Courtney Hohne is Chief Storyteller at X, the Moonshot Factory. She’s steered X through its first decade of innovation, telling the stories of iconic moonshots like autonomous cars, delivery drones, smart contact lenses, carbon-neutral fuel from sea water and Internet-beaming balloons.
In this episode of the podcast, she joins Daniel Gross to discuss the early days of Waymo and Loon, the challenges of commercializing clean fuel from sea water and what it would look like to pitch and produce self-replicating nanobots at X.
Pioneer Podcast Episode #4
What is a Moonshot
Daniel Gross: Hello, hello. How you doing, Courtney?
Courtney Hohne: Hey there. Good morning.
DG: Thanks for being with us today, extremely excited about this. This should be very inspiring and a nice shift from the traditional conversation in Silicon Valley around how to rent-seek on simple pieces of software. You are in fact doing almost the inversion of that. Courtney has been 10 years on Google's comms team. And now you have one of, I think, the most envious jobs known to man. You are the storyteller, chief storyteller for Moonshots at X. First, kind of fairly simple question is, what does that mean?
CH: Yes. Great place to start. Hi, everyone. I'm CH. I have, yeah, found myself in this strange position of chief storyteller for Moonshots at a Moonshot Factory. So, why don't I start by explaining what the heck a Moonshot Factory even is.
We are trying to invent and launch radical new technologies that could make the world a much, much better place. And the mechanism we use to do that is we actually create businesses which could live within Alphabet. X as in Google's parent company, or in some cases, we've actually spun them out to become standalone businesses.
But what's unique about a Moonshot Factory is really the ambition and audacity of the ideas and problems that we are tackling. So, we are very deliberately setting out to work on problems that affect many, many millions, or ideally billions of people. And we are looking out into a five to ten-year time horizon, which is further out in the future than most say, venture capitalists and traditional investors tend to look, but yet, it's not so far out in the future that the world will have changed too much by the time we actually get there. So five to ten years feels like a sweet spot.
My role within X has really been kind of on two levels. One is to explain what X and what a Moonshot Factory is overall, because we grew out of Google. We were originally founded as Google X in 2010. And then, when Alphabet was created, in 2015, we became our own division responsible for essentially inventing some of the future of Alphabet.
So part of my role is to explain X and attract the next generation of Moonshot takers to come and give this a go with us. And then I also spend a lot of time coaching the entrepreneurs and inventors and creators at X as they are tackling their own Moonshot. So, sometimes that is helping them set up their communications and marketing foundations, make first contact with a real world of partners and testers and others to kind of give them feedback and help them advance their ideas.
And other times, I'm providing kind of all-around leadership and entrepreneurship coaching. So, my job works on a lot of different levels. And that's actually why I'm still here after so many years. It's a role that constantly reinvents itself. And the role is itself helping to invent the future, which is awfully easy to get out of bed for any day of the year.
DG: This is very interesting. If we look at federal R&D spending as a fraction of GDP, it, of course, peaked like I think in mid-'60s, and pretty much has been on a steady decline ever since. And if you contrast that with business spend – on we're talking base substrate R&D here, not like a little Python app, but really space elevators – it's very much gone up, almost to replace it. Do you kind of think of yourself at X as kind of basically fixing a deficit almost in how government spends?
CH: That's such a great question. It really gets to the heart of whose job is it to solve the world's biggest problems. I actually think not enough people think it is their job to go after radical new solutions. There's a bit of not-my-job-itus on all sides of the ecosystem. I think governments certainly have played that role with R&D funding.
There's very, very few organizations outside of say, government and national labs that have the resource to look really far into the future and fund basic breakthrough science that may take decades to turn into a real economic value. But at the same time, governments are often prone to thinking, oh, how are the political winds blowing right now, or they have other more pressing things taking their attention.
I think big companies, especially public companies, tend to be subject to the shorter term pressures of the market. There's relatively few who have the bravery to be like, nope, we're staring a course out. A decade plus from now, you're just going to have to bear with us. Larry and Sergey put that in Google's shareholder letter back in the early 2000s.
I think small companies tend to think, "Oh, well, we can work a corner of a problem, but we're not big enough to solve the whole problem." Universities have a very, very big, big role to play in being those bridges that get closer from science to commercialization, but they often are an incented by publishing, interested in pushing knowledge forward, rather than them doing that next lap through to prototypes that start to look like products.
So I do think there's this challenge where everybody's kind of looking around expecting other people to do it. And the reality is we all need to spend more of our time and attention and willpower and money on these long term and high risk concerns.
