This incident reminds me of a mental model I have learned & developed with experience over my career:
“When you come across something that looks stupidly irrational on the surface, instead of falling prey to first-order thinking, pause, take a step back, try putting yourself in that situation and think through some reasons why someone could indulge in that seemingly foolish or irrational behavior?”
In the case of this billboard, clearly the founders are smart enough & shrewd enough that institutional investors are handing them $25Mn. So it’s highly likely that they are trying to achieve some goal by putting up this cringeworthy sign.
Most likely, the goal was to drive awareness & word-of-mouth by making this meme-worthy. Similar to how celebrities say & do crazy, PR-worthy things strategically close to a big movie release.
While this billboard case is a bit frivolous, it highlights an important idea that we all should have in our mesh of mental models – when something doesn’t add up in plain sight, or when the herd has 100% consensus on an idea, it shouldn’t be believed prima facie. Rather, it deserves an even deeper investigation.
The crowd is largely a blob of first-order thinkers. Value almost always resides in second-order thinking & beyond. Train your cognitive radar to spot these signals & act accordingly!
Leveraging rare moments in time like Bitcoin requires having a prior mental model for how to behave when coming across an asymmetric option.
It’s crazy that in hindsight, Bitcoin was one of those super-rare, asymmetric-upside options that should have been a no-brainer to buy, esp. at the <$1k levels.
That’s why most tech HNIs, at least anecdotally from my network, ended up being early adopter buyers of Crypto. They had the right channels of early intel that informed them of why it was worth having at least some exposure to it.
Funnily enough, having these proprietary sources of info didn’t matter much given the long price runway that especially Bitcoin has shown. The dealer showed all the cards, multiple times over several years. Hell, you could have just read this 2011 post from Fred Wilson, trusted the OG who has gotten it right multiple times in tech, and bought maybe just a few thousand dollars of BTC. Do you know what price you would have entered at when this post was written? $2.75!!
And yet, few people bought any Bitcoin over these years, fewer ended up HODLing and even fewer ended up doubling down. Why do you think that is? I believe it’s because people don’t have a prior mental model for how to behave when coming across an asymmetric option.
Conviction comes from having a mesh of these mental models already in place, especially those that are drawn from experiential learning and therefore, become much more deep-rooted than those imbibed from mere academic study.
I don’t blame folks for not knowing what to do with Bitcoin. It is one of those once-in-a-generation movements and therefore, by definition, entire cohorts would have lived their lives without seeing anything similar to it before.
This is where experience becomes important. Ironically, even though Bitcoin is referred to as a Gen Z asset class, the people who have made real money off it are the grey-haired (or no-haired!) Michael Saylor, Mike Novogratz, and Bill Miller. Interestingly, both Saylor and Novogratz are 59 years old while Miller is almost 74!
This is because, over 4 decades of working and investing, these gentlemen have seen enough human behavior in the real world, as well as put skin in the game by taking multiple explosive-payoff bets one after the other, to recognize how the system works and how to leverage these waves to their benefit.
50% of my networth is in Bitcoin.
Bill Miller (born 1950)
In this fascinating interview, Bill Miller talks about how Roosevelt confiscated everyone’s physical gold in the US in 1933 and that’s the mental model that Bill uses to view Bitcoin as digital gold that can’t be confiscated due to the Internet (see my post ‘Bitcoin ETFs and The Challenges of Digital Gold‘). He then nullifies the argument used by the likes of Warren Buffett that Bitcoin has no intrinsic value, by saying that what intrinsic value does a rare baseball card or a Picasso painting have? They still sell for millions as their supply is scarce and people ascribe value to them.
I am actually a Bitcoin observer. I am observing its trajectory as a new technology and comparing it to things like the printing press, or the steam engine, or the railroads, or the automobile, or electricity. And it seems to be following a well-understood path to adoption of any new technology.
