Afford Anything - What to Fix First When Everything Feels Stuck, with former Lyft COO and Tesla President Jon McNeill

Episode Date: April 10, 2026

#705: Jon McNeill, former president of Tesla and COO of Lyft, starts with a simple problem: his teenage son is about to start driving, and he’s worried about texting behind the wheel. Instead of setting rules, he builds a solution. That idea becomes TruMotion, a company that uses smartphone sensors to track driving behavior. You hear how the app figures out whether someone is actually in the driver’s seat, and how that technology ends up powering programs used by major insurance companies. From there, we zoom out. McNeill walks us through the systems he uses to build and scale companies. He explains how to question assumptions, including a case where his team reduces a 12-page car loan document down to a few sentences after realizing none of it is legally required. We also talk about speed. At Tesla, he learns to make decisions quickly, even without perfect information. He describes how faster decision-making compounds advantage over time. You hear a story from his early days working with Tesla, when he visits multiple stores, signs up for test drives, and never gets a follow-up. That leads him to identify thousands of missed sales opportunities sitting in the pipeline. The fix comes from focusing on the bottleneck, not adding more leads. McNeill also shares how he approaches negotiations at scale, including working with government officials in China and learning how incentives and systems shape outcomes. Throughout the conversation, he returns to a few core ideas: simplify the problem, identify the constraint, and move quickly once you have enough information to act. McNeill’s new book is The Algorithm: The Hypergrowth Formula That Transformed Tesla, Lululemon, General Motors, and SpaceX. Timestamps: Note: Timestamps will vary on individual listening devices based on dynamic advertising segments. The provided timestamps are approximate and may be several minutes off due to changing ad lengths. (00:00) Jon McNeill, former Tesla President and former COO of Lyft (06:50) The "First Principles" Mindset (15:05) Managing Hyper-growth at Tesla Solving for "Pain Points" vs. Chasing Profit Autonomous Driving and Electric Vehicles Working with Visionary Founders Building a Culture of Innovation in any Organization Learn more about your ad choices. Visit podcastchoices.com/adchoices

When John McNeill was in high school, in Kearney, Nebraska, where he attended the local public school, he needed a way to pay for college. So he started mowing lawns and grew that business to more than 100 commercial accounts and hired multiple employees all before he graduated from high school. That's how he paid for college. He got a degree in economics from Northwestern. Fast forward many, many years. He's a dad of two. He has a teenage son who's about to start driving, and he is terrified that his son, is going to text while driving. I let him in a moment tell the story himself of how he solved that problem. But suffice to say, the solution came in the form of a company that he started called True Motion, which is a technology that's now used by huge insurers like State Farm, Geico, Progressive, and frankly, if he had only done that in his entire life, if that had been his only achievement,

that alone would be pretty darn impressive. We could learn about entrepreneurship from him. But it turns out he's done a few other things as well. He started and sold six companies. He was the chief operating officer of Lyft. He was the president of Tesla and ran Tesla's global sales during its very high growth phase from 2015 to 2018.

He's served on the boards of companies like CrossFit, Lulu Lemon, and General Motors. He was named the most admired CEO in Boston, by Boston Business Journal, and he co-founded Venture Incubator DVX Ventures, which, as of last year, raised approximately $100 million in funds. What can he teach us about business and entrepreneurship? We're about to find out. Welcome to the Afford Anything Podcast, the show that knows you can afford anything, not everything. This show covers five pillars, financial psychology, increasing your income, investing, real estate, and entrepreneurship, which is the topic we will talk about today,

although more broadly, this conversation is not just for people who want to start businesses, it's for anyone who wants to improve their problem-solving skills. Because that is the skill that John has honed. He solves problems. His new book, The Algorithm, is all about the problem-solving skill set that led to his success, and much of it comes back to simplification. So to hear him describe this process, here he is, the former president of Tesla and C-O-O of Lyft, John McNeil.

Hi, John. Hi. Thank you for joining us. Yeah, thanks for having me here. John, how many kids do you have? Two. Your son, he's the oldest? He's the oldest, yeah.

When he was about to get his driver's license, you were up all night worried. Why, and what did you do about it? I was worried he was going to text while driving and either kill himself or kill somebody else. And so I wanted to solve that problem. Most parents would solve that problem by lecturing their kid. I didn't think I was going to work. Because I'm a little bit of a techno nerd. I started to research, how could I shut down texting while driving on his phone?

The easy thing was, hey, if that phone is like going faster than 10 miles an hour, odds are he's in a car. So like, could I shut the texting off if he was going faster than 10 miles an hour? Turn out, you can do a lot of things to an iPhone, but you can't do that. So I called a friend of mine at Apple and I said, why can't I do this? And they said, oh, Steve Jobs actually made this decision. If a phone is in motion, it probably means somebody's in a car, and that probably means they're

going to consume content. And we'd like them to consume content. Like navigation? Navigation, exactly. Or if they're in the passenger seat, music, they can read, watch videos, whatever. So Steve has personally made the decision, we're not going to allow this. And they said, in addition to that, you don't know whether this person is in the driver's seat or not. So like you wouldn't want to shut off texting if somebody wasn't in the driver's seat and needed help.

And so we're not doing that. I then figured out, okay, like, how would I take the next step? And I just kept working that problem and eventually figured out that I could develop an app that would gamify driving without texting and would score the way he was driving. So I could use the accelerometers and the gyroscopes in the phone to score the way he was driving. But I still couldn't figure out like, how do you figure out whether he's in the driver's seat or not? not. And then I met a couple of physics PhDs from MIT who were working on a similar problem. And I said, do you want to work on this together? We solved the problem about six months later of how to figure out if somebody was in the front seat, driver's seat of the car. We figured out how to score their

driving. So we couldn't shut off texting, but we could gamify it and give them an incentive not to. And the incentive was cheaper car insurance, which parents are kind of into when a teen driver starts to drive, your insurance costs go through the roof. Right. And so my son was kind of getting a kick out of this that I was like working this problem and working it and working. And eventually we solved the problem and created this app and we created a company. And that company today is most of the driving scoring app.

So if you see like State Farm or Geico or progressive like score your driving, it's that company that's behind that technology. That all got created from a parent being worried about texting while driving. It's a little bit nuts. Well, so many things had to happen for that story to unfold. So first of all, the standard answers that tend to stop somebody in their tracks. I mean, first there's the challenge of even knowing, you know, through GPS, if a phone is in a car, there's that. And then once you establish, I mean, can you go into that problem that you solved with the MIT guys? How do you know if that phone is in the driver's seat versus that front passenger seat? It's a really kind of fun question. So the answer is you can. Because GPS is only accurate to 30 feet. So you could be in the front seat. You could be beside the car like 30 feet.

It exceeds the diameter of the car or the radius of the car. So you could be anywhere. And so we could not figure out how to know if somebody was in the driver's seat. One day one of the physicists, his name is Brad Cordova. Brad came back. He was like, oh my gosh, I figured it out. And I said, how did you figure it out? He said, because when you get in the car in the driver's seat, the pattern that

your legs move and that your body moves is different because you have to swing around the steering wheel. And so he showed me the gyroscope charts. And it basically showed like when you get in the car, passenger side, the front seat, rear seat, you get this smooth entry, but like it's really janky entry. These curves are really janky when you're in the driver seat. He's like, that's how we're going to know. I was like, that is so simple. How did nobody figure this out? But it turned out sometimes the simple is the answer. It just takes you a while to figure it out and get to the simple. That answers the way the human body moves as it's getting into a car. Yeah. But your phone could be, it could be in your hand, it could be in your pocket, it could be in your purse. Totally. Yeah.

So how does. So then we studied like phone movement post that like what happens. It turns out that 90% of the people put their phone either in the coffee holder or the cup holder or in the console, 90%. Yeah. And 2% of the people take it, it's like in a purse or a backpack and it goes in the backseat. So you could solve the problem with 98% accuracy by assuming that it was going in the console or in the cup holder because that's where it went most of the time. Wow.

