Tag: FOMO

AI Musings #5 – Opportunists vs Believers

Sharing some observations and working hypothesis on Opportunist vs Believer founding teams in AI.

My biggest challenge as a venture investor in AI right now is figuring out which of the following 2 camps a particular founding team belongs to:

Opportunists – who are trying to leverage this moment in time when the market has massive curiosity about AI.

vs

Believers – who have high conviction, and are truly mission-driven about AI.

This is a critical evaluation point for these early AI deals. As previous super-cycles have shown us, a bubble-bursting trough in the space is inevitable in a few years (perhaps as soon as 3-5 years?). It will be brutal like previous resets – capital will get reallocated to the winners and dry up for the rest, exits will be on brutal terms, customers will tighten their belts, early-stage talent will flee and the general sentiment will turn from greed to fear.

In my experience, Opportunist founding teams are less likely to survive this trough. It will require grinding out on fumes and focusing on real customer problems vs vanity metrics and perpetual fundraising. It will need gut-wrenching decisions that sacrifice short-term gratification so that the long-term upside can be captured. It will require possibly resurrecting the company many times from the dead.

Being able to do all this requires extremely high conviction deep down in the gut. Founders who are Believers will have this conviction in their DNA, and when the cycle turns negative, this will become their competitive advantage.

Given this is turning out to be a key evaluation point for AI deals, have been thinking through what leading signals can be used to spot Believers with higher probability. Here are some working hypothesis thoughts on this:

[Disclaimer: am just thinking out loud here so please take this with a pinch of salt. This is nowhere near any gospel of truth, nor do I have significant experiential validation around these points given we are literally in the first wave of AI deals].

1/ Pre-ChatGPT AI builders – likely to have been working in AI much before ChatGPT was launched. They were most likely building with ML, NLP, and neural networks in a Big Tech team, a lab, a university, or some sort of R&D/ academic environment.

2/ Pre-AI domain experts – likely to have been working deeply in a specific domain/ industry/ sector/ function from pre-AI days and are now adopting LLMs to carry forward their domain work and solve customer problems that were previously unsolvable or unviable.

3/ Young tinkerers – likely to be fresh grads who started building AI-native products as a hobby during university, maybe as part of a side hustle, or even just out of intellectual curiosity. They would have likely built products and hacked a few early users even without “doing a startup”.

These are only some of the personas I have been thinking through. As I meet more teams, I will keep adding to this list.

If one looks at how the early days of Web 1.0 played out (eg. in eCommerce and Search), most first-movers ended up dying. The 2nd generation companies leveraged both the market that was created by the 1st gen, as well as learnings from their failures, to create new categories and emerge as viable businesses.

History doesn’t repeat exactly but often rhymes, thus requires being even more thoughtful about which companies to back in this 1st generation of AI. In my case, as a US-India corridor investor, there is an additional complexity to think through – how will AI companies being built out of India compete with those in Silicon Valley? Who is most likely to be stronger in which part of the AI stack?

With domestic data being of strategic importance to each country and the rise of country-specific models, is AI going to be an extension of the globally decentralized software product/ SaaS story of recent years? Or will there be opportunities in ring-fenced, domestic AI in each major geography?

These questions and unknowns are what make the present times in AI investing both interesting and challenging at the same time. To manage this context, I am trying to be open-minded, learn fast, and think from first principles as much as possible. But at the same time, balancing this default-optimism stance with being non-trigger-hungry, consciously thoughtful, and taking the time to build personal conviction on each opportunity.

PS: check out the previous post #4 in the AI Musings series – How To Differentiate As An AI Applications Startup?

Subscribe

to my weekly newsletter where in addition to my long-form posts, I will also share a weekly recap of all my social posts & writings, what I loved to read & watch that week + other useful insights & analysis exclusively for my subscribers.

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.

Subscribe

to my weekly newsletter where in addition to my long-form posts, I will also share a weekly recap of all my social posts & writings, what I loved to read & watch that week + other useful insights & analysis exclusively for my subscribers.