25 Dec 2020 · via The Art of Doing Science and Engineering: Learning to Learn 📚
The always-sharp Richard Hamming on the legal challenges delaying a broader deployment of computers to medical diagnostics:
One major trouble is, among others, the legal problem. With human doctors so long as they show “due prudence” (in the legal language), then if they make a mistake the law forgives them – they are after all only human (to err is human).
But with a machine error whom do you sue? The machine? The programmer? The experts who were used to get the rules? Those who formulated the rules in more detail? Those who organized them into some order? Or those who programmed these rules?
With a machine you can prove by detailed analysis of the program, as you cannot prove with the human doctor, that there was a mistake, a wrong diagnosis. Hence my prediction is you will find a lot of computer-assisted diagnosis made by doctors, but for a long time there will be a human doctor at the end between you and the machine.
We will slowly get personal programs which will let you know a lot more about how to diagnose yourself but there will be legal troubles with such programs. For example, I doubt you will have the authority to prescribe the needed drugs without a human doctor to sign the order.
You, perhaps, have already noted all the computer programs you buy explicitly absolve the sellers from any, and I mean any responsibility for the product they sell! Often the legal problems of new applications are the main difficulty, not the engineering!
Building on Hamming’s insights, I would speculate that much of the conversation about AI paradoxes (e.g. the trolley problem applied to self-driving cars) also stems from challenges in accountability.
We are used to treating humans as agents that can be hold accountable for the consequences of their acts (except for, say, children and elderly with decreasing mental capacity.)
If our present model of accountability is based on two premises:
The question then becomes: How to translate them to a world where machines are ubiquitious and ever smarter? Will we wait until they seem to have free will and things to lose?
20 Sep 2020 · via @patio11 🐦
Patrick McKenzie on twitter:
I think people in the tech community tend to undervalue large portions of the marketing skillset, and e.g. building a narrative for a decisionmaker persona then solving backwards to the artifacts that would create it is useful.
But in many phases of the business, this works:
The secret to marketing, and I’m 100% serious, is to not do it very well. That way you are charmingly, endearingly incompetent and constantly build up reserves of trust and goodwill from all the value you’re leaving on the table
Patrick then continues:
A good portion of some advice in the community, like “write for yourself”, is a shortcut on having to do the whole decisionmaker thing, because you’re overwhelmingly likely to yourself have problems that at least some other people do and to speak in a way some of them will like.
A semi-considered guiding light I had when writing for many years is “Just write about things you would have found surprising 5~10 years ago in a way that you of 5~10 years ago would have found maximally compelling.”
I do tend to believe that if you can figure out a way to create compounding value over time then things will often work out swimmingly, though you do have to continue putting work into the other things.
(A tragedy, and I mean that phrasing, is when someone who has figured the value creation thing out then ends up in starving-artist land and has to curtain their output and get a job doing something much less important simply because the job is competent at turning work into $.)
I think the ideal marketing is when you are able to build narratives for key decisionmakers but no-one can see you actually doing it. It’s hard as hell but if your team can pull it off, it’s the best of both worlds.
Brendan Greene had a singular vision to bring battle royale to the video game market. He started as a modder, and he was a fan of movies like Battle Royale and The Hunger Games. He started working on a mod that could do this kind of a first-person shooter game mode where the territory for fighting kept shrinking until there was just one player left standing.
And the rest was history. Greene hooked up with Daybreak Games on H1Z1 and then went to Bluehole, which set up a subsidiary, PUBG Corp., to make a battle royale game. There, in South Korea, Greene helped create PlayerUnknown’s Battlegrounds. It became a huge hit when it debuted in March 2017, and it saw a meteoric rise on PC, consoles, and mobile.
Greene recently spoke about this experience with Rami Ismail, cofounder of Vlambeer, at the Gamelab event in Barcelona. He talked about his life as a modder and being thrust into game development with almost no experience beyond what he taught himself. For nine months, he toiled with the development team and eventually put their creation out in to the wild. Then he got a rush out of the huge popularity of PUBG. The mobile game alone has topped more than 400 million downloads, and the team has grown from 30 people to more than 400.
But why Fortnite (not PUBG) ended up “winning” the West?
