How to think (and invest) like a child
Discover more from Moneyball
Moneyball is a fortnightly newsletter from Koble exploring the limitations of human decision-making and their implications for startup investing.
We've spent two years developing our groundbreaking algorithms, which discover early-stage startups that outperform the market and predict their probability of being successful.
This week
🧠 Mental model #2 – First Principles, or How to think (and invest) like a child – What Aristotle, Elon Musk, and every child on planet earth have in common.
📖 Investor reading – Private markets are bigger than you think – The future of VC secondaries – Michael Lewis on false experts.
💬 Some tweets – “The smartest person I know” – Little rules about big things – Replying to founders.
Koble update
At Koble we’re building a deep-learning model that can predict the success of early stage startups. Here’s what’s happening…
We have finished data construction (a mammoth task) and built our baseline model. The baseline model is an intermediary model with a less complex architecture than our production model will have (machine learning vs deep learning / neural networks) and is trained on less data and fewer features.
This model enables us to quickly identify any anomalies in the data or code, and run tests to understand if we’re going in the right direction. We’re busy crunching the numbers, which we will share with you soon.
How to think (and invest) like a child
Aristotle, Richard Feynman, and Elon Musk were very different people. But they all had something in common; a secret sauce that enabled them to innovate and build transformational value.
That secret sauce is First Principles Thinking – a mental model that can accelerate learning, break down seemingly inscrutable problems, and bestow great gifts on humanity.
A first principle is a basic proposition that can’t be deduced from any other proposition. In other words, it’s foundational knowledge that stands on its own two feet, without recourse to wider assumptions or beliefs.
Acquiring knowledge and breaking down problems relies on fresh perspectives, not analogies, prior assumptions and dreaded “best practices” (TAM anyone?).
These tend to result in groupthink, the driver of bubbles, manias, crashes, and other unpleasant things. As Mark Twain put it, “Whenever you find yourself on the side of the majority, it’s time to pause and reflect.”
Aristotle built his entire philosophical framework on First Principles Thinking. Fast forward circa 2,406 years, and its modern torchbearer is Elon Musk.
Musk has been doing this throughout his career, with PayPal, Tesla, and SpaceX, but the most compelling example is his approach to space travel. By pioneering reusable rockets to cost-effectively deliver payloads into Low Earth Orbit, he has re-engineered the economics of space travel, catalysing an industry that will in turn drive growth for his own company. Today, a SpaceX launch can be 97% cheaper than a Russian Soyuz ride cost in the 1960s.
First Principles Thinking is really a way of reverse-engineering solutions to problems that seem unsolvable (or already solved in sub-optimal ways). We throw out the existing model and start building from scratch, with new ideas, techniques, and components.
Implications for investors
First Principles Thinking is a power-tool for founders and investors looking to create new categories and capture unrealised value. But how do we actually do it?
We can commit to actively questioning our beliefs, but the thing about assumptions is that they often don’t look like assumptions – they look like truths. A great hack to deconstruct supposed truths is to bring others into the process.
Getting input from a diverse range of external sources is a useful way of mitigating bias and challenging our assumptions. Novices, strangers, and cross-functional colleagues can provide a fresh perspective and build a robust thesis on solid ground.
An interesting quality of First Principles Thinking – it seems almost childlike in its naiveté.
Nobel Prize-winning theoretical physicist Richard Feynman recognised this and actually structured children into his learning and teaching process.
Feynman developed a technique that involved pretending to teach a concept to a sixth-grade student, which forced him to simplify things and communicate simply and clearly. This leads to a deeper understanding of the concept – it’s the difference between regurgitating information and acquiring knowledge.
Children make interesting soundboards. They’re less exposed to adult groupthink and social convention – they ask “stupid” questions and often come up with thought-provoking answers, cutting through our world-weary assumptions with ideas for how we can change things.
Their fondness for asking “Why?” (often repeatedly in quick succession) helps us step outside of our ossified beliefs and look at the world through new eyes. Imagine the impact on capital allocation if startup investors took the same approach...
“Why do we need another service that delivers groceries in under 15-minutes?”… Why do we need another meditation app?”… “Why do we need another marketplace for tradespeople?”…
To build the next generation of paradigm-shifting startups, perhaps founders and investors should spend more time thinking like children?
Join our waitlist
At Koble, we’re building a group of forward-thinking angels, VCs, family offices, and hedge funds that want to play a role in re-engineering startup investing with AI.
If this applies to you, sign up to our waitlist.
Investor reading
🚀 Private markets are bigger than you think – Growth is measured by dollars flowing into funds and deals, but those metrics don't capture their true size.
💰 Industry Ventures on the present and future of VC secondaries – How the VC secondaries market has come to be worth nearly $130 billion.
🎧 The Overconfidence Game – Michael Lewis explores the not-so-secret power of men to offer themselves up as experts, when they clearly are not.
Some tweets
Parting shot
“The first principle is that you must not fool yourself and you are the easiest person to fool.”
– Richard Feynman
Regards from your [hyperactive] startup investing AI,
About Koble
Koble is re-engineering startup investing with AI, applying quantitative strategies that have disrupted public markets to early-stage startup investing.
We've spent two years developing our groundbreaking algorithms, which discover early-stage startups that outperform the market and predict their probability of being successful.