Why Cutting Losses Early Is the Hardest—and Most Crucial—Skill in Startups and Venture Capital

Cutting losses is one of the hardest decisions in startups, investing, and leadership—but it’s also what separates winners from those stuck in the sunk cost trap. Here’s why mastering this mindset is essential.

Recently read this Forbes article on Igor Tulchinsky, a Billionaire quant trader who runs the hedge fund WorldQuant. In particular, this section on cutting losses caught my eye:

Source: This Billionaire Quant Is Turbocharging His Trading Models With ChatGPT-Style AI

While I don’t come from the public markets world, I have taken a series of major risks as a founder, operator, and investor. Of course, now that I am a full-time venture investor, I live in a world where I take and manage risk every day, including macro, business, tech, portfolio construction, and people, among others.

Based on my journey so far, I can’t emphasize enough the importance of developing the ability to quickly cut losses. Interestingly, before making a major decision, most people are fairly good at identifying & mitigating key underlying risks. However, I have learnt with experience that even after executing the best risk management process, things will still go wrong. And once things go wrong, even the most intelligent organizations & individuals easily fall prey to the sunk cost fallacy (“throwing good money after bad money”).

Let’s take the classic example of finding your next job. As part of a thoughtful risk management process, an intelligent candidate consciously tries and figures out mutual fit during interviews, gathers feedback on the company’s culture, perhaps speaks to customers & competitors to evaluate the product, or, in the case of startups, even does a 1-2 week part-time project before commiting full-time.

A similar scenario is also playing out on the employer’s side. Most hiring managers give high weightage to candidates who come recommended from trusted connections or with whom they share a past history. The interview process consists of multiple rounds to stress-test skills & personality. The company does rigorous reference checks, often also focusing on off-sheet checks to eliminate bias.

So both employers and candidates follow a fairly rigorous risk management process. Yet, as most of us have seen in the real world, leadership hiring has a 50 %+ failure rate in Corporate America. Here are some summarized stats from ChatGPT on this:

In this case, even the most rigorous upfront risk management process can’t account for a variety of post-decision risks, including process weaknesses (a great hiring process can be undone by a weak onboarding & training process), uncontrollable externalities, and random one-off events.

In these scenarios, a willingness to quickly cut losses & limit further damage of time & money on both sides is the best way forward. And make no mistake, it requires a lot of courage. That’s why I found Starbucks firing their last CEO in less than 18 months of tenure to be a very bold move, especially for a company of that scale & history (you would expect them to be sluggish).

While exec hiring missteps can be major setbacks even for large companies, they can often become matters of life and death for an early-stage startup. A wrong hire for a critical role can do strategic & cultural damage that might be irreversible with the existing runway. That’s why the best founders believe in the “fire-fast” philosophy.

Zooming out from hiring, startups succeed by taking calibrated risks on top of a technology change that an incumbent would just find extremely hard to do. This requires running a bunch of iterative experiments with very limited upfront data, but balanced by an asymmetric risk-reward profile (if this works, it will massively move the needle).

By the very nature of these experiments, a majority of them will fail. Combine this with a very limited cash runway that even the best startups get at each stage to get to the next set of milestones, and founders need to combine controlling the cost of each such experiment with an active intent to cut losses once it’s clear that the experiment is not working.

Essentially, a mindset to cut losses early till you get to something that is clearly working is a key requirement for startups to successfully emerge from this maze of early experiments with real product-market-fit. Windsurf CEO & Co-Founder Varun Mohan framed this idea brilliantly in his recent interview with 20VC:

Never fall in love with your idea…

One of the weird thing about startups is that you don’t win an award for doing the same wrong thing for longer.

Coming to my world of venture capital, I have seen many instances where the aversion to cut losses has come back to bite the investor. The context I have seen this the most over the years is in ill-conceived bridge rounds.