The benefit of age and living through multiple cycles is that one can fit the arc of a new tech wave within a very long historical view of how things have evolved in the past and leading up to this point, as Bill does above. It’s how Millennials like myself will likely use the lived experiences of GFC’08, ZIRP, the pandemic, and the peak of 2021 as mental models for decisions going forward.
Therefore, let’s bookmark this post as a note to self: the next time we encounter an asymmetric option, strongly consider taking a swing at it (after due consideration, of course!).
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Seeing my kid get bombarded with activities in 1st grade prompted me to think about the relative importance of ‘discovery’ vis-a-vis ‘focus’.
While conventional wisdom talks about the importance of each in silos, I have come to experience that a healthy mix of both is needed to design a thriving career and live a fulfilling life.
My older son just started 1st grade. As expected with any kid growing up in the Bay Area, he is already being bombarded with tons of activities – from soccer classes & cricket camps to music classes, karate & regular play dates. This is in addition to a school schedule that to me, already looks super intense.
Just 2 weeks into the new school year, I have been compelled to bring up the importance of prioritization with my better half. With work commitments & regular school duties, there is only so much a kid and 2 working parents can get done in 24 hours.
My humble submission to the family has been that we need to be smart in picking our battles. Essentially, have the kid gradually start focusing on a few areas, instead of spreading himself thin.
This predicament has prompted me to look back at my own career and reflect on what I have experientially learned about this topic both directly while executing in my jobs as well as indirectly by observing others around me. In particular, what I have gathered from working with and studying founders & investors I have come to respect.
Reflecting on my journey – the ‘discovery’ part
Growing up, I was the kid who always wanted to try out a variety of things and experiences. Even for a specific school project, I would boil the ocean, reading every book and resource I could get my hands on. While preparing for IIT JEE, I would read every reference book any friend recommended, and try and do every practice test series that looked even remotely relevant.
I carried this same behavior into my professional career. Over a decade and a half, I worked directly or indirectly in multiple sectors (oil & gas, software, medical devices, consumer Internet, eCommerce, SaaS, etc.), dabbling in multiple functions (finance & investment banking, product, operations, strategy, BD, partnerships, etc.), operating across multiple regions (US, India, China, SE Asia, etc.) and stages of maturity (founding my own startup, Series B startup, tech conglomerate, institutional VC, operator-angel).
Luckily, I figured out last year that venture investing is my true calling and this type of career design actually feeds really well into pursuing it professionally. Be it public or private markets, the best investors have a diverse set of mental models and best practices from many different fields meshed in their heads. This helps them to connect the dots in unique ways while evaluating any opportunity, thus giving them the proverbial ‘edge’. The best example of this is Charlie Munger. PS: I wrote about how he thinks in ‘Munger’s Tao‘.
Having a rich tapestry of experience across many areas definitely helped me develop a unique ‘strategic 360⁰ product leader’ positioning as an operator vis-a-vis my peers, and is now helping me carve my path as a venture investor.
Coming back to the earlier retrospective exercise, though this story so far made sense, a specific question still kept bothering me – “Have I missed a trick by not focusing deeply enough on any one area?”.
As we operate in a cluttered and flat global marketplace where everyone has access to almost the same information, and it has become easy to create shallow narratives in any area, I started questioning whether I had peanut-buttered my career to my own detriment.
Reflecting on my journey – the ‘focus’ part
During discussions with some of my friends, mentors, and especially my better half, an interesting nuance hidden in my story was uncovered. Even while hopping across many fields, countries, and skills, the one parallel constant in my life’s equation was venture investing. Since stepping into VC for the first time in 2011, I continued to go deeper into it, studying and practicing it over the subsequent decade.
During 2011-13, when Indian VCs were yet to discover Twitter in a mainstream way, I was one of the most active investors on the platform, trying to replicate the playbook of Valley VCs on it. PS: credit to Shradha of YourStory for encouraging me to get on Twitter during those early days. Twitter has added value to my world in ways that are hard to quantify.
