Steve Chen Quotes

I had several friends from law school who were very enterprising guys, much more so than the average law student. They each started businesses after practicing law at large firms for multiple years. What kind of businesses did they start? They started boutique law firms. This is completely unsurprising if you think about it. They’d spent years becoming good at delivering legal services. It was a field that they understood and could compete in. Their credentials translated too. People learn from what they’re doing and do it again on their own. It’s not just lawyers; the consulting firm Bain and Company was started by seven former partners and managers from the Boston Consulting Group. Myriad boutique investment banks and hedge funds have spun out of large financial organizations. You can see the same pattern in the startup world. After PayPal was acquired by eBay in 2002, its founders and employees went on to found or cofound LinkedIn (Reid Hoffman), YouTube (Steve Chen, Jawed Karim, and Chad Hurley), Yelp (Russel Simmons and Jeremy Stoppelman), Tesla Motors (Elon Musk), SpaceX (Musk again), Yammer (David Sacks), 500 Startups (Dave McClure), and many other companies. PayPal’s CEO, Peter Thiel, famously made a $500,000 investment in Facebook that grew to over $1 billion. In this sense, PayPal is one of the most prolific companies of recent times. But if you look at any successful growth company you’ll start to see their alumni show up doing parallel things. Former Apple employees founded or cofounded Android, Palm, Nest, and Handspring, companies that revolve around devices. Former Yahoo! employees founded Ycombinator, Cloudera, Hunch.com, AppNexus, Polyvore, and many other web-oriented companies. Organizations give rise to other organizations like themselves.

As I’ve said throughout this book, networked products tend to start from humble beginnings—rather than big splashy launches—and YouTube was no different. Jawed’s first video is a good example. Steve described the earliest days of content and how it grew: In the earliest days, there was very little content to organize. Getting to the first 1,000 videos was the hardest part of YouTube’s life, and we were just focused on that. Organizing the videos was an afterthought—we just had a list of recent videos that had been uploaded, and you could just browse through those. We had the idea that everyone who uploaded a video would share it with, say, 10 people, and then 5 of them would actually view it, and then at least one would upload another video. After we built some key features—video embedding and real-time transcoding—it started to work.75 In other words, the early days was just about solving the Cold Start Problem, not designing the fancy recommendations algorithms that YouTube is now known for. And even once there were more videos, the attempt at discoverability focused on relatively basic curation—just showing popular videos in different categories and countries. Steve described this to me: Once we got a lot more videos, we had to redesign YouTube to make it easier to discover the best videos. At first, we had a page on YouTube to see just the top 100 videos overall, sorted by day, week, or month. Eventually it was broken out by country. The homepage was the only place where YouTube as a company would have control of things, since we would choose the 10 videos. These were often documentaries, or semi-professionally produced content so that people—particularly advertisers—who came to the YouTube front page would think we had great content. Eventually it made sense to create a categorization system for videos, but in the early years everything was grouped in with each other. Even while the numbers of videos was rapidly growing, so too were all the other forms of content on the site. YouTube wasn’t just the videos, it was also the comments left by viewers: Early in we saw that there were 100x more viewers than creators. Every social product at that time had comments, so we added them to YouTube, which was a way for the viewers to participate, too. It seems naive now, but we were just thinking about raw growth at that time—the raw number of videos, the raw number of comments—so we didn’t think much about the quality. We weren’t thinking about fake news or anything like that. The thought was, just get as many comments as possible out there, and the more controversial the better! Keep in mind that the vast majority of videos had zero comments, so getting feedback for our creators usually made the experience better for them. Of course now we know that once you get to a certain level of engagement, you need a different solution over time.

When examined through the lens of Meerkat’s Law and the central framework of this book, it is obvious why the resulting networks generated by big launches are weak. You’d rather have a smaller set of atomic networks that are denser and more engaged than a large number of networks that aren’t there. When a networked product depends on having other people in order to be useful, it’s better to ignore the top-line aggregate numbers. Instead, the quality of the traction can only be seen when you zoom all the way into the perspective of an individual user within the network. Does a new person who joins the product see value based on how many other users are already on it? You might as well ignore the aggregate numbers, and in particular the spike of users that a new product might see in its first days. As Eric Ries describes in his book The Lean Startup, these are “vanity metrics.” The numbers might make you feel good, especially when they are going up, but it doesn’t matter if you have a hundred million users if they are churning out at a high rate, due to a lack of other users engaging. When networks are built bottom-up, they are more likely to be densely interconnected, and thus healthier and more engaged. There are multiple reasons for this: A new product is often incubated within a subcommunity, whether that’s a college campus, San Francisco techies, gamers, or freelancers—as recent tech successes have shown. It will grow within this group before spreading into other verticals, allowing time for its developers to tune features like inviting or sharing, while honing the core value proposition. Once a new networked product is spreading via word of mouth, then each user is likely to know at least one other user already on the network. By the time it reaches the broader consciousness, it will be seen as a phenomenon, and top-down efforts can always be added on to scale a network that’s already big and engaged. If Big Bang Launches work so poorly in general, why do they work for Apple? This type of launch works for Apple because their core offerings can stand alone as premium, high-utility products that generally don’t need to construct new networks to function. At most, they tap into existing networks like email and SMS. Famously, Apple has not succeeded with social offerings like the now-defunct Game Center and Ping. The closest new networked product they’ve launched is arguably the App Store, but even that was initially not in Steve Jobs’s vision for the phone.87 Most important, though, you aren’t Apple. So don’t try to copy them without having their kinds of products.