Business vs technological viability
DG: Fascinating. And, of course, one of the reasons you mentioned this, and one of the reasons why companies, of course, don't usually do fundamental researches, they are vehicles that are subject to kind of short-term pressure for profit. How do you guys think about that, especially given the fact that a lot of the great research that has kind of produced many of the innovations we all rely on radar, satellites, many of the drugs we use, was not initially made, I believe, with the original and business concept online.
And so, if I present to Google X, and I say, "Look, this is really cool. I need a couple million dollars just to play with atoms in this particular way. I don't know why." Does that type of thing get funded, or must one really describe the kind of end business result?
CH: So, we believe that that kind of profit and purpose go hand in hand. So, we are working on the big problem. We need to be able to articulate the big real problem in the world we're trying to solve. And we need to have some sense, even if it's kind of back of the envelope for now, that there is a business to getting there. So, that's where X is in the ecosystem.
But to address specifically your question like, well, where is the handoff from basic science or even kind of early lab prototypes and then where does X fit in, we don't fund a lot of super basic science. We've certainly been known to invest in labs here and there small amounts of money more for just encouraging interesting explorations to keep going, but not with an eye toward, "Oh, that is a Moonshot ready to feed into our pipeline."
We keep close ties with the research community, so that we know what breakthrough technologies are just starting to kind of ferment and foment such that they could wrap into our thinking somewhere. But it's very, very unlikely that we're going to find a whole fully articulated kind of Moonshot project lying around in a national lab somewhere.
DG: Very interesting. Maybe we can almost think of kind of three notches on the free market spectrum here where you kind of have obvious products that produce short-term revenue. Of course, the company is going to do that. And maybe at the other extreme, you have like, "I don't even sure how this ever makes money, or will anyone want it." Maybe it seems like the Google strategy there is we'll fund labs to do that. And you kind of have this interesting sweet spot in the middle of once there is kind of an interesting commercial purpose for it, which with a slightly maybe elongated timeline, then maybe it can get folded in.
And now I'm kind of curious just for maybe some interesting stories around the early stories of Waymo or Loon, how all of that went about, these nitty gritty details you can, of course. Don't spare us anything.
Early stories from Waymo and Loon
CH: I've got lots of good stories from those early days, and actually self-driving cars, now Waymo is a great one to take a look at. So, I believe it was in the early '90s that the first self-driving car trip crossed the United States. So, I think that was a group at Carnegie Mellon, if I'm not mistaken. There were also groups at Stanford.
But there was a lot of academic research happening, a lot of DARPA money going in, DARPA Grand Challenges in that '90s and early 2000s timeframe, to self-driving cars when they really were purely in research stage. Then the self-driving car team at Google was founded in 2009 when it was clear from the progress of the research that these things were going to be viable.
We thought, again, not definitively in 2009, 2010, but there was starting to be a sense that that a significant kind of new stage of belief had been reached where it was starting to be possible to dream of these things operating on real roads and around your grandmother and your kids or with your grandmother or your kids in them.
That's really the stage where X is at its best. We have our blueprints to help us spot that kind of perfect tipping point for when something could and should be of interest to X. But it's three circles, a Venn diagram. One of the circles is, you need a huge problem in the world, as I mentioned.
In the case of self-driving cars, it was the fact that 1.2 million people die on the roads around the world every year. In fact, it might be closer to 1.3 now. And that doesn't even get into the kind of tax of distracted driving or worrying about your grandfather driving at age 85. And then dreading that conversation about taking the car.
We ask every team to articulate a huge, huge problem in the world. And that's also to prevent folks, especially engineering types from being like, "I'm not sure what this is going to be good for. But I'm sure if we can just make it work, then millions of dollars and millions of users will follow." It's some intellectual rigor around the problem.
The second circle is a radical proposed solution to that huge problem in the world. Can you say, okay, what is the collection of things if you put them together in the right way to solve a problem? In the case of self-driving cars, the radical proposed solution, which seems sort of obvious now, 12 years on, is cars that can drive themselves. I mean, back in 2008, 2009, this was one on nobody's radar.
Then our third circle is a breakthrough technology or technologies that are just starting to emerge out of research, out of labs, out of kind of paper, earliest prototype land and into a space where we think that that seems possible. There's still a ton of work to do to prove it out. But we can lean on that too. If that could work reliably at scale, we could make that radical solution and then solve the problem. So, in the case of self-driving cars, that was smart sensors and software working together such that a car could establish itself in space, understand its environment and navigate on its own.
DG: What were some of the early arguments, obviously, now, it's so clear to everyone in 2020 hindsight that this is the very obvious kind of next future microwave, satellites, internet, self-driving cars, it's kind of a clear continuum. But back then I imagine it wasn't so clear. What were some of the kind of common knocks on maybe why Alphabet should not be investing in self-driving cars?