Subsequently, when I stepped out of the VC world and became an operator in the Bay Area, I continued deploying my salaried money into early-stage startups each year, a majority of which was invested in the first round at an idea stage. By the way, this was before it became fashionable to become an angel during ZIRP.
While working intense continent-hopping jobs, I continued to get on calls with founders at 2 AM, trying to work on strategies to save a company on its last breath. In between building products and founding a startup, I strived to keep making myself better as an operator-angel by studying the journeys & frameworks of the likes of Semil Shah (totally in love with his blog), Elad Gil (substack), Jason Calacanis (love his old but raw Angel Podcast episodes), Ron Conway & Pejman Nozad.
Purely as a result of following my natural curiosity, I had inadvertently ended up focusing and going extremely deep into the craft of venture investing.
Balancing ‘discovery’ and ‘focus’
Connecting the dots now with my kid’s 1st-grade predicaments, there is an idea here from my journey that I believe is relevant. Careers (and life) are about a balance between ‘discovery’ and focus’. While conventional wisdom talks about the importance of each in silos, I have come to experience that a healthy mix of both is needed to design a thriving career and live a fulfilling life.
It’s important to have enough room to discover – try different things & test different ideas, while still striving for focus and actively looking for leading signals that indicate what to focus on.
The relative proportion of discovery and focus will be dependent on each person’s context. While most kids and youngsters will naturally have a high proportion of discovery, we also know prodigies tend to start focusing really early in life (Tiger Woods took to golf at 6 years of age; Warren Buffet bought his first stock at age 11).
People in the middle phase of their careers typically tend to gravitate more towards focus, trying to climb the ladder at a specific company or type of job. A counter view would be that many of them would do well to increase the proportion of discovery in their careers, in order to get to a global maxima.
Folks in the latter phase of their careers organically become experts at something, thereby increasing the proportion of focus in their lives. A view worth considering here is whether increasing the proportion of discovery in their careers might help avoid getting jaded and bring in fresh perspectives into their field of expertise.
There are no right or wrong answers here. Everyone will need to find their own balance considering their holistic context – age, location, family structure, social setting, and economic circumstances. Although, just based on a sample size of 1 (i.e. my journey), is following your natural curiosity a good way to organically evolve an optimal mix of discovery & focus? Perhaps…
To close out, I would like to share a pictorial representation of this idea of balancing discovery and focus. I tend to think of ideas & mental models in terms of pictures; I guess there is some merit to that age-old wisdom of “a picture is better than a thousand words”.
To me, this balance can be represented as a free-flowing river being directed by its banks. The middle of the river is in discovery, having enough room for the water to go in any direction, form vortexes, change color, and experiment with constituents like soil, mud, rocks, etc. But, the banks give the river focus, ensuring it stays on a desirable path, moving within specific boundary conditions and ultimately, meeting its true calling of merging into the sea.
As a parent, I hope to be the river bank that provides focus to my kid’s discovery. As you reflect on your own journey, how might you strike the balance between discovery and focus in your career and life? Are there areas where you feel the need to freely discover more, and others where honing your focus could lead to breakthroughs? Would love to hear your insights and experiences in the comments below, or on LinkedIn and Twitter.
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This Generative AI wave is both a tremendous opportunity over the long term and a ticking bomb in the short term.
Sharing a framework to navigate & eventually thrive in this hype cycle as a tech investor.
As the Generative AI fire rages on with full force, I have been thinking through the best approach for me as an operator-angel to navigate the current environment.
What makes this AI wave particularly challenging for venture investors is that it’s full of contradictions depending on what time horizon you choose to view it from.
In the short term…
But over the long term…
The space is clearly in the early stages of the hype cycle.
It’s perhaps the most defining technology shift of our lifetime, likely to drive a socio-economic change like the agrarian ➡ industrial age transition.
Though AI is “consensus” in Silicon Valley, the agreeing crowd has a track record of being right quite often.
The only way to generate outlier returns is to be “non-consensus-and-right”.