05 Sep 2020 · via John Collison – Growing the Internet Economy – [Invest Like the Best, EP.178] 🎙
Here is what John Collison recommends for anyone looking to study the history of successful B2B companies in tech:
If someone wanted to understand kind of how we got to where we are today in 2020, what technology companies would you encourage them to study and why?
Stripe sells to businesses, and so I am probably indexed more on boring B2B behind the scenes, content then maybe someone who is starting a consumer company. I think the history of Salesforce is quite interesting to look at, similarly the history of Oracle is interesting to look at.
There’s a good book on Oracle called Softwar: An Intimate Portrait of Larry Ellison and Oracle.
I would say there’s obviously tons of content on Google, Facebook, all the super prominent mainstream companies. I think the interesting things to think about are, one, there’s a lot of content out there that’s essentially propaganda by these companies or “the blessed accounts”. And so it’s not like there aren’t interesting facts there, but they’re probably not as interesting as the thing is the company really wished you didn’t read because they go a little bit off script as the official accounts. And those can be a little bit harder to find.
13 Aug 2020 · via The Critical Path #247: Usually, You Say CPUs @ 59:00 🎙
Horace Dediu speculating about how the Apple Glasses might come to be:
If you were to look at glasses: What if Apple glasses look like a regular pair of glasses? What if it have absolutely no technological appearance?
The question on the glasses or anything worn on the faces, as I said before, it’s a very delicate thing. The watch when it was introduced it didn’t look that different from any watch. And so what the logic I think for wearables for Apple has been is, “Let‘s not ask people to accept a behavior or appearance or a burden in terms of the weight or anything else that they”re not already accepting”.
And we go back to this, if you want to know where wearables are going, look at where jewelry has gone. That’s been my thesis about wearables.
We find it acceptable to hang in our bodies a lot of metal, a lot of rocks – which could be substituted with silicon and plastic, and maybe some other metals.
The area around the ears, the neck, the eyes and potentially the top of the head – where a hat would reside – these have been conquered. [We have] over-the-ear and in-ear headphones but [nothing] yet on the face.
And this is one of the things that with Apple Silicon they might actually be able to deliver on such a small headset that it actually would be indistinguishable from a normal pair of sunglasses.
Actually, what I think they would go for in a glasses model would be the degree of customization. Everybody has a different style of glasses. I’ve gone into these places in the past and gone through everything available. And I was like, I didn’t like any of them. You know, they did not fit me. How do you make a pair of glasses or how do you make a lenses-based system which have to conform to so many face shapes and styles?
I would think it would be along the lines of a custom order based on a 3D face scan. The idea is that they use your phone to scan your face, that gets you a 3D map of the head. You use that scan to have effectively a 3D render of your head and the glasses. Then you say, OK, I accept and I buy. And then they send it to you in the mail, and you get perfectly fitting glasses. This would take into account obviously the face shape, but also your nose and your ears and all the other touch points.
The logic then would be that the customization is key to a face device, not only in terms of size, but in terms of style. If that’s the case, then how do you create compute and sensor hardware as the embedded piece into this otherwise physical object that has so many shapes that it can be? That would be the breakthrough that I think they would seek in a wearable for the face.
- First of all, do not force people to adopt new behaviors
- Secondly, do not force people to adopt new aesthetics
- A third would be that it would be completely shaped by the user, as opposed to here‘s the choices you have
- And then make a useful product. Make it so that it does make a quantum leap in usability
The advantage of making a proper set of glasses (not sunglasses) is that the general population that does have corrective lenses (whether these contacts or not) is higher than 50%. If that’s the case, then the market is huge. Possibly even bigger than the watch market, and yet it’s more difficult. Because everyone is very particular about what they choose to wear on their face, as they would be for anything they wear on their bodies as clothing. Not so much wrist-worn or even ear-worn, but face is a very special place.
We started this discussion about silicon. The fact is that it might be that the key to embedding that technology into a very customizable outer appearance is possible through only this particular breakthrough in their ability to integrate. In which case, that becomes the next category. If they‘re able to crack that nut, it becomes the next category. Implications thereafter are profound, because again you are dealing with a new user experience.