CH: Yeah. Interestingly, there was this feeling of, "Whoa, yeah, that would be amazing if we could make that happen." Because it sounds like the future. And of course, you would look to a company like Google to have the kind of magical brave brains who would make that happen. But the biggest fear, and you could feel it in the team's communications at the time was safety. Like robot cars coming for you and your grandmother.
And then just a sense of like, that's just way too hard. I think that's probably a common feeling across all the projects that we work on, where most people would hear what we're proposing, and be like, "Oh, we already know that space. We know that industry. We know that problem. We know that technology. That's just way too hard. You're crazy and wasting your time."
And when we hear that, that tends to be a positive signal for us. We're like, "Well, maybe we're on to something." Now, that doesn't mean we don't listen to the people who are saying, "That's too hard. That technology isn't ready. There's still too many challenges to uncover." And we are deeply curious and want to learn from those people.
But you can't take those things as utter deterrents. That's why the world's problems aren't getting solved fast enough. In fact, I have what I call the "yeah, yeah, yeah" problem. One common thing I've seen every time we have announced a new area of Moonshot exploration is a lot of the people who first hear about this problem we're trying to solve, they're like, "Yeah, yeah, yeah. Why do you guys need to do that? That problem already has lots of smart people working on it. It's going to get solved eventually. It doesn't need giant stratospheric balloons."
And this is a true story. This is back in 2013 so we had founded Loon. And by founded I mean, three Xers and their dog driving around the Central Valley in their beat up Subaru ordering balloons off the internet and putting them up in the air with a Wi-Fi receiver to see if we could actually get a connection down to the ground.
2011, 2012 after we've been kind of playing around and basically proving that we hadn't found a reason not to go forward, lots people being like, "This shouldn't work." And we're like, "Well, I think you can." They just kept going, and it kept working.
Spring of 2013, we were getting ready to go test in the real world at some scale for the first time. And New Zealand was a country that was okay having us hanging out among the airplanes in their airspace. And also, they've got plenty of Pacific Ocean off their coasts. So, they're like, "Okay, sure. Give it a go, but be safe." And so, that spring, we are gearing up toward, I think it was a mid-June launch of about 30 balloons off of the coast of Christchurch, New Zealand, the South Island.
And I was calling up a handful of journalists to see if they wanted to make the trip. And I rang up a reporter, who was based in the UK and who I had called because they covered the problems of internet connectivity a lot in their career. They had covered the problems of rural England. They had gone to Africa. So, here was someone who was I thought dialed in to the problem at a time when no one in Silicon Valley was talking about this problem. This was pre-Facebook's internet.org work. This problem was just not on the radar for those of us in kind of apartments and houses where we already had.
I rang up this journalist and pitched him my story of these dreamy internet balloons. And well, heck, it's going to be an adventure and who doesn't want to go to New Zealand. And there was this pause on the phone. And he goes, "Courtney, that just seems like an awful lot of effort. I think cell phones and Wi-Fi, and fiber is going to get us there." And I tried to debate and argue with him. But I was flabbergasted because who doesn't love a balloon? And who wouldn't try to keep solving this problem?
And so, I ran back to the team and I'm like, "You guys, we've got a fundamental disconnect here, which is the world still doesn't believe that new innovation in this area is needed. The world is just not feeling the urgency and that is why this problem is not getting solved. And therefore, we matter more than ever to keep going. Yay."
DG: Very good in-out-group dynamic bonding there. Yeah.
CH: Totally. And we've seen that play out in field after field. I mean, self-driving cars, we were in there. We had smart contact lenses. We've winged delivery drones were early. I mean, I think Amazon was in there around the same time horizon, but we're often in these problem spaces and in these new technology options long before the rest of the world is like, "Okay, we should have a guy look into that." And if we can be released signalers, fine, we're happy in that position.
Optimism as a service and how conventional success kills creativity
DG: What do you think drives that? Why do you think it is? It seems to be a fact of nature almost that the pessimism is always there and it's almost easier to reach for than the optimism? What do you think drives that?
CH: I do think it is fundamental in the human brain. I mean, I am not a neuroscientist, but I am a disciple of Daniel Kahneman's Thinking Fast and Slow. I do a lot of psychology and sociology reading on my kind of side because I do think it is human nature and our need for certainty and stability and our innate discomfort with the new and different that holds us back.
And you even feel it at different stages of your life. I have a whole long set of opinions about how eight-year-olds are probably better positioned to come up with really creative solutions to the world's biggest problems than most of us.