Early entrants are likely to attract significant venture capital, potentially generating quick mark-ups for early investors.
Like previous platform shifts (eg. Web and Mobile), early entrants are unlikely to be the eventual winners (there were at least 8 major search engines before Google came along).
Pre-product stage startups commanding rich valuations is perhaps justified, given investor-demand & the hockey stick growth potential of the space.
The best way to generate above-average returns is investing in the best companies at reasonable valuations.
Clearly, there is a time horizon tension at play here. As an investor, one doesn’t want to miss out (or appear to have missed out) on the earliest stages of the greatest platform shift in our lifetimes. At the same time, as the recent Web3 wave taught us, maintaining discipline during hype cycles is key to ultimately realizing cash-on-cash returns.
To manage this tension & navigate this wave in a risk-adjusted manner, I have been using a framework I like to call “Macro-Optimism, Micro-Skepticism”. This approach involves always keeping two opposing emotions in your mind while evaluating opportunities:
Macro-Optimism – a strong belief that AI is going to be a super-powerful force of positive change in our lifetimes. Having this belief should translate to an immense yearning to learn as much as possible while the tech is still embryonic. It should also translate to keeping an open mind about its possibilities & having the imagination to think about “if it works in this way, what could this idea become?”.
It should lead to a low-ego & eyes-wide-open mindset while meeting founders working on the frontiers of AI. It should also lead to having the awareness to not underestimate any person or idea, no matter how divergent it sounds within your current lens.
Micro-Skepticism – realizing that in the initial stages of a hype cycle:
(1) most ideas will turn out to be invalid, as how a major platform shift shapes the future is, to quote Brad Gerstner of Altimeter Capital, “unknown & unknowable”. And;
(2) the space will initially attract a lot of low-quality actors, including scammy founders, tourist investors & others with a get-rich-quick mindset.
Realizing this should translate to looking at each new investment opportunity with default-skepticism – keeping the bar high, asking hard, intellectually honest questions & calling BS when you see it. This approach requires running a rigorous conviction building process, keeping FOMO at Bay & staying true to your investing value system.
Of course, parallel processing these opposing ideas is easier said than done. As I wrote in my recent post “Investing Landmines”, we are susceptible to many biases that get further exaggerated during hype cycles. Some ways to get better at managing them include:
1/ Leveraging complementary peers or team members that can keep you honest & call out your blind spots.
2/ Using some sort of light-weight system to ensure you are asking all critical questions & spotting typical pitfalls. As an example, learning from the likes of Atul Gawande & Mohnish Pabrai, I have found simple checklists to be helpful.
3/ Consciously sleeping on a deal before pulling the trigger, giving the ‘think-slow’ part of your mind enough time to digest facts.
Ultimately, am excited at the opportunity this AI wave is providing for investors with a growth-mindset to test & fine tune their systems. While I have no doubt that all of us in the tech ecosystem will benefit from this platform shift one way or another, I also hope some of us emerge wiser from it.
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Earlier this year, my younger son got admitted to the same preschool that the older one attended in SF. As parents, we were elated! Our older one loved this school, we know the Principal and teachers really well, and it significantly reduces uncertainty for us given this school goes up to Middle. A win-win in every respect!
Except, we were caught completely off-guard by how the first few weeks turned out. That the kid was having “adjustment issues” would be an understatement. Everything from sleep schedules & toilet training to eating & social behavior went majorly South. While this is normally expected when kids change schools, what surprised me was how much this derailed us as parents. We were maniacally struggling to manage the kid in this transition while trying to cope with all the mood swings & changes this was bringing to our daily routine.
Of course, things started improving after a couple of months & as we speak, the kid seems all settled in the new environment🤞🏽. But I couldn’t stop introspecting on why we got caught so off-balance in this episode, even when we knew the school intimately & had gone through this exact experience before with our older one?
