the number one thing every

13:46 out the number one thing every

13:46 out the number one thing every entrepreneur is looking for is do you

13:48 entrepreneur is looking for is do you

13:48 entrepreneur is looking for is do you have something that someone else wants

13:51 have something that someone else wants

13:51 have something that someone else wants and is it real? Meaning like it's not

13:54 and is it real? Meaning like it's not

13:54 and is it real? Meaning like it's not artificially inflated with discounts and

13:57 artificially inflated with discounts and

13:57 artificially inflated with discounts and marketing dollars and you know just

13:59 marketing dollars and you know just

13:59 marketing dollars and you know just other ways to inorganically grow. Um

14:01 other ways to inorganically grow. Um

14:01 other ways to inorganically grow. Um will people actually use it? Will they

14:03 will people actually use it? Will they

14:04 will people actually use it? Will they actually tell their friends about it if

14:05 actually tell their friends about it if

14:05 actually tell their friends about it if they actually like the service? And

14:07 they actually like the service? And

14:07 they actually like the service? And that's what we found early on with

14:09 that's what we found early on with

14:09 that's what we found early on with places like Palo Alto. Even when you

14:11 places like Palo Alto. Even when you

14:11 places like Palo Alto. Even when you were called Palo Alto delivered

14:13 were called Palo Alto delivered

14:13 were called Palo Alto delivered >> especially when we were called money

14:14 >> especially when we were called money

14:14 >> especially when we were called money right yeah we had no exactly we were we

14:16 right yeah we had no exactly we were we

14:16 right yeah we had no exactly we were we were we ran this out of my bank account

14:18 were we ran this out of my bank account

14:18 were we ran this out of my bank account and that's why I knew early on even

14:20 and that's why I knew early on even

14:20 and that's why I knew early on even though look we didn't have any models or

14:23 though look we didn't have any models or

14:23 though look we didn't have any models or you know unit economic forecast or

14:25 you know unit economic forecast or

14:25 you know unit economic forecast or anything like this but even though I was

14:26 anything like this but even though I was

14:26 anything like this but even though I was running out of my bank account where I

14:29 running out of my bank account where I

14:29 running out of my bank account where I also had student debt at the time my

14:32 also had student debt at the time my

14:32 also had student debt at the time my bank account wasn't going down you know

14:35 bank account wasn't going down you know

14:35 bank account wasn't going down you know every single week or every single month

14:36 every single week or every single month

14:36 every single week or every single month so something was telling me that maybe

14:39 so something was telling me that maybe

14:39 so something was telling me that maybe this is a chance of working.

14:41 this is a chance of working.

14:41 this is a chance of working. >> What were your costs at the time? Cuz

14:42 >> What were your costs at the time? Cuz

14:42 >> What were your costs at the time? Cuz you have the four founders lab

14:44 you have the four founders lab

14:44 you have the four founders lab essentially labor. You probably not

14:45 essentially labor. You probably not

14:45 essentially labor. You probably not paying yourself. Exactly. You're not

14:46 paying yourself. Exactly. You're not

14:46 paying yourself. Exactly. You're not paying yourself free labor, right? Just

14:48 paying yourself free labor, right? Just

14:48 paying yourself free labor, right? Just your time. You built a $9 website. Yeah.

14:52 your time. You built a $9 website. Yeah.

14:52 your time. You built a $9 website. Yeah. >> I heard something that was hilarious. We

14:53 >> I heard something that was hilarious. We

14:53 >> I heard something that was hilarious. We were like, well, we we don't have a

14:55 were like, well, we we don't have a

14:55 were like, well, we we don't have a sophisticated dispatch system, so we

14:56 sophisticated dispatch system, so we

14:56 sophisticated dispatch system, so we just use the Find My Friends app.

14:58 just use the Find My Friends app.

14:58 just use the Find My Friends app. >> We used Find My Friends. We used Find My

14:59 >> We used Find My Friends. We used Find My

15:00 >> We used Find My Friends. We used Find My Friends. We used

15:00 Friends. We used

15:00 Friends. We used >> to track the drivers, which just

15:02 >> to track the drivers, which just

15:02 >> to track the drivers, which just happened to be all of you,

15:03 happened to be all of you,

15:03 happened to be all of you, >> our co-founders.

15:03 >> our co-founders.

15:04 >> our co-founders. >> You have a Google voice number.

15:05 >> You have a Google voice number.

15:05 >> You have a Google voice number. >> You're not There's no marketing

15:07 >> You're not There's no marketing

15:07 >> You're not There's no marketing advertising, right?

15:07 advertising, right?

15:07 advertising, right? >> No. No. No, we had no money to market or

15:10 >> No. No. No, we had no money to market or

15:10 >> No. No. No, we had no money to market or advertise.

15:11 advertise.

15:11 advertise. >> So, what are you what other expenses did

15:12 >> So, what are you what other expenses did

15:12 >> So, what are you what other expenses did you have back then? Do you remember?

15:13 you have back then? Do you remember?

15:13 you have back then? Do you remember? >> It was all kind of like self-unded. This

15:15 >> It was all kind of like self-unded. This

15:15 >> It was all kind of like self-unded. This entire uh you know activity was

15:17 entire uh you know activity was

15:17 entire uh you know activity was selfunded until we had to start

15:18 selfunded until we had to start

15:18 selfunded until we had to start recruiting drivers and actually you know

15:20 recruiting drivers and actually you know

15:20 recruiting drivers and actually you know testing this out beyond just the four of

15:22 testing this out beyond just the four of

15:22 testing this out beyond just the four of us.

15:22 us.

15:22 us. >> This is when you applied to Y Combinator

15:24 >> This is when you applied to Y Combinator

15:24 >> This is when you applied to Y Combinator or No.

15:24 or No.

15:24 or No. >> Yeah. Yeah. I mean in that time period.

15:26 >> Yeah. Yeah. I mean in that time period.

15:26 >> Yeah. Yeah. I mean in that time period. >> Okay. By the time you apply to Y

15:27 >> Okay. By the time you apply to Y

15:27 >> Okay. By the time you apply to Y Cominator, do you have more than drivers

15:29 Cominator, do you have more than drivers

15:30 Cominator, do you have more than drivers than just the founders or No,

15:31 than just the founders or No,

15:31 than just the founders or No, >> we may have had one or two.

15:33 >> we may have had one or two.

15:34 >> we may have had one or two. >> Okay.

15:34 >> Okay.

15:34 >> Okay. >> Yeah. Very quickly we realized, well,

15:36 >> Yeah. Very quickly we realized, well,

15:36 >> Yeah. Very quickly we realized, well, we're we're in class and so, you know,

15:40 we're we're in class and so, you know,

15:40 we're we're in class and so, you know, we took turns doing deliveries while we

15:41 we took turns doing deliveries while we

15:41 we took turns doing deliveries while we were in class, but at some point it's

15:42 were in class, but at some point it's

15:42 were in class, but at some point it's tough to, you know, be a student and do

15:44 tough to, you know, be a student and do

15:44 tough to, you know, be a student and do the deliveries.

15:45 the deliveries.

15:45 the deliveries. >> How many years did you have left of

15:46 >> How many years did you have left of

15:46 >> How many years did you have left of business school? Like, how many years

15:48 business school? Like, how many years

15:48 business school? Like, how many years were you in school and running?

15:49 were you in school and running?

15:49 were you in school and running? >> We had

15:52 >> We had

15:52 >> We had maybe 6 months left before graduation. I

15:55 maybe 6 months left before graduation. I

15:56 maybe 6 months left before graduation. I mean, we were effectively Stanford's

15:57 mean, we were effectively Stanford's

15:57 mean, we were effectively Stanford's delivery service, you know, for the

15:59 delivery service, you know, for the

15:59 delivery service, you know, for the second half of or for the first half of

16:00 second half of or for the first half of

16:00 second half of or for the first half of 2013. We were effectively Stanford's

16:02 2013. We were effectively Stanford's

16:02 2013. We were effectively Stanford's delivery service. Then we then we um um

16:05 delivery service. Then we then we um um

16:05 delivery service. Then we then we um um get Door Dash um the URL and and and the

16:09 get Door Dash um the URL and and and the

16:09 get Door Dash um the URL and and and the company name and then we launch out of Y

16:11 company name and then we launch out of Y

16:12 company name and then we launch out of Y Cominator in the summer June 20.

16:14 Cominator in the summer June 20.

16:14 Cominator in the summer June 20. >> So was it like now once somebody starts

16:15 >> So was it like now once somebody starts

16:15 >> So was it like now once somebody starts using Door Dash or when I start using

16:17 using Door Dash or when I start using

16:17 using Door Dash or when I start using Door Dash, right? I'm like, "Oh, this is

16:18 Door Dash, right? I'm like, "Oh, this is

16:18 Door Dash, right? I'm like, "Oh, this is very convenient." I just keep using it

16:19 very convenient." I just keep using it

16:19 very convenient." I just keep using it over and over again, did you see that

16:21 over and over again, did you see that

16:21 over and over again, did you see that same behavior pattern back then?

16:22 same behavior pattern back then?

16:22 same behavior pattern back then? >> Yeah, with a very small group of users

16:24 >> Yeah, with a very small group of users

16:24 >> Yeah, with a very small group of users because in the beginning we actually did

16:26 because in the beginning we actually did

16:26 because in the beginning we actually did not have high volume. I mean it was

16:28 not have high volume. I mean it was

16:28 not have high volume. I mean it was probably 10 orders a day, something like

16:30 probably 10 orders a day, something like

16:30 probably 10 orders a day, something like that. and maybe our high day was like 21

16:32 that. and maybe our high day was like 21

16:32 that. and maybe our high day was like 21 orders a day, something like this. Most

16:34 orders a day, something like this. Most

16:34 orders a day, something like this. Most of them uh however were done by a small

16:37 of them uh however were done by a small

16:37 of them uh however were done by a small group of users at Stanford. When you see

16:39 group of users at Stanford. When you see

16:39 group of users at Stanford. When you see that fact that the same customers are

16:41 that fact that the same customers are

16:41 that fact that the same customers are ordering over and again uh even though

16:44 ordering over and again uh even though

16:44 ordering over and again uh even though it wasn't growing like wildfire um but

16:46 it wasn't growing like wildfire um but

16:46 it wasn't growing like wildfire um but our bank account also wasn't getting

16:47 our bank account also wasn't getting

16:47 our bank account also wasn't getting depleted um it gave us enough conviction

16:49 depleted um it gave us enough conviction

16:50 depleted um it gave us enough conviction to keep going. What were the

16:51 to keep going. What were the

16:51 to keep going. What were the conversations amongst the founders when

16:53 conversations amongst the founders when

16:53 conversations amongst the founders when you guys are saying that let's keep

16:55 you guys are saying that let's keep

16:55 you guys are saying that let's keep going and let's I think we viewed it as

16:58 going and let's I think we viewed it as

16:58 going and let's I think we viewed it as a project more than we viewed it as a

17:00 a project more than we viewed it as a

17:00 a project more than we viewed it as a company. In fact, we were barely

17:03 company. In fact, we were barely

17:03 company. In fact, we were barely incorporated. We were not incorporated

17:05 incorporated. We were not incorporated

17:05 incorporated. We were not incorporated when we were running this um at Stanford

17:07 when we were running this um at Stanford

17:07 when we were running this um at Stanford University and then we you know just got

17:09 University and then we you know just got

17:09 University and then we you know just got incorporated when we actually um got

17:12 incorporated when we actually um got

17:12 incorporated when we actually um got into YC. But at the time it was just

17:15 into YC. But at the time it was just

17:15 into YC. But at the time it was just like let's just see what the next phase

17:16 like let's just see what the next phase

17:16 like let's just see what the next phase should be. I think sometimes when you

17:18 should be. I think sometimes when you

17:18 should be. I think sometimes when you start these projects, you absolutely

17:21 start these projects, you absolutely

17:21 start these projects, you absolutely should have a point of view on maybe

17:23 should have a point of view on maybe

17:23 should have a point of view on maybe where this can go in terms of going the

17:24 where this can go in terms of going the

17:24 where this can go in terms of going the distance, but the most important thing

17:27 distance, but the most important thing

17:27 distance, but the most important thing is to just get started and then to have

17:29 is to just get started and then to have

17:29 is to just get started and then to have a sense of what the next two or three

17:30 a sense of what the next two or three

17:30 a sense of what the next two or three steps are. No one is able to, you know,

17:33 steps are. No one is able to, you know,

17:33 steps are. No one is able to, you know, know everything about the future. And

17:35 know everything about the future. And

17:35 know everything about the future. And for us, the summer was really

17:36 for us, the summer was really

17:36 for us, the summer was really instructive. I mean, the summer, I think

17:38 instructive. I mean, the summer, I think

17:38 instructive. I mean, the summer, I think doing the deliveries ourselves for the

17:39 doing the deliveries ourselves for the

17:39 doing the deliveries ourselves for the first six months gave us the clarity

17:42 first six months gave us the clarity

17:42 first six months gave us the clarity that the summer was really about

17:43 that the summer was really about

17:43 that the summer was really about answering three questions. what

17:45 answering three questions. what

17:45 answering three questions. what consumers want to pay us six bucks,

17:46 consumers want to pay us six bucks,

17:46 consumers want to pay us six bucks, which is what we charged. Um, are there

17:49 which is what we charged. Um, are there

17:49 which is what we charged. Um, are there restaurants who would be willing to

17:50 restaurants who would be willing to

17:50 restaurants who would be willing to partner with us for 15%. And, you know,

17:54 partner with us for 15%. And, you know,

17:54 partner with us for 15%. And, you know, could we afford a wage that we could pay

17:56 could we afford a wage that we could pay

17:56 could we afford a wage that we could pay dashers, the drivers, for the service?