DG: Much better form by the way. If you just watch how they hip hinge when they sit down, stand up. They really got everything right.
CH: They do and then we crush it out of them. What do we do? We load them down with backpacks. We stick them in front of computers. We stick them in educational frameworks that kind of squash all that out of them. And so, I think there is, especially in high achiever kind of the process by which you become a very successful human and professional, I think a lot of that process turns you into a certain type of brain and a certain shape of thinker. And it squashes out a lot of creativity.
And you don't even realize it's happening to you because you are still being successful as you are going through this process, like you graduate from a fancy school and you get degrees. And then you go into a company, where your boss gives you goals. And then you're a good employee, and you get rewarded and promoted if you hit those goals
Before long, you've woken up, and I don't know age, 35, 40, 45 in a certain shape that works for a certain type of organization for a certain type of success. And then the thing that really kills me is that all these super talented people who've been turned into these little shaped puzzle pieces, they then have to go out and hire innovation consultants and creativity consultants and personal coaches to help them tap into their real personal purpose. And I'm like, "Hang on, guys. I think we're getting something backwards here. Let's call in those eight-year-olds and tell us where we're going wrong."
DG: Yeah, totally. It's like we're born with perfect energy. And then we start dosing ourselves with caffeine over time, just to make up for a deficit we have elsewhere, or we create elsewhere. Curious to go back, though, for a minute to the stories of origin.
So, you mentioned with Waymo, certainly there was a lot of fear that it would obviously be worse than the human or be impossible to do. Loon seems like an interesting different genre of just not a needle mover societally right now, which is, of course, can very confusing in hindsight, but makes sense. I'm very curious to hear other stories things getting started from those projects or others, reasons for rejection that are common.
CH: Yeah. Well, I can give you a few examples of companies that actually were spun out of X because they didn't necessarily meet the very high bar that we have for creating businesses for Alphabet. Because, I mean, Alphabet doesn't need tiny little 100 million-dollar businesses. Alphabet has tasked us with finding the next Google. So, I can give you an example.
DG: I mean, it's so funny. I mean, this makes sense and I reflect on this having worked at Apple, I used to hear the same quotes. A $100 million revenue business would be, I think, in the 1% of 1% of businesses on Planet Earth, perhaps the galaxy. So, it is fascinating. Yeah, but of course, this propels you to build really incredible things as a result, maybe a good stressor. But please, yeah, continue.
CH: Yeah. And this is actually one of the challenges of the entrepreneurs coming into X. They're just like, "Wait, you're expecting us to hit the grand slam?"
CH: "And you're not interested in the singles and doubles." And we're like, "Yeah, we're not going to hate on you if you produce singles and doubles, but we're going to harvest the singles and doubles and set them to the side or give them away as open source or maybe another company could, you could spend on a company. We are here to hit the grand slam."
And so, there's a whole mental and emotional resetting that our entrepreneurs and Xers have to go into. Because there's fear. There's fear in thinking, but what if I can't hit the grand slam? What happens to me now? And our view is this is a safe place for taking grand slam swings. We will reward you for the grand slam-ishness of your attempt, not presently achievement of the grand slam.
Foghorn, carbon-neutral fuel from sea water
DG: Fascinating, fascinating. We're interested in the height of the mountain you want to climb, not really in your results of summitting it. Okay. So, what is the story here? If you're coaching me and I'm an entrepreneur that's coming to X, and I have an idea, what do I need to be doing for kind of my first meeting? What are kind of do's and don'ts?
CH: I talked about the three circles and the importance of articulating the problem, and the radical solution and the breakthrough technology. We would be looking for your kind of hypotheses of one or two of those circles. Now, just starting with the problem, that's not ... I mean, there's lots of people who could say, "Yes, internet access, or agriculture is a big problem." But what is the angle on the problem that you're particularly interested in? And more importantly, what's a technical approach or a solution that you're interested in exploring.
I can give you an example of something that to this day still feels like an amazing X Moonshot, even though we had to put it on the shelf. So, this is a project that we called Foghorn. And Kathy Cooper, who was the founder of the Foghorn project, she and some other Xers had found a research paper, I think it was over at Xerox PARC, where the researchers at PARC had proven that it was possible to make a carbon neutral fuel out of seawater. If you could do that! Imagine.
DG: Victory condition for the planet. Yes.
CH: Yes, yes. So, of course, Kathy and others got super excited. They called up Matt Eisenman, who was the researcher over at PARC and they said, "Matt, would you like to come and give a tech talk over at X." And so, Matt came to give a tech talk. They spent time getting to know him. He came on as kind of a 20% advisor. And they started exploring whether Matt's work in the PARC labs was actually something that they could prototype and repeat.
