I am in the Elon Musk fan club. It’s hard not to be in awe of what he’s achieved – four multi-billion dollar companies and he’s only in his forties. I’ve even read his biography, not something I’ve done for many people.
Lots has been written about why he is successful, mostly focused on his drive, vision, tenacity, resilience and intelligence, but I happened on a post morning which highlighted something that was new for me. Forbes columnist Michael Sims was seeking to understand how he has been successful across a wide range of very different industries – auto, space travel, energy and software.
The answer, he believes, is that Elon Musk is an expert-generalist:
Expert-generalists study widely in many different fields, understand deeper principles that connect those fields, and then apply the principles to their core specialty.
That struck a chord with me because that is what good venture capitalists do. In his book The Second Bounce of the Ball, Ronald Cohen, who has a good claim to being the first true VC here in the UK, wrote:
[investors] have to be financially trained and to have an understanding of management, but you also have to have a strategic brain while being sensitive to tactical and people issues
To that I would add empathy, patience, grounding, creativity and hustle. So we have to be generalists in that sense. Then on top of that we need to master multiple areas of investment – at least if you are to have a long career. In my seventeen years in this industry, I have invested in enterprise software, semiconductors, SaaS, social media, adtech, and ecommerce across multiple sectors. That has required a lot of reading! Then right now I am getting to grips with Bayesian Networks, Hidden Markov Models, Convolutional Neural Networks and back propagation as Forward Partners investigates whether to have a big push in what we are currently calling “Applied AI”. Further, all of this applies across multiple industries, from fintech to fashion to healthcare (one of my colleagues is up to his neck in microbiome research as we speak).
You can see the need to be an expert-generalist.
All this begs the question of how one becomes an expert-generalist, or if you are already an expert-generalist, how you become a better one.
The answer is to get good at learning. Fortunately Sims spells it out for us. Here is what he describes as Musk’s two stage process for learning:
- Grasp the fundamental principles
- Reconstruct those fundamental principles in new fields
There are no short cuts here. Musk used to read 60 books per month. But when, and only when, you understand the fundamentals you can more quickly learn and apply things in new areas. Returning to AI – Bayesian Networks are much easier to understand if you grasp the fundamentals of statistics, and once you grasp the fundamentals of Bayesian Networks (and all the other components of AI) it is much easier to understand where they can be successfully employed and where they can’t. Similarly with regard to human behaviour, a solid grasp of behavioural psychology makes it easier to predict how people will react to new products and services.
And getting good at learning isn’t just important for VCs. It’s important for everybody. The world is changing so fast now that one area of knowledge is most unlikely to be enough to build a career. A quick look at this Wikipedia article on the history of programming languages shows what developers have to deal with, but something similar is true for just about everyone else.
As a keen observer of startups over the last 17 years, one of the most remarkable and welcome developments has been the application of scientific method to building startups. In 1999 when I started in venture capital there were no blogs and very few business books that were useful for entrepreneurs. All founders could do was accumulate wise advisors and rely on their wits and instinct.
If I was to pick a watershed moment in the emergence of ‘entrepreneurship as a science’ it would be the publication of Steve Blank’s Four Steps to the Epiphany in 2005. It’s not the easiest read, but for the first time founders had a playbook they could follow. However, it was also around that time that Brad Feld, Fred Wilson and a number of other wise souls started blogging and startup best practices started to be widely shared.
There were two great things about that. Firstly sharing leads to discussion and discussion leads to iteration, making everybody involved smarter. Thus it was that Eric Ries both extended Blank’s work and made it more accessible with the publication of The Lean Startup in 2011. Secondly, people outside of Silicon Valley were able to join in the conversation and get smarter to a much greater extent than they ever had been before which was a massive boon to other startup ecosystems around the world, including London.
Here at Forward Partners we have worked hard to contribute to this development by publishing The Path Forward – a playbook and set of practical guides for founders in their first year or two.
All this work has, I think, made it easier for founders to climb the learning curve and become masters at running their companies. It’s easier to know about and avoid common pitfalls (e.g. assuming you know what customers think) and to pick up tactics and best practices (e.g. OKRs for managing objectives). Of course, that doesn’t mean it’s now easy to be founder, far from it, but it is easier than it was.