This was a manifestation of what I call the Familiarity Conundrum. When we deal with things we are intimately familiar with, there is a double-edged sword at play. While familiarity arms us with high-fidelity, experiential data that can be incredibly useful in making a smart decision, it also creates overconfidence-driven blind spots in our ability to deal with the familiar.
In highly familiar situations, our brain tends to short-circuit the decision-making process, perhaps gathering comfort from past anecdotal experience regarding similar situations. The result is a quick decision based on 1st order thinking. We went through this in the above school episode – our brains used a quick, 1st order heuristic – “because this school was so great for our older son, it will be equally good for our younger one too”. We failed to ask even a basic set of questions regarding this decision eg. are the teachers the same this year, is our younger son starting at the same age as the older one, should we expect any changes to the school routines post-Covid etc. These are basic diligence questions that we would have definitely tried to answer had this been an unfamiliar school for us.
This Familiarity Conundrum often leads to sub-optimal decisions in other aspects of life as well. Some examples that I have personally experienced or witnessed:
When hiring someone we are highly familiar with eg. an ex-colleague or classmate, our brain tends to unfairly magnify our last, dated view of their strengths, not pushing us enough to evaluate them independently, especially with respect to fit with the current opportunity.
When a trusted person introduces us to a deal, say an investment opportunity, our brain wrongly transfers trust with the referrer onto the referred deal, without a rigorous evaluation of the deal on a stand-alone basis as well as the referrer’s true competence in the specific area being evaluated.
When operating in an area where we have prior work experience, we tend to under-diligence the opportunity & overestimate our likelihood of success. In areas of perceived expertise, our brain doesn’t push hard enough on 2nd & 3rd order thinking like figuring out ways in which this context is different from our prior experience, trying to see around corners for lurking risks etc.
So what can we do to effectively deal with this Conundrum? Based on what I have learned from my experience as well as studying great rationalists like Charlie Munger, here are a few ideas:
1/ First step is spotting it at the right time – training your mind to spot times when familiarity could be creating blind spots for you, is itself a major part of keeping biases at bay. Personally, I tend to keep a matrix of such mental models both layered in my head as well as often as part of a diligence checklist. For decisions that cross the bar of impact and/or irreversibility, I like to run them through this matrix to check for potential blind spots.
2/ Don’t deviate from the “checklist” – Dr. Atul Gawande argued for the importance of checklists as a tool to make surgeries safer in his popular book “The Checklist Manifesto – how to get things right“. Professionals as diverse as surgeons, pilots & public market investors leverage checklists to handle uncertainty & make better decisions under stress.
The key is not deviating from your operating process even when the context is highly familiar and your brain is pushing you to use crude heuristics to arrive at a quick decision. Like a pilot who will diligently run through the aviation checklist even on the best-weather days, one needs to strive to do the same, each time, every time while taking high-impact decisions.
3/ Always have an independent feedback mechanism – even in areas where you believe you have deep knowledge and/or extensive on-ground experience, it’s always good to get feedback from independent players who are likely to see the opportunity in an unbiased way.
During my early days as an angel investor, I had a tendency to predominantly rely on my own judgment of a startup & often made decisions without taking the time to gather feedback from other sources. Having learned from several missteps, I have now incorporated gathering feedback from several sources including market experts, customers, founder references & other investors, as a core part of my investing process.
In this context, I find the idea of having a “feedback buddy” incredibly useful. For important projects eg. buying a house, a product launch, a big investment, it’s good to have someone who is unrelated to the project be a sounding board to bounce off ideas, poke holes in current thinking & simply provide common-sense feedback.
The bottom line is this – as opposed to explicitly unfamiliar terrain where our natural survival mode gets alerted, familiar contexts are significantly more likely to get our brains in “lazy thinking” mode, creating blind spots that will catch us off-guard. Proactively spotting this dynamic, having the discipline to stick to a rigorous process at all times & consciously incorporating an independent feedback mechanism within it, goes a long way in offsetting this Familiarity Conundrum.
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