The watch was a potential new category for computing as well. It turns out that its glanceable nature, despite the fact that you might glance at it 100-200 times a day, is not a sufficiently immersive experience. It is secondary. It is still a wonderful place to put technology. It does seem to affect your behavior quite a bit as a passive sensor. But the leap we might need to get people to be interacting with computers more might still require a position around the ears and the eyes.
13 Aug 2020 · via The Critical Path #247: Usually, You Say CPUs @ 29:00 🎙
Horace Dediu on how Apple is usually not a first mover into new product categories:
Apple doesn’t jump on a bandwagon. It doesn‘t develop a product strategy and doesn‘t actually firmly launch something until 2% (or more) of the market has been already explored through products sold. Meaning, until the adoption of that technology goes beyond 2% of the population that ultimately adopts it.
If you think about the mobile phone, when the iPhone launched in 2007, it had been already about seven or eight years of smartphones in the market. For Americans, it was mostly the BlackBerry, maybe a bit of Windows Mobile. But for Europeans, it would have been Symbian or Nokia-based smartphones that ran some crude operating system. But it was an operating system with apps. There were app stores. There were apps, there was media, there was imaging, there was a messaging with imaging, and so on. All these prototypical services we have today.
Effectively, by the time the iPhone shipped, tens of millions of smartphones had already shipped and arguably, about 2% of the market had been developed. And that‘s when Apple reset the expectations with the iPhone.
If you go back to MP3 players, same thing. The iPod, when it launched, was said that it was not competitive with the Nomad, which was one of the brands of the time. The iPod was lame because it didn’t have as much capacity as an existing MP3 player. By 2001, when the iPod did ship it already was 2-3 years of MP3 players in the market. Everyone at the time was like, why is Apple so late? Why is their product so limited?
The fact is that super early adopters are frustrated. They’re banging on about something. This is true for micromobility, it might be true for AR/AV too, where would you have already tons of VR headsets that kind of came and went. The Google Glass that came and went. The HoloLens from Microsoft.
We also had, by the way, tablet computing starting in the late 90s. That’s a good decade before the iPad shipped.
The pioneering happens early, and failures happen early. And Apple kind of comes in just when… I believe it is not because Apple thinks it can get a better advantage later, but because I think they toy with it. They put things together and say, “Now, it‘s good enough”. It‘s good enough for the Apple brand. And, as a result, it‘s good enough for the average user.
In the adoption curve, they come in after the so-called innovator phase, in the middle of the early adopter phase. The early adopter phase is between 2 and 13%. Above 13% is the early majority up to about 50%. Then after 50% until about 85% is the late majority. And then the last 15% are called laggards. Roughly, that’s how the famous adoption curve has been segmented.
13 Aug 2020 · via The Critical Path #247: Usually, You Say CPUs @ 26:30 🎙
Horace Dediu on how Apple seems to beta test new technologies:
One of the curiosities that I noticed was the inclusion of a 3D LiDAR.
What is it doing in an iPad?
Well, short-distance LiDAR might become one of the core technologies in AR. So they‘re putting it into an iPad almost as a beta test. Let‘s see how it works in real world. Let‘s use some of the data from it to calibrate our own other systems.
Again, the M Series, the chips that detect motion, were first shipped on an iPhone. Using an iPhone you could detect steps, but nobody‘s thinking of that anymore. We‘re using the watch for that. But I think that the development of the core silicon for the Apple Watch was started with the iPhone.
The M Series was sort of planted in there for getting some early data and then using it to deploy future technologies. Because the roadmap is so far ahead, I think there’s a lot of foreshadowing going on there.
That’s what I would be looking at is if there are acquisitions in enterprise or acquisitions in AR or acquisitions in AI that are leading us to kind of put together this elephant by touching a piece of it.
And sometimes it goes nowhere. There’s possibly dead-ends all around. That’s the game.
13 Aug 2020 · via The Critical Path #247: Usually, You Say CPUs @ 57:00 🎙
Horace Dediu on how Apple Silicon might be the source of a competitive advantage in wearables and AR for Apple:
If Apple is no longer constrained by what foundries and what architectures are going on in other companies, we might be looking at a new era of compute.
Again, what if you go from old metaphors/UXes and repackaging them, but rather (potentially) coming up with something new? That‘s always the question out there. Does this silicon enable more rapid prototyping of user interactions and user interfaces, along the lines of AR?