Classic scenario – the company has exhausted most of its last round of capital, has created just enough progress to keep existing investors somewhat interested, but if looked at with rigor and intellectual honesty, is nowhere near product-market-fit. Combine this with a founder who is good at storytelling and can pitch “if we get just this much more money, we will break through”, and existing investors are highly likely to cave in & bridge the company.

Unfortunately, in my experience, a majority of these types of bridge rounds don’t end up working. Peter Thiel said this uncomfortable truth a few years back about what he has observed in the Founders Fund portfolio over the decades (paraphrasing):

Once something starts working, people often underestimate it. And when things aren’t working, people often underestimate how much trouble they are in

Everytime a company raised an up round done by a smart investor, it was almost always a good idea to participate…

Steeper the upround, the cheaper it was…

In flatrounds and downrounds, it was almost always a bad idea to participate…

This behavioral weakness is perhaps why Michael Kim of Cendana, a major LP in emerging managers, recently said in an interview that the biggest mistake he has seen GPs make is deploying reserves poorly. My logic is that reserves deployment, especially in rounds without quality external signaling or real business progress, is particularly prone to multiple human biases kicking in, including loss-aversion, likability bias, optimism bias, and overconfidence bias.

Funds with relatively large reserve ratios should think deeply about potential solutions to this problem. One thing I have seen a few funds do is have a dedicated GP whose sole job is to evaluate each reserves-deployment situation like a fresh late-stage deal from the ground up. This can help counter the personal biases of the lead GP on the original deal.

To summarize, the ability to avoid the sunk cost fallacy & cut losses early is critical not just for entrepreneurs & professional investors, but also for each of you as every contact with the real world exposes you to risks big and small, whether you realize it or not. Getting out of sticky situations early enough ensures that you stay in the game and keep compounding your advantages.

That Series A Billboard On The 101

A reminder not to fall into the trap of first-order thinking.

My LinkedIn feed is full of posts making fun of that startup that has its Series A announcement up on a billboard on the 101.

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!

Avoiding Risk Of Ruin

Eliminating weak links that introduce the possibility of Ruin is key to thriving in the real world.

I recently read what 92-year-old, legendary mathematician and hedge fund manager Ed Thorp had to say on longevity (via Nithin Kamath on X):

Source: How a Pioneering Blackjack Master Beats the Odds of Aging (Bloomberg)

I particularly found the part on what Ed calls “defense” highly intriguing – he says: “It just takes one weak link to finish you off”. Essentially, my understanding is that among other things, defense involves avoiding a bunch of things that when done repeatedly, could essentially wipe you out (as in, you die!).

Ed gives the example of “a terrible skiing accident” but other things that come to mind include say helicopter rides, binge drinking, bungee jumping, living next to a dangerous turn on a busy street etc. While the probability of death in a one-off instance of these games might be low, when done repeatedly, the chance of death becomes non-trivial due to repeated exposure.

Nassim Nicholas Taleb calls this concept Risk of Ruin, and I remember getting blown away when I read about it for the first time in his books ‘Skin in the Game‘ and ‘Antifragile‘. So much so that Ruin has become an essential mental model in my toolkit both personally and as an investor.

In particular, I love 2 specific examples of Ruin that Taleb frequently cites:

The Casino Experiment – let’s say we know that 1% of all gamblers playing at the Casino win. So for every batch of 100 gamblers that visit the Casino daily for 100 consecutive days, we know that each day, 99 will be wiped out and 1 will walk away with money. Now take a different case – one gambler visits the Casino daily for 100 consecutive days. In this case, his probability of getting wiped out at some point is 100%.
Russian Roulette (quoting Taleb directly here) – “Assume a collection of people play Russian Roulette a single time for a million dollars –this is the central story in Fooled by Randomness. About five out of six will make money. If someone used a standard cost-benefit analysis, he would have claimed that one has 83.33% chance of gains, for an “expected” average return per shot of $833,333. But if you played Russian roulette more than once, you are deemed to end up in the cemetery. Your expected return is … not computable”.