Yeah. Turn out you didn't have to make the problem too complicated. Yeah. And that's sort of a theme you have when it comes to solving all business problems is don't over solve for the edge cases. Don't make it too complicated. Can you talk about that philosophy? Yeah, it starts with the inverse of that is just be a simplifier. And simplifiers are rare. And so when you find them and you can put simplifiers on a team together, you can really do a lot of damage together and or you can really create exciting businesses and breakthroughs together. And so simplification is this real challenge that a lot of people have. Mark Twain wrote about it. He said, I would have written you a shorter letter if I would have taken the time. Basically, saying in a long way, simplification's hard. But what I thought is,

found is if you can simplify the complex, you can have breakthroughs. But it's really hard to get breakthroughs in the complex because it's really hard to see where the leverage points are. How does a person go about simplifying? So we talked about this in the algorithm because this was really the basics of how we invented and drove innovation at Tesla was based on simplification. So the first step that we would start with is the easiest way to simplify is get rid of all the dumb requirements of whatever you're looking at. So ask yourself, is this a requirement of law, of physics, of safety? And if it's not, then it's a candidate for deletion. And so I'll give you an example of that. We looked at how complicated the car buying process was online. And the most

complex part of the carbine process is getting a loan release. And those documents are like 12 pages long. Right. And so we asked how many of these paragraphs in these 12 pages are the requirement of law or regulatory bodies. And the answer that came back from our lawyers, after they analyzed it was none. And so none of our competitors would have thought to ask that question, I don't think. None of them had acted on it. And so when we figured that out, we knew we could get down to a one paragraph loan dock, which was, here's how much the car costs, here's the interest rate, here's the time period, here's the monthly payment. That's four sentences. And so you could turn a 12-page loan dock, which involved about 44 clicks to get.

through, you can turn that into one click. That is the first step in our simplification process. Just don't assume anything that you're being told is an absolute requirement. Dig into it and figure out if you can delete it. I mean, this sounds great in theory, but a couple of things come to mind right away when I hear you tell the story. First, you need the lawyers on your team who are actually going to come back with that answer because there are so many attorneys who are very risk-averse. I mean, that's their job. Their job is to protect you from legal risk. They'll say, like, traditionally it's done this way for this reason. Here's why the status quo exists. And here are some of the risks that you might face. If we do this unprecedented thing,

first you need the people on your team who have that same mentality. Yeah, that same mentality. Then, and I know you went with, I think, Ally Bank and U.S. Bank, you went with some of the smaller banks, But you need institutional lenders who will also play game, right? And so amassing a team that is willing to take on that same, the same unknown unknowns when doing something so innovative. Yeah. Right. How do you even begin that? So it's kind of easy in practice.

You screen for it while you're interviewing people. So you ask them, like, give me an example of the best work of your life. people will say like I was involved in this or I was involved in this and you start to break it down with them you say okay tell me how big did the problem look when you started and then how did you break it down and you can quickly hear were they shrinking that problem or were they accepting it at its current size or were they making it even more complex and so like literally 10 minutes into an interview you know whether you're talking to a simplify or not and so that would move that candidate to the next step but that is how we assembled a team

of simplifiers because we were testing for it as we were interviewing people. And we were adamant that they had to have this skill set. If you're going to be on one of my teams, you had to have this skill set. It was absolutely necessary. You couldn't figure out how to grow a company. At the time, we were growing Tesla from $2 billion in revenue to $20 billion in revenue, so $10xing it in 30 months. That meant we were doubling the company roughly every eight months. And you can only do that if you're making things really dead simple. If they're complex, it gets tied up and trips itself up. Wow. Yeah.

You've created the algorithm. It's five steps towards that kind of hyperscaling. I want to walk through it step by step. But before we do, before you became president of Tesla, your own, I guess, what in retrospect was sort of a pre-interview was they brought you in as a consultant. This wasn't overtly an interview. This was just you being a consultant. And you actually went over Elon's head in a decision. Yeah.

Can you tell us that story? Yeah. So I actually, when he and I were getting to know each other, we have this similar approach where we want to be useful. And so I said to him like a dozen times, like I just want to make sure that I can be useful to you. Like your company is twice as big as my biggest company. I didn't even sign on as a consultant. I said, let me just, what's your biggest challenge? He's like, the biggest challenge right now is I'm not sure we're going to sell enough cars to meet our quarter. So I said, cool, let me work on that challenge, not as a consultant or anything. Like, I'll just do this as a friend. I was selling a company at the time. And so I was trying to traveling a lot. And I said, I'm just going to go poke around to that problem. I'll talk to you in a week. And so I, over the course of the next few days, I went to eight stores, eight Tesla stores. And I was told, like, the fulcrum of the sales process was to do a test drive. Because you do a test drive and electric car, you hit the accelerator, and it's like hitting a rocket ship, a go button. You just don't forget about it. And so people that do that can't stop talking about it.

They buy the car. So I went to eight stores, did test drive, had that experience, left my contact the information, but at all eight stores, I didn't want them to know what is up to, so I used the different email address at all eight stores. Several days later, nobody had called me back. I thought, this is kind of odd. They must know who I am, because if this is the key point in the sales process, of course, I'd be getting called back, but I wasn't going to call back. So Elon had introduced me to his head of sales ops. I got on the phone. I said, how many cars do you have to sell this quarter? And he said, 12,000. And we were about a third of the way into the quarter. And I said, how many of you sold? And he said, three thousand.

I said, you're not going to make your number. You can come up like 3,000 short. He's like, yeah, that's, I think, why Elon is talking to you. And I said, can you tell me how many test drives you've given that haven't been followed up on? He said, give me like an hour. I'll go into our CRM and I'll figure that out. So he calls me in an hour and he said, 9,000. I'm like, you have 9,000 test drives you've given and you haven't followed up.

Like, these are easy, easy sales potentially because they're almost all the way through the funnel. So I said, tell you what, why don't you shut down the store's ability, anybody in the store's ability to take on a new lead until they've called all their previous test drives back? I said, can you do that? He said, I can do that within the hour. He said, great, do it. So he did it. Calls me back the next day and says, you wouldn't believe what's happening.

Like, we're selling cars. I'm like, of course you are. You're like following up. And he said, this is almost miraculous. He said, I think we're going to meet our quarter. And I said, I think you are too, because now you have two months left in the quarter. to go do more test drives and do the follow-ups on. So, like, let's reopen the funnel.

Let's give it a few days, have them follow up on all their past test drives, and then let's reopen the funnel again for everybody. And then it dawned on me. I was thinking like a CEO, because that's what I was. This wasn't my company. I didn't even work here. So I called Elon and I said, hey, you know, we talked about me poking around on this problem. I poked around.

Here's what I found. Here's what the root cause is. People aren't calling people back. And he was like, how could this be? And I said, well, put that aside for a second. Here's what we did. We shut down this ability for people to take on new leads until they call everybody back and now you're selling cars. I said, but Elon, I got to ask for forgiveness.

It's like, this is your company, not mine. And I just made a decision that was yours, not mine. I'm super sorry. And I'm just not good at like asking for permission because I haven't done this in a long time. And there was this long period of silence. Like he's known for now, but I didn't know about this. It was probably 60 or 90 seconds, but it felt like forever. He just went silent on the phone.

And I was like, oh my gosh, what am I done? He came back on and said, I think you're going to fit in here just fine. So it was kind of the big icebreaker for us. Because like it showed me I could be useful in this environment. And I showed him that he could have somebody be super useful in this role too. And that ethos of ask for forgiveness, not permission. Was that an ethos that came naturally to you? I don't know.

It was an ethos because I didn't set out to intend to ask for forgiveness. I was just solving a problem. It turned out that that's the culture of Tesla. It is push decision making to the edge. Give people agency to make decisions so that you can move faster. And when he and I sat down and talked about it, I said, hey, look, let's just, let's do a postmortem on this. Like, here's why I did what I did.

And he said, there's one thing I want you to know. And that is the thing that matters most to me is speed and decision making. If we make decisions faster than our competitors, we compound advantage against them. So speed here is really important. And you won't get everything right. And that's okay too. And he said, but what you did in that moment was you took data in, you made a decision. So your speeded decision delay was almost zero from receiving information to making the call.

He's like, just keep doing that. And what I found out was that's, that was the Tesla culture. So it wasn't this ethos of ask for forgiveness. It was an ethos of decided speed. With the information that you have at hand, make the best to see. you can. Unless it was going to violate the law or cost us millions of dollars or violate safety principles that we had, just make the decision go. And it turns out that was the culture that really enabled a lot of innovation to happen at speed. Right. You said the three laws. So it's the law,

safety and the laws of physics. Exactly. Right. Those are some things you can't deny. Yeah. The parameters. Yeah. Even when things are coded in, there are still work around. So you actually You joined Tesla. One of your first projects was to go to Beijing and work with the Chinese government. Yeah. Who coded into their formal practices was a certain way of doing things that you had to work around. Can you tell us about that? Yeah.

So at the time, if you wanted to be a Western business, a non-China business operating in China, you had to fit within a framework. And their framework was that you do a joint venture, 50-50 joint venture with a local Chinese entity. It could be the government. It could be a business partner, but you had to have a 50-50 joint venture, and that meant that you were sharing half the profits with that joint venture partner. And that's the way it was done. And so over the course of 30 years of China opening their economy to the West, whether it was General Motors or Procter & Gamble or BMW or Mercedes or whoever entered the country, they had to have a 50-50 partner and share the profit interest 50-50. And so when we started to look at China, it's the world's largest car market times two. So like we sell 15 million new cars roughly every year in the U.S.