In which case, by the way, from a competitive point of view: How hard it would be for Microsoft or Google or Huawei to, without custom silicon, being able to implement some of these newer ideas about interaction modes?
Especially in the wearables segment, where you’re pushing on miniature, on power, on sensing.
30 Jul 2020 · via @andrepaulj 🐦
André-Paul on twitter quoting Elad Gil:
One sign of raw product-market fit is when something has grown despite itself.
I love @eladgil’s definition of PMF because it really emphasizes the need to resist perfecting your product until you know that you’re building the right thing.
30 Aug 2018 · via Slack & Flickr: Stewart Butterfield – How I Built This with Guy Raz 🎙
In a conversation with Guy Raz (transcript), Stewart Butterfield tells the story of how Slack was born. Besides the great insights on product-market fit, it is also an amazing plot — full of spectacular ups and heartbreaking downs.
They started out around 2009 and the intent was to create a multiplayer online game. The conditions seemed perfect:
Guy Raz: So what did you do when you walked out of Yahoo? What was your plan?
Stewart Butterfield: There wasn’t an immediate short-term plan. But it didn’t take long for a lot of the same people who worked on Flickr and had worked on the previous game to decide that we wanted to work on the game again.
Guy Raz: You wanted to go back to gaming? You didn’t learn your lesson the first time around?
Stewart Butterfield: Yeah, we apparently didn’t. I mean, so the world looked pretty different at that point. So now it’s the beginning of 2009. There was at least an order of magnitude more people online, whereas, in 2002, the majority of people didn’t have Internet access at home. Now the majority did. Computers are way faster. All the hardware was way cheaper. Online games were something that was really popular. And so we figured, like, oh, this time we can’t fail.
There is — you know, all of the conditions are perfect, so we should do this.
There was me and three of the engineers, and what we decided to do it, which was called the Glitch. It was completely different than anything that anyone had ever seen before.
This game — it was a bizarre, fantastical world — really tried to encourage individual creativity. People could create stuff inside the world. You would milk butterflies in order to get butterfly milk, and eggs grew on trees. And the look was kind of Dr. Seuss meets Monty Python meets modern-day graphic novels. As you moved around the world, the look changed dramatically.
Guy Raz: So you had a track record with Flickr. Like, you already had a reputation. You’d been on the cover of Newsweek. You’d worked for Yahoo. So when it came time to raise money, was it pretty easy?
Stewart Butterfield: Yeah, absolutely. It was very easy for us to raise money. And so we started off with you know, a million and a half dollars. We were able to hire someone. We were able to afford all the technology we wanted.
As they began developing the Glitch, they faced a crucial point: there was a niche of people very interested in the product, but, despite a lot of effort, they never managed to improve their metrics with a broader audience.
Stewart Butterfield: And as we started developing the game, we had a bunch of really positive early indications. So we charged people money, and they were — they paid a lot, you know? Like, the average person who paid was paying $70 a year.
Guy Raz: And this is, like 2010, 2011, something like that. And people are already paying for it. It was that good?
Stewart Butterfield: Well, it was that good for a very small population. In fact, it was really hard for us to get people even to go through the first few minutes of the game because it was just so different and so weird. Most people who tried it were — what the hell is this? And just pass out in the first three minutes of gameplay.
Guy Raz: All right. So you guys launch this thing. There’s some early success. You raise lots of cash. And then November of 2012, you shut it down. What happens?
Stewart Butterfield: Well, being in business, and I think especially being a CEO requires a lot of unnatural optimism.
And at some point, that optimism was exhausted. We had what’s called a leaky bucket. People would come in the top of the funnel. And the funnel is kind of describing: first people hear about your thing, then they go to the website, then they sign up, then they in our case, play the game a little bit, then they end up paying you. And in each of those stages, some people fall out of the process. So, that’s why it’s called the funnel. The leaky bucket is when you get people in the top, but they just fall out. They fall out the process too early. Not enough of them make it all the way through.
Guy Raz: They didn’t stick with it.
Stewart Butterfield: Yeah, they didn’t stick with it. And it was always the next thing that was going to fix it. Like, the next game dynamic we added, the next bit of customization, the next thing, the next thing, the next thing. But as we continued to try those things, we just never found that magic formula that would make it work economically.