However, building a startup can never be reduced to pure science. Some magic, art and wit is always required. I was talking to the chairman of one of our companies a year or so back (I won’t name him for reasons that are about to become obvious) as he was helping them through a rebuild of their product. The founder is a disciplined practitioner of lean startup principles who had achieved good growth through lots of experimentation and optimisation, but they had got stuck. They had hit a local maxima. The chairman explained how they had over indexed on startup science and ended up with a product that was boring. They needed more soul.
This story has a happy ending; they rebuilt the product and are now growing fast once again, but it is a reminder that there needs to be a balance between the disciplined application of startup best practice and inspiration.
I’m writing this today because whilst reading Are Liberals on the Wrong Side of History in The New Yorker I was struck by the similarity between the recent evolution in startup thinking and the way The Enlightenment impacted western thought in the eighteenth century. I don’t have the deepest grasp of the history of philosophy, but it was during The Enlightenment that thinkers like Descartes, David Hume, Adam Smith, and Immanuel Kant had the great rationalist vs empiricist debate which developed the concept of the scientific method, introduced the idea that everything might be explainable through thought and rules, and then hotly debated the limitations of that approach to understanding the world.
As The New Yorker points out, you can, in fact, trace this debate back to the ancient Greeks with Plato on one side and Aristotle on the other, so the rationalist vs empiricist debate has actually been running for millennia.
When I was an under graduate studying social science in the 1990s I had a good run synthesising the work of the leading thinkers of the time across sociology, political science, social psychology and social anthropology. It worked for me then and I find myself repeating the pattern here. When there is a significant change in society then the pendulum almost always swings too far, whilst what we really need is to find the right balance. During the great debates of The Enlightenment in a sense both sides were right. It is beyond doubt that rationalist thought and the scientific method brought great advances to our understanding of the world and many great things flowed from that, including the liberal-capitalist system which has given us unprecedented individual freedom and prosperity. However, there are still many things that we don’t understand from first principles where all we can do is treat them like a black box developing predictions for what will happen next based on what we’ve seen in the past without understanding the underlying workings – the human brain is one example, and the workings of the economy being another (hence our difficulty understanding the impact of Brexit).
Returning to startups (and this is a bit of a stretch, but bear with me) – Steve Blank and Eric Ries can be likened to Descartes and other early enlightenment thinkers from the rationalist camp who achieved great advances by using scientific method to shine light into areas that had previously relied upon intuition and rules of thumb. The next step is to balance that thinking with the an approach that can be likened to the work of David Hume who pushed back on the rationalists noting that great insights can also be had by drawing on our experiences.
Throughout his career Steve Jobs famously eschewed market research and relied on his intuition to build amazing products. That’s an extreme position which worked for him, but doesn’t work for most of. The balance I’m talking about cultivates that sense of intuition but then finds ways to quickly and cheaply test the resulting ideas with customers. Now that we are in an era where our basic needs are sated MVPs need to be increasingly sophisticated before customers will engage. That means more investment in development before ideas can be tested than was the case ten years ago, increasing the cost of failure (hopefully not too much) and thus making it more important that only good ideas are tested (again, hopefully not too much). Hence the point of balance is shifting. At the margin the value of good intuition is increasing and the value of disciplined application of lean startup principles is decreasing.
The pendulum is starting to swing back the other way.
Unless you’ve been hiding under a rock, you will have noticed there’s a lot of heat around AI as an investment theme right now. Octopus’s recent announcement of a £120m dedicated AI fund is one of many recent events I could cite as evidence.
In that same announcement Octopus mention that they have had three AI exits (Swiftkey, Magic Pony and Evi) so this is not a new investment trend.
It is, however, a trend that is changing. Up until this point AI exits have largely been driven by a desire to acquire talent. Even Deep Mind’s $400m sale to Google in 2014 is, I think, best understood as an acqui-hire.
Going forward two things will be different. Firstly, universities have responded to the demand for AI PhDs. Hence talent will be less scarce going forward and acqui-hires will be less necessary.
Second, and perhaps more interesting, is that it’s becoming much easier and much cheaper to build AI driven products and we are seeing an explosion in the number of AI startups with a clear path to delivering value to their customers and making profits. There were, of course, numerous companies in the previous generation of AI startups that were on this path, just nothing like as many as we are seeing now and expect to see in the years ahead.
AI startups are becoming cheaper and easier to build, because many of the underlying technologies are now mature enough to apply predictably, and because of the declining cost of cloud computing – including many AI as a service products on AWS and Google Cloud.