And then in parallel, they started exploring whether there was actually going to be a viable business, was probably too like tight a word to put on it, but we actually had to check the economic viability because there's an awfully long distance between squeaking a vial of fuel out of however many gallons of seawater, and actually getting something to the pump at a price that a consumer is willing to pay, not to mention the logistics and regulations and the taxes and the environmental stuff.
And so, they started. They had two parallel tracks of exploration where the technical folks were pushing forward on the prototype to identify big challenges and scaling that And then, Kathy was leading an exploration of all the different factors that go into producing a gallon of this fuel. And Kathy had actually followed one of X's most deeply held principles, which is we call it find your monkey.
What we mean by that, it's basically a beautiful analogy, which I can come back to. But the idea is work on the hardest highest risk part of your problem first. So, what most people like to do, because we're human and we like to feel good, not uncomfortable is we work on this stuff we know how to solve. It might be challenging, but we think we can solve it. So we go there.
What Kathy and all X teams were taught to do was go find the thing that if you cannot solve it, you might as well just pack up, go home and move on to the next thing. And for Moonshot in fuel, that had to be what the cost of that gallon of fuel is. I mean, there are probably other things as well. And we did uncover some other monkeys. But the big one was the cost of that gallon of fuel.
And at the time, this was what 2014, 2015-ish, I think, in Scandinavia, where fuel tends to be very expensive, I think fuel was selling it like $8-$9 a gallon. But in America, you'd have to get much closer to that three, $4-$5 a gallon, where even the most diehard kind of planet fighters would consider paying kind of a much smaller premium.
They set that target of $5 a gallon. They knew for sure they had to get it well under 15. And when they ran all these experiments and talked to lots of people who knew how to produce large amounts of hydrogen and how to produce large amounts of carbon and all these things, they realized they couldn't actually get the target down anywhere too far south of 15. And so, they voted to kill the project.
And so, that remains one of those things that Kathy lived the ideal and led the ideal Moonshot experience where it was just this beautiful hypothesis. The breakthrough technology was in this really nascent form. There was still a lot of exploration to do. Very few other companies would have bothered to kind of go on that journey. But she did it. She led us through it in as efficient a way as possible, such that we're glad of the investment we made, but we're able to shut it down and move on to the next thing.
And Kathy ended up actually founding another Moonshot, which she then spun out of X and now, she's the president of her own company called dandelion, which is a home geothermal heating and cooling company. So she's lived that Moonshot arc twice now. And by the way, she started at Google as an AdWords support rep.
DG: That's amazing.
CH: Yeah. And Moonshot takers are everywhere, like Kathy is proof positive of that.
Self-replicating nanobots at X
DG: That's really fascinating. The high volatility narrative or story that really reminds me of Pixar. They'll have moments where directors break multiple times as they go throughout the script, sometimes changing the entire movie. And it's a similarly very emotional process there. And Ed Catmull will talk about a lot of his job is just coaching people through this, the moment failure where you put together a movie, and Pixar is a big deal, a lot of rendering. And then you kind of realize after watching some of the dailies, it's just not there. You got to start from scratch, almost like realizing we can't make it happen with the water to oil thing.
I'm kind of curious to walk this through for a minute, just because I think it would be informative for people trying to figure out how to do a much harder feat, in my opinion, which is trying to do this in like the public investor market with Moonshot ideas. Obviously, this is why Google X exists is because the investors are just much short-term minded.
But let's imagine I'm at Google and I come in and I say, "Well, I've read Richard Fineman's paper. What is it, 'there's a lot of room at the bottom' or something. And I would like to build self-replicating nanobots. And I've read the paper and I can paint you a picture that it's really important. And it unlocks many technologies.
I mean, we could build better silicon processors with this. We could do healthcare with this. It's one of those Victory Conditions. It's like energy. You solve this, you can manufacture anything. We'll live like the Jetsons, where literally food is just a bag of atoms coming in and it's assembled in the right way. And then you get whatever you want out. Perfect nutrition, what have you. So, I don't think it's hard to articulate how lucrative and how valuable it would be. It's extremely unclear that this would ever work."
And so, Fineman has a nice paper where he explains it like he does to almost to a child, and he says, "Just make robots that make smaller and smaller things periodically." And so, let's imagine I present this to you. But now, what I'm interested in is it's like three, four months in. And I have, to your earlier story, I have just like a very toy example, we can manufacture maybe like silicon wafers, which you could do with traditional manufacturing techniques. But it's neat. What happens now at the Google X meeting?