Taleb calls the former case where different groups do an activity, and probabilities and expected values are computed “in average”, as Ensemble Probability whereas the latter case of a single person repeatedly doing an activity across time as Time Probability.

As common sense would tell us, Ensemble Probability represents a mathematically driven, academic (almost artificial?) scenario analysis, whereas Time Probability represents how we as individuals get exposed to risk in real life.

Time Probability suggests that there is an underlying Risk of Ruin in many more things & activities in real life than our brains can cognitively appreciate in the thick of the action.

Over the years, as I have read/ listened to more thinkers across fields, many of them highlight this same concept of avoiding Ruin in their own words. Examples include:

It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent. – Charlier Munger

Never forget the six-foot-tall man who drowned crossing the stream that was five feet deep on average. – Howard Marks

The 1st rule of investment is don’t lose money. And the 2nd rule of investment is, don’t forget the 1st rule. – Warren Buffett

[Paraphrasing] “Arithmetic returns are false hopes; the truth lies in geometric returns” / “Profit is finite. Risk is infinite”. – Mark Spitznagel

Essentially, all these quotes are pointing to the same underlying idea:

The most important force that governs life, be it in health, relationships or portfolios, is compounding.

Given its cumulative nature, the optimal strategy for enabling the magic of compounding is combining avoidance of ‘Ruin’ (going to zero/ total destruction) with ensuring ‘Survival’ over a long enough period of time.

Audio Overview of this post (via NotebookLM):

The Success Flywheel – Part 2 (Superhuman, Perplexity)

Following up with a Part 2 of my last year’s post on ‘The Success Flywheel’ – how the journey of the Founder of Superhuman, as well as Perplexity’s cap table, shows that winners keep winning.

While attending the recent Camp Hustle’24 (which btw, was an awesome LP-GP event; my notes from the event here), I got the opportunity to witness a candid fireside chat with Rahul Vohra, Founder of Superhuman.

I have followed Rahul’s journey for a while now. My last startup Workomo was tackling a similar problem statement to Rahul’s previous startup Rapportive. Also, his article ‘How Superhuman Built an Engine to Find Product Market Fit‘ from First Round Review really helped me as a 0-to-1 founder. In fact, I wrote a post on it myself in 2019 deconstructing Superhuman’s PMF playbook.

Listening to Rahul talk through his life journey in detail during Camp Hustle reminded me of one of my core mental models – the ‘Success Flywheel‘. I first wrote about it in a May’23 post. It essentially means that our world is wired in a way that winners keep winning.

Unpacking this a bit more, I have seen that in every case, the “winner” had a clear first event of success that then kickstarted the Success Flywheel in their lives.

Let’s look at Rahul Vohra’s life journey as an example (from what he shared during Camp Hustle):

Started coding at the age of 8.
Completed undergrad in Computer Science from the University of Cambridge. Went on to enroll in the PhD program but dropped out.
Reid Hoffman (Founder of LinkedIn) was speaking at an event in Cambridge. Rahul met him and asked for one piece of advice, to which Reid responded – “move to the Bay Area”.
Rahul followed this advice, moved to SF, started Rapportive, and as luck would have it, got acquired by LinkedIn!
As Rahul was thinking through his next startup idea after spending a couple of years at LinkedIn, he got this golden advice from a mentor:

If you are a first-time founder, start by going after a niche market with little competition, even if it’s small in the beginning, so you can differentiate more easily.

If you are a second-time founder, go after a very large and crowded market from the very beginning, because you are likely to out-execute and out-raise competition in the space.

Rahul followed this advice and started building Superhuman to go after the behemoth Gmail (which…is free!). On the back of his previous success with Rapportive, Superhuman was able to get backed by top-tier VCs like a16z, First Round, and IVP, in addition to celebrity angels like Ashton Kutcher, Will Smith, and the Chainsmokers.
Through Rapportive and now Superhuman, Rahul obviously became deeply entrenched in the Valley venture ecosystem, building relationships with some of the best founders, angels, and VCs out there. Given this access, he started angel investing on the side and soon started running into Todd Goldberg (Founded Eventjoy; Acquired by Ticketmaster) on several deals.
They both connected, decided to join hands, and started Todd and Rahul’s Angel Fund. If the founding and operating success weren’t enough, check out some of the portfolio companies of this Fund – Mercury, Circle, Descript, Clearbit, and AngelList.