They sell 30 million new cars. So it's a market you want to be in if you're in the car manufacturing business. But to be there, you'd have to split half the profits. So now you're back to a market the size of the U.S. Right. Do they also have decision-making authority? Are they a silent partner? No, they're not a silent partner.

You have a board. You have an executive. The executive has to be Chinese national. So, no, they have a lot of governance power. It's a really good question. Yeah. Yeah. So we started to talk to our China team.

about entering China and they sort of read us the framework and said like here's what it's going to need to look like. We said is it really a requirement of law? Is it really true? The Chinese government every five years publishes a five-year economic plan and they had just published their economic plan. And their economic plan for the next five years was enter and eventually dominate several industries. Electric cars, batteries, solar cells, async chips and autonomy. And we were like, okay, we check all of these boxes as a potential partner. Right.

So they're going to want to negotiate with us, and we're going to want to enter into this market. So we ought to be able to find a better common ground than maybe everybody else is negotiated because we have some more negotiating power. So he would get like a sparkle in his eye when he's going to act something like super ambitious and or goofy. He said, how about this? Would you be up for going over negotiating the first joint venture with China? with no economic sharing by Western country.

And I said, we just heard that, like, Microsoft doesn't get this. GM doesn't get this. Procter & Gamble doesn't eat. Like, we're tiny compared to these guys. But yeah, challenge accepted. We'll see if we can do it. So for the next 14 months, we stubbornly hung on to this position in negotiations. Like, we'll come over.

We're going to check all five boxes of your economic plan. But we're not sharing the economics and we're in charge. Eventually, there was a yes on the other end to that. And so we launched the Shanghai factory. The Chinese were great partners. We built that factory in 14 months. It usually takes 36 months to build a factory. We built it in 14.

And it became the largest Tesla factory in the world by a throughput basis and the lowest cost super rapidly. So it opened doors to us that were necessary and it ended up being a real success story too. You said it was about 14 months between when you first made the request and when they finally said yes? Yeah. And then it was 14 months after that, we had a factory. Wow. So during that 14 months, walk me through this. First, was it a matter of having a more persuasive argument or talking to the right people? You know, what were the key things that you did during that 14 month period? It's another really good question because the Chinese system, I had to learn. I did, like I was a student of their system. And their system is way different than ours. In the U.S., the top graduates come out of undergrad and they're going to Goldman Sachs or they're going to McKinsey or they're going to Google. There's a handful of companies they'll go to, but it's all industry. What I learned was in China, When those graduates come out, 50% go into industry, the other half go into government. And so you got the brightest of the brightest going into government.

And they're given a small neighborhood as their starter job. And their sole metric in that neighborhood is to grow jobs. And if they grow jobs, they can double or triple their cash salary. If they're good at that, then they get a bigger chunk of the city. And if they're really good at growing jobs in that bigger chunk of the city, then they get like a mayor's job in a city. They're good at growing jobs there. They get promoted and promoted and promoted until they're up on the. the Politburo. And the Politburo literally are the best job creators in the whole entire

system. So what it means is the entire governmental system is run off of one metric, and that's job growth. And so understanding that, then helped me understand who I was talking to. So if I was in Beijing, I was talking to the mayor of Beijing and the mayor of that territory is a huge city. There's eight mayors of Beijing. And you could understand that their whole motivation was for us to bring seven or 10,000 jobs. Same in Shanghai. Same in Guangzhou. and one of the things that you learn about the Chinese political system is that the promotion track comes through Shanghai. Like if you've run the party or run government in Shanghai, your next stop is at the top of government. And Shanghai was amongst the bidders, and we knew that they were probably going to merge the winner because those were the likely candidates for the next set of people who were going to run the country.

And they wanted to take advantage of this. So it helped me understand, like, not only who we were talking to, but what their motivation was. so that we could actually offer them something that mattered in return for what we were asking for. And so we were offering a lot of jobs and a lot of technology that was really attractive to the country. Right. So it sounds like the key is understanding incentives. Yeah. And understanding the system. And then understanding the culture. Because one of the core values of that culture is never to embarrass anybody. They call it shame. And so you couldn't in a negotiation take a hard line in public because you were shaming your counterparty in public.

And if you did, they would just shut down. And they may just exit the negotiations because it's that offensive in that culture. So, yeah, it's knowing the system. It's knowing what the rules are. And it's also knowing what culturally, you've got to make sure that you're getting right. How big was BYD at this time? BYD was this tiny little upstart at the time. Not so tiny, but they were a smaller company.

We knew them because Warren Buffett owned at that point 20% of that company because he'd invested early in BID. But they were dealing with like lead acid batteries, cars that could go less than 50 miles. It didn't seem like they were going to be a serious competitor. And boy, was that assessment wrong. What do you think changed for them? I guess from the outside looking in. They have a founder who is equally relentless as Elon.

And so he kept pushing battery technology, kept pushing his teams. And they eventually invented now today the world's ubiquitous battery technology called LFP. which is much cheaper and has higher energy density. So you get a car for a lot less money that can go further. And he and his team drove those breakthroughs. And that's what landed them in the position they are today. We're the best-selling EV manufacturer in the world.

Step one of this algorithm is identifying constraints. And some of the constraints, just to recap what we've discussed, we talked about the constraint of not knowing if a cell phone is in the driver's seat versus the passenger seat and how it sounds like you didn't let that constraint be a no. Right. And just kept thinking through the problem in different ways. Yeah. Until you could innovate around it.

Yeah. And the way that things were done in China, the 50-50, mandatory 50-50 partnership was another constraint. And you innovated a way around it. Before we move off of this step one of identifying constraints, one of the things that you talk about is identifying, on an assembly line floor, it's, identifying inventory pileups. Wherever the inventory is piling up, that's the symptom of where the bottleneck is. Exactly. How do we as ordinary individuals take that and apply it to our lives? If you want any process to go faster, the process can only go as fast as the slowest step. So consider like there are five people hiking up a mountain, that group only gets to the top

as fast as its slowest hiker. So what you want in a process that exists is to identify the slowest thing. The clue to that in factories is inventory piles up at the slowest point. Right. That's the point where it can't go as fast as everybody else. And so people just keep stacking stuff over it on the side. Right. And so that's how you identify where the constraint is. And then typically you would go in, the Japanese invented this problem solving technique, identify the constraint. So that's where the inventory piles up. And then get super creative about how you would bust that constraint. In other words, speed that slowest process up or speed the slowest hiker up. that's how I entered Tesla.

I was trained by the Japanese in this Toyota production system. And so I could go to the line and help like that. But what I discovered quickly was that that framework of constraints wasn't sufficient to drive breakthroughs. And if you really wanted big breakthroughs and innovation, then he had to do something else that was quite different. And that was to really question every requirement. That's the first step of the algorithm. them. The second step was then to map a new process and delete everything that the customer isn't paying you for, which turns out in most businesses is a lot. Like the customers don't pay

you for your back office systems. They don't pay you for your accounting. 65 cents on every dollar in companies goes to this stuff. And the customer's not paying you for it. So just eliminate it. Eliminate enough of it where it gets so painful that you have to add some steps back. Then you're like now poised to innovate because now you've got this. very simple thing that you can apply, speed up, and automate and really challenge yourself to like take the company or the process up to the next level or the product. All right. So delete everything until it gets so painful that you have to add some things back. You hear some people talk about that when it comes to they've got too much clutter,

for example. Yeah. I've heard people who say, you know what? I just took everything I owned, packed it all into cardboard boxes as though I was moving out of my home. Right. And over the next month. If I needed something, I would unpack it. Yeah. So I've heard those examples. I've heard people who overspend just say, all right, I just went through. I canceled every single subscription. I canceled every single out. And then if I really missed something, I could add it back. Yeah. It was like mass opt out. Exactly. And then you make something fight to get back in. Right. And so like in your example, I goofily do this with my closet once or twice a year. I move stuff that I haven't worn in a long time, either out of the closet or to the

far right edge. And then I'll come back and say, if I haven't touched that thing in six months, then it's gone. And so I'll then delete anything I haven't touched in six months to get rid of clutter. That's like a super easy way to do it. And essentially you're doing this in a business context where you're saying, I'm going to delete all this stuff and I'm going to make it beg to get back in the process. And some things do beg to get back in. They're like, hey, you can't forget me. You still have to bill your customer. So like you got to add that piece of the process back in if you've deleted it is something the customer didn't pay you for. A lot of the people who are listening to this are small-time entrepreneurs.