It would have been a fine, what people call, lifestyle business. But it was never going to become the kind of business that would justify $17.5 million of venture capital investment.
This is a very important learning: fixing leaky buckets is extremely hard. This matches with my own experience building software products for consumers. There is also the good reminder that, in the context of venture-backed business, you aim big and try to get there as fast as you can.
Back to Raz and Stewart:
Guy Raz: So at what point did you come to the decision to shut it down?
Stewart Butterfield: I was losing a lot of sleep in those days. It was like 2 or 3 in the morning. And I was in bed. And I hadn’t been sleeping for hours. And I just realized, like, I don’t believe this can work. Like, I don’t believe it anymore.
There’s a saying — if you’re thinking about firing someone a lot, you should just fire them. That intuition — if that keeps coming up, it’s almost certainly correct. And you wouldn’t be thinking that all the time if there was a real shot at making the relationship work.
I think it’s exactly the same thing with a business. Once I began not to have little doubts, but once I hit a fundamental level, I was just, like, I don’t think this is going to work. It’s not going to work. So, you know, first thing that morning, I wrote to all the co-founders and then to our board of directors and just said, it’s over. And that definitely was not a unanimous point of view. And there was a lot of contention... And argument, and... Because we had developed an enormous amount of kind of equity.
Guy Raz: Content — you had content, tons of content.
Stewart Butterfield: Yeah, millions of frames of animation, hundreds of hours of original music.
Guy Raz: So how did you break the news to the team? I mean, they must have been - it must have been excruciating.
Stewart Butterfield: Yeah, it was a horrible experience. And I say, we’re going to have an all-hands meeting. And everyone, you know, files in and gets together. People have their coffee in the morning, and they’re chitchatting. And finally I stand up. The meeting starts, and I start to tell them that we’re going to shut down the game. Before I could even get the first half of the sentence out, I was crying.
You know, almost everyone in the room I had personally convinced that they should come work in this company, that they should accept our stock options, that they should believe in the project, that they should believe in me. It’s humiliating. There’s a real sense that I had failed all these people…
That I had an obligation to them. And I was — I had locked eyes with this one software engineer who had just three months before moved. He had an infant daughter, maybe 6 months or a year old. He was moving away from his in-laws, who were helping take care of the kid, moving to a new city with his whole family, and now I was telling him he didn’t have a job anymore.
I will now fast-forward the story several months because, here and now, I am focused on product-market fit.
Once you have the time, you should listen to the whole episode. He tells how they returned to a very small team, how they decided to transform the communications tool they’ve used internally into a new company that became Slack, how difficult it was to sell other people and companies on Slack in the early days, how their distribution strategy of enterprise software was very unconventional (and hard for VCs, like a16z to get their heads around it), and so on.
Back to Stewart telling what were clear signals of Slack’s product-market fit:
Stewart Butterfield: Well, so by the time we officially launched, it was evident that this was going to be something. The leaky bucket problem that I talked about in the context of the game was completely eliminated.
We found that once people started using it — as hard as it was to get people to start, once they started, they almost never stopped. At that point, people weren’t paying us. They were just using it for free.
But we could see that they were getting utility out of it. They were logging out at the end of the day, and first thing in the morning they were right back in there.
Guy Raz: So you launch in February of 2014 officially. It goes out into the app store or whatever and into the world?
Stewart Butterfield: Yep. We also told other people who had been using it for free, like — hey, now you’re going to have to start paying. We’ll give you a nice, healthy credit to thank you for being one of our early testers.
And we found the conversion was excellent. You know, within maybe two or three weeks of launching that officially, we had sold a million bucks’ worth of Slack.
It costs $80 per person per year. So you would pay — you would only pay for the people who are actually using it. So if you have a 50-person company and there are 20 people using it, then you just pay for 20 people.
We were off to the races. Unlike almost any enterprise software ever, people would talk about it. Like, they would be in line at the coffee shop, and they would say, oh, my God, you’ve got to start using Slack. It’s amazing. It changed my life. And they would post to Twitter and say, like, I — you know, I recommend it. And that — you know, no one ever says that about the software that they have to use at work.
Guy Raz: It’s amazing. By October of 2014 — so this is just two years after you shut down Glitch and, like, have to break the news to all these people — you raise 120 million bucks. It has a $1.2 billion valuation. I mean, that’s nuts. That’s totally insane.