CH: Sure. So, you would have come into the meeting with, yes, your prototype, and shown us why that was important, but more importantly, not all the things that the prototype was doing well and perfectly at that point, but you would come in with lists of all the things that you had learned and all the things that you had been wrong about.
At that stage, and really, for the first few years of any ambitious venture like this, what we're listening for as leaders and coaches at X is, are you learning as hungrily as you can? Are you experimenting in these really smart, beautiful ways that is helping you de-risk the core problem. And this comes back to the find your monkey idea. To unpack that a little bit:
This grew out of Astro Teller, who is the captain of Moonshots at X. He tells a story about what if you were asked to, if you're in a big project, was to teach a monkey to recite Shakespeare while standing on a pedestal? And as I said, most humans would go, "Build the pedestals because makes your boss feel good. There's progress. Yay." But it hasn't taught you anything about whether or not the monkey can stand on a pedestal and recite the Shakespeare.
And so, we've used that repeatedly with our teams as a way to say to them, what are the biggest risky things that you are facing? What are the biggest questions that you need to answer and give us a stack rank, like the activities that you were taking on, the experiments that you are running should match up with the highest risk on your list right now.
And so, really, what we're listening and looking for is kind of inside your mind and soul as an entrepreneur, how are you approaching the problem? And how deep is your understanding of it? And are you uncovering anything that says, "You know what, this just isn't going to work," or you're coming at it in a way that it's not actually going to get you all the way to the end. It might just kind of get you another couple years, and then you run into another dead end.
It's really just like unpacking some of the assumptions and the hypotheses that you're operating on and really helping you kind of design the next set of experiments to teach you.
DG: That's interesting. So, my understanding is, so, I've come to you with my self-replicating robot, and really what you're looking for in me is not even the amount of progress I'm making. But counterintuitively, you're just looking for my learning rate. That is to say, the amount of ways I've kind of changed my thinking, updated my model on various things. Is that right?
CH: That's right. And that's counterintuitive. And unlike how most kind of meetings with your boss tends to go.
DG: Exactly. That's very interesting. Now, another thing I'm curious about is what exactly am I asking for with my self-replicating robot? Let's say it's been three months. What am I asking you for at that point? I'm asking for enough financing to run it for a year, for 10 years, for a day. How does that work?
CH: Yeah. So, at X, and this is one way we're quite different than say if you're raising venture funding. With venture funding, the entrepreneur is kind of deciding what they want. They're looking for trenches of money basically to buy themselves independence until they have to go out and raise some more.
At X, we ask Xers to operate under much I think smaller and scrappier amounts of money so that teams use the money for learning and not for scaling the operations of a business.
Now, there are some people, some entrepreneurs who really want to move very quickly to the stage where you have products and market, customers that you're taking care of, you're scaling your operations. There are a lot of entrepreneurs for whom like, that's their jam. And so, (well, that's also how you get WeWork) --
But that is a particular way to build and grow a company. We tend to push our entrepreneurs at X to stay in a much smaller, scrappier learning focus, tech journey focused mindset for longer. And we trust that when we found that idea, that grand slam potential idea that we want to pour money on, heck you're at Alphabet, the money is going to show up.
I can give you an example of this is we have a team that's working on something related to the future of hearing. And the lead of that project actually worked through I believe 35 different iterations of a Moonshot idea. I don't know if they were all in hearing. But at the end, we now have a project that we are proud to call the NX Project. And now he gets more money. And over time, as the confidence grows, then more money shows up, and you graduate and become another bet.
But we found there's so much inefficiency in large teams. Once you start getting... I mean, you felt it as a leader, right? Like three, five, eight people, you can move really fast, almost like one brain. You start getting north of 10, 10, 20 layers of communication, infrastructure creep in. You go north of 20, 30, like you're adding more and more layers. And that's all a distraction from kind of that cracking that core problem. We try to keep the team small so that we can be as efficient as possible.
DG: I presume, of course, the strength of Google is I just want to make sure, correcting me here, suppose I come to you. And I mean, the team is, we're three people here. But we do need $5 million, $10 million because we have to buy some parts or whatever, how do conversations like that work, where it's very high upfront investments to get any experiment validation?
CH: Yeah. We have lots of different stages of the pipeline. I think the earliest stuff, like the sort of two physicists and a dog, you're probably talking some tens of thousands of dollars, maybe low hundreds of thousands of dollars. And then as you get a little bit more learning and a little bit more confidence in the idea, going from hundreds of thousands to small millions of dollars, that happens.
And so, we have conversations in all those stages. And now, you can see by the investment we've made in Loon and self-driving cars, and others, there are plenty of millions of dollars available, but the scrappiness drives creativity. And that constraint, I mean, everyone's going to complain about it. I've never seen an entrepreneur not complain about the amount of money they've been given. But that constraint forces focus and creativity, even if it's a bit jarring to be that scrappy at a trillion dollar company.