Yeah. Bootstrapped solo entrepreneurs who are sort of facing the opposite problem. They're tracking their expenses by inputting things into a Google spreadsheet because they don't have any kind of like software for that. Yeah. They're doing too many things manually. For those people, should they be applying this to their lives or should they be kind of doing the opposite? it should they be building out the systems and then stepping back and saying, did I overbuild? I think it depends on what your goal is. So let's say I'm a small business owner and I want to

get more profitable is a different decision than I want to grow. And so if I was a small business owner and wanted to get more profitable, I would say like, hey, one way to get profitable is to track expenses and make sure that I'm keeping track of where my outflows are. And I think is today you can use AI tools to do that. You can basically say, hey, look, here's a stack of receipts. I want you to process these receipts for me and turn it into a set of financials, and AI can do that for you. If you want to grow, though, I think you now have to start to think about to get this thing to grow. I need to have a stable platform to grow from. And a stable platform is usually systems for stuff.

By systems, I mean process. And so like if I'm going to double my business, now I'm going to have double the stuff coming in. I probably can't list ad hocs in that to an AI to figure out what to do with it. So now I'm going to have to start maybe to add resources and maybe people are really. on that to grow, but I want to do that as efficiently as possible so that I can be profitable as I grow. And so I do think you can apply this at early, early stages, depending on what's your choice is. Like I'm trying to be profitable, grow, or both, that can be a choice too. And then what is going to be absolutely necessary to be true if I'm going to like double the size of this business?

And that tells you where to work. You asked what is absolutely necessary to be true. What are some of the things that you've seen that people assume are necessary but are not. I'll give an example of this. So a lot of people assume that you need to market to grow and that you need to have a marketing budget to grow. As Elon and I were getting to know each other, he said, hey, there's going to be one challenge in this job that I don't think you've seen before and you might be surprised by.

And I said, what's that? He said, you have a marketing budget of exactly zero. And you have to double this company every eight months. Do you know how to do that? I said, no, I've never done that before. And he said, let me show you how. He said, basically, we rethink marketing because basically we can't afford it. He started questioning, like, do you really need to have a marketing budget in a company?

Now, everybody would assume the answer to that is yes. But he questions requirements right up front and says, is that really a requirement? Can you do this without spending money? If so, what would that look like? We would do things that would get us a lot of publicity, but not cost money. So an example of that is, like, we're going to introduce all-wheel drive for the first time. And we know that the free way to do that is to shoot that out of the canon of Elon's Twitter account. But at the time we started, he didn't have a ton of Twitter followers.

So we had to build it up and we built it up with space fans first and put a bunch of content that space people liked. And then we built from there into the Tesla fan base. So we could have him announce like a new feature in a creative way. It could be the video. It could be an event. It could be a bunch of different things. But we'd have content. and we would tell content-hungry distributors like the New York Times, Wall Street Journal,

influencers, et cetera, hey, you're going to get first dibs on this content. We're going to shoot it out of the Twitter can and can you repurpose it. And you can add your own articles in so you're getting the clicks. And so we would do an announcement. It would hit those channels and then just explode because people were adding their own links, passing them on, repurposing them. and we became part of then the storyline in the web. So if somebody was searching two years later for all-wheel drive EV, there's like dozens

of articles out there about Tesla's EV four-wheel drive announcement. It turns out that content is permanent. So it feeds search engines, et cetera. And we were able to fuel growth without spending a single marketing dollar. And when I meet companies now, or I sit on boards of companies that have large marketing budgets, one of the things I drive the marketers nuts about is, like what if we took your budget away? What would you do?

And I get these looks back of panic. Like, I wouldn't know what to do. And I say, I can totally relate to that because I had a look of panic once too when somebody told me I had to do this. It turns out you can't. If you actually start with the assumption you don't have to spend money, you end up in a very different solution. But if you start with the assumption you've got to spend money, you end up looking like everybody else. When you said shoot out of a cannon, the thing that I thought you were going to say was when you shot a Tesla into space. Yeah.

Yep. And that's an example of free publicity, right? So there was extra room on a SpaceX launch. We have this roadster sitting around that's collecting dust. We put like a guy in a space suit in an astronaut suit in the front seat and we shoot it out of the rocket. That was viewed worldwide hundreds of millions of times. That's free. That's putting the brand in front of people for free. It's not buying a sponsorship at a football stadium. It's not putting your name on the front of it. It's Jersey, it's just fun and it's free. And that was kind of our rules. Like, let's make this super fun so people like to consume it. But it's got to be free marketing for us. Right. And it's creative and it's funny. And there were, I'm a big fan of the hitchhiker's guide. There were a little, exactly, a little like these crigs on that. That guy and that roadster are still floating around space. So every once in a while, they'll whiz by a satellite that has camera capabilities and you get a glimpse of that, that guy sitting in that front seat of that roadster. Step one is question every constraint.

And step two, and I guess we've sort of touched on this, is delete every step. Before we move off of step two, I want to talk through another example of deleting unnecessary steps. And this is a step that most of us take for granted. You go to a restaurant, you've had your food, you've had your drinks, you flag the waiter to ask for the bill, and then you sit there for 20 more minutes. Right. And you went through that experience, as we all have, sitting at a restaurant and thought, couldn't this step get deleted? Yeah. So this was, I run a venture capital firm now, and I've got a number of partners that are with me in that firm.

And we're having dinner in New York. One of the guys said, hey, wouldn't it be cool if every restaurant was like a London supper club? His wife teaches at London School of Economics, so they're over in London. And I said, that'd be super cool. Because to your point, it saves like at least 20 minutes. at the end of a meal. And it saves this awkwardness of like, are you paying? Am I paying? People get an alligator arms. They're not like pulling out their credit cards. We are like, that'd be super awesome. So he says, I'm going to pursue this actually, because I wonder what's in the way, like,

why we can't get up from a meal after we're done and just walk out. What would need to be true? So he starts pulling the string on this problem and finds out that there's been a tech stack that's been built in the restaurant industry that totally disables this capability, not intentionally. It just is the way the tech stack grew up. Eventually, we solved this technical problem, which was in the core of that, which is, how do I know that it's you that sat down, Paula, in this seat, you ordered this stuff, and therefore here's how much you owe the restaurant. And it turns out that's a hard problem to solve technically.

And it's similar to like knowing whether or not you're in the driver's seat of a car. And so we solve that technical problem and we could tell the restaurant, Hey, Paul had a reservation. She sat down. She ordered this. And when she comes to our restaurant, she usually orders these things. And these are her favorites. This is the kind of wine she likes, et cetera.

So not only could we eliminate the check at the end of the meal, we could tell our servers when Paul sits down. Here is what she likes. So why don't you say, hey, look, we've got an off-manue item tonight. We know you like the chicken parm. So we've got a special treatment with vodka sauce tonight. Would you like me to ring that out? Like, this is a special thing for you. And I know you like this kind of wine and we actually have a new vendor.

We just got in and we'd like you to try this bottle of wine on us. And so they started to deploy this software that enables this. And it turns out that it increased repeat visit frequency by 60% and increased the check size by 20% because people felt known. And they love the convenience of just getting up and enjoying the meal and getting up at the end of the meal and walking out like they were a member of a club. And so that business is called Zumi. It started from that one simple idea and then has grown into now a real business for us. How does that work? So when you've got four people at dinner, sometimes all four are going to split the check.

Sometimes it's two couples, so they're splitting the check in two ways instead of four ways. Sometimes one person is going to pay for the entire group. How do you factor for that when you're doing this technology? Basically default stuff up front. So you can, as a user, you can default to. I will usually pay the whole check or I will split the bill. And here's my tip amount. Like I'll tip 22% every time.

So if it's just a couple and they're eating, they can just walk out. The tips included, everything is fine. If they indicate, hey, if I'm with somebody else, then as the wait staff, you can ask us, do we want to split the bill or not. I may opt to take the whole bill. We may opt to split it. And if so, they split it in the system and we get up and walk out. It's not perfect, but it's a lot better.

And that's another one of our mantras is don't let the perfect get in the way of getting better. We couldn't make it perfect out of the shoot to cover all those permutations of like who's paying. But we knew like with that one toggle that that would be good enough to get started. And it'd be way far ahead of what restaurants are able to do today. How is the server clued in? You know, oftentimes when the table asks for the check, that's the server's mental cue to just cognitive. close it out and say, all right, cool, I can stop thinking about that table. Right.

And I can shift my focus to these other tables. Yeah. How does the server get that cognitive clue? So the server typically will come and say, hey, like you've wrapped up your meal, would you like dessert? And would you like a coffee? Would you like a tea? They're doing the closing of that ticket, essentially. And if the party says, hey, we're all set.

And then the server says, okay, well, you know you've got the option to get up and leave. You have to wait for the check. Would you like to do that tonight? Or would you like me to bring a check over? Do you want to split it, et cetera? So that's the, as the server's wrapping up, the last question they ask is, do you just want to get up and leave or would you like to pay the check in a more standard way? Oh, that makes sense. Yeah, super easy.