Stewart Butterfield: Yeah. It was completely insane. And, you know, at that same period, we’re still growing, like, somewhere between 5 and 10 percent a week.
What a ride.
Steve Jobs was interviewed by Nick Wingfield in early August 2008 about the iOS App Store. At the time the marketplace for iPhone apps was just one month old.
It is obvious in 2018 — ten years later —, how big of a winner the App Store is. It is more interesting though to realize that Steve was already very aware of the hit he had in his hands. I believe he was able to grasp it at such early stage because of a product-market fit sense he had developed.
For anyone intending to build successful consumer products, it seems wise to hone in our abilities and pay close attention to his train of thought.
He starts the interview by explaining how the App Store was built on top of iTunes:
Steve Jobs: The way we think about this is that the App Store is to iPhone like iTunes is to iPod. Just like with the iPod, where we enhanced it with an internet service to bring content to it, we’re doing the same thing with the iPhone. We’re enhancing it with an internet service to deliver content right to the phone.
It’s built on the same iTunes infrastructure, including all the storage and all the billing and getting email receipts and all of that kind of stuff. The downloads are fast and reliable because it’s the same system as iTunes. Customer reviews, buying with one tap, just like one click on music and stuff. No one’s ever duplicated iTunes in over five years. This’ll be even harder because it’s built on top of it.
He then talks about the early numbers of the App Store:
Steve Jobs: We have over 1,500 applications on the App Store today. We thought that the input would start to slow down from developers, but it’s accelerating.
My gut is that we’re seeing around 50 new apps a day coming in. As I mentioned, over 1,500 apps, 27% of them are free, leaving 73% paid. Of the paid apps, over 90% are under $10.
What you really want to know is how many apps have been downloaded. I'm going to put everything in terms of next Monday because we can project very accurately, over 60 million apps. Users have downloaded over 60 million apps from the App Store in the first 30 days.
Nick Wingfield: What’s the installed base of iPhones? The last publicly released figure was six million.
Steve Jobs: I can’t give you a number because we’re in the middle of the quarter.
I’ll tell you. The total revenue has been $30 million in the first 30 days. Developers get 70% of that. Developers get $21 million. Nine of that $21 million is going to the top 10 developers. A lot of small developers are making a lot of money. This is just in the first month.
We actually were putting the number of downloads on every app initially, if you went and look but we were asked to take that down [by the developers].
He talks next about how app downloads were growing much faster than music downloads (recall that the iTunes Store was a big success in the 2000s):
Steve Jobs: I can tell you an interesting fact in just a second. That is 30% as big as iTunes for music downloads. Let me say that again. App downloads equal 30% of all iTunes song downloads during the last 30 days.
Nick Wingfield: What does that number say to you?
Steve Jobs: It says the App Store is much larger than we ever imagined, iTunes has been out for over five years. In 30 days, users downloaded 30% as many apps as everybody in the world downloaded songs from iTunes. We didn’t expect it to be this big. The mobile industry’s never seen anything like this. To be honest, neither has the computer industry. [laughs] 60 million downloaded applications in the first 30 days. 30% as big as iTunes song downloads during the last 30 days, this is off the charts.
He then foresees the huge growth that would come from the expansion of the iPhone user base. He also mentions that small developers were already seizing the opportunity:
Nick Wingfield: Is it concentrated to a percentage of your user base, would you say, or…
Steve Jobs: It appears to be very wide, yeah. I have met a few people who had bought 30 apps. Everybody I know that has an iPhone has bought a handful and enjoys it.
Music is a $2.5 billion dollar business a year for us. I think we’re not quite in the same league as music, but I think this is really significant. Who knows, in the fullness of time? I don’t know.
Remember, we’re on a ramp. There’s going to be even a lot more iPhones out there in the future and a lot more iPod touches. We’re already at a $360 million a year run rate. This thing is going to crest to half a billion soon. Who knows? Maybe it’ll be a billion dollar marketplace at some point in time. This doesn’t happen very often. A whole new billion dollar market opens up. 360 million in the first 30 days, I’ve never seen anything like this in my career for software.
