Why Slack may be worth $20 Billion by 2020. Signals from Occulus, Github, Bitcoin and Stripe.
I wrote recently about how Bitcoin and Stripe are examples of technology success stories that may have been relatively predictable due to an early consensus among developers. Paul Graham was one of the first to popularise this idea with his article Return of the Mac. Are there other examples of this? If developers flock to a certain technology, is it a sure thing in terms of success?
There are many stories about the homebrew computer club as a precursor to the popularity of the home computer. But anecdotally it wasn’t obvious that Microsoft and IBM would be the main winners.
I had previously used Hacker News as an unscientific way to get a sense for these emerging technologies or companies that had a developer consensus. Y combinator now release their application data which provides a useful guide to what is ‘hot’ in Silicon Valley at least. Unsurprisingly VR, AR and Machine Learning have become popular.
In terms of companies that provide platforms, unscientifically, Slack has emerged as the most visible in the last year. The same may have been said for Github at one stage, with a strong developer surge of enthusiasm. Slack had a valuation of 3.8B around last round of funding. It will be interesting to see if it IPO’s or raises a bigger round, particularly as the funding environment has become more challenging.
There is a possibility that Y Combinator applicants have become more of a reflection of market trends than a signal. The book Superforcasters highlights that predictions need to be specific to be useful. They also need to be independently observed which is hard to ensure in an industry that can be an echo chamber. Having said that, many applicants to YC are risking their time on projects in this area so it may have some signal. Risking your money might be a better predictor.
When Oculus launched it was crowdfunded and a lot of early adopters were right in predicting that the technology was ready to breakout. Unfortunately due to the lack of an app coin, or crowdsale of shares the only people who benefitted were VCs. Erik Voorhees discusses this on the Bitcoin Epicentre podcast. If the regulations around this change, we may see more early adopters providing signaling and investment.
Another way to find this signaling might just be to follow those who have been contrarian and right in the past, and who express their predictions clearly on Twitter. By their very nature they have been able to resist public sentiment and persist with their theory until the were proved correct. A few examples would be:
Paul Graham. - , Apple’s resurgence, rise of angel investors
Naval Ravikant - Rise of Angel investors, Twitters success.
David McWilliams- Irish Property Crash
Robert Shiller - US property crash
Peter Thiel - Tesla, Paypal, Stripe, Palantir
Scott Adams - Trump will become president. Predicted before the primaries.
The ability to curate thoughts from these people on twitter may prove to be very useful if you could compile enough of them and use something like Nuzzel to distill some consensus. The danger is that they may only have been correct in the past and that provides no future potential. Also that they don’t stick to very specific timelines on their preditions so again you get nothing concrete to work with.
We know from that data around Venture Capital exits that there is a Power Law distrubution of outcomes. Which seems to disprove the idea that some companies like Stripe were destined for big things. But if you were to ask the early investors to put a probability on their potential for a $1B+ valuation, I suspect it would have been in the 50%+ range which is way off the average odds for success at angel investment level. The early Occulus backers felt the same way. Maybe crowdfunding, and superforecasters will eventually combine to create much more obvious signaling that was previously thought possible.
I give this prediction an 80% chance of success.
I wrote recently about how Bitcoin and Stripe are examples of technology success stories that may have been relatively predictable due to an early consensus among developers. Paul Graham was one of the first to popularise this idea with his article Return of the Mac. Are there other examples of this? If developers flock to a certain technology, is it a sure thing in terms of success?
There are many stories about the homebrew computer club as a precursor to the popularity of the home computer. But anecdotally it wasn’t obvious that Microsoft and IBM would be the main winners.
I had previously used Hacker News as an unscientific way to get a sense for these emerging technologies or companies that had a developer consensus. Y combinator now release their application data which provides a useful guide to what is ‘hot’ in Silicon Valley at least. Unsurprisingly VR, AR and Machine Learning have become popular.
In terms of companies that provide platforms, unscientifically, Slack has emerged as the most visible in the last year. The same may have been said for Github at one stage, with a strong developer surge of enthusiasm. Slack had a valuation of 3.8B around last round of funding. It will be interesting to see if it IPO’s or raises a bigger round, particularly as the funding environment has become more challenging.
There is a possibility that Y Combinator applicants have become more of a reflection of market trends than a signal. The book Superforcasters highlights that predictions need to be specific to be useful. They also need to be independently observed which is hard to ensure in an industry that can be an echo chamber. Having said that, many applicants to YC are risking their time on projects in this area so it may have some signal. Risking your money might be a better predictor.
When Oculus launched it was crowdfunded and a lot of early adopters were right in predicting that the technology was ready to breakout. Unfortunately due to the lack of an app coin, or crowdsale of shares the only people who benefitted were VCs. Erik Voorhees discusses this on the Bitcoin Epicentre podcast. If the regulations around this change, we may see more early adopters providing signaling and investment.
Another way to find this signaling might just be to follow those who have been contrarian and right in the past, and who express their predictions clearly on Twitter. By their very nature they have been able to resist public sentiment and persist with their theory until the were proved correct. A few examples would be:
Paul Graham. - , Apple’s resurgence, rise of angel investors
Naval Ravikant - Rise of Angel investors, Twitters success.
David McWilliams- Irish Property Crash
Robert Shiller - US property crash
Peter Thiel - Tesla, Paypal, Stripe, Palantir
Scott Adams - Trump will become president. Predicted before the primaries.
The ability to curate thoughts from these people on twitter may prove to be very useful if you could compile enough of them and use something like Nuzzel to distill some consensus. The danger is that they may only have been correct in the past and that provides no future potential. Also that they don’t stick to very specific timelines on their preditions so again you get nothing concrete to work with.
We know from that data around Venture Capital exits that there is a Power Law distrubution of outcomes. Which seems to disprove the idea that some companies like Stripe were destined for big things. But if you were to ask the early investors to put a probability on their potential for a $1B+ valuation, I suspect it would have been in the 50%+ range which is way off the average odds for success at angel investment level. The early Occulus backers felt the same way. Maybe crowdfunding, and superforecasters will eventually combine to create much more obvious signaling that was previously thought possible.
I give this prediction an 80% chance of success.
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