Yeah. Yeah. And it turns out for the restaurant, it's a real fine for them because 20 minutes per table means an extra turn of tables in the restaurant every night. Right. Yeah, because you usually get two seating. So you're getting 40 minutes of free time on a table. So now you can actually get an extra half a seating to a seating. Right.

So that's another perfect example of deleting every single. step. Yeah. And questioning assumptions. Like, do I have to have a check at the end of the meal? Yeah. I've worked in the past with developers who really overdesigns for edge cases. His position, because even I in the past sitting on like hour three of a Zoom call have been like, dude, we are really over designing for the edge case. Can we, can we not? Yeah. And his position has always been, look, if we don't do this design up front, then you as the CEO, your time is going to get bottlenecked, like you're going to be the bottleneck for having to make individual decisions about every individual, you know, exception.

Yeah, exactly. Yeah. And so, again, my brain goes back to small business where typically you do have like an individual who becomes the bottleneck. Right. How do you not overdesign for edge cases, but also not have the situation where somebody is a bottleneck? First of all, we had this understanding amongst each other.

and we do today, in terms of teams I work with, that the old adage that every battle plan is perfect on paper until it meets the face of the enemy. And then when you're actually in battle, like the whole plan goes out the window because the enemy's doing things that you didn't think they were going to do. The way to prepare, I think appropriately, is to decide what needs to be true about this product. So I'll give you an example. I was talking to Steve Jobs' longtime chief of staff. His name is James Higga. And James is absolutely brilliant. You can imagine how brilliant you need to be to be Steve's right hand.

I said, give me an example of how you guys developed product. He said, oh, we would do the definition up front of what absolutely had to be true in the product, and it could only be two or three things. I said, give me an example. He said, I'll give you two examples. The iPhone, no buttons. No keyboard, no buttons. That had to be true about the iPhone, which meant that the engineers had to go invent glass you could touch,

keyboards that were actually responsive and accurate, that sort of stuff. He said, but even a clear example is when we developed the iPod. He said, get into the way back machine, go way back to your first iPod. He said, Steve and I sat in a room for almost a week with 50 different things, features that we could have had on that thing. And we emerged at the end of the week with two things that had to be true about the iPod. It had to hold a thousand songs, and you had to be able to get to the song you wanted in four seconds. That provides absolute clarity for engineering teams. You cannot be working on edge cases now because you only can be working on.

on those two core things. And it turns out that the things that enabled a thousand songs and getting to them in four seconds didn't exist at the time. There wasn't a disc drive that was big enough and dense enough to hold a thousand songs and not be huge. And there wasn't an operating system or chips that could go fast enough to search through those thousand songs and find your song within four seconds. All that had to be invented. So that meant as engineers, you weren't starting planning on edge cases. You were starting with, I got to get the core right, which means I to invent solid state disks, I have to invent a fast operating system, and then I have to invent a user experience of a circle wheel that is the fastest way to get to songs in four seconds.

All that stuff had to be invented. So I think the short answer to your question is, if you're an engineer or you're working on new product, determine the two or three things that have to be true and nail those things. And oftentimes, unless you're inventing around those two or three things, your business is super vulnerable because anybody could come in and copy it or enter that business. But it turns out those two or three things are super hard. Now you've got a moat that's going to be hard to get into. And concentrating on those two or three core things doesn't allow you to think about age cases. So you can't be over designing up front.

And the second principle we would say is introduce that product to the market as fast as possible and start the feedback loop. Because a little bit like the battle plan, the market is going to have immediate feedback for you about what matters and what doesn't. And so then your engineers again are working on the core things that matter to the customer because now you've got a feedback loop. But if you delay that market entry because you're working on perfection and answering every edge case, you're a delaying the feedback loop and you're likely building stuff that's never going to be utilized. And that is the definition of waste. And nobody wants to waste time. It's certainly not capital in an early stage company because those two, things are the biggest limitations you've got in a small company as time and capital. So it keeps

everybody away from edge cases. And that is absolutely critical in our startups. And we keep like a hawk eye out for edge case type people. And then we say you haven't really either defined the three things that really matter about this product or you haven't committed to those three things. Because if you've defined them and you've committed to them, you don't have time for edge cases. I want to move to step three. The step is technical. called what simplify and optimize, but I like to think of it as the be so great they'll talk about you at dinner. Yeah.

Before we move to that one, though, just to kind of spice things up, there's a funny story that you have. And I just don't know where else to tell the story, but I just want to trot it out here. I read about you in Walter Isaacson's bio of Elon Musk. I didn't remember your name. I just remembered you as the guy who laid on the floor in a dark room in order to have something conversation, some important conversation. Tell us that story. Actually, Walter called me when he was writing the book and said, can I tell this story? And I said, this is such a personal story. I think only Elon and I and his chief of staff know it. And so I said, Walter, like, I got to call Elon to make sure he's cool

with me telling this story. Because it begins with Elon is really struggling with some really serious mental health issues. And I called him, said, do you want me to talk about this? Because this is really personal. To his credit, he said, yeah, I want people to know that if you're suffering from a serious mental health issue, you can still achieve stuff. It's not a showstopper. It's not the end of the road for you. So he said, please tell the story. So here's the story. So Elon was really struggling in a deep depression. One of the ways he coped with that was he would close the doors of a conference room, turn the lights off, get on the floor. The challenge was this particular afternoon he was dealing with that. And we had an earnings call. CEO's got to show up to a

public earnings call. If you don't show up to the public earnings call, there's going to be a lot of questions about the company and the stock, and there's a lot of potential market loss of market value. And so the team came to me and they said, hey, look, you're the one person that we, that I think he'll be comfortable with this. Can you just go in there and get him on the earnings call? So I walk into this dark room and I see him laying under the table and I just laid down next to him and said, how are you doing? He said, not good. And we just started a conversation. where it generally was, hey, I know that you're feeling like you can't do this, but I'm telling you, like, the whole business depends on you getting on this earnings call. So how can I help you get out of this room?

Eventually, after, I don't know, half hour, an hour, he was ready to come join the earnings call, thank God. The reason Walter wrote about that, I think it is because he wanted to show people, like, sometimes we hold really accomplished people up on pedestals and assume they have no. problems and they have no obstacles themselves of like achieving what they're achieving. And both Elon and Walter wanted to say, no, that's not really true. There are people that struggle mightily that can still accomplish huge things. Yeah. Thank you for sharing that story. How was that for you? I mean, you're you're an operations guy. You build systems. You build processes. You're not, you're not someone who's like, hey, buddy, you're feeling vulnerable right now. How can I help?

Yeah, I felt like totally inadequate. Because to you're, I can walk in a factory and I can look at a process and have a pretty good jump on how to solve that problem, where I can look at a balance sheet and try to figure that out and look at a, I can look at a set of code and read that. But I don't have skills in this area. So like the big thing I felt in that room that day was totally inadequate. It gave me an even deeper appreciation for people who do that work because they have a skill set that is really important. And it's a skill set that I don't have. And so for me it was like super stressful because I, I, didn't even know how to approach the problem. And the other layer to that problem is not only do you need high EQ to be able to talk to

to somebody who's in the throes of a mental health crisis, but also there's a hierarchy, right? He's your boss. Right. How did you navigate that? Well, I consider him, first of all, I consider him a human, that situation, like he's a fellow human, he's a friend, and I want to help. The hierarchy was kind of out the window.

I just had this instinct by laying on the floor next to him, then he could feel like I was, like we were equals at that point. We're just fellow humans. There's a humility in that. And also an empathy. Like I just wanted him to know like, I'm feeling for you. And so much of them I'm just going to lay down next to you. Kind of stemming off of this,

one of the conversations that I've had with many people over the past several weeks, we've had several guests on the show who have talked about the skills that people are going to need as we move into an age of AI. Yes. And the recurring theme is EQ. As we go into an AI future, it is that emotional connection that's going to matter most. As you've just said, you're an operations guy. You're not trained in EQ, but it seems like in the moment when it mattered, you demonstrated it. In a really awkward, I think, in a rough way.

yeah, like nowhere near what a professional could have done for sure. But I do agree with some of the folks you've talked to, Bill Gurley and others. Like, I think EQ is a skill that really matters because it's really, really hard to teach machines to do things like drive a car. It's really, really, really hard to teach them EQ. We can teach tone and we can teach language, but that human connection is a really unique thing, especially as it comes to designing products that work for people, and hospitality and elevating people's potential. Like, that's all human stuff that comes from some combination of EQ, empathy, humility.

There's a lot of like ingredients, I think, in that stew that enables somebody to really be uniquely competitive in a world of automation and AI. Do you have any recommendations for people listening to this who want to strengthen their EQ if it doesn't feel natural? That's a really good question. The first reaction I have to that is, I mentor that I had in college. He would say, if you want to get out of your own bubble, go serve somebody. He was instrumental in a number of us like tutoring fourth grade kids to learn to read in inner city Chicago or going to really poor areas of Latin America and building orphanages or something.