Rahul’s journey is another great example of the Success Flywheel in action – how he was able to keep parlaying his initial success into more success, and it continues.

Even before his move to Silicon Valley and starting up, the initial success event that seems to have catalyzed the Flywheel in Rahul’s journey was his getting into the ultra-competitive CS undergrad course at a top-tier uni like Cambridge. Few get the opportunity to meet OGs like Reid Hoffman in person, let alone get his advice. Being part of a highly selective cohort of young students positioned him to get this sort of early exposure.

As I was ruminating on these learnings from Camp Hustle, I saw this LinkedIn post from Aravind Srinivas, Co-founder and CEO of Perplexity:

Based on current vibes, Perplexity seems to have the best odds among the new generation of AI-native companies to be the “Google-killer”. If this is true, then check out who has access to the next (potential) Google – Jeff Bezos, the entire YC gang, Naval Ravikant, Elad Gil, Balaji Srinivasan, Tobi of Shopify, and other successful repeat founders, operators & prominent investors. It’s the same set of folks who succeeded first in Web 1.0 and Web 2.0, many of whom then also benefited in Web 3.0/ Crypto.

These individuals are already at the top of the pyramid, operate at the tip of the spear of capitalism, and keep parlaying their success from one economic cycle to the next, one asset class to the next, and one technology to the next. Each of their Success Flywheels keeps ripping and getting exponentially stronger with each rep.

Of course, it’s important to acknowledge the hustle, passion, and hard work that continues to grease these Flywheels. But the Flywheel nature ensures that the ROI on each ounce of input keeps compounding at an exponential pace. Then it’s a personal choice whether one eases the input-effort but still gets growing outcomes, or like Bezos and Musk, keeps growing the input-effort and given improving ROI, translates to even better outcomes with each parlay.

PS: for thoughts on how to get the Success Flywheel going in your own life, check out my May’23 post ‘The Success Flywheel‘.

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The Funnel Of Doing New Stuff

Whenever someone thinks of starting anything new, say a habit like working out or reading regularly, a side hustle, a passive income project, or even a full-time venture, they should expect to enter the “Funnel of Doing New Stuff”.

This past week, I launched an experiment of extending An Operator’s Blog into a podcast (I call them “jamming sessions”). Through these sessions, my idea is to discuss real operating questions and challenges faced by early-stage founders and folks in the venture ecosystem. Also, invite guests who are deep experts in their area but aren’t very visible.

The first episode is on “Doing 0-to-1 as a cybersecurity startup” where I went into brass tacks with two amazing venture-backed founders and engineering leaders in the domain – Buchi Reddy B (Founder and CEO of Levo.ai; ex-Traceable AI, ex-AppDynamics) and Ruchir Patwa (Co-founder and CEO of SydeLabs; ex-Google, ex-Mobile Premier League).

If there is one thing I learned from my past experience as a founder, it was to ship the MVP and put it in front of users as fast as possible so that the iterations can begin. Therefore, we recorded the episode on Apr 19 and I released a fully edited version to the public on Apr 23. Even before experimenting with this new format, I had resolved to ensure that whenever an episode gets recorded, it gets released within the next few days.

This idea also stems from my frustration wherein I was a guest on podcasts where the episodes were still not public even after a few months of recording. I thought this was just my experience but talking to others in my network, this apparently is quite common.

Given we live in an age where content is being thrown at us with high velocity from every direction, even the most insightful conversations have a relatively limited shelf life. An episode recorded 2 months back is likely to feel stale to listeners today. Then why are these part-time recorders hell-bent on maintaining a huge backlog of recorded material?