Let me characterize what I’ve seen with my own eyes that’s happened in the last 90 days. I’ve seen one- or two-person teams develop amazing applications and they’re ready to go in less than 90 days, and that are up on the App Store—we’re running an average of 48 hours after submission and they’re up in the store. 48 hours after they submit, they are in front of millions and millions of customers.
Being at the epicenter of the mobile explosion, Jobs was even able to foresee the potential of mobile games:
Steve Jobs: There’s only one other thing that’s interesting to me, the largest category of apps, by no means the majority, but the largest category of apps is games. You’ve got everything from games to medical software to business analytics software to all sorts of stuff on it, but games is the single biggest category.
I did dig up some information on the mobile gaming market for myself. I’ll share it with you. 20 million handheld gaming players are expected to be sold this holiday season, for about $3 billion in revenues.
This is the No. 1 and 2 are the Nintendo DS and the Sony PSP. We’ve got two contenders for that. We’ve got the iPhone, which costs zero if you have it as a phone, zero incremental to have it as a game player. Then we’ve got the iPod touch, which currently sells for $299, but who knows what could happen over time there.
On the Nintendo and Sony, the average game title, at the street level, costs $30. Our average game title’s less than 10, some are free. It’s delivered instantly right on your device, which of course is not the case with these other guys.
I actually think the iPhone and the iPod touch may emerge as really viable devices in this mobile gaming market this holiday season.
Nick Wingfield: Do you think we should look for advertising that stresses this message?
Steve Jobs: I don’t know. I just find it very interesting.
Nick Wingfield: Is gaming something that Apple has a lot of experience with, do you think?
Steve Jobs: No, I don’t, except that we sure delivered a lot of games in the last 30 days.
No, we thought games would be a part of it, but I’ve always been excited about Epocrates and some of the medical apps. There are people that are excited about this category, that category.
He also pointed out that mobile was a serious contender to desktop — which was the major software platform at the time:
Nick Wingfield: Facebook is doing an app for BlackBerry.
Steve Jobs: Yeah, but if you go talk to them, the best one by far is on the iPhone, so I’ll take that.
Nick Wingfield: How much of the traffic to a site like Facebook might come from iPhone? [Ask] any of these guys… because I know Google I think has talked about iPhone being the No. 1, by far, mobile search product.
Steve Jobs: By far. And bought mobile maps and everything, Facebook would tell you. I believe if you talked to Facebook they would also tell you some statistics that are similar to that on the iPhone Facebook app.
Nick Wingfield: If you looked at overall traffic…
Steve Jobs: How serious will mobile be relative to desktop is your question. I think there are a lot of people and I’m one of them who believe that mobile’s going to get quite serious because there are things you can do... Obviously, mobile’s with you all the time, but there are services you can provide with mobile that obviously are not relevant on a desktop, such as location-based services integrated into your application.
They can be mighty useful and we’re just at the tip of that. That’s going to be huge, I think.
Finally, it is kind of comforting to see that he did get some things wrong. Predicting the future is very hard, after all:
Nick Wingfield: I think you guys have said that you see the iPod that’s sort of stand-alone MP3 player evolving into a wireless-enabled device.
Steve Jobs: I think there’s going to be two kinds of devices in the music space. One is going to be just the pure evolved music device. People want it for music, maybe music videos, maybe an occasional movie, but they really want it for music.
That would be a device that just keeps evolving, getting better.
As we all know today, there is no such a thing as a “pure evolved music device”, the iPhone has eaten them all.
30 Aug 2018 · via Elad Gil – How to Identify Interesting Markets – [Invest Like the Best, EP.101] 🎙
He is a famed angel investor, who has experienced first-party what success in tech startups looks like. In my mind, although he hasn’t framed it that way in the interview, he clearly is enumerating (in points #2, #3 e #4) ways to spot product-market fit.
Elad Gil: If I look back at data in terms of what has actually worked in the set of companies I’ve invested in —
1. They have launched a product or at least had a crappy demo when they started raising money
And if the fact that they actually build something, even if it was awful, showed a mentality of going and building. So that’s one key thing. Just investing on a PowerPoint deck tends not to work well. Although I think I invested in OpenDoor and Wish before they had much built. But even then there was sort of something going on.