DG: A hundred percent. Are renders or kind of photoshopped images, movies, is that ever used and did expense on to create a sense of what this could become? Or is everything in just words?
CH: Oh, goodness. We have one of the best prototyping labs in the world. In fact, we, just few weeks ago, put up a video on our YouTube channel. Inside the Design Kitchen is what we call it. And so, Joe Sargent is a former Mythbusters stunt guy, who now runs the Design Kitchen. And in the Design Kitchen, we have all manner of tools for prototyping and exploration.
And our building, which due to the pandemic, only small numbers of people can get into now, we have laser labs and biolabs and we have lots of low pressure, high pressure chambers, almost all the goodies that you would want if you're making things that are not just software. And then we do also use visual design tools. My team often gets tapped for storytelling because often, the story you tell yourselves as a team is itself kind of a very strategic and inspirational process. So, yeah, all those tools we use.
DG: Now, as a storyteller, I'm curious to get your take on one particular thing for my nanobots project, but also more broadly, I think across all areas of biology. I think it's one thing to try to get mankind excited about a self-driving car. I can see it. I can visualize it. Loon is incredibly scenic, especially the way you guys rolled it out in New Zealand, to your point, who doesn't want to travel there?
Yet, if you're working on, say, synthetic biology, if you're working on nanobots, the whole point is that it's really small. So, how do you think about getting people excited about that given that size issue?
CH: Yeah. So, those are the situations that my team loves to kind of work on because they're kind of intellectual and emotional puzzles. My deep belief is that Moonshots are built not just with heads, but with hearts. And so much of what my team tries to do, and what every entrepreneur needs to do, is really get people to believe to show up and be like, either explicitly, I support you, here's money, here's partnership, here's advice.
Or in many cases, with very radical risky, new technologies, we just need people to be like, "Okay, I see what you're doing. I think you're kind of crazy. But I'm not going to stand in your way right now." We've seen things cut both ways honestly with X, anyone who remembers Glass remote, which I worked on quite a lot, both in iteration one and iteration two more recently. The pendulum of opinions swinging wildly from Monday to Friday, like best thing in the world, worst thing in the world.
DG: But right, so Glass, obviously very visual, I mean, I guess that's the whole point. Still today, I think one of the best products with that original video with a cyclist. But say, I'm working on something with biology to your earlier example, I mean, what would be your recommendation to me? I mean, should I make these animated renders of like cells moving? Is that exciting? How would you convey it?
CH: I always start with, who is the audience you're trying to reach. Because if you are talking to an investor, that is a very different audience, even an investor with deep life sciences or biotech experience, it might be an investor with a PhD in the field that you're working in, and they already know the science, or it can be an investor with industry experience, where they're kind of just having faith that the science will work out, and you seem like a smart person, so, great.
An investor audience is very different than if you're asking someone to be on your board. Perhaps you are talking to an academic who, again, might be able to speak science with you, but they don't know as much about commercialization. And so, how do you find that common bridge?
Or maybe you're bringing someone on to the board who is from industry, and you need to explain your vision so that they feel like they're spending their time on something that has commercial potential. Or maybe you're preparing for the kind of ethics that you're trying to do a research study, and you have to prove that you've thought through all the things you need for to get through the ethics and IRBs, the independent review boards. That's a very different communications task.
In every case, start with your audience. And then from there, understand what it is that you want them to think, feel or do after they've engaged with you. And then think about, based on that goal and what shift you need them to make, do something for you or to stay neutral or whatever, then you start to get into, okay, what might be the right moments and tactical vehicles to do that? What are the kind of most important messages?
I mean, the easiest thing in the world is like, if you can't write down on a Post-It note in three little things what you need someone to think or feel or do, like you got more thinking to do on your own side before you even get to thinking about what you're going to say to them.
Communicating Verily, smart contact lenses
DG: It's very interesting. I'm kind of curious, you spent, obviously, a lot of time at Alphabet and Google, obviously honing the craft that we're just talking about now. Any kind of interesting stories of a product that was particularly difficult to communicate that you had to workshop?
CH: Sure. So, I'll tell you about my adventures with the smart contact lens. So, I think we announced it in January 2014. And at that time, we were still part of Google. And at that point, I mean, everyone was starting to get tuned into, "Whoa, Google is stretching into all parts of your life and all the data."