I liken this development to the time when cloud computing first emerged around ten years ago. Resources that were previously the preserve of cash rich companies became available to anyone who could pull together a few grand and a thousand flowers bloomed. I think we will see something similar again now.
A couple of times recently I’ve found myself coaching people to stay positive. In both cases they very reasonably pushed back, saying great idea, but they didn’t want to be false and pretend to feel positive when inside they felt anything but. Two conversations about the art of being authentically positive ensued and I’ve been collecting my thoughts on the subject since then.
Let me start by taking a step back. This may be obvious to many of you, but we all like being around positive people. It’s more fun and it helps us keep our own energy up.
Positivity is doubly important in startups where the ups and downs will inevitably lead to periods where we question whether the whole endeavour is worth our time. Happiness is contagious and companies full of positive people climb out of the dark patches more quickly.
However, to really work, the positivity must be authentic. Saying or implying you feel good when you’re really not sure is better than giving into cynicism, but people can tell, and after a while it will chew you up inside.
One trick for staying authentically positive is to avoid dwelling on the big problems and focus on the little wins. When someone asks how you are doing, reflect on something that has gone well recently. If you made minor progress with a major client in the last 24 hours, say so. It’s genuine, and will make you and the person you are talking to feel better than a negative or neutral statement.
Underlying this is a really important point, which is that effective operators respond to feeling down by finding something positive to do. When we were still working out the details of our model here at Forward Partners we had a chap who started to get cynical about key aspects of his role. To his credit he responded by taking ownership of one of our content initiatives. It was a side project for him, but he had success there which kept him positive whilst we sorted out his bigger issues.
Other helpful tricks are getting enough sleep, exercising, eating well, meditating, and – simplest of all – remembering to smile. If you feel good in your body you will have more energy and find it easier to stay positive.
Like happiness, positivity is a function of mindset and behaviour. It can and should be cultivated.
It’s fashionable in certain quarters now to slate some of the billion dollar startups that have been created recently and the investors that helped them get there. Zebras Fix What Unicorns Break is a good example. The piece makes three criticisms of the status quo:
- Pursuit of extreme growth results in companies with unpleasant characteristics and a negative impact on society – e.g. Facebook (fake news) and Uber (where do I start…)
- Companies with pure for-profit motives aren’t well equipped to solve many of society’s most pressing problems – e.g. homelessness in San Francisco, education, healthcare
- Companies that aren’t chasing unicorn status find it hard to raise money
There’s some merit in these arguments, but they need to be put into context.
- There is clearly dysfunction in chasing growth at all costs – inherently unprofitable companies grow to employ thousands of people before going bust, resulting in much personal anguish and not a little wasted capital. However, that’s a cyclical dysfunction which hit notable peaks in 2000 and 2015 and which needs to be understood as an unfortunate part of a larger system which overall has been an incredibly positive force for good. Five of the six largest companies in the world today were venture backed startups and just about all net new job creation comes from young companies.
- It’s also true that many of society’s deepest problems aren’t likely to be solved by for-profit companies. That’s because there’s no money in solving them (otherwise the market would have been solved already). What we need here is government intervention.
- The startup community has taken the ‘go big or go home’ mantra so much to heart that good mid-level outcomes – including exits in the hundreds of millions – aren’t seen as sufficiently ambitious. There are structural reasons why we’ve ended up here. As Fred Destin explained in his recent post Why VC’s are obsessed with large outcomes, investors with large funds have to chase unicorns to make their numbers work. Those large funds are often the ones everyone wants on their cap table and so almost everyone in the food chain, from smaller funds to angel investors and entrepreneurs alike, orientates themselves around giving those larger investors what they want, with the result that companies without unicorn potential find it disproportionately harder to raise money. That’s not a good thing.
So what should we do?
- Recognise that the system is imperfect, but not broken. We need massively successful companies like Facebook, and even Uber to generate growth, employment and the profits needed in the venture industry to finance the next generation of companies. Some unicorns are bad, but lots are good. Some investors back unsustainable growth in pursuit of short term profit (often unknowingly) but most are sensible.
- Celebrate mid-level outcomes as much as massive outcomes. Or at least almost as much. For me companies that exit for $200m are as noteworthy as many of the companies that raise money with a $1bn valuation, and often the lessons they’ve learned are more widely applicable than lessons from companies in the unicorn club. Talking about their stories more would help shift some of the dialogue and mindset in the startup community away from the needs of larger funds, towards the middle of the bell curve where most founders exist.