17:59 dashers, the drivers, for the service?

17:59 dashers, the drivers, for the service? That was it. That was the entirety of

18:01 That was it. That was the entirety of

18:01 That was it. That was the entirety of the YC summer. It was not about demo day

18:04 the YC summer. It was not about demo day

18:04 the YC summer. It was not about demo day or, you know, raising the most amount of

18:06 or, you know, raising the most amount of

18:06 or, you know, raising the most amount of money or becoming the most popular, you

18:08 money or becoming the most popular, you

18:08 money or becoming the most popular, you know, at some event. Um, it was just

18:10 know, at some event. Um, it was just

18:10 know, at some event. Um, it was just answering those three questions. And if

18:12 answering those three questions. And if

18:12 answering those three questions. And if we had enough conviction answering those

18:13 we had enough conviction answering those

18:13 we had enough conviction answering those questions, then we'd keep going. Again,

18:14 questions, then we'd keep going. Again,

18:14 questions, then we'd keep going. Again, >> you told this hilarious story um where,

18:17 >> you told this hilarious story um where,

18:17 >> you told this hilarious story um where, you know, during the summer, some of

18:19 you know, during the summer, some of

18:19 you know, during the summer, some of your classmates are like, "Yeah, I'm

18:20 your classmates are like, "Yeah, I'm

18:20 your classmates are like, "Yeah, I'm going to go, you know, ski in or

18:22 going to go, you know, ski in or

18:22 going to go, you know, ski in or something like that. What are you doing,

18:23 something like that. What are you doing,

18:23 something like that. What are you doing, Tony? Like, I'm delivering hummus in my

18:25 Tony? Like, I'm delivering hummus in my

18:25 Tony? Like, I'm delivering hummus in my Honda."

18:26 Honda."

18:26 Honda." >> Yes. Yes. That was uh Yeah. Look, I

18:28 >> Yes. Yes. That was uh Yeah. Look, I

18:28 >> Yes. Yes. That was uh Yeah. Look, I mean, I think we had a lot of classmates

18:30 mean, I think we had a lot of classmates

18:30 mean, I think we had a lot of classmates at Stanford who looked at us and just

18:32 at Stanford who looked at us and just

18:32 at Stanford who looked at us and just thought, "Boy, like I thought they were

18:35 thought, "Boy, like I thought they were

18:35 thought, "Boy, like I thought they were like, you know, smart, but you know, I I

18:37 like, you know, smart, but you know, I I

18:37 like, you know, smart, but you know, I I guess they want to spend their time

18:39 guess they want to spend their time

18:39 guess they want to spend their time doing this." Um, and so look, in the

18:42 doing this." Um, and so look, in the

18:42 doing this." Um, and so look, in the beginning of a lot of these

18:43 beginning of a lot of these

18:43 beginning of a lot of these entrepreneurial ventures, nothing looks

18:46 entrepreneurial ventures, nothing looks

18:46 entrepreneurial ventures, nothing looks that amazing, right? We were working out

18:48 that amazing, right? We were working out

18:48 that amazing, right? We were working out of an apartment. We had dashers in that

18:52 of an apartment. We had dashers in that

18:52 of an apartment. We had dashers in that apartment. We had the co-founders live

18:53 apartment. We had the co-founders live

18:53 apartment. We had the co-founders live in that apartment. We worked 10:00 a.m.

18:56 in that apartment. We worked 10:00 a.m.

18:56 in that apartment. We worked 10:00 a.m. to 2 a.m. every single day, but it

18:58 to 2 a.m. every single day, but it

18:58 to 2 a.m. every single day, but it wasn't like this glamorous exercise. And

19:01 wasn't like this glamorous exercise. And

19:01 wasn't like this glamorous exercise. And but nor did we seek that, you know, we

19:03 but nor did we seek that, you know, we

19:03 but nor did we seek that, you know, we were just trying to answer those three

19:04 were just trying to answer those three

19:04 were just trying to answer those three questions that summer. We didn't care

19:06 questions that summer. We didn't care

19:06 questions that summer. We didn't care that much about what our friends were

19:07 that much about what our friends were

19:07 that much about what our friends were doing. Clearly, we thought that um it

19:09 doing. Clearly, we thought that um it

19:10 doing. Clearly, we thought that um it was um interesting enough to keep going

19:13 was um interesting enough to keep going

19:13 was um interesting enough to keep going that if we can actually answer these

19:15 that if we can actually answer these

19:15 that if we can actually answer these questions, I think we're actually on to

19:17 questions, I think we're actually on to

19:17 questions, I think we're actually on to something.

19:18 something.

19:18 something. >> We just had uh Mark Andre on the show

19:20 >> We just had uh Mark Andre on the show

19:20 >> We just had uh Mark Andre on the show and he's got this great line where he

19:22 and he's got this great line where he

19:22 and he's got this great line where he says, "I firmly believe that people that

19:23 says, "I firmly believe that people that

19:23 says, "I firmly believe that people that do great things are doing them for the

19:25 do great things are doing them for the

19:25 do great things are doing them for the first time."

19:25 first time."

19:25 first time." >> Huh. Did anybody have any restaurant or

19:29 >> Huh. Did anybody have any restaurant or

19:29 >> Huh. Did anybody have any restaurant or or actually not even restaurant

19:30 or actually not even restaurant

19:30 or actually not even restaurant experience because you're not even in

19:31 experience because you're not even in

19:31 experience because you're not even in the restaurant, any delivery? Any of the

19:32 the restaurant, any delivery? Any of the

19:32 the restaurant, any delivery? Any of the founders have anything to do with

19:34 founders have anything to do with

19:34 founders have anything to do with logistics or delivery, anything?

19:35 logistics or delivery, anything?

19:35 logistics or delivery, anything? >> No. No. It's actually why we had to do

19:38 >> No. No. It's actually why we had to do

19:38 >> No. No. It's actually why we had to do the deliveries. I mean I mean the reason

19:40 the deliveries. I mean I mean the reason

19:40 the deliveries. I mean I mean the reason why we did so the reason why we were so

19:42 why we did so the reason why we were so

19:42 why we did so the reason why we were so hellbent on doing the deliveries besides

19:44 hellbent on doing the deliveries besides

19:44 hellbent on doing the deliveries besides the fact that we had no idea whether we

19:45 the fact that we had no idea whether we

19:45 the fact that we had no idea whether we had any business recruiting other

19:47 had any business recruiting other

19:47 had any business recruiting other drivers was how does this work? How

19:49 drivers was how does this work? How

19:49 drivers was how does this work? How should it work? I think Door Dash early

19:51 should it work? I think Door Dash early

19:51 should it work? I think Door Dash early on even to this day but early on was so

19:53 on even to this day but early on was so

19:53 on even to this day but early on was so hard to explain because it was actually

19:55 hard to explain because it was actually

19:55 hard to explain because it was actually even to build the MVP yes to test it was

19:58 even to build the MVP yes to test it was

19:58 even to build the MVP yes to test it was just this website you know palmut.com

20:01 just this website you know palmut.com

20:01 just this website you know palmut.com but we had to build like four things. We

20:03 but we had to build like four things. We

20:03 but we had to build like four things. We had to build this website for consumers.

20:05 had to build this website for consumers.

20:05 had to build this website for consumers. We had to build some app for the

20:07 We had to build some app for the

20:07 We had to build some app for the restaurants actually receive the orders.

20:08 restaurants actually receive the orders.

20:08 restaurants actually receive the orders. We had to build an app for the drivers,

20:10 We had to build an app for the drivers,

20:10 We had to build an app for the drivers, the dashers. And then we had to build a

20:13 the dashers. And then we had to build a

20:13 the dashers. And then we had to build a dispatch system, you know, that actually

20:15 dispatch system, you know, that actually

20:15 dispatch system, you know, that actually could oversee all of the operations. So

20:17 could oversee all of the operations. So

20:17 could oversee all of the operations. So even in the very beginning, we realized,

20:19 even in the very beginning, we realized,

20:19 even in the very beginning, we realized, wow, this is actually pretty

20:21 wow, this is actually pretty

20:21 wow, this is actually pretty interesting. It's just such a fun

20:23 interesting. It's just such a fun

20:23 interesting. It's just such a fun problem that you in order to actually

20:25 problem that you in order to actually

20:25 problem that you in order to actually just bring you a burrito, you have to

20:27 just bring you a burrito, you have to

20:27 just bring you a burrito, you have to build these four things. And then to do

20:29 build these four things. And then to do

20:29 build these four things. And then to do it really, really well, I mean, that's

20:30 it really, really well, I mean, that's

20:30 it really, really well, I mean, that's why we did all the deliveries to figure

20:32 why we did all the deliveries to figure

20:32 why we did all the deliveries to figure out how you actually do that. So, you

20:34 out how you actually do that. So, you

20:34 out how you actually do that. So, you were misunderstood back then. You just

20:35 were misunderstood back then. You just

20:35 were misunderstood back then. You just said something interesting. You think

20:36 said something interesting. You think

20:36 said something interesting. You think that's still the case to this day?

20:38 that's still the case to this day?