He's like, if you just start to serve somebody, you're going to get out of your own skin, your own limitations, your own psyche. and you're going to have to, like, pour yourself into discomfort in serving somebody else. And that will grow your EQ. And so that's the first reaction I would have is somebody said, how do you grow ET? EQ? How do you grow EQ? You serve somebody. That's going to get you out of your own headspace into somebody else's.

Actually, EQ sort of leads us perfectly to step three of your five steps in the algorithm, because step three, which is the step of be so good they'll talk about you at dinner, there's an EQ component to that as well. Yeah, definitely. We wanted people to understand the Tesla culture in a sense. And we would talk about like wowing people, surprising people, delighting people, all this stuff. But we wanted to have like just a better phrase for that. And so the team came up with make them talk about you at dinner tonight, which meant if I was

standing in front of you as a customer, now I need to get to know you. I'm putting myself in your shoes. Hey, I've had my car breakdown. It's not going to be fixed tonight. What would I want in that situation? I wouldn't want, hey, here's a card called the rental car company. I would want somebody to say to me, I'm giving you a brand new car to drive as long as you can drive as long as you want while we're fixing your car. Here's the keys.

Have at it. No questions asked. And so when we put the principle in front of people like make them talk about you at dinner tonight, they started to think about, okay, how can I like totally blow away this person that is sitting in front of me with either like a wild surprise, kindness, empathy, something. And so that phrase then led to a whole lot of really cool stuff happening for our customers. Right. There was one person, they were having a baby. Yeah. Can you tell us that story? Yeah. So there was a customer of ours who is, they had a Model X. The mom in the house was

pregnant and she went into labor and they went out to the Model X and it wouldn't start. So they had to call some friends and neighbors to get them to the hospital. On the way of the hospital, the father called the local Tesla operation and just was irate. He's like, guys, I depend on your car for a lot of things, but this was the one moment I needed your car to work. I'm taking my wife to the hospital. She's in labor and your car doesn't work. He happened to get the service manager for this area on the phone.

And the service manager was hearing this. And so the service manager said, I am so sorry, I'm going to bring a brand new Model X to the hospital for you. And so once you have your baby, you got a brand new car to drive. I'm going to pick up your car. I'm going to get it fixed. We can swap out the cars whenever it's convenient for you. So he goes and drops off a car at the hospital. He goes, picks up the broken down Model X at the customer's house and notices that it's a house full of kids home with grandma.

who's watching the kids. So he thinks about the situation. He decides to go to the grocery store, comes back with groceries and dinner for the kids and for grandma, and then picks up the Model X, goes back and fixes it. A few weeks later,

I get a call from the father whose wife was in labor. And he said, I just have to tell you this story. Here's what happened. My car broke down at the moment that I needed it most. And so I'm listening to this on the phone and I'm like my stomach's churning, getting tight.

And he tells me then the story of what this guy did. Like he dropped off a new car. He went to our house. He saw our kids. He immediately got them groceries, got them dinner. The grandmother couldn't believe it. Called us. He said, you wouldn't believe what just happened.

But this guy picked up the car. But not only picked up the car, he left a bunch of food for us. And we're going to be fine. Don't worry about us while you guys are at the hospital. And this father said, I can't thank you enough for this person. And I just wanted you to personally hear from me. like how much this meant to us and how good an employee you have. My next call was to that employee.

And I said, I just heard the story. It's unbelievable what you did for this family. I said, how in the world did you think to bring them groceries? He said, well, you tell us, make them talk about you at dinner tonight? I wanted them to talk about me at dinner every holiday. Do you remember that guy who fixed our Model X and brought us food? And those stories would happen all the time, like our head of mobile service, her name was Leah and Leah got this idea to put espresso machines in all of our mobile service cars

so we'd come and fix your car in your driveway and we'd offer you an espresso like just surprise people delight people and that sort of stuff happened all the time based on this principle make them talk about you at dinner tonight it has Tony Shay Zapos vibes kind of does yeah it kind of does and Tony was in that era where he was doing that kind of stuff too and he was inspirational to me I read all this stuff Tony was doing at Zappos. And Nordstrom had the same approach. You know, you could bring in a product. You didn't even buy from Nordstrom.

You could return it. And the Nordstrom people would smile politely and let you return the product. There are just a handful of examples of this. And we wanted to be one of those handful. A lot of the people listening to this are e-commerce or, you know, they have, they're small business owners that operate entirely digitally. You know, maybe they are graphic design. But their business is entirely digital.

How can they take this principle and apply it in a digital small business context? I think like if you consider a designer or e-commerce, like just think about how you could surprise your customer. So like in e-commerce, what could I throw in the box that is going to be super fun and literally to get them talked about me at dinner tonight? Like you could do something pedestrian and you could drop a sticker for your business in, but sort of everybody does that. Right. And so I'd want that owner to think about no, no, no, no, no, go. step beyond the pedestrian thing that everybody does. Like, what could you do to like really wow somebody? They open that box and they go, oh my gosh, I love this company. Think about that.

And then that's probably going to with your team or if you're just a small business owner by yourself, a solopreneur, if you think about that long enough, you will come up with something to try. It doesn't have to be perfect at the start, but just try it and see if you can find yourself on a path to like blowing people away when they open that box. One more question about the Be So Great They'll Talk About You at dinner. That phrase reminds me of Steve Martin says, Be So Good, they can't ignore you. Did that phrase come from him? No.

No, I've never even heard that phrase before. But it's a pretty good corollary to, I have a big Steve Martin fan. I hadn't heard that quote. Yeah, yes. When people would ask him how to become a famous comedian. Right. His answer to how to be a famous comedian is, be so good. good, they can't ignore you. Yeah. And Seinfeld has a twist on that. As Seinfeld, as you probably know,

would say, be so funny that you don't have to swear to make people laugh. Right. And so like, he holds himself. Like, there is no vulgarity in his, in his routines, because he's like, I have to be that good. Like, I can't rely on a cheap shot to get people to laugh. I have to be that good. Right. Yeah. So I guess the online equivalent of that would be not relying on, like, quote unquote, hacks. Yeah. Short cuts. Or kind of to our earlier conversation, not even relying on paid marketing. Right. Yeah. Yeah, exactly. Nice. All right. So step four, you talk about cycle time. First, for people who've never heard that phrase, can you define what cycle time is? Yeah, cycle time is from the start of a process to the end of the process. So let's, I'm in a laundry business. The cycle time starts with the customer drops off their clothes to the time that's the cycle time. So you measure that entire elapse time, period, basically. And cycle time is just a fancy way to say speed. What you're trying to do is like measure how long a process takes and then make it take a lot.

less. The way that you prove to yourself, you've optimized the process in step three is if you can run it fast. And if you can run it fast and it works, that means you're getting high quality because quality issues slow down a process. So if you're not slowing it down with quality issues, now you've got good quality coming out. And then the second thing that does is, the faster the process goes, the more throughput you get, the more things that come out of that process. The more throughput you get, the lower the cost is. So you get low cost, high quality through speed. It turns out you can have good, fast and cheap. But within cycle time, and so again, I'm thinking about the small business. And within that cycle time, I guess first there's the delivery of the service itself, the service or product itself. And there seem to be, when you're thinking about cycle time, just certain, especially with a limited team, just certain constraints around, let's say you've got three or four people on the team, the number of hours that you and your fellow colleagues can work.

And it sounds good to say move faster, but how does a person actually do that? That's a good question. So you can structure this and find a way to move faster is the good news. So I discovered this in, of all places, an auto repair shop. So the definition of a small business. At the time, we had this theory that we could really professionalize auto repair. And so we started by owning one shop. Our starting point is for really damaged cars, it takes 18 days to repair them.

We're like, how could we get that down to one day? And it turns out when you analyze those 18 days, 99% of the 18 days, the car was sitting there and nobody was touching it. So we decided to concentrate on something I call touch time, which is during that 18 days, how much did it get touched? Now, in an auto repair business, you give billings on every car. And the billings are the number of hours. The technician worked on the car.

And so you see this on every repair. And what we found was, is although it was an 18 day cycle time. So that's between the keys that the customer drops off to the keys they get back with the fixed car, 18 days. We looked at the average billings of hours, six hours. So we were taking 18 days to do something that we only touched for six hours. Then the question was, how do we get rid of all that wait time? So this isn't just speed it up.

This is, let's just get rid of that wait time. If we drop all that wait time, now we're down to a same-day repair. So that's how you like attack cycle time. Right. But in that case, I mean, so a week of that was they had to order a part. Exactly. I'm thinking about that in terms of plenty of people who are listening to this are also rental property investors. Yeah.