2. Organic growth, even if it's a very small base
Most early-stage investors really discount early tractions. They say, “well, that went from 100 to 120, to 150 over 2 or 3 months. Is that real?” But in reality, if something is growing 20-30% a month organically, just through word of mouth, usually there may actually be something there. So I think that’s a clear sign, even if it’s tiny numbers.
3. On the enterprise/SaaS side, 1-2 major brands are using them that just found them randomly
That’s usually a very good sign. When I invested in PagerDuty, which is now a very successful company on the Ops/Infrastructure side, they had, I believe, Amazon and Apple as their customers. I don’t know if they still do, but, you know, they 7-8 years ago they did. They didn’t have a sales force, it was just 4 engineers. They were just getting traction because the product was so good that random people at big companies were finding it and adopting it, even if they were sort of overruling their own internal IT to do it.
4. Utilization, even if the product is really broken
If something looks really janky — and, you’re like, how can anybody use this? — but people are still using it, there’s usually a very good sign. I’d say, for example, Snapchat in their early days was kind of like that. Most people even in that demographic didn’t get it and it was still just working, even though the UI was kind of rough, and tough to get into and everything else.
I mean, there are other obvious criteria, like talking to customers and seeing if there’s real traction, or looking at metrics, like negative churn. But in terms of the things that were just high-level data that I normally wouldn’t have looked at, those are the things that in hindsight really correlated.
Later in the same conversation, he adds another key point on product-market fit that may sound counter-intuitive to many people — but it does match with my own experience:
The other non-intuitive item is: in general, things that work tend to work early.
You always talk about people grinding for 5 years until it finally works. In enterprise or in highly regulated areas, where it takes time to build a product, that’s very true. But in many cases, if people need the product, the second the product is available, it kinds of starts moving.
You need to do some iteration to really get to escape velocity. But at least the very biggest things tend to work early.
30 Aug 2018 · via How to Find Product Market Fit – Dorm Room Tycoon Podcast 🎙
William: Let’s talk about the basics. What is product market fit? We hear this term a lot.
Andy: I coined it. I don’t know if you knew that, but I’m the one who coined the term.
William: Amazing. I never knew that. Where did that come from? What epiphany did you have?
Andy: Well, it came from an observation of what led to the success or failure of my portfolio companies. I noticed over the years that another firm called Sequoia Capital — with whom we often co-invested and often competed as well — did an amazing job of focusing on this subject.
Now, I’m not sure they use the term product-market fit to describe it, but their founding partner Don Valentine used to say: “I want to invest in companies that can still succeed if they screw everything up when it comes to execution because the pull from the market is so strong”.
And that is what I define as product-market fit: when the customers want your products so badly that you can screw everything up and still succeed.
William: So, word-of-mouth is how you grow. But what are your channels?
Andy: We’re almost exclusively organic and therefore almost exclusively word-of-mouth. We institutionalized word-of-mouth with our the incentivized invitation system — and we also have physical word-of-mouth. Those two drive probably 75% of our new client growth.
The reason that we get word-of-mouth is that if you delight your customers they’re going to tell their friends. So I think delight is the greatest form of virality.
I’m not a big fan of paid marketing because I think that it always gets arbitraged away. I’d rather invest in building delight than in something that gets arbitraged.
William: How do you know when you have something delightful?
Andy: Well, at least for us, we see it in a couple of ways.
Number one. People add more money to their accounts. So, in our case, you make an initial deposit, probably to test out what we do, and if you have a good experience with it you’re likely to continue to add money as you save.
As I said before, we focus on people who are under 40, they are in the wealth accumulation phase of their lives versus the wealth preservation phase of their lives. And, as they make more money and save more money, we hope they’re going to keep giving us more money, but they’re only going to do that if they’re delighted.
And they’re only going to invite their friends if they are delighted. So, we track the rate at which people and on deposits and invite their friends.
Now, by the way, you asked me in the beginning of the show: How do you know if you have product-market fit? Or what is product-market fit?
A question that I’m often asked is: How do you know when you have product-market fit? And the best answer that I can give you is: when you have exponential organic growth.
You can fake growth by buying it. But, let’s say you buy a customer, but then they don’t stay with you, they churn. That’s not real growth. So I’m not a big believer in buying growth, because you can’t really tell if you’ve achieved product-market fit.