I was brainstorming this with my better half and an interesting idea developed during the conversation. Whenever someone thinks of starting anything new, say a habit like working out or reading regularly, a side hustle, a passive income project, or even a full-time venture, they should expect to enter the “Funnel of Doing New Stuff”.

The Funnel Of Doing New Stuff (©️Soumitra Sharma)

This is how the funnel plays out in real life – almost everyone out there is constantly ideating about something new they want to do. Everyone wants to start posting more on LinkedIn, or write more, or hike more, or network more.

However, this is where the first stage of drop-offs happens. Very few people take the first step. The inertia of being busy with daily life kicks in for most people. Other times, it’s the fear of failure that stops folks. Or the potential public embarrassment in case things don’t work out.

Next, for the few brave hearts who take the first step, a new challenge awaits them. This is the challenge of staying consistent with this new thing. This is another stage of massive drop-offs, where people begin but don’t consistently execute and eventually give up.

I see a few psychological aspects at play in this stage of the funnel. People generally struggle with any new habit formation, in part because they are unaware of nudges and brain hacks one can use to make the process easier.

Also, we are dopamine-driven creatures wherein our brain naturally seeks excitement. And this excitement is easily found more in doing new things and getting into new experiences (eg. travel, adventure sports, trying new restaurants, social media, etc.) vs. repeating the same task. Hence, consistent repetition is always a mental and psychological challenge for most people.

Now, even for this next cohort of amazing souls who have both started and also stayed consistent, the game isn’t over yet. For any new initiative to translate into real outcomes (business, financial, or life), it’s crucial to constantly iterate and improve on the initial minimal offering (eg. my podcast MVP).

The initial phase of any new project is almost always internally driven – a hypothesis, belief system, or worldview. But for it to resonate with others – your users, customers, audience, partners, or even your own sensibilities, requires running a continuous feedback loop that includes perpetual learning and refinement until people start loving it. Then, this love is a currency that one can use to drive many types of outcomes.

This loop of continuous iteration and improvement isn’t natural to even the best talent, hence there are again drop-offs at this final stage of the funnel. Staying grounded in reality, listening to feedback, and having the humility to change or let go of stuff are all ingredients needed to succeed at this stage. Many don’t make the cut here.

This funnel idea also has an interesting implication for how one should view competition. At a macro level, most fields look cluttered and competitive because one tends to focus on the top of the funnel (the ideating mass) as competition. The reality is that the real competition is at the bottom of the funnel – the handful of highly driven people who started, stayed consistent, and also constantly improved with each rep*. That number is usually fairly small in whatever area or field you look at, and in my view, there is always room for more there.

*An analogy that people who grew up in India would understand – for a serious student attempting to crack the prestigious IIT JEE engg. entrance exam, the competition isn’t the 1Mn students who have registered to take the exam but only the ~100k or so who have put in adequate reps to prep for it.

Staying In The Ring Long Enough

While the key to generating outlier returns in any asset class is to be non-consensus-and-right, the “right” can take a long time to play out. Case in point: Bitcoin.

With inflows into Bitcoin ETFs gaining momentum, the price of Bitcoin has reached ~$52k. Driven by tailwinds of broad-based institutional and retail adoption, a $100k price point appears to be an eventuality, with the imagination of believers now extending to $500k levels (Cathie Wood’s Bitcoin price predictions don’t seem that outrageous anymore!).

Was recently discussing this with an old friend who has been a super-early adopter of Crypto (from the $100-200 BTC price days!). As I congratulated him on what I presumed were “giant payoffs from his early conviction”, he said something interesting:

Even those who got into Bitcoin very early, very few of them have been able to hold on to it during the down cycles.

He was alluding not just to people holding Bitcoin, but even those holding Coinbase stock, including employees who worked there. As the SEC cracked down on the company, combined with the FTX scam and plunging price of Bitcoin, even the most ardent believers in Coinbase ended up selling.