You see this happen and, you know, you're doing a renovation on one of your properties. Yeah, they've got to order some part and it's going to take five days for it to come in. Yeah. I'll attack it both from the car repair and like the rental property owner. What dawned on me one day as I was watching cars get fixed. When a customer dropped a car off, it was the first time that auto shop had ever seen a repair. They're writing repair order from scratch. They're ordering parts.

The parts often aren't right. And it occurred to me like, we fixed 10,000 of these cars this year. If people described it was what's wrong, we know what parts need to be ordered. So we could have asked that on the phone. Paul, what's the symptom? Well, I've got this knocking and I've got this and I've got that. Okay, cool. We know what that means in terms of parts.

We'll pre-order the parts before you show up. I would say the same thing on property management. Like, is this the first renovation that's ever been done by humans? No. If you're going to renovate a kitchen, what are you going to need? Appliances. You're going to need wiring. You're going to need countertop materials.

You're going to need cabinets. All right. So why don't we think about that up front? And if we're renovating 10 units, why are we not pre-buying those? You can pre-buy those on terms. But you're not going to have the excuse of, oh gosh, we just ordered the countertops, and now it's going to be eight weeks before the countertops come in. Know that before you start the job. And that was our mantra and honor

repair. Know it before you start the job. And so then we would ask people like, what can you know before the car shows up? Make it a game. Oh, I know the parts I need. I know the technician I need because it turns out that he or she is really good at fixing this kind of thing. And if you know before, then you can really shrink cycle time. But you've got to act like you've seen it before. Right. Yeah. A small property owner has seen a lot of renovating. So they ought to be able to get way ahead of this and really collapse the cycle time of renovation. Right. Right.

What happens when you open up the guts of the house and then you discover a new problem? Totally. Car repairs that way too. So you open up the problem and it turns out it's a lot more complex than it looked like from the outside. Right. And so therefore, like in today's world, you can rely on data for that. So you can say, okay, 10% of the time we open the walls up, there's other stuff that has to be fixed. But it's usually the same darn thing.

So let's just examine our data. Let's examine data of other renovations, the similar renovations, and what are the change orders that look like, or that are a part of that. And then you say, okay, we're just going to, you know, we're going to overorder the parts up front. We're going to over order for change orders. And the change orders usually look like this. And so we'll have a little too much stuff and we'll just return that stuff at the end

versus suffering the delay and the repair or the renovation. Yeah. Yeah. So it's just a way of thinking. And it's kind of fun to like have these problems and say, like, how would I get in front of this? How would I have everything I need so that I do not stop once I start that job? Right. Right. And AI could help a lot with that too, especially in terms of or getting some aggregate information of what are some of the most common change orders. Exactly. You know, we're about to do X. What are some of the most common unforeseen Y's that emerge from X?

Yep. Can you tell us a story of Lulu Lemon and how they compressed their whole cycle time down to one-fourth of what it used to be? It took us at this time, 60 or 70 weeks to go from product concept to on the shelves. It was 52 weeks in a year, so that means it takes more than a year. The Canadian Olympic Committee came to Lulu Lemon and said, we'd like to award you the apparel contract for the Olympic Games. That means you're going to outfit all the athletes, able-bodied and para. And so you've got designed multiple collections, four collections, men's, women's, able-bodied para. And, oh, by the way, the Olympics are eight weeks from now. So you can imagine the panic that sits in like, do we even take this contract?

Because it takes us 60 or 70 weeks and they're really given us eight. We decided to take the contract because it had been with a competitor, Roots in Canada for a number of years. We decided to take the chance and do it. And so the CEO at the time took a team of ninjas and said, the rules are suspended. You guys can do whatever it takes to get this collection done. And the whole organization was saying, you can't do fast and do it well. The reason it takes us 60 weeks is because we thoroughly test the dyes on every product. And we do like six or seven rounds with the weavers and with the manufacturers to make sure that we get the color right.

And then we do a bunch of sewing tests to figure out if we get the seams right. And so this stuff takes time. You shouldn't be doing this. But this team and ninjas didn't take no for an answer. They said, okay, if that dying process takes that amount of time, why? Well, it's because we're doing it in Vancouver and the machines and the dyes are in Vietnam. And so it takes forever to send samples back and forth. So why don't we just move the designers to Vietnam for the next couple weeks?

They can sit beside the people who are doing the dyes, and hour by hour they can change. Same things with the seams and the fabric and the weave. And so it turns out that they delivered that apparel within six weeks. And so they proved they could do it much faster just by doing it differently and kind of suspending the rules. But the question was, did they do it well? And so the athletes in the Olympics, each country has kind of their own homegrown team that are a company that the designs. So like in the U.S., it's polo. In Italy, it's Prada.

And at the end of the Olympics, there's this little fashion event that's kind of like the Grammys. Everybody votes for who had the most attractive collection. And that year, Lulu Lemon was voted by all their pure fashion companies as having the best collection at the Olympics. So they proved that they could not only do it way faster, they could do it at a super high quality level. And it sounds like the thinking process to begin that was, it sort of goes back to step two, just deleting everything. Deleting like crazy. Yeah. Deleting everything and starting from scratch.

Right. And cycle time forces you to do that. So it makes sure that you got through step two and step three. Cycle time is kind of the chief arbiter of like, have you done your work. Yeah. How do you think about that if you have multiple concurrent things? that you are making. So I'm thinking through for myself, as we're sitting here talking, I'm thinking, okay,

what is the cycle time of a podcast episode? Yeah. And it's hard for me to even wrap my brain around that because there are always so many concurrent episodes in production. I frankly don't know how long it takes to get from concept to publication. I think most people don't. Like most people haven't ever measured the cycle time of steps in their business or or in their personal life or whatever.

So if you have somebody on your team that's structured or if you can get into your own mind space that's structured, you could break down the steps in your business. So I would just guess a front end step is booking, like what talent do you want on this podcast? And then it's research. Like what am I going to ask this person and what kind of content's going to be interesting to my audience?

I've got to do research. I got to writing. I do prep. I do scheduling, recording, and then I do editing. And then I finally do release. And you line that process. up and you start to ask yourself, okay, what's the total time end to end on average? I can look

back at my calendar. Like, when did we start talking to this particular, or talking about this particular talent? And when did the episode air? And that's my total cycle time. And then I could break down, how much of that was in booking? How much of that was in research? How much of that was in actually scheduling, recording, editing, release? And you start to see, oh, there are opportunities in these buckets. But you can only start that if you're actually measuring it. Right. Yeah. There's some shows that are new shows, right? Yeah.

And so they necessarily want to do just in time recording because they're talking about what happened to that week. Right. There are other places. Well, I guess Lulu Lemon would be an example of this. Seems like they took pride in the length of their process. Yes. Because they equated length with quality. Quality.

Exactly. To what extent is that a valid equation, the length as a proxy for quality? So I would say, like, you have to produce the same. amount of quality at the same cost in half the time. And then people can't think about like incremental like little changes because you've given them a big goal. And this is something Elon's known for too. And the reason he gives these huge stretch goals and promises is he wants to force quantum thinking versus like little incremental improvements. And so if you say like yeah, you got to keep quality the same, but now half the time or in Lulu's case quarter the time, how are you going to do that?

and people then get out of this mentality of like that's the status quo process that I know. There's no way in the world that can deliver same quality at a quarter of the time. So now I have to think completely differently about it. But you can start with the simple tool of, okay, let's measure the cycle time of our current process. And let's just measure this touch time. And the quickest hack is let's get rid of all the wait time. And some of that stuff is easy to get rid of and some's hard. But if you get rid of the wait time, you probably got 90% of the problem done.

Right. Yeah. So it's not like random and all that hard when you start to break the problem down in the right way. Right. It seems like a lot of this thinking process. He's basically asking the right questions to force the right type of thinking. That's right. And setting goals ambitious enough where you're going to get quantum thinking versus incremental thinking. Right. Right. When it comes to incremental thinking, though, you also hear the other side of the argument that you hear about the 1% margin for improvement. there's a story of Dave Brailsford, who headed the 2012 British cycling team to victory. What do you think about that?

Those examples, so just to put it in context of what you're talking about, there is this school of thought that if you're improving 1% every, say, month, those little improvements over time add up to big improvements. Right. The aggregation of marginal gains. Exactly. Yeah.

You nail it. But marginal gains are used in world-class athletes who are the top 1-100th of a percent of us. So if take cycling in the Tour de France, the difference between first place and last place in the Tour de France is 7%. That's the time difference between the person that finishes first and the person that finishes last. So these are 160 of the best of the best of the best in the world that race every summer, and there's a 7% difference between first and last. in that context, half a percent gains and one percent marginal gains matter.