20:38 that's still the case to this day? >> Absolutely. Because I think most people,

20:40 >> Absolutely. Because I think most people,

20:40 >> Absolutely. Because I think most people, and I totally get it. I mean, think of

20:41 and I totally get it. I mean, think of

20:41 and I totally get it. I mean, think of Door Dash as a consumer app. You know,

20:43 Door Dash as a consumer app. You know,

20:43 Door Dash as a consumer app. You know, most people think of us as lunch and

20:44 most people think of us as lunch and

20:44 most people think of us as lunch and dinner. And I think what they don't see

20:46 dinner. And I think what they don't see

20:46 dinner. And I think what they don't see is everything behind the scenes. I think

20:48 is everything behind the scenes. I think

20:48 is everything behind the scenes. I think a lot of times I think you can look at,

20:50 a lot of times I think you can look at,

20:50 a lot of times I think you can look at, you know, products like ours, especially

20:52 you know, products like ours, especially

20:52 you know, products like ours, especially as a consumer, and you say, "Wow, this

20:54 as a consumer, and you say, "Wow, this

20:54 as a consumer, and you say, "Wow, this looks like any other product. You know,

20:56 looks like any other product. You know,

20:56 looks like any other product. You know, there are so many of them." But then I

20:58 there are so many of them." But then I

20:58 there are so many of them." But then I would ask the question, well, how come

21:00 would ask the question, well, how come

21:00 would ask the question, well, how come one just gets used more often than the

21:03 one just gets used more often than the

21:03 one just gets used more often than the next or the others? And it comes down to

21:06 next or the others? And it comes down to

21:06 next or the others? And it comes down to everything that you can't see. You know,

21:09 everything that you can't see. You know,

21:09 everything that you can't see. You know, one of the things we say a lot

21:10 one of the things we say a lot

21:10 one of the things we say a lot internally at the company at Door Dash

21:11 internally at the company at Door Dash

21:11 internally at the company at Door Dash is it's always the data that you can't

21:12 is it's always the data that you can't

21:12 is it's always the data that you can't see that kills you. Because if you can

21:14 see that kills you. Because if you can

21:14 see that kills you. Because if you can see a truck coming at you, you're just

21:15 see a truck coming at you, you're just

21:15 see a truck coming at you, you're just going to dodge and get out the way, but

21:17 going to dodge and get out the way, but

21:17 going to dodge and get out the way, but if you can't see it, you're dead. And

21:19 if you can't see it, you're dead. And

21:19 if you can't see it, you're dead. And it's no different with our business. Our

21:21 it's no different with our business. Our

21:21 it's no different with our business. Our business is one where all of the magic

21:24 business is one where all of the magic

21:24 business is one where all of the magic or the secret sauce, if you will, are in

21:26 or the secret sauce, if you will, are in

21:26 or the secret sauce, if you will, are in things that you cannot see. You know, no

21:28 things that you cannot see. You know, no

21:28 things that you cannot see. You know, no consumer is sitting there while they're

21:30 consumer is sitting there while they're

21:30 consumer is sitting there while they're ordering Door Dash thinking about what

21:32 ordering Door Dash thinking about what

21:32 ordering Door Dash thinking about what the Dasher experience should look like

21:35 the Dasher experience should look like

21:35 the Dasher experience should look like or what the operations should be to get

21:37 or what the operations should be to get

21:37 or what the operations should be to get the best quality experience at the most

21:39 the best quality experience at the most

21:39 the best quality experience at the most affordable price or what are the ways in

21:42 affordable price or what are the ways in

21:42 affordable price or what are the ways in which you take out every single friction

21:44 which you take out every single friction

21:44 which you take out every single friction and cost with a restaurant or a retailer

21:47 and cost with a restaurant or a retailer

21:47 and cost with a restaurant or a retailer and make sure that all the items are

21:49 and make sure that all the items are

21:49 and make sure that all the items are actually there even when they're not

21:50 actually there even when they're not

21:50 actually there even when they're not there. You know, I think all of these

21:52 there. You know, I think all of these

21:52 there. You know, I think all of these things are the things that make Door

21:54 things are the things that make Door

21:54 things are the things that make Door Dash special and make Door Dash an

21:55 Dash special and make Door Dash an

21:56 Dash special and make Door Dash an end-to-end experience that's very

21:57 end-to-end experience that's very

21:57 end-to-end experience that's very difficult to replicate. But yeah, I

21:59 difficult to replicate. But yeah, I

21:59 difficult to replicate. But yeah, I think early on we knew that because we

22:00 think early on we knew that because we

22:00 think early on we knew that because we we did all the deliveries. You know who

22:02 we did all the deliveries. You know who

22:02 we did all the deliveries. You know who knows it? Your competitors. So, you're

22:05 knows it? Your competitors. So, you're

22:05 knows it? Your competitors. So, you're not going to like this cuz you're in my

22:07 not going to like this cuz you're in my

22:07 not going to like this cuz you're in my opinion really humble, probably too

22:08 opinion really humble, probably too

22:08 opinion really humble, probably too humble uh for my liking. Uh but people

22:12 humble uh for my liking. Uh but people

22:12 humble uh for my liking. Uh but people in your industry are afraid of you. And

22:14 in your industry are afraid of you. And

22:14 in your industry are afraid of you. And uh one I I have to tell you a personal

22:16 uh one I I have to tell you a personal

22:16 uh one I I have to tell you a personal story that I don't even think you know.

22:18 story that I don't even think you know.

22:18 story that I don't even think you know. And um I didn't know I I've heard about

22:20 And um I didn't know I I've heard about

22:20 And um I didn't know I I've heard about you before. I didn't really, you know,

22:21 you before. I didn't really, you know,

22:22 you before. I didn't really, you know, obviously use Door Dash, but I never

22:23 obviously use Door Dash, but I never

22:23 obviously use Door Dash, but I never thought about it. Exact. What you just

22:25 thought about it. Exact. What you just

22:25 thought about it. Exact. What you just described is exactly my experience. I

22:26 described is exactly my experience. I

22:26 described is exactly my experience. I was just like, I have a magic button

22:27 was just like, I have a magic button

22:27 was just like, I have a magic button that brings me a burrito.

22:29 that brings me a burrito.

22:29 that brings me a burrito. >> Exactly.

22:30 >> Exactly.

22:30 >> Exactly. >> Okay. I love that magic button. Don't

22:32 >> Okay. I love that magic button. Don't

22:32 >> Okay. I love that magic button. Don't take that magic button away from me,

22:33 take that magic button away from me,

22:33 take that magic button away from me, whatever you do. But I was in Stockholm

22:36 whatever you do. But I was in Stockholm

22:36 whatever you do. But I was in Stockholm about a year and a half ago

22:38 about a year and a half ago

22:38 about a year and a half ago >> and uh Daniel was very kind to host uh

22:41 >> and uh Daniel was very kind to host uh

22:41 >> and uh Daniel was very kind to host uh me and like a handful of European

22:42 me and like a handful of European

22:42 me and like a handful of European founders. And one of the European

22:44 founders. And one of the European

22:44 founders. And one of the European founders that was sitting next to me and

22:45 founders that was sitting next to me and

22:46 founders that was sitting next to me and Daniel at dinner was somebody I had

22:47 Daniel at dinner was somebody I had

22:47 Daniel at dinner was somebody I had never met before and it's Mickey from

22:49 never met before and it's Mickey from

22:49 never met before and it's Mickey from Vault.

22:50 Vault.

22:50 Vault. >> Okay.

22:50 >> Okay.

22:50 >> Okay. >> Right. Cool.

22:51 >> Right. Cool.

22:51 >> Right. Cool. >> But he told me something interesting

22:52 >> But he told me something interesting

22:52 >> But he told me something interesting because you know basically the story was

22:55 because you know basically the story was

22:55 because you know basically the story was he's just like listen I built the Door

22:57 he's just like listen I built the Door

22:57 he's just like listen I built the Door Dash of Europe I guess is how was

22:58 Dash of Europe I guess is how was

22:58 Dash of Europe I guess is how was described.

22:59 described.

23:00 described. >> And uh he's like I always thought of

23:03 >> And uh he's like I always thought of

23:03 >> And uh he's like I always thought of myself as an entrepreneur. I never

23:05 myself as an entrepreneur. I never

23:05 myself as an entrepreneur. I never thought I would work for anybody. And

23:06 thought I would work for anybody. And

23:06 thought I would work for anybody. And he's just like we were in a head-to-head

23:09 he's just like we were in a head-to-head

23:09 he's just like we were in a head-to-head battle right and he's like I had a term

23:11 battle right and he's like I had a term

23:11 battle right and he's like I had a term sheet in front of me if I remember the

23:12 sheet in front of me if I remember the

23:12 sheet in front of me if I remember the number correctly. He was getting like a

23:13 number correctly. He was getting like a

23:13 number correctly. He was getting like a bill. He had the ability to raise

23:15 bill. He had the ability to raise

23:15 bill. He had the ability to raise another fresh billion dollars of

23:16 another fresh billion dollars of

23:16 another fresh billion dollars of capital.

23:17 capital.

23:17 capital. >> Yeah.

23:17 >> Yeah.

23:17 >> Yeah. >> And he was looking at the term sheet

23:18 >> And he was looking at the term sheet

23:18 >> And he was looking at the term sheet thinking about signing it. And then he

23:20 thinking about signing it. And then he

23:20 thinking about signing it. And then he said involuntarily something came out of

23:23 said involuntarily something came out of

23:23 said involuntarily something came out of his mouth. And he says, I can't beat

23:26 his mouth. And he says, I can't beat

23:26 his mouth. And he says, I can't beat him.

23:28 him.

23:28 him. He's like, I can't beat him. And he's

23:30 He's like, I can't beat him. And he's

23:30 He's like, I can't beat him. And he's like, I cannot believe that came out of

23:32 like, I cannot believe that came out of

23:32 like, I cannot believe that came out of my mouth. And he's like, and then he

23:33 my mouth. And he's like, and then he

23:33 my mouth. And he's like, and then he looked down. He's like, I could either

23:34 looked down. He's like, I could either

23:34 looked down. He's like, I could either light this money on fire or I could sell

23:36 light this money on fire or I could sell

23:36 light this money on fire or I could sell my company for life-changing money and

23:38 my company for life-changing money and

23:38 my company for life-changing money and go work for Tony and learn a lot. And I

23:40 go work for Tony and learn a lot. And I

23:40 go work for Tony and learn a lot. And I think to this day, he still directly

23:41 think to this day, he still directly

23:41 think to this day, he still directly reports to you. Correct. Yeah,

23:43 reports to you. Correct. Yeah,

23:43 reports to you. Correct. Yeah, >> he runs all of our European business

23:46 >> he runs all of our European business

23:46 >> he runs all of our European business >> and he was trying to explain to me and

23:47 >> and he was trying to explain to me and

23:47 >> and he was trying to explain to me and Daniel about just you don't it's all the

23:49 Daniel about just you don't it's all the

23:50 Daniel about just you don't it's all the magic is very similar what the stuff

23:51 magic is very similar what the stuff

23:51 magic is very similar what the stuff that you don't see how hard he is to to

23:53 that you don't see how hard he is to to

23:53 that you don't see how hard he is to to compete against. You had some another

23:55 compete against. You had some another

23:56 compete against. You had some another interesting quote I want to read to you.

23:57 interesting quote I want to read to you.

23:57 interesting quote I want to read to you. You say the way that Door Dash has

23:58 You say the way that Door Dash has

23:58 You say the way that Door Dash has achieved so much success is tens of

24:00 achieved so much success is tens of

24:00 achieved so much success is tens of thousands of experience 95% of which

24:02 thousands of experience 95% of which

24:02 thousands of experience 95% of which never even make it to the customer

24:04 never even make it to the customer

24:04 never even make it to the customer before they fail. The way to get a more

24:06 before they fail. The way to get a more

24:06 before they fail. The way to get a more to get more accurate on a delivery

24:08 to get more accurate on a delivery

24:08 to get more accurate on a delivery probably requires some level of detail

24:10 probably requires some level of detail

24:10 probably requires some level of detail that is lower and deeper than you

24:12 that is lower and deeper than you

24:12 that is lower and deeper than you realize. Can you explain what you meant

24:14 realize. Can you explain what you meant

24:14 realize. Can you explain what you meant behind that statement?

24:15 behind that statement?

24:15 behind that statement? >> This again starts from actually doing

24:18 >> This again starts from actually doing

24:18 >> This again starts from actually doing the work ourselves and realizing that if

24:21 the work ourselves and realizing that if

24:21 the work ourselves and realizing that if you actually want to get something on

24:24 you actually want to get something on

24:24 you actually want to get something on time,

24:25 time,

24:25 time, um I think it's very easy to think about

24:28 um I think it's very easy to think about

24:28 um I think it's very easy to think about uh when you're just intellectualizing

24:30 uh when you're just intellectualizing

24:30 uh when you're just intellectualizing it, you know, on the outside when we're

24:32 it, you know, on the outside when we're

24:32 it, you know, on the outside when we're getting started. Oh, maybe there's a

24:34 getting started. Oh, maybe there's a

24:34 getting started. Oh, maybe there's a traffic issue or maybe oh the food is

24:36 traffic issue or maybe oh the food is

24:36 traffic issue or maybe oh the food is taking longer than it than it should.

24:38 taking longer than it than it should.

24:38 taking longer than it than it should. Whatever the reasons might be, but you

24:41 Whatever the reasons might be, but you

24:41 Whatever the reasons might be, but you actually have no idea actually what are

24:43 actually have no idea actually what are

24:43 actually have no idea actually what are all the sources of delay in an order

24:46 all the sources of delay in an order

24:46 all the sources of delay in an order until you actually go and do the work.