Since then, the US landscape for Crypto has completely changed (read my post: Bitcoin ETFs and The Challenges of Digital Gold). With Binance out of the equation and the regulator proactively bringing all Bitcoin activity onshore and under its domestic purview, Coinbase has emerged as the dominant exchange infra backbone for Bitcoin. This has resulted in the stock being up ~128% in the last 6 months!

So why am I doing this hindsight analysis? I think it highlights a concept I think about a lot, especially given its relevance to my job as a venture investor:

To generate asymmetric returns, you need to have the capacity to stay in the ring long enough for your high-conviction yet non-consensus beliefs to play out.

As I wrote in my post ‘An Investing Framework to Find Startup Diamonds‘, the key to generating benchmarking-beating returns in any asset class is to be non-consensus-and-right. However, there is a hidden nuance in this. The “right” can take a long time to play out.

Benjamin Graham, the Guru of value investing, has taught us that any security’s price should ultimately converge to its intrinsic value (calculated by discounting its future cash flows or DCF). However, he doesn’t give any guarantees as to when this convergence will happen. As the OG investor Joel Greenblatt says:

If you do good valuation work, the market will agree with you eventually. You just don’t know when.
Joel Greenblatt

This is a critically important point. Having a strongly held, non-consensus belief is necessary but not sufficient. Translating this belief into actual returns requires having enough staying power (personal and professional) to withstand the gyrations of Mr Market till its view converges with your own.

This also applies to the frequently discussed topic of the importance of timing for a startup. Essentially, in hindsight, every outlier startup seemed to have started at just the right time to be able to get massive market adoption from some sort of secular tailwind. Think of Uber as leveraging that moment in time when smartphones got GPS capabilities. Or Zoom leveraging the rise of remote work through Covid lockdowns.

I have a strong view on this. I believe narratives around timing are all post-facto. Even the best founders and investors can at best, only build strong conviction on a long-term secular trend from first principles. It’s impossible to predict exactly when this trend will reach a tipping point. Brian Armstrong (Coinbase Founder) and Fred Wilson (USV, first investor in Coinbase) spotted the power of Bitcoin early. Still, they could never have predicted the continued prevalence of zero interest rates for a decade, rampant money printing, rise in national debt, and ultimately, Covid as a tipping point for Crypto.

However, what was in their control was having the conviction to stay in the game and keep building for a decade till the market started agreeing with them. For startups to survive this long, this means:

(1) Founders need grit,

(2) Investors need patience; and

(3) The company needs a continuous cash runway.

That’s why the more outrageously non-consensus the founder’s thesis is, the more I advise such founders to watch their burn as:

Having enough runway is key to staying in the ring. Runway comes from either the ability to periodically access capital markets and/or control burn to make the capital last longer. The former is often not in the founder’s control. The latter always is.

I use this Bitcoin/ Coinbase mental model to keep reminding myself to be extraordinarily patient with my non-consensus bets as a venture investor and also to keep reminding portfolio founders about the importance of staying in the game. From a picking perspective, this means indexing on “grit” as a critical founder trait while evaluating new investments.

Want to leave you with this quote from John Maynard Keynes, the father of modern macroeconomics:

Markets can remain irrational longer than you can remain solvent.
John Maynard Keynes (via a Howard Marks memo)

Negative Expectations Often Lead To Surprising Positives

How expectations versus reality has unfolded over the last couple of years—from inflation and recession to Google and crypto—prompting me to share an interesting working theory.

Well, that’s a surprise! Contrary to all expectations, the US economy grew 3.1% in 2023, compared to 0.7% in 2022. The stock market continues the rally from 2023-end – the S&P500 recently hit all-time highs, powered by the so-called ‘Magnificent Seven’ BigTech stocks.

I remember the OG Stanley Druckenmiller telling CNBC he’d be stunned if a recession didn’t happen in 2023. Going against all such predictions and in the face of interest rates being at 23-year highs, the fact that the economy is poised for a soft landing has got me thinking about market expectations and their bearing on how things eventually play out.

I have a working theory on this – based on observation, I believe that when the market has