Essentially, you're creating a hundred percent advantage versus the best of the best in the world. For the rest of the world that is not at the Olympic caliber or World Cup caliber or World Championship caliber, 50 percent gains are possible. But for those athletes, 50 percent gains aren't possible because they are at the very edge of human performance. So they have to think about half percents to push that edge. edge of human performance. But like me, if I got on a bike and I average 18 miles an hour and I got to average 30 miles an hour to ride in the tour to France, 18 miles an hour, 50% improvement

is 18 plus 9. Could I teach myself to ride at 27% or 27 miles an hour with coaching? Probably could. So I could get a 50% gain. But Tadipagacha, who's the best writer in the world right now, cannot get a 50% gain. He can get a half percent gain. So the marginal gains works for the best of the best, the most sophisticated, the most well-funded. But for the rest of us, we don't have to live in a half-percent marginal gain world. We can live in a 50% quantum leap world. Okay. That makes sense. Yeah. Interesting. Okay. So aggregation of marginal gains is for the edge cases. I agree. Yeah. It's for the fat tail. It is. And not for the middle of the bell curve. Exactly. Yeah. The rest of us can aim higher. And we can achieve on a percentage basis more.

Wow. Yeah. Let's talk through the fifth step, the fifth and final step, which is to automate last. And this is also the opposite of what you often hear, where people talk about, you know, eliminate, then automate, then delegate. Yeah. We would say eliminate, optimize, automate, automate, and the very last step. But the reason is because automation becomes a form of concrete that once you pour it over the process, you don't change that process unless you get a jackhammer out. Like it freezes the process in time.

We learned this in the production of the Model 3 where we over automated the Model 3 production line. That automated Model 3 production line never worked. It never produced a car. It was scrapped. And we had to start over and manually produce cars in a tent. It turns out that most businesses that start super small, start manually, and then they automate.

And some of the most famous businesses in the world started this way. And this is the way they actually teach entrepreneurship now at Stanford. They tell you to come up with an idea and then run it manually first. Because Amazon, when they started, put up a website to order books, but they had no fulfillment capability on the back end. They just wanted to learn the process. So they would get an order on the Amazon site and they would run down to a local retail bookseller, buy the book at retail, put it in a box and ship it to the customer.

And in that process, they learned the distribution model. similarly with DoorDash, five computer science graduates at Stanford put a PDF of menus up online with a phone number on the bottom. So you couldn't even like order online. You would call that phone number.

It rings in their dorm room. They would go pick up the food from a local restaurant, buy it, deliver it, and then start to develop this manual process. Big businesses like Amazon and DoorDash started manually. we flubbed up Model 3 by starting automated.

We couldn't even produce a car. So we had to go back to the first step, which was do it manually and optimize the process steps and then add cycle time and then automate. This all came from a post-morning than we did. Like after doing a face plan on Model 3 production, we said, how did we get here? Like, we almost killed the company. The answer was, we automated first. Like, we knew not to do this, but we'd somehow let ourselves do this.

So that became then the last step of the algorithm. which was you've got to automate last. And we got to hold ourselves to that because we almost killed the company when we didn't. And example after example will lead you to this conclusion that even though like this sounds totally counterintuitive coming from people who are software people because that's who we were at Tesla, it was like I want to put my hands on the keyboard and I want to figure out how to automate this. Turns out to be the wrong answer.

I really admire that DoorDash founders who still talk openly about this. Every time they try a new product, it's all manual. And these are people whose fingers naturally go to. keyboards to code and automate. But it turns out that's not the first step. That's the last step. It used to be that automation would take some time because hiring coders was expensive. Yeah. That friction, that cost friction is no longer there. Now anyone can vibe code. Right. And so how, as we move into a future in which coding is often more increasingly the first step that people take when they've come up with a new idea rather than the last.

How do we square the fact that society is sort of moving in this direction? I think generally when society is moving in a direction, I do not want to be a lemming. So if society's moving in a direction, I start to think about like, what's the contrarian side of this argument? Like you said, you can vibe code anything. But if you haven't figured out, like what the product needs to do, what it has to look like, all automation is doing is getting you to the wrong. answer faster. And that's a really dumb thing to do. This is applied in venture today,

maybe the most successful venture capital firm in Silicon Valley is a firm that very few people have heard of unless you've been out there and that's Sutter Hill. Sutter Hill invented little companies like Snowflake and Prism and Pure. They have this rule that every one of their startups has to talk to more than 200 customers before they put their hands on the keyboard. the purpose of that is simple. Like you want to create a product that the customers want. But if you start creating product before you know what they want, you've created a bunch of waste.

You've wasted your time. Again, you've wasted your time and capital if you're paying something to do it. And you haven't solved the customer's problem. So you're not going to have a business. And Sutter Hill's perspective on this is you should really, really, really, really, really know the customer's problem. And it takes 200 customer interviews to really know that.

And you could really, really, really know what features they're going to pay for and then build only those. and to the point of our earlier conversation, do not code edge cases. Get that product out and now confirm that what they told you in 200 interviews is true. And oftentimes the 200 interviews hasn't revealed everything. So get the product out, start the feedback loops so they can then do rapid correction. If the most successful venture firm in Silicon Valley goes manual first and automates second, I think you're pretty safe following that path.

Two more questions. One is a lot of people say that Tesla truly is an AI company. Would you agree with that statement? I think that's the commitment that Elon's making right now. I was thinking like just several years ago, you could say Tesla is a software on wheels company, but now it's very much emerging as an AI company because Elon has said, hey, the future of Tesla is in two forms of robots, robotaxies and humanoid robots. and both of those are powered by AI.

So I think it's fair to say that Tesla's an AI company now. And then final question. Do you believe humans will become multi-planetary? I hope they will because I like a lot of people grew up on science fiction. And the fact that we have such a huge universe with so many trillions of galaxies means that the odds of there's something else being out there would be really fun to explore. And so I think multi-planetary is a very cool idea. Yeah. Do you think it'll be in our lifetime?

I hope it is. I hope I'll have to see it. Would you go to Mars? I wouldn't be first. Elon has said this. I wouldn't be first because the odds of survival are so low. But once the odds of survival becomes acceptable, maybe. Yeah. Yeah. He said, I want to die on Mars just not on impact. Exactly. Yeah. Yeah. Nice. Well, thank you for spending this time with us. Where can people find if they'd like to learn more?

You can find the book on Amazon or at your local book retailer, but you can also find me on LinkedIn. Thank you, John. three key takeaways that we got from this conversation. Key takeaway number one, question every assumption because most quote unquote rules are not real. A lot of what slows you down, what slows you down in business, in your career, in your negotiations. That slowdown comes from assumptions that many people have never questioned. And the people who move fastest are the ones who stop and ask, really, is this actually required? Or can we delete this? Can we shrink it down and make it simpler? Ask yourself, is this a requirement of law, of physics, of safety? And if it's not,

then it's a candidate for deletion. We looked at how complicated the car buying process was online. And the most complex part of the car buying process is getting a loan release. And those documents are like 12 pages long. Right. And so we asked how many of these paragraphs in these 12 pages are the requirement of law or regulatory bodies? And the answer that came back from our lawyers after they analyzed it was none. Question quote unquote requirements and see how much you can delete. That's key takeaway number one.

Key takeaway number two. Speed, especially speed in decision making, is a huge, huge advantage. You don't need perfect information. you need fast decisions. And the faster that you act on data that is good enough, the more you compound advantage. You know, compounding interest is the eighth Marvel of the universe, whatever that quote is from Einstein. You want to continually compound your advantages. And the faster you move, the more likely you are to do that, the faster you speed up that compounding clock. There's one thing I want you to know. And that is the thing that matters most to me is speed and

decision making. If we make decisions faster than our competitors, we compound advantage against them. So speed here is really important. And you won't get everything right. And that's okay too. And he said, but what you did in that moment was you took data in, you made a decision. So your speeded decision delay was almost zero from receiving information to making the call. He's like, just keep doing that. And what I found out was that's, that was the Tesla culture. So it wasn't this ethos of ask for forgiveness, it was an ethos of decide at speed. With the information that you have at hand, make the best decision you can. Unless it was going to violate the law or

cost us millions of dollars or violate safety principles that we had, just make the decision. Go. Finally, key takeaway number three, growth comes from fixing the obvious bottleneck. A lot of people spend a lot of time looking for new opportunities, rather than do that, look at the bottleneck and fix that. Look at what's already working and fix the step where things are getting stuck. If you want any process to go faster, the process can only go as fast as its slowest step.

So consider like there are five people hiking up a mountain, that group only gets to the top as fast as its slowest hiker. So what you want in a process that exists is to identify the slowest thing. The clue to that in factories is inventory piles up at the lowest point. Those are three key takeaways from this conversation with John McNeil. His new book is called The Algorithm. It's the hypergrowth formula that transformed Tesla, Lulu Lemon, General Motors, and SpaceX. Technically, it's a business book about how to scale organizations, but truly it's a book for anyone who wants to solve problems by simplifying.

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