24:50 until you actually go and do the work.

24:50 until you actually go and do the work. Sure, there might be some of the issues

24:51 Sure, there might be some of the issues

24:51 Sure, there might be some of the issues that I I think you can think about on

24:53 that I I think you can think about on

24:53 that I I think you can think about on the outside, but then very very quickly

24:55 the outside, but then very very quickly

24:55 the outside, but then very very quickly you realize that there's a lot of

24:58 you realize that there's a lot of

24:58 you realize that there's a lot of seconds of delay in every emotion. In

25:00 seconds of delay in every emotion. In

25:00 seconds of delay in every emotion. In fact, there's about 20 steps you can

25:02 fact, there's about 20 steps you can

25:02 fact, there's about 20 steps you can decompose a delivery into. And there's

25:04 decompose a delivery into. And there's

25:04 decompose a delivery into. And there's delays at each one of those moments. And

25:08 delays at each one of those moments. And

25:08 delays at each one of those moments. And that's, you know, even more complicated

25:10 that's, you know, even more complicated

25:10 that's, you know, even more complicated if, you know, the delivery today is uh

25:13 if, you know, the delivery today is uh

25:13 if, you know, the delivery today is uh they happen outside of restaurants, they

25:15 they happen outside of restaurants, they

25:15 they happen outside of restaurants, they happen inside shopping contexts like

25:17 happen inside shopping contexts like

25:17 happen inside shopping contexts like groceries or retail items or if they

25:20 groceries or retail items or if they

25:20 groceries or retail items or if they happen inside malls that are

25:21 happen inside malls that are

25:21 happen inside malls that are multi-story, sometimes below ground,

25:23 multi-story, sometimes below ground,

25:23 multi-story, sometimes below ground, sometimes above ground. And one of the

25:26 sometimes above ground. And one of the

25:26 sometimes above ground. And one of the things you start realizing is, wow,

25:28 things you start realizing is, wow,

25:28 things you start realizing is, wow, actually there are a lot of causes for

25:31 actually there are a lot of causes for

25:31 actually there are a lot of causes for delays. And there's no way that you're

25:33 delays. And there's no way that you're

25:33 delays. And there's no way that you're going to know about all of them until

25:35 going to know about all of them until

25:35 going to know about all of them until you literally actually encounter it for

25:37 you literally actually encounter it for

25:37 you literally actually encounter it for the first time. A lot of what's

25:38 the first time. A lot of what's

25:38 the first time. A lot of what's difficult about Door Dash is we're

25:41 difficult about Door Dash is we're

25:41 difficult about Door Dash is we're trying to build a structured data set in

25:44 trying to build a structured data set in

25:44 trying to build a structured data set in a world that is chaos. That's the

25:46 a world that is chaos. That's the

25:46 a world that is chaos. That's the physical world. The one of the reasons

25:49 physical world. The one of the reasons

25:49 physical world. The one of the reasons why there's all these sources for

25:50 why there's all these sources for

25:50 why there's all these sources for mistakes, for delays, for costs that

25:52 mistakes, for delays, for costs that

25:52 mistakes, for delays, for costs that ultimately, you know, yield into costs

25:54 ultimately, you know, yield into costs

25:54 ultimately, you know, yield into costs and good or bad um you know, experiences

25:56 and good or bad um you know, experiences

25:56 and good or bad um you know, experiences for customers is because there is no

25:58 for customers is because there is no

25:58 for customers is because there is no data that exists. There is no nice data

26:01 data that exists. There is no nice data

26:01 data that exists. There is no nice data set that a company like a Google or

26:05 set that a company like a Google or

26:05 set that a company like a Google or somebody else has organized for you. Um

26:07 somebody else has organized for you. Um

26:08 somebody else has organized for you. Um because it's all physical information

26:10 because it's all physical information

26:10 because it's all physical information and it's also changing all the time.

26:11 and it's also changing all the time.

26:11 and it's also changing all the time. When you go into a grocery store and

26:13 When you go into a grocery store and

26:13 When you go into a grocery store and somebody moves an apple from aisle 6 to

26:15 somebody moves an apple from aisle 6 to

26:15 somebody moves an apple from aisle 6 to aisle 8, is that always going to get

26:17 aisle 8, is that always going to get

26:17 aisle 8, is that always going to get documented? Of course not. Uh those are

26:20 documented? Of course not. Uh those are

26:20 documented? Of course not. Uh those are the kinds of things we have to work on

26:21 the kinds of things we have to work on

26:21 the kinds of things we have to work on every single day. And and and you

26:23 every single day. And and and you

26:23 every single day. And and and you wouldn't know that. You know what? If I

26:24 wouldn't know that. You know what? If I

26:24 wouldn't know that. You know what? If I told you the the cause for a delay was

26:26 told you the the cause for a delay was

26:26 told you the the cause for a delay was because actually somebody was homesick

26:29 because actually somebody was homesick

26:29 because actually somebody was homesick that day. How would you know that

26:31 that day. How would you know that

26:31 that day. How would you know that actually, you know, until that event

26:32 actually, you know, until that event

26:32 actually, you know, until that event actually transpired? And what would you

26:33 actually transpired? And what would you

26:34 actually transpired? And what would you do to respond, you know, to that event

26:36 do to respond, you know, to that event

26:36 do to respond, you know, to that event if that were to occur, which happens

26:37 if that were to occur, which happens

26:37 if that were to occur, which happens every single day, you know, when we're

26:39 every single day, you know, when we're

26:39 every single day, you know, when we're doing millions of orders every single

26:40 doing millions of orders every single

26:40 doing millions of orders every single day. the one in a million event happens

26:43 day. the one in a million event happens

26:43 day. the one in a million event happens a lot and the one in a thousand event

26:46 a lot and the one in a thousand event

26:46 a lot and the one in a thousand event happens way more than that. And so

26:48 happens way more than that. And so

26:48 happens way more than that. And so building a system that can ideally

26:51 building a system that can ideally

26:51 building a system that can ideally detect and prevent these issues, but

26:53 detect and prevent these issues, but

26:53 detect and prevent these issues, but then also a very fast twitch muscle to

26:56 then also a very fast twitch muscle to

26:56 then also a very fast twitch muscle to actually be able to build this I mean

26:57 actually be able to build this I mean

26:58 actually be able to build this I mean almost like an emergency response system

27:00 almost like an emergency response system

27:00 almost like an emergency response system when something actually goes ary to fix

27:03 when something actually goes ary to fix

27:03 when something actually goes ary to fix it. That requires doing the work over

27:07 it. That requires doing the work over

27:07 it. That requires doing the work over and again and building the system that

27:09 and again and building the system that

27:09 and again and building the system that can learn over time to get better and

27:12 can learn over time to get better and

27:12 can learn over time to get better and better and better. Most of the time we

27:13 better and better. Most of the time we

27:14 better and better. Most of the time we have no idea. We start with the these

27:15 have no idea. We start with the these

27:15 have no idea. We start with the these experiments and that's why most

27:16 experiments and that's why most

27:16 experiments and that's why most experiments fail. But when you get

27:18 experiments fail. But when you get

27:18 experiments fail. But when you get enough goodness out of it, if you can

27:20 enough goodness out of it, if you can

27:20 enough goodness out of it, if you can get the 5% out of tens of thousands of

27:22 get the 5% out of tens of thousands of

27:22 get the 5% out of tens of thousands of experiments to work, you know, in one

27:24 experiments to work, you know, in one

27:24 experiments to work, you know, in one year, that has the benefit on all of

27:26 year, that has the benefit on all of

27:26 year, that has the benefit on all of your audience for the next year. And

27:28 your audience for the next year. And

27:28 your audience for the next year. And then you just keep going and that adds

27:30 then you just keep going and that adds

27:30 then you just keep going and that adds compounding surplus for all of the

27:31 compounding surplus for all of the

27:31 compounding surplus for all of the audiences.

27:33 audiences.

27:33 audiences. Deal will help your business hire, pay

27:35 Deal will help your business hire, pay

27:35 Deal will help your business hire, pay and manage any worker anywhere in the

27:37 and manage any worker anywhere in the

27:37 and manage any worker anywhere in the world. Deal is the best company in the

27:39 world. Deal is the best company in the

27:39 world. Deal is the best company in the world at building infrastructure for

27:40 world at building infrastructure for

27:40 world at building infrastructure for global hiring. Deal is one platform for

27:42 global hiring. Deal is one platform for

27:42 global hiring. Deal is one platform for payroll, HR, benefits, and device

27:45 payroll, HR, benefits, and device

27:45 payroll, HR, benefits, and device management across 150 countries. Deal

27:48 management across 150 countries. Deal

27:48 management across 150 countries. Deal gets you everything you need to run a

27:50 gets you everything you need to run a

27:50 gets you everything you need to run a high-erforming global workforce on a

27:52 high-erforming global workforce on a

27:52 high-erforming global workforce on a single AI native platform. From first

27:55 single AI native platform. From first

27:55 single AI native platform. From first offer to final offboarding, deal handles

27:57 offer to final offboarding, deal handles

27:57 offer to final offboarding, deal handles the complexity so you can stay focused

27:59 the complexity so you can stay focused

27:59 the complexity so you can stay focused on your business. The best founders and

28:02 on your business. The best founders and

28:02 on your business. The best founders and operators in the world have one thing in

28:04 operators in the world have one thing in

28:04 operators in the world have one thing in common. They control as much of their

28:06 common. They control as much of their

28:06 common. They control as much of their business as possible. And the founders

28:08 business as possible. And the founders

28:08 business as possible. And the founders of Deal do exactly this. When you use

28:10 of Deal do exactly this. When you use

28:10 of Deal do exactly this. When you use Deal, you aren't using a third-party

28:12 Deal, you aren't using a third-party

28:12 Deal, you aren't using a third-party payroll processor or a messy network of

28:15 payroll processor or a messy network of

28:15 payroll processor or a messy network of incountry providers. Deal built and owns

28:17 incountry providers. Deal built and owns

28:17 incountry providers. Deal built and owns the rails. That means faster speed,

28:20 the rails. That means faster speed,

28:20 the rails. That means faster speed, better service, and total

28:21 better service, and total

28:21 better service, and total accountability. The founder of 11 Labs,

28:23 accountability. The founder of 11 Labs,

28:23 accountability. The founder of 11 Labs, who I use to make transcripts for this

28:25 who I use to make transcripts for this

28:25 who I use to make transcripts for this podcast, has a great description of the

28:27 podcast, has a great description of the

28:27 podcast, has a great description of the value that deal can give your company.

28:30 value that deal can give your company.

28:30 value that deal can give your company. He said, "We built 11 Labs to break down

28:32 He said, "We built 11 Labs to break down

28:32 He said, "We built 11 Labs to break down language and communication barriers.

28:33 language and communication barriers.

28:34 language and communication barriers. With deal enabling us to hire and

28:35 With deal enabling us to hire and

28:35 With deal enabling us to hire and support exceptional talent anywhere, we

28:37 support exceptional talent anywhere, we

28:38 support exceptional talent anywhere, we can accelerate our innovation and bring

28:39 can accelerate our innovation and bring

28:39 can accelerate our innovation and bring more voices, stories, and ideas to every

28:42 more voices, stories, and ideas to every

28:42 more voices, stories, and ideas to every corner of the world. Deal is trusted by

28:45 corner of the world. Deal is trusted by

28:45 corner of the world. Deal is trusted by over 40,000 customers and growing fast.

28:48 over 40,000 customers and growing fast.

28:48 over 40,000 customers and growing fast. Learn how they can help your business by

28:50 Learn how they can help your business by

28:50 Learn how they can help your business by going to deal.com/enra."

28:52 going to deal.com/enra."

28:52 going to deal.com/enra." That is deal.com/enra.

28:56 That is deal.com/enra.

