The frothiness of today’s environment in Silicon Valley makes it easy to get sucked into a warped sense of reality. Valuations are high, capital is cheap, housing prices are skyrocketing, and RSUs are flowing like wine.
Talk of another “bubble” is rebuffed, even by those who were scarred by the Dot-com collapse of 2000. Some argue we’ve exited the installation phase of technology—which was still sputtering along at the dawn of the new millennium—and have entered what Carlota Perez calls the ‘deployment phase’ of technology. In this phase, startups move “up the stack”, switching from building core infrastructure (i.e. interstate highways) to applications that go on top of it (i.e. Teslas).
Undoubtedly, changes in technology over the last 15 years have been breathtaking. The cost of bringing new products to market has dropped exponentially, and companies that hit product/market fit can build value incredibly fast through escape-velocity, engines of growth—going from worth nothing to worth billions, seemingly overnight. Unparalleled access to capital has led to an arms race for talent, with top tech companies stockpiling software engineers like ballistic missiles for the Tech Wars of the future.
One risk of living in this Gilded Age of Tech is the temptation to view your own career and compensation through a disproportionately financial lens—much as a growing company would.
Companies are built on 5 to 10 year time horizons, so navigating the feast-or-famine fundraising environment and tracking jaw-dropping economic headlines across the globe are functions of survival. But when it comes to evaluating your own compensation and growth, focusing on the financial dimension is problematic because it’s too short-sighted.
Since the time horizon for your career is long, the most valuable startup compensation you can acquire isn’t a competitive salary, a chunk of stock or a Yoga-laiden benefits package. If you look at the expected rate-of-return for each of these and benchmark them against the market, they aren’t dramatically different from what you could get working at the stereotypical big company. In fact, they are worse on average—with one exception:
The most valuable compensation for working at a startup as opposed to a “normal job” is a dramatically higher rate-of-learning (ROL).
Your rate-of-learning is a better proxy for how successful you will be than your current salary or stock compensation because it’s a leading rather than lagging indicator. Abandoning the cubicle at your normal job to throw yourself head-first into a startup is a fiery accelerant for growth, changing your career trajectory by orders of magnitude through a substantially increased rate-of-learning. To explain why, let’s define ROL:
Definition: Rate-of-learning is the velocity at which you are aggregating new insights and deploying them in ways that build value.
In physics, velocity maps the relationship between speed and direction. In this case, the pace at which you are uncovering new insights (speed) has a direct relationship with the momentum you accumulate deploying these new insights (direction). Whether this process of aggregating and deploying insights is in the form of writing code or driving growth, scaling this steep learning curve is the forging process that turns you into a badass full-stack developer or full-stack marketer with a high market value—not getting paid a large salary to sit in meetings all day.
There are three reasons why I believe rate-of-learning is your most valuable personal asset class:
Compounding interest on learning. You may have noticed in the graph above that the line representing startup rate-of-learning is exponential while that of a normal job is linear. While this is more conceptual than anything else, it illustrates an important point: if you reach a fast enough rate-0f-learning you start generating compounding interest on those learnings.
Let’s use a real life example. Imagine you’re a growth marketer at a startup and uncover a new way to drive sign-ups by aggressively retargeting people who have visited your blog organically. You deploy the retargeting campaign and it works, so next, you find a way to generate more quality blog content by syndicating posts from experts in your space so you can attract even more eyeballs. Having successfully widened the top of your funnel, you switch gears and figure out how to dramatically increase conversion by personalizing sign-up page copy and background images based upon location data you’re pulling off a visitor’s IP address. This leads to another insight about a series of fields that can be moved out of the sign-up form and into the onboarding flow to reduce friction. The cumulative effect? You increase sign-ups by 20%.
In a startup, this series of experiments can happen over the course of a few days. In the alternative universe of a normal company you might be waiting a week for a small retargeting budget or approval from your manager. Therefore the valuable insights that should theoretically follow your initial insight may never come. If you extend this slower rate-of-learning over months or years, the opportunity cost of missed insights is massive.
Learning equals leverage. People think having “fuck you” money is leverage, but in reality, a high rate-of-learning gives you more leverage than money does. If I were to give you a choice between wiring $10,000 to your checking account or an opportunity to uncover 50 powerful insights that could land you an awesome job at Airbnb or Dropbox, which would you take?
Another way to think about rate-of-learning dividends: the present value of money is low, especially when interest rates are at 0%, because you can’t generate as much compounding interest on money as you can on your learnings. So if you have a choice between getting paid $50K at a startup or $100K at a dying company, your future self will thank you for taking half the pay in exchange for a 3-5X ROL. A high rate-of-learning is the most bankable asset you can have in the startup world because it’s the vehicle by which longterm value is created, both within yourself and for your startup.
Learning is an end to itself. The interesting thing about highly successful people is that most of them don’t stop working once they’ve “made it”. They continue climbing the learning curve long after the millions from big exits have been wired to their bank accounts. Why? After years in high rate-of-learning roles, they discover that learning was an end in itself.
Though it may seem like money is spilling all over the streets in Silicon Valley, don’t get distracted by shiny objects. Play the long game. Put yourself in a position to maximize your rate-of-learning, even—and especially—if it makes you a little uncomfortable. The long game is hard, but rewarding, because you’ll know you had the strength to make the steeper climb.
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