Tag: Biases

Doubling Down Before Consensus

The best founders often stay non-consensus for longer. That’s the time for insiders to build ownership.

It’s crazy how extremely solid founders who are clearly executing really well still end up being fairly non-consensus when being evaluated by new investors in the first few rounds.

In my experience, this happens due to one or more of the following reasons:

(1) The founder is still learning the art of effective pitching/story-telling. Therefore, the quality of the opportunity isn’t being adequately communicated in the pitch. [Frequently the case with technical founders in deeptech].

(2) Details around the exact addressable market are still fuzzy. So unless an institutional investor has a pre-prepared mind for that particular space, they struggle to build conviction around it. [Eg. people passing on Zepto Series A & B].

(3) Even with awesome growth & metrics, the target market is simply out of favor at the moment with investors due to recent history or macro headwinds. [Eg. anything related to edtech in India at the moment].

(4) A multitude of internal issues at a VC firm that have nothing to do with the company. [Eg., bad history with previous investments in the space, already over-exposed to the sector, not having enough dry powder, deal sponsor is not a GP/ lacks internal political capital to push it through etc. etc.]

This is where existing investors in the company, particularly those who have been spending enough time with the founder and have been tracking execution closely enough to be able to accurately judge the slope of the team/business, have a massive information asymmetry advantage.

This creates valuable opportunities for insiders to build ownership at attractive valuations while the market struggles to build a firm POV.

As an existing investor, the key is to take a step back, block out the noise and distractions from external signals, and do a fresh, rigorous underwriting from the ground up as a new deal, while keeping emotional biases at bay (commitment bias, consistency bias, throwing good money after bad, etc.).

As long as you can be intellectually honest in this new underwriting process, the superior quality & trendline of signals gathered while being on the cap table will work massively in your favor, both in terms of allocating more to the right companies, as well as avoiding the landmines that look like goldmines to new investors!

The key risk in all doubling-down decisions is “your own sh*t always smells sweet to you”. So, keeping a significantly high & tight bar for what goes through, as well as having some fund-level guardrails (% of fund caps for reserves & cross-fund deals) will hopefully help counterbalance the human biases.

Macro-Optimism, Micro-Skepticism: A Framework for AI Investing

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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Investing Landmines

Successful investing, be it in stocks or venture capital, requires avoiding behavioral landmines at every step of the way.

Here are the major ones that every investor should have top-of-mind.

Successful investing outcomes, be it in public or private markets, are typically the result of the following sequence of events:

#1 Real world research and/ or experience germinates a non-consensus view.

#2 A conviction-building process for this view helps in getting to a probabilistic distribution of future outcomes.

#3 Courage helps in putting real money behind the view.

#4 If all goes well, the non-consensus view starts turning out to be right (non-consensus ➡ non-consensus-and-right).

#5 After a certain hold-out period, the market provides a liquidity opportunity that is attractive-enough for the investor to cash out.

Investors have to fight specific pitfalls at each step of this sequence:

For #1, it’s the herd mindset that evolution has deeply wired into our psychology. We seek comfort in others validating our views, which is the exact opposite of what contrarian thinking entails.

A by-product of herd mindset is FOMO, which has quickly become the dominant driving emotion of modern urban life.

For #2, it’s hasty bias-to-action. Individuals have a tendency to overcommit & get positively biased very quickly, often even before adequate investigation. Every investing action releases dopamine, which makes individuals feel powerful & good about themselves. Therefore, even sophisticated individuals are quite trigger-happy & demonstrate a tendency to “just do it”.

Running a solid investing process calls for a scientific approach that starts with default skepticism, generating a hypothesis & then putting in the work to approve/ disapprove it with intellectual honesty. PS: check out more about bias from consistency & commitment tendency in this amazing write-up by Charlie Munger on Farnam Street.

For #3, it’s fear. Fear of losing money, of losing face, of future distress. Am sure we all have seen many examples around us of folks who did a decent job at #1 and #2, but never pushed chips on the table. That friend who spotted Google at the earliest stages. Or who had heard of Bitcoin from credible sources before everyone else. Or who was seeing East Bay become the new South Bay or Gurgaon become the new Delhi.

Am also confident that as children, each of us saw our parents hold a non-consensus view for those times & not act on it, which in hindsight, would have led to asymmetric gains.

For #4, it’s lack of patience. Markets typically take time to appreciate & subsequently reward non-consensus views. This period can range from a couple of years to sometimes more than a decade. Holding out with a view that doesn’t match the crowd for long periods of time is extremely hard psychologically for even the most experienced investors.

Humans by nature seek thrill & quick rewards. While a lucky few are born with the delayed gratification gene (like this Nevada’s Pension Fund Manager), for others like us, we have to train ourselves to get better at it.

For #5, it’s greed. Once the market slowly starts appreciating your non-consensus view, given its pendulum nature, it then starts gradually moving towards the other extreme. At a certain point in time, it will soon provide windows where very attractive, & sometimes egregious, returns can be booked. Case in point: after the Nvidia stock stayed flat for several years, the recent AI-fueled stock run-up is finally providing an opportunity for insiders to cash-out.

But then, greed starts kicking in. Maybe hold-out longer for even better returns? This is where the discipline of taking chips off the table & booking profits becomes really important. However, this is really hard to do when investors have faced a long lean period & are now starting to see things finally go up. As legendary fund manager Mohnish Pabrai often says – the art of when to sell is the most difficult.

To summarize, the key to successful investing is recognizing and working towards actively avoiding the above landmines at every step of the way, most of which are behavioral.

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