28:56 That is deal.com/enra. How do you do that many experiments

28:57 How do you do that many experiments

28:57 How do you do that many experiments though and on a like is this a yearly

28:59 though and on a like is this a yearly

28:59 though and on a like is this a yearly basis? Is this like over the history of

29:01 basis? Is this like over the history of

29:01 basis? Is this like over the history of Door Dash? Like you're running thousands

29:03 Door Dash? Like you're running thousands

29:03 Door Dash? Like you're running thousands of experiments every year

29:04 of experiments every year

29:04 of experiments every year >> ideally. Yeah. Yes. I I think when we

29:06 >> ideally. Yeah. Yes. I I think when we

29:06 >> ideally. Yeah. Yes. I I think when we are at our best that's that's that's

29:08 are at our best that's that's that's

29:08 are at our best that's that's that's what's happening. But but but it starts

29:10 what's happening. But but but it starts

29:10 what's happening. But but but it starts with actually building a system that

29:11 with actually building a system that

29:11 with actually building a system that actually wants to learn. If you think

29:13 actually wants to learn. If you think

29:13 actually wants to learn. If you think about like like why do we have to learn?

29:15 about like like why do we have to learn?

29:15 about like like why do we have to learn? It's because the physical world a is not

29:18 It's because the physical world a is not

29:18 It's because the physical world a is not structured. It's not documented

29:20 structured. It's not documented

29:20 structured. It's not documented anywhere. It's you you can't scrape it.

29:23 anywhere. It's you you can't scrape it.

29:23 anywhere. It's you you can't scrape it. Um it's constantly changing. It's I mean

29:25 Um it's constantly changing. It's I mean

29:25 Um it's constantly changing. It's I mean there's a winter storm right now, for

29:27 there's a winter storm right now, for

29:27 there's a winter storm right now, for example, in the Northeast. I mean, these

29:29 example, in the Northeast. I mean, these

29:29 example, in the Northeast. I mean, these are all things that happen differently.

29:31 are all things that happen differently.

29:31 are all things that happen differently. You know,

29:32 You know,

29:32 You know, >> it's beautiful here in California.

29:33 >> it's beautiful here in California.

29:33 >> it's beautiful here in California. >> Yeah, I know. We would have no idea

29:34 >> Yeah, I know. We would have no idea

29:34 >> Yeah, I know. We would have no idea here. We're spoiled here in the Bay

29:36 here. We're spoiled here in the Bay

29:36 here. We're spoiled here in the Bay Area. But like, but in general, all

29:38 Area. But like, but in general, all

29:38 Area. But like, but in general, all these things are happening every single,

29:40 these things are happening every single,

29:40 these things are happening every single, you know, hour of the day. Okay. There's

29:43 you know, hour of the day. Okay. There's

29:43 you know, hour of the day. Okay. There's going to be some missing item today.

29:46 going to be some missing item today.

29:46 going to be some missing item today. There's going to be some order that took

29:47 There's going to be some order that took

29:47 There's going to be some order that took a lot longer today. There's going to be

29:49 a lot longer today. There's going to be

29:49 a lot longer today. There's going to be some incorrect gate we entered at an

29:52 some incorrect gate we entered at an

29:52 some incorrect gate we entered at an apartment complex. there's going to be

29:53 apartment complex. there's going to be

29:53 apartment complex. there's going to be some dasher who's going to get lost

29:55 some dasher who's going to get lost

29:55 some dasher who's going to get lost coming up the stairs of this office

29:57 coming up the stairs of this office

29:57 coming up the stairs of this office building. There will be guaranteed. And

30:00 building. There will be guaranteed. And

30:00 building. There will be guaranteed. And so the question is like well it would be

30:03 so the question is like well it would be

30:03 so the question is like well it would be impossible to try to you know figure out

30:05 impossible to try to you know figure out

30:06 impossible to try to you know figure out all of that if you can't build a system

30:08 all of that if you can't build a system

30:08 all of that if you can't build a system to learn how to do this. So the most

30:10 to learn how to do this. So the most

30:10 to learn how to do this. So the most important thing is actually building

30:11 important thing is actually building

30:11 important thing is actually building systems and building a system that you

30:15 systems and building a system that you

30:15 systems and building a system that you know at Door Dash really starts with

30:17 know at Door Dash really starts with

30:17 know at Door Dash really starts with testing things in a very operational

30:19 testing things in a very operational

30:19 testing things in a very operational hacky do things that don't scale kind of

30:22 hacky do things that don't scale kind of

30:22 hacky do things that don't scale kind of way into then taking the things that

30:25 way into then taking the things that

30:25 way into then taking the things that ultimately work the ideas and actually

30:27 ultimately work the ideas and actually

30:27 ultimately work the ideas and actually building products around them and then

30:29 building products around them and then

30:29 building products around them and then engineering the ones that actually work

30:31 engineering the ones that actually work

30:31 engineering the ones that actually work so that you're actually very efficient

30:32 so that you're actually very efficient

30:32 so that you're actually very efficient with this learning loop so that you can

30:34 with this learning loop so that you can

30:34 with this learning loop so that you can go from learning to shipping something

30:38 go from learning to shipping something

30:38 go from learning to shipping something that actually works. Because you know

30:40 that actually works. Because you know

30:40 that actually works. Because you know it's a resource constraint with you know

30:41 it's a resource constraint with you know

30:41 it's a resource constraint with you know how many engineers we have and how many

30:43 how many engineers we have and how many

30:43 how many engineers we have and how many things that we can actually ship

30:45 things that we can actually ship

30:45 things that we can actually ship especially when the stakes are high and

30:47 especially when the stakes are high and

30:47 especially when the stakes are high and you want to make that loop as tight and

30:49 you want to make that loop as tight and

30:49 you want to make that loop as tight and as fast as possible. That's how you

30:51 as fast as possible. That's how you

30:51 as fast as possible. That's how you build a system in which you can learn

30:54 build a system in which you can learn

30:54 build a system in which you can learn thousands of things and you just have to

30:55 thousands of things and you just have to

30:56 thousands of things and you just have to keep doing it over and over. You know

30:58 keep doing it over and over. You know

30:58 keep doing it over and over. You know our business is one where we believe we

31:00 our business is one where we believe we

31:00 our business is one where we believe we have to earn you know the right to serve

31:02 have to earn you know the right to serve

31:02 have to earn you know the right to serve you the next day. Even though you

31:03 you the next day. Even though you

31:03 you the next day. Even though you ordered with us today, thank you very

31:05 ordered with us today, thank you very

31:05 ordered with us today, thank you very much for your business. We have to earn

31:07 much for your business. We have to earn

31:07 much for your business. We have to earn it again. you know, the scoreboard goes

31:08 it again. you know, the scoreboard goes

31:08 it again. you know, the scoreboard goes back down to zero tomorrow and we have

31:10 back down to zero tomorrow and we have

31:10 back down to zero tomorrow and we have to just do that all over again.

31:11 to just do that all over again.

31:12 to just do that all over again. >> Where did you learn the importance of

31:13 >> Where did you learn the importance of

31:13 >> Where did you learn the importance of that?

31:13 that?

31:13 that? >> Of what?

31:13 >> Of what?

31:14 >> Of what? >> Of starting over again every day. I've

31:15 >> Of starting over again every day. I've

31:15 >> Of starting over again every day. I've heard you say that before and I love

31:16 heard you say that before and I love

31:16 heard you say that before and I love that idea.

31:17 that idea.

31:17 that idea. >> Very early at Door Dash. Um, we learned

31:21 >> Very early at Door Dash. Um, we learned

31:21 >> Very early at Door Dash. Um, we learned um how how hard it is to keep someone's

31:23 um how how hard it is to keep someone's

31:23 um how how hard it is to keep someone's trust and how easy it is to lose it. And

31:27 trust and how easy it is to lose it. And

31:27 trust and how easy it is to lose it. And you know, I I I think I may have said

31:28 you know, I I I think I may have said

31:28 you know, I I I think I may have said this before, but there was um there was

31:31 this before, but there was um there was

31:31 this before, but there was um there was a Stanford football game in which we

31:32 a Stanford football game in which we

31:32 a Stanford football game in which we lost um a lot of trust where we were

31:36 lost um a lot of trust where we were

31:36 lost um a lot of trust where we were late on every single delivery because we

31:38 late on every single delivery because we

31:38 late on every single delivery because we didn't have enough drivers on the road.

31:39 didn't have enough drivers on the road.

31:39 didn't have enough drivers on the road. We had no ability to shut down the

31:40 We had no ability to shut down the

31:40 We had no ability to shut down the website, but we had a lot of those

31:42 website, but we had a lot of those

31:42 website, but we had a lot of those >> pause there. So, where in Door Dash

31:44 >> pause there. So, where in Door Dash

31:44 >> pause there. So, where in Door Dash history is this this game?

31:46 history is this this game?

31:46 history is this this game? >> This is the third month of our

31:47 >> This is the third month of our

31:47 >> This is the third month of our operations, September of 2013, where it

31:50 operations, September of 2013, where it

31:50 operations, September of 2013, where it was a Saturday. We had no ability to

31:54 was a Saturday. We had no ability to

31:54 was a Saturday. We had no ability to fulfill the orders that came in. We had

31:55 fulfill the orders that came in. We had

31:56 fulfill the orders that came in. We had no ability to even shut down the

31:57 no ability to even shut down the

31:57 no ability to even shut down the website. So, we couldn't even like stop

31:58 website. So, we couldn't even like stop

31:58 website. So, we couldn't even like stop the floodgates. And usually,

32:00 the floodgates. And usually,

32:00 the floodgates. And usually, >> why were you having floodgates 3 months

32:02 >> why were you having floodgates 3 months

32:02 >> why were you having floodgates 3 months in?

32:03 in?

32:03 in? >> We had floodgates not 3 months in on

32:05 >> We had floodgates not 3 months in on

32:05 >> We had floodgates not 3 months in on that day specifically, for whatever

32:07 that day specifically, for whatever

32:07 that day specifically, for whatever reason, because of when the game ended,

32:10 reason, because of when the game ended,

32:10 reason, because of when the game ended, people wanted to order Door Dash for

32:12 people wanted to order Door Dash for

32:12 people wanted to order Door Dash for dinner in Palo Alto.

32:13 dinner in Palo Alto.

32:13 dinner in Palo Alto. >> And for whatever reason, um you know,

32:17 >> And for whatever reason, um you know,

32:17 >> And for whatever reason, um you know, that volume spiked pretty hard. We had

32:19 that volume spiked pretty hard. We had

32:19 that volume spiked pretty hard. We had no ability to turn it off and no ability

32:21 no ability to turn it off and no ability

32:21 no ability to turn it off and no ability to to fulfill. So, we were late by at

32:24 to to fulfill. So, we were late by at

32:24 to to fulfill. So, we were late by at least an hour on every single delivery.

32:26 least an hour on every single delivery.

32:26 least an hour on every single delivery. I think when you go through experiences

32:27 I think when you go through experiences

32:28 I think when you go through experiences like that, but not just once, but we've

32:29 like that, but not just once, but we've

32:30 like that, but not just once, but we've had a lot of those kinds of experiences

32:31 had a lot of those kinds of experiences

32:31 had a lot of those kinds of experiences at Door Dash. I mean, you know, I still

32:33 at Door Dash. I mean, you know, I still

32:33 at Door Dash. I mean, you know, I still do customer support every day. I see

32:35 do customer support every day. I see

32:35 do customer support every day. I see them literally every single day. When

32:37 them literally every single day. When

32:37 them literally every single day. When you see that you can lose someone's

32:38 you see that you can lose someone's

32:38 you see that you can lose someone's trust um on one order, you realize that

32:42 trust um on one order, you realize that

32:42 trust um on one order, you realize that you got to earn it again the next day.

32:45 you got to earn it again the next day.

32:45 you got to earn it again the next day. And there is no such thing as this, you

32:47 And there is no such thing as this, you

32:47 And there is no such thing as this, you know, just set it and forget it kind of

32:49 know, just set it and forget it kind of

32:49 know, just set it and forget it kind of mentality. Yeah, that came a lot from

32:51 mentality. Yeah, that came a lot from

32:51 mentality. Yeah, that came a lot from the early days. But I think this daily

32:53 the early days. But I think this daily

32:53 the early days. But I think this daily reminder when I do customer support is

32:55 reminder when I do customer support is

32:55 reminder when I do customer support is also another great reinforcing function.

32:58 also another great reinforcing function.

32:58 also another great reinforcing function. >> So what happened that night of the game?

33:00 >> So what happened that night of the game?

33:00 >> So what happened that night of the game? >> We were late on every single delivery.

33:03 >> We were late on every single delivery.

33:03 >> We were late on every single delivery. Um, and

33:05 Um, and

33:05 Um, and I think it was probably somewhere around

33:08 I think it was probably somewhere around

33:08 I think it was probably somewhere around 1000 p.m. or something where we're

33:09 1000 p.m. or something where we're

33:09 1000 p.m. or something where we're tallying up all the refunds that it

33:12 tallying up all the refunds that it

33:12 tallying up all the refunds that it would, you know, cost us if uh we wanted

33:15 would, you know, cost us if uh we wanted

33:15 would, you know, cost us if uh we wanted to make right and kind of give back

33:16 to make right and kind of give back

33:16 to make right and kind of give back everybody their money.

33:17 everybody their money.

33:17 everybody their money. >> Were the customers asking for the

33:19 >> Were the customers asking for the

33:19 >> Were the customers asking for the refunds or no one was asking? No one was

33:20 refunds or no one was asking? No one was

33:20 refunds or no one was asking? No one was asking for anything. We were the the

33:22 asking for anything. We were the the

33:22 asking for anything. We were the the night was over. We finished our last

33:24 night was over. We finished our last

33:24 night was over. We finished our last delivery and we said, "Okay, that was a

33:29 delivery and we said, "Okay, that was a

33:29 delivery and we said, "Okay, that was a terrible night.

33:31 terrible night.

33:31 terrible night. what are we going to do about it? We

33:33 what are we going to do about it? We

33:33 what are we going to do about it? We could complain about, you know, the

33:34 could complain about, you know, the

33:34 could complain about, you know, the orders or or something, but at the end

33:36 orders or or something, but at the end

33:36 orders or or something, but at the end of the day, I I think within a very

33:38 of the day, I I think within a very

33:38 of the day, I I think within a very short period of time, 15 seconds, we

33:41 short period of time, 15 seconds, we

33:41 short period of time, 15 seconds, we decided, okay, we got to make right by

33:43 decided, okay, we got to make right by

33:43 decided, okay, we got to make right by the customer. So, we got to refund

33:45 the customer. So, we got to refund

33:45 the customer. So, we got to refund everybody. Now, the complication is we

33:47 everybody. Now, the complication is we

33:47 everybody. Now, the complication is we had no money at the time. I was having a

33:49 had no money at the time. I was having a

33:49 had no money at the time. I was having a hard time raising I mean, this is a

33:52 hard time raising I mean, this is a

33:52 hard time raising I mean, this is a pattern for me. I've had a hard time

33:54 pattern for me. I've had a hard time

33:54 pattern for me. I've had a hard time raising capital for the company in the

33:56 raising capital for the company in the

33:56 raising capital for the company in the earliest years. Uh, and that started

33:58 earliest years. Uh, and that started

33:58 earliest years. Uh, and that started right from the beginning. I mean like we

33:59 right from the beginning. I mean like we

33:59 right from the beginning. I mean like we were maybe two or 3 weeks of cash out

34:02 were maybe two or 3 weeks of cash out

34:02 were maybe two or 3 weeks of cash out and this refund would have cost us about

34:05 and this refund would have cost us about

34:05 and this refund would have cost us about 40% of the bank account. So it would

34:07 40% of the bank account. So it would

34:07 40% of the bank account. So it would have just made the two or three weeks

34:08 have just made the two or three weeks

34:08 have just made the two or three weeks and just shrunk that into even fewer

34:10 and just shrunk that into even fewer

34:10 and just shrunk that into even fewer days. But yeah, you're right. Nobody

34:13 days. But yeah, you're right. Nobody

34:13 days. But yeah, you're right. Nobody asked us for the refunds. I'm sure they

34:14 asked us for the refunds. I'm sure they

34:14 asked us for the refunds. I'm sure they were pissed, but nobody asked. We did we

34:17 were pissed, but nobody asked. We did we

34:17 were pissed, but nobody asked. We did we did the refund right away and then we

34:19 did the refund right away and then we

34:19 did the refund right away and then we stayed up that night actually baking

34:20 stayed up that night actually baking

34:20 stayed up that night actually baking cookies and we delivered those cookies

34:23 cookies and we delivered those cookies

34:23 cookies and we delivered those cookies at around 5:00 a.m. U before we thought

34:25 at around 5:00 a.m. U before we thought

34:25 at around 5:00 a.m. U before we thought when customers would awake. And the idea

34:28 when customers would awake. And the idea

34:28 when customers would awake. And the idea was

34:29 was

34:29 was we'd rather die trying to be excellent

34:32 we'd rather die trying to be excellent

34:32 we'd rather die trying to be excellent or at least die trying to do the thing

34:34 or at least die trying to do the thing

34:34 or at least die trying to do the thing that we want to stand for than to live

34:36 that we want to stand for than to live

34:36 that we want to stand for than to live to be mediocre and not something that

34:38 to be mediocre and not something that

34:38 to be mediocre and not something that we'd be proud of. And that's what we

34:40 we'd be proud of. And that's what we

34:40 we'd be proud of. And that's what we did.

34:41 did.

34:41 did. >> That's excellent. So tell me more about

34:42 >> That's excellent. So tell me more about

34:42 >> That's excellent. So tell me more about building the system, this

34:43 building the system, this

34:43 building the system, this self-reinforcing like learning system.

34:45 self-reinforcing like learning system.

34:45 self-reinforcing like learning system. >> Look, these things kind of happen um in

34:48 >> Look, these things kind of happen um in

34:48 >> Look, these things kind of happen um in in in steps, right? So it started with

34:52 in in steps, right? So it started with

34:52 in in steps, right? So it started with the four of us doing the deliveries and

34:56 the four of us doing the deliveries and

34:56 the four of us doing the deliveries and Okay. Well, we can keep doing the

34:57 Okay. Well, we can keep doing the

34:57 Okay. Well, we can keep doing the deliveries. Um, but at some point we're

35:00 deliveries. Um, but at some point we're

35:00 deliveries. Um, but at some point we're going to start um running into scale

35:02 going to start um running into scale

35:02 going to start um running into scale issues. I mean, four people can only do

35:03 issues. I mean, four people can only do

35:04 issues. I mean, four people can only do so many deliveries. So, of course, we're

35:05 so many deliveries. So, of course, we're

35:05 so many deliveries. So, of course, we're going to start recruiting dashers. We're

35:07 going to start recruiting dashers. We're

35:07 going to start recruiting dashers. We're going to start recruit um recruiting

35:08 going to start recruit um recruiting

35:08 going to start recruit um recruiting consumers um selling restaurants. Um and

35:13 consumers um selling restaurants. Um and

35:13 consumers um selling restaurants. Um and you start noticing uh a as you do the

35:16 you start noticing uh a as you do the

35:16 you start noticing uh a as you do the deliveries, well, you have to build

35:18 deliveries, well, you have to build

35:18 deliveries, well, you have to build products to scale yourself. That's one.

35:19 products to scale yourself. That's one.

35:19 products to scale yourself. That's one. Two, you also just start noticing all

35:21 Two, you also just start noticing all

35:21 Two, you also just start noticing all the problems. And when you whenever you

35:23 the problems. And when you whenever you

35:23 the problems. And when you whenever you see a problem recur more than once, you

35:25 see a problem recur more than once, you

35:25 see a problem recur more than once, you would say to yourself, "Aha, maybe

35:26 would say to yourself, "Aha, maybe

35:26 would say to yourself, "Aha, maybe that's, you know, an example of a

35:29 that's, you know, an example of a

35:29 that's, you know, an example of a problem that we should actually build

35:30 problem that we should actually build

35:30 problem that we should actually build something for or actually run an

35:32 something for or actually run an

35:32 something for or actually run an experiment to see if we could actually

35:34 experiment to see if we could actually

35:34 experiment to see if we could actually solve." So I think very early on um the

35:37 solve." So I think very early on um the

35:37 solve." So I think very early on um the bias for action turned into this

35:40 bias for action turned into this

35:40 bias for action turned into this experimentation mentality. Now, we

35:42 experimentation mentality. Now, we

35:42 experimentation mentality. Now, we didn't have like any organizations at

35:44 didn't have like any organizations at

35:44 didn't have like any organizations at the time or anything like that. It was

35:45 the time or anything like that. It was

35:45 the time or anything like that. It was just like a few of us in my apartments.

35:46 just like a few of us in my apartments.

35:46 just like a few of us in my apartments. It wasn't like, "Okay, there's this like

35:48 It wasn't like, "Okay, there's this like

35:48 It wasn't like, "Okay, there's this like rigorous system that I'm talking about."

35:51 rigorous system that I'm talking about."

35:51 rigorous system that I'm talking about." That's probably the earliest inklings

35:53 That's probably the earliest inklings

35:53 That's probably the earliest inklings though of how we thought about okay, you

35:55 though of how we thought about okay, you

35:55 though of how we thought about okay, you can go from doing things that don't

35:57 can go from doing things that don't

35:57 can go from doing things that don't scale to identifying hypotheses to test

36:00 scale to identifying hypotheses to test

36:00 scale to identifying hypotheses to test to then running experiments and then to

36:02 to then running experiments and then to

36:02 to then running experiments and then to shipping products. That was probably the

36:03 shipping products. That was probably the

36:03 shipping products. That was probably the earliest like time, the first year of

36:06 earliest like time, the first year of

36:06 earliest like time, the first year of the company. You fast forward maybe a

36:08 the company. You fast forward maybe a

36:08 the company. You fast forward maybe a year as we started launching into

36:10 year as we started launching into

36:10 year as we started launching into multiple cities, all of the general

36:12 multiple cities, all of the general

36:12 multiple cities, all of the general managers of different cities. So you

36:13 managers of different cities. So you

36:13 managers of different cities. So you could be running Boston, someone else is

36:15 could be running Boston, someone else is

36:15 could be running Boston, someone else is running Dallas, someone else is running,

36:16 running Dallas, someone else is running,

36:16 running Dallas, someone else is running, you know, a different city. Uh they

36:18 you know, a different city. Uh they

36:18 you know, a different city. Uh they would be reporting into me. Um and you

36:21 would be reporting into me. Um and you

36:22 would be reporting into me. Um and you start seeing that oh okay well patterns

36:24 start seeing that oh okay well patterns

36:24 start seeing that oh okay well patterns actually emerge you know from city A to

36:27 actually emerge you know from city A to

36:27 actually emerge you know from city A to city B to city C but they are still

36:29 city B to city C but they are still

36:29 city B to city C but they are still quite local um there's slightly you you

36:33 quite local um there's slightly you you

36:33 quite local um there's slightly you you know for example in Boston there's not a

36:34 know for example in Boston there's not a

36:34 know for example in Boston there's not a lot of cars um car ownership is one of

36:37 lot of cars um car ownership is one of

36:37 lot of cars um car ownership is one of the lowest in Boston you know in the

36:39 the lowest in Boston you know in the

36:39 the lowest in Boston you know in the United States versus other places

36:41 United States versus other places

36:41 United States versus other places there's there's some strange setups

36:43 there's there's some strange setups

36:43 there's there's some strange setups because of the historic nature of the

36:45 because of the historic nature of the

36:45 because of the historic nature of the city in terms of that hub and spoke

36:47 city in terms of that hub and spoke

36:47 city in terms of that hub and spoke nature I was describing that that

36:48 nature I was describing that that

36:48 nature I was describing that that actually violate that that that setup.

36:51 actually violate that that that setup.