And this was going to be the first time that Google was going to go on, or slash, in your body as in a contact lens on your eye, with a little computer chip and a teeny little glucose sensor because the Moonshot there was, could we make a contact lens with this teeny tiny glucose sensor and teeny-teeny computer chip that could measure the glucose in tears such that it would be easier for people with diabetes to keep track of their blood sugar, like if we could prove the correlation between the tears and the blood.
We had to figure out how to explain this to the world. And Brian Otis, who was the creator of this project, he had come from the University of Washington, where he had proven this in a lab, as in he could get the sensors really tiny. And he was attaching them to the sides of plastic water bottles in a lab to see if it could measure in liquid.
DG: Oh, interesting.
CH: So, that was as far as he got it as an academic. And the reason he came to X was because he wanted to actually see if this teeny, tiny midget miniaturized electronics could be used in real applications and actually help people in their daily lives. And so, we had gone through the building contact lenses and we were ready to move into some clinical trials. We had done some early trials that were promising.
And the challenge was, how do you explain this such that the world hears the, oh my gosh, we're going to help potentially people with diabetes, but we steer clear of two third rails essentially. One was the FDA. So, the FDA does not like it when researchers and ambitious types start mouthing off about what their medical device will do before the medical device has gone through trials and been proven to say it does what it does. So, we had to be super clear not to tweak the regulators.
And we also had to watch out for the people who were watching Google to be like, "Oh, my god, Google's coming into my body to take all the things." And so, Brian had never worked on a big unveil like this. And he certainly had never worked with the kinds of journalists and others who watch Google so closely. And I kept saying to him, we have to find this really inspirational and accessible way to make this land on the inspiring side of the line, not the terrifying creepy side of the line.
Now, part of this was storytelling with images. So, if you go back and look at our website, x.company, there are beautiful images of this elegant, magical looking contact lens, balanced on the tip of your finger. But we also had to get over that kind of yuck weird factor of like, "Wait, is this a computer chip stuck on my eye? What?" And so, one day, we were in the lab, and Brian showed me the glucose sensor and computer chip, and he put it on the tip of my finger with tweezers. And I said, "Oh, it's like glitter."
Now, keep in mind, he's a PhD in electrical engineering. The man looked at me with this deep horror on his face. And he's like, "It's not like glitter. It's like one of the most incredibly impressive intellectual innovations on the planet. How dare you little fluffy word PR girl, like how dare you?" And I was like, "Yeah, but Brian, this is how we get people to understand what this is, so that then they can appreciate the impressiveness of the achievement and its potential. You got to anchor them in something they know, which in this case is it's like glitter."
And so, we sort of agreed to disagree in the moment. And then at about 10pm at night, I got a link in my email to a PDF from the International Glitter Standards Foundation. Brian had researched the tech specs of glitter. And actually, glitter is the same dimensions as his little chip. And so, he's like, "Okay, you can use glitter." And the rest is history.
DG: Fascinating. That's interesting. And that's a great mnemonic, I guess, for everyone to think of what their glitter equivalent is.
CH: We also, by the way, spent a ton of time educating people on the problem of diabetes and what it's like to live with diabetes. I was talking earlier about, yeah, yeah, yeah, problems. In 2014, everyone was aware that diabetes is a disease that a lot of people are living with. But because so many people are living with it, it had really masked the fact that it is a quite a dangerous disease. And it is a big burden on you to manage it effectively.
We interviewed a bunch of Googlers to understand what it was like to live with diabetes, either to have it yourself or to have a family member with it. And a friend of mine said, "Courtney, it's like having a part-time job on top of my daily life," just managing her diabetes. And I was like [head explosion]. So, actually, okay, so this is a three-part story of how do you tell these stories, and it's beautiful visuals helped us in this case. An analogy that helps people anchor in the reality so then they could hear, feel your future as well.
And then thirdly, anchoring them in the problem and a really emotional way to cut through the, yeah, yeahs. So, yeah, that really stuck with me.
DG: That's fascinating. And probably a great point to end on. Thank you so much. I mean, I really enjoyed both the hearing the origins about the project, the reasoning behind it. I appreciate you humoring me with my Richard Fineman walkthrough there in the middle. But I do think that's quite helpful for anyone kind of thinking about how to fund something high stakes.
Yeah. I mean, as a citizen and humanoid of this planet, I guess we're all really thankful to you for your work. Keep it up with the glitter.
CH: Oh, thanks for having me. And I really do believe we need more Moonshot factories and more Moonshot takers and honestly, so much of what's stopping us is the sense that it's someone else's job and it could be all of our jobs, so let's live into that potential.
DG: Great. I think you've earned yourself a few cold emails, so apologies and thanks for that. Thank you, again, Courtney.
CH: Thanks so much. Take care. Bye.
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