36:51 actually violate that that that setup. So there there are like local nuances

36:53 So there there are like local nuances

36:53 So there there are like local nuances and you start realizing well okay well

36:55 and you start realizing well okay well

36:55 and you start realizing well okay well how do I actually you know teach this

36:58 how do I actually you know teach this

36:58 how do I actually you know teach this way of doing things that don't scale all

37:00 way of doing things that don't scale all

37:00 way of doing things that don't scale all the way to shipping you know some

37:03 the way to shipping you know some

37:03 the way to shipping you know some feature that we know is going to work to

37:05 feature that we know is going to work to

37:05 feature that we know is going to work to each one of these people so that we

37:06 each one of these people so that we

37:06 each one of these people so that we could run more experiments at the same

37:08 could run more experiments at the same

37:08 could run more experiments at the same time and then we would just build more

37:10 time and then we would just build more

37:10 time and then we would just build more products that would actually um you know

37:13 products that would actually um you know

37:13 products that would actually um you know go across all of these different

37:14 go across all of these different

37:14 go across all of these different patterns. So that's kind of how this

37:16 patterns. So that's kind of how this

37:16 patterns. So that's kind of how this thing you know has morphed over the

37:18 thing you know has morphed over the

37:18 thing you know has morphed over the years where you basically start with

37:20 years where you basically start with

37:20 years where you basically start with some basic scientific you know process

37:24 some basic scientific you know process

37:24 some basic scientific you know process if you will. You meet some point in

37:27 if you will. You meet some point in

37:27 if you will. You meet some point in which you have to figure out the next

37:29 which you have to figure out the next

37:29 which you have to figure out the next iteration in order to scale that process

37:32 iteration in order to scale that process

37:32 iteration in order to scale that process and then you just keep that going and

37:33 and then you just keep that going and

37:33 and then you just keep that going and you're always testing you know against

37:35 you're always testing you know against

37:35 you're always testing you know against whether or not you're delivering better

37:36 whether or not you're delivering better

37:36 whether or not you're delivering better for customers. That's always going to be

37:37 for customers. That's always going to be

37:38 for customers. That's always going to be the northstar metric of whether or not

37:39 the northstar metric of whether or not

37:39 the northstar metric of whether or not this process is actually making a

37:41 this process is actually making a

37:41 this process is actually making a difference or not. Is it better for

37:42 difference or not. Is it better for

37:42 difference or not. Is it better for customers if it's faster, cheaper, more

37:44 customers if it's faster, cheaper, more

37:44 customers if it's faster, cheaper, more efficient? Like what are the

37:45 efficient? Like what are the

37:45 efficient? Like what are the >> Yeah, it's all of the above. So, look,

37:47 >> Yeah, it's all of the above. So, look,

37:47 >> Yeah, it's all of the above. So, look, customers, I mean, this business is

37:48 customers, I mean, this business is

37:48 customers, I mean, this business is tough because customers unfortunately

37:50 tough because customers unfortunately

37:50 tough because customers unfortunately don't just judge us on one dimension.

37:53 don't just judge us on one dimension.

37:53 don't just judge us on one dimension. Some customers, all customers want the

37:56 Some customers, all customers want the

37:56 Some customers, all customers want the widest available selection. They want

37:57 widest available selection. They want

37:57 widest available selection. They want every item they can get, you know,

37:59 every item they can get, you know,

37:59 every item they can get, you know, delivered. They want the lowest possible

38:01 delivered. They want the lowest possible

38:01 delivered. They want the lowest possible price. They want the fastest possible

38:03 price. They want the fastest possible

38:03 price. They want the fastest possible delivery. They want obviously no

38:04 delivery. They want obviously no

38:04 delivery. They want obviously no mistakes. They absolutely, you know,

38:07 mistakes. They absolutely, you know,

38:07 mistakes. They absolutely, you know, expect it to be on time. And then if

38:09 expect it to be on time. And then if

38:09 expect it to be on time. And then if something were to go wrong, of course

38:10 something were to go wrong, of course

38:10 something were to go wrong, of course they deserve to be treated correctly.

38:13 they deserve to be treated correctly.

38:13 they deserve to be treated correctly. We get judged on all of those things on

38:16 We get judged on all of those things on

38:16 We get judged on all of those things on every single order.

38:17 every single order.

38:17 every single order. >> So this is this idea of like you can

38:18 >> So this is this idea of like you can

38:18 >> So this is this idea of like you can build a business around things that

38:19 build a business around things that

38:19 build a business around things that don't change.

38:20 don't change.

38:20 don't change. >> Yes.

38:21 >> Yes.

38:21 >> Yes. >> What are the things that don't change

38:22 >> What are the things that don't change

38:22 >> What are the things that don't change from the customer's perspective for Door

38:23 from the customer's perspective for Door

38:23 from the customer's perspective for Door Dash? Then

38:24 Dash? Then

38:24 Dash? Then >> customers are always going to want more

38:26 >> customers are always going to want more

38:26 >> customers are always going to want more and more selection. They're going to

38:28 and more selection. They're going to

38:28 and more selection. They're going to always want more and more affordability.

38:30 always want more and more affordability.

38:30 always want more and more affordability. They're going to want faster deliveries.

38:32 They're going to want faster deliveries.

38:32 They're going to want faster deliveries. is like Amazon almost the exact like

38:35 is like Amazon almost the exact like

38:35 is like Amazon almost the exact like mirror of what Amazon

38:36 mirror of what Amazon

38:36 mirror of what Amazon >> well I think when you when you just

38:37 >> well I think when you when you just

38:38 >> well I think when you when you just think about what people want I I I

38:40 think about what people want I I I

38:40 think about what people want I I I actually think it's pretty easy because

38:42 actually think it's pretty easy because

38:42 actually think it's pretty easy because we can play that role ourselves and yeah

38:44 we can play that role ourselves and yeah

38:44 we can play that role ourselves and yeah I I I I think you just ask the you can

38:47 I I I I think you just ask the you can

38:47 I I I I think you just ask the you can ask very basic questions about what's

38:50 ask very basic questions about what's

38:50 ask very basic questions about what's the direction of travel of certain

38:52 the direction of travel of certain

38:52 the direction of travel of certain things like for example like do you

38:53 things like for example like do you

38:53 things like for example like do you think people are going to expect more

38:55 think people are going to expect more

38:55 think people are going to expect more convenience or less convenience

38:57 convenience or less convenience

38:57 convenience or less convenience especially in a world where you think

38:59 especially in a world where you think

38:59 especially in a world where you think that people are earning more um you know

39:02 that people are earning more um you know

39:02 that people are earning more um you know whether today versus the past tomorrow

39:04 whether today versus the past tomorrow

39:04 whether today versus the past tomorrow versus today. What do you think they're

39:06 versus today. What do you think they're

39:06 versus today. What do you think they're going to do with those dollars? Is it

39:09 going to do with those dollars? Is it

39:09 going to do with those dollars? Is it going to go more towards consumption?

39:10 going to go more towards consumption?

39:10 going to go more towards consumption? Are they going to expect or demand more

39:12 Are they going to expect or demand more

39:12 Are they going to expect or demand more convenience or less? I think when you

39:13 convenience or less? I think when you

39:14 convenience or less? I think when you start asking questions just out loud,

39:17 start asking questions just out loud,

39:17 start asking questions just out loud, you you get the common sense answers in

39:19 you you get the common sense answers in

39:19 you you get the common sense answers in which you can build a business around.

39:21 which you can build a business around.

39:21 which you can build a business around. >> We were talking about this with the crew

39:22 >> We were talking about this with the crew

39:22 >> We were talking about this with the crew at breakfast. It's just like, well,

39:23 at breakfast. It's just like, well,

39:23 at breakfast. It's just like, well, their cornerstone of their business is

39:25 their cornerstone of their business is

39:25 their cornerstone of their business is some a trait in human nature that's

39:26 some a trait in human nature that's

39:26 some a trait in human nature that's never going to change, which is like we

39:27 never going to change, which is like we

39:28 never going to change, which is like we want more convenience.

39:28 want more convenience.

39:28 want more convenience. >> Yeah. Always. I I I it's not um it's not

39:31 >> Yeah. Always. I I I it's not um it's not

39:31 >> Yeah. Always. I I I it's not um it's not rocket science. I think the rocket

39:33 rocket science. I think the rocket

39:34 rocket science. I think the rocket science is actually how do you make it

39:35 science is actually how do you make it

39:35 science is actually how do you make it happen?

39:36 happen?

39:36 happen? >> Yeah. I love this idea of like you're

39:37 >> Yeah. I love this idea of like you're

39:37 >> Yeah. I love this idea of like you're hiding the complexity. I I spent several

39:40 hiding the complexity. I I spent several

39:40 hiding the complexity. I I spent several hours with Basos uh oneonone and u I'm

39:44 hours with Basos uh oneonone and u I'm

39:44 hours with Basos uh oneonone and u I'm obviously a massive fan of his. I've

39:45 obviously a massive fan of his. I've

39:45 obviously a massive fan of his. I've done like 15 episodes on him and he had

39:48 done like 15 episodes on him and he had

39:48 done like 15 episodes on him and he had he listens to my other podcast and I

39:50 he listens to my other podcast and I

39:50 he listens to my other podcast and I told him I was like, "Dude, you know how

39:52 told him I was like, "Dude, you know how

39:52 told him I was like, "Dude, you know how crazy it is that they put a guillotine

39:53 crazy it is that they put a guillotine

39:53 crazy it is that they put a guillotine in front of your house in Washington?"

39:55 in front of your house in Washington?"

39:55 in front of your house in Washington?" And I go, "You made a magic button I can

39:56 And I go, "You made a magic button I can

39:56 And I go, "You made a magic button I can press that that anything I want in the

39:58 press that that anything I want in the

39:58 press that that anything I want in the world shows up to my house in two days

40:00 world shows up to my house in two days

40:00 world shows up to my house in two days and now it's like a few hours and all I

40:02 and now it's like a few hours and all I

40:02 and now it's like a few hours and all I do is press the button and you handle

40:03 do is press the button and you handle

40:04 do is press the button and you handle all the other complexity behind it." I

40:05 all the other complexity behind it." I

40:05 all the other complexity behind it." I was like, "You deserve all the money. I

40:06 was like, "You deserve all the money. I

40:06 was like, "You deserve all the money. I hope you have all the money." He just

40:08 hope you have all the money." He just

40:08 hope you have all the money." He just laughed and laughed and laughed. You

40:10 laughed and laughed and laughed. You

40:10 laughed and laughed and laughed. You said something. You're doing customer

40:11 said something. You're doing customer

40:11 said something. You're doing customer support every day. Is this customer

40:12 support every day. Is this customer

40:12 support every day. Is this customer support? Emails. What is this? Emails or

40:14 support? Emails. What is this? Emails or

40:14 support? Emails. What is this? Emails or chats? Sometimes phone calls every day?

40:17 chats? Sometimes phone calls every day?

40:17 chats? Sometimes phone calls every day? >> Yeah. Say more about this.

40:19 >> Yeah. Say more about this.

40:19 >> Yeah. Say more about this. >> Well, why do you do this? You know, I I

40:21 >> Well, why do you do this? You know, I I

40:21 >> Well, why do you do this? You know, I I was saying earlier that for a few

40:23 was saying earlier that for a few

40:23 was saying earlier that for a few reasons. You know, one of the things

40:25 reasons. You know, one of the things

40:25 reasons. You know, one of the things that we're talking about earlier is that

40:27 that we're talking about earlier is that

40:27 that we're talking about earlier is that so much of the magic or the difficulty

40:29 so much of the magic or the difficulty

40:29 so much of the magic or the difficulty of building a company like Door Dash is

40:32 of building a company like Door Dash is

40:32 of building a company like Door Dash is in all the things you can't see. And so,

40:35 in all the things you can't see. And so,

40:35 in all the things you can't see. And so, the first thing you got to do is you got

40:36 the first thing you got to do is you got

40:36 the first thing you got to do is you got to build observability everywhere. you

40:38 to build observability everywhere. you

40:38 to build observability everywhere. you know, of course there's observability

40:40 know, of course there's observability

40:40 know, of course there's observability with dashboards and systems and

40:43 with dashboards and systems and

40:43 with dashboards and systems and um you know, increasingly, you know, AI

40:46 um you know, increasingly, you know, AI

40:46 um you know, increasingly, you know, AI tools, but but also I can see the

40:49 tools, but but also I can see the

40:49 tools, but but also I can see the inbound, you know, of of customers who

40:52 inbound, you know, of of customers who

40:52 inbound, you know, of of customers who write us, whether it's a consumer, a

40:53 write us, whether it's a consumer, a

40:54 write us, whether it's a consumer, a merchant, a dasher, an advertiser, and I

40:57 merchant, a dasher, an advertiser, and I

40:57 merchant, a dasher, an advertiser, and I can choose to ignore them, but those are

41:00 can choose to ignore them, but those are

41:00 can choose to ignore them, but those are freebies. I mean like how lucky am I to

41:02 freebies. I mean like how lucky am I to

41:02 freebies. I mean like how lucky am I to actually have a product in which people

41:04 actually have a product in which people

41:04 actually have a product in which people care enough you know even I mean usually

41:08 care enough you know even I mean usually

41:08 care enough you know even I mean usually usually they're not very positive emails

41:11 usually they're not very positive emails

41:11 usually they're not very positive emails but I mean like but they care enough to

41:12 but I mean like but they care enough to

41:12 but I mean like but they care enough to actually let me know you know I think

41:14 actually let me know you know I think

41:14 actually let me know you know I think the greatest killer of a business is

41:15 the greatest killer of a business is

41:15 the greatest killer of a business is usually silence and and here they're

41:19 usually silence and and here they're

41:19 usually silence and and here they're actually they care enough to actually

41:21 actually they care enough to actually

41:21 actually they care enough to actually let me know something went wrong in

41:23 let me know something went wrong in

41:24 let me know something went wrong in their experience. I owe them, you know,

41:26 their experience. I owe them, you know,

41:26 their experience. I owe them, you know, uh certainly not just a response, but

41:28 uh certainly not just a response, but

41:28 uh certainly not just a response, but actually I think the and not the

41:31 actually I think the and not the

41:31 actually I think the and not the courtesy, but I owe them the

41:33 courtesy, but I owe them the

41:33 courtesy, but I owe them the responsibility of actually solving that

41:34 responsibility of actually solving that

41:34 responsibility of actually solving that problem ultimately. And so, first, it's

41:37 problem ultimately. And so, first, it's

41:37 problem ultimately. And so, first, it's an obligation to the the customers.

41:39 an obligation to the the customers.

41:39 an obligation to the the customers. Second, it's actually something that I

41:41 Second, it's actually something that I

41:41 Second, it's actually something that I want the rest of the company to do. You

41:42 want the rest of the company to do. You

41:42 want the rest of the company to do. You know, I think one of the easiest things

41:44 know, I think one of the easiest things

41:44 know, I think one of the easiest things as companies get a little bit bigger,

41:47 as companies get a little bit bigger,

41:47 as companies get a little bit bigger, perhaps earn a little bit more success

41:49 perhaps earn a little bit more success

41:50 perhaps earn a little bit more success is there more obstacles between them and

41:54 is there more obstacles between them and

41:54 is there more obstacles between them and the uh the the customers or the jobs to

41:57 the uh the the customers or the jobs to

41:57 the uh the the customers or the jobs to be done. You know, for example, when you

42:00 be done. You know, for example, when you

42:00 be done. You know, for example, when you become a company, you know, all of a

42:02 become a company, you know, all of a

42:02 become a company, you know, all of a sudden there are the only things that

42:04 sudden there are the only things that

42:04 sudden there are the only things that kind of get spotlighted are the

42:05 kind of get spotlighted are the

42:05 kind of get spotlighted are the financial metrics, your revenue, your

42:07 financial metrics, your revenue, your

42:07 financial metrics, your revenue, your profits. Um none of which are metrics

42:10 profits. Um none of which are metrics

42:10 profits. Um none of which are metrics that customers care about.

42:12 that customers care about.

42:12 that customers care about. that there are no metrics in in what we

42:15 that there are no metrics in in what we

42:15 that there are no metrics in in what we report uh you know to to as a public

42:18 report uh you know to to as a public

42:18 report uh you know to to as a public company that customers know about

42:20 company that customers know about

42:20 company that customers know about probably or care about frankly and that

42:23 probably or care about frankly and that

42:23 probably or care about frankly and that always is quite bothersome to me because

42:26 always is quite bothersome to me because

42:26 always is quite bothersome to me because it's because of our ability to serve

42:27 it's because of our ability to serve

42:27 it's because of our ability to serve customers that can hopefully achieve you

42:30 customers that can hopefully achieve you

42:30 customers that can hopefully achieve you know strong financial metrics that uh

42:32 know strong financial metrics that uh

42:32 know strong financial metrics that uh investors care about and so a lot of

42:35 investors care about and so a lot of

42:35 investors care about and so a lot of what I'm trying to do is building as

42:38 what I'm trying to do is building as

42:38 what I'm trying to do is building as many reinforcing and repetitive

42:41 many reinforcing and repetitive

42:41 many reinforcing and repetitive mechanisms and motions, including things

42:43 mechanisms and motions, including things

42:43 mechanisms and motions, including things that I do individually, that will allow

42:46 that I do individually, that will allow

42:46 that I do individually, that will allow this company to always

42:49 this company to always

42:49 this company to always recognize that the number one job and

42:51 recognize that the number one job and

42:51 recognize that the number one job and the only religion at this company is to

42:53 the only religion at this company is to

42:53 the only religion at this company is to solve problems for customers.

42:55 solve problems for customers.

42:55 solve problems for customers. >> What do you do when the data and the

42:56 >> What do you do when the data and the

42:56 >> What do you do when the data and the anecdotes conflict?

42:58 anecdotes conflict?

42:58 anecdotes conflict? >> It's a tough one. Um, I think that um,

43:02 >> It's a tough one. Um, I think that um,

43:02 >> It's a tough one. Um, I think that um, usually there's always an element of

43:04 usually there's always an element of

43:04 usually there's always an element of truth in what customers are saying and

43:07 truth in what customers are saying and

43:07 truth in what customers are saying and and it usually becomes a trade-off, you

43:10 and it usually becomes a trade-off, you

43:10 and it usually becomes a trade-off, you know, discussion. uh you know for for

43:12 know, discussion. uh you know for for

43:12 know, discussion. uh you know for for different teams. The the reason why it's

43:14 different teams. The the reason why it's

43:14 different teams. The the reason why it's a tough decision is because it is so

43:17 a tough decision is because it is so

43:17 a tough decision is because it is so easy to always just veer on the side of

43:19 easy to always just veer on the side of

43:19 easy to always just veer on the side of the data because almost always when a

43:23 the data because almost always when a

43:23 the data because almost always when a customer notices something that is wrong

43:26 customer notices something that is wrong

43:26 customer notices something that is wrong um or or there's an anecdote um uh that

43:29 um or or there's an anecdote um uh that

43:29 um or or there's an anecdote um uh that may be a quote unquote edge case. It's

43:32 may be a quote unquote edge case. It's

43:32 may be a quote unquote edge case. It's usually at some tail of a distribution.

43:35 usually at some tail of a distribution.

43:35 usually at some tail of a distribution. Um, a distribution of the wait times for

43:38 Um, a distribution of the wait times for

43:38 Um, a distribution of the wait times for customer support, a distribution of how

43:40 customer support, a distribution of how

43:40 customer support, a distribution of how friendly we were when we actually took

43:42 friendly we were when we actually took

43:42 friendly we were when we actually took the call, a distribution of how on time

43:44 the call, a distribution of how on time

43:44 the call, a distribution of how on time we were or how late we were or how

43:46 we were or how late we were or how

43:46 we were or how late we were or how accurate we were, or what are the number

43:48 accurate we were, or what are the number

43:48 accurate we were, or what are the number of items of the types of SKUs you care

43:51 of items of the types of SKUs you care

43:51 of items of the types of SKUs you care about in a particular category of

43:53 about in a particular category of

43:53 about in a particular category of lettuce. Just lettuce, not vegetables,

43:55 lettuce. Just lettuce, not vegetables,

43:55 lettuce. Just lettuce, not vegetables, but just lettuce, right? So, it's always

43:58 but just lettuce, right? So, it's always

43:58 but just lettuce, right? So, it's always some tail example. And so the data is

44:01 some tail example. And so the data is

44:01 some tail example. And so the data is probably always going to win when it

44:02 probably always going to win when it

44:02 probably always going to win when it comes to a some sort of a prioritization

44:04 comes to a some sort of a prioritization

44:04 comes to a some sort of a prioritization discussion. But when you actually think

44:06 discussion. But when you actually think

44:06 discussion. But when you actually think about how to make a product better, it's

44:09 about how to make a product better, it's

44:09 about how to make a product better, it's going to almost always by definition be

44:11 going to almost always by definition be

44:11 going to almost always by definition be in improving the edges, you know, and

44:14 in improving the edges, you know, and

44:14 in improving the edges, you know, and that's why a lot of times what I like to

44:16 that's why a lot of times what I like to

44:16 that's why a lot of times what I like to do personally is I love to spend time um

44:19 do personally is I love to spend time um

44:19 do personally is I love to spend time um uh you know, with a lot of our power

44:21 uh you know, with a lot of our power

44:21 uh you know, with a lot of our power users, whether it's, you know, the the

44:23 users, whether it's, you know, the the

44:23 users, whether it's, you know, the the top dashers or um uh the consumers who

44:26 top dashers or um uh the consumers who

44:26 top dashers or um uh the consumers who order the most often or the merchants

44:28 order the most often or the merchants

44:28 order the most often or the merchants who we've been doing um you know,

44:30 who we've been doing um you know,

44:30 who we've been doing um you know, business with for a very long period of

44:32 business with for a very long period of

44:32 business with for a very long period of time and also the new users. They're at

44:34 time and also the new users. They're at

44:34 time and also the new users. They're at the tales of the distribution of almost

44:36 the tales of the distribution of almost

44:36 the tales of the distribution of almost every outcome. A new user, you know,

44:38 every outcome. A new user, you know,

44:38 every outcome. A new user, you know, who's never touched Door Dash before

44:39 who's never touched Door Dash before

44:40 who's never touched Door Dash before and, you know, for the 13 years that

44:41 and, you know, for the 13 years that

44:41 and, you know, for the 13 years that we've been around will absolutely, you

44:44 we've been around will absolutely, you

44:44 we've been around will absolutely, you know, tell us about how easy or

44:46 know, tell us about how easy or

44:46 know, tell us about how easy or difficult it is to place their first

44:47 difficult it is to place their first

44:47 difficult it is to place their first order in a way that, you know, someone

44:50 order in a way that, you know, someone

44:50 order in a way that, you know, someone who's been used to all the things that,

44:52 who's been used to all the things that,

44:52 who's been used to all the things that, you know, we've been training together

44:53 you know, we've been training together

44:53 you know, we've been training together with customers on have figured out. a

44:56 with customers on have figured out. a

44:56 with customers on have figured out. a power user also, you know, you know,

44:58 power user also, you know, you know,

44:58 power user also, you know, you know, sees all the issues too because they

45:00 sees all the issues too because they

45:00 sees all the issues too because they have the most shots on goal for some

45:02 have the most shots on goal for some

45:02 have the most shots on goal for some chaotic event to happen in the real

45:04 chaotic event to happen in the real

45:04 chaotic event to happen in the real world that we couldn't capture. And so

45:08 world that we couldn't capture. And so

45:08 world that we couldn't capture. And so those edges of the distribution are

45:10 those edges of the distribution are

45:10 those edges of the distribution are almost always where the anecdotes are

45:12 almost always where the anecdotes are

45:12 almost always where the anecdotes are that are the most valuable um that you

45:15 that are the most valuable um that you

45:15 that are the most valuable um that you have to pay the most attention to

45:16 have to pay the most attention to

45:16 have to pay the most attention to because they almost always will disagree

45:19 because they almost always will disagree

45:19 because they almost always will disagree with the data and they are probably

45:21 with the data and they are probably

45:21 with the data and they are probably worth the most in terms of improving

45:23 worth the most in terms of improving

45:23 worth the most in terms of improving your product. So let's say you find one

45:24 your product. So let's say you find one

45:24 your product. So let's say you find one of these edge cases as you're doing

45:26 of these edge cases as you're doing

45:26 of these edge cases as you're doing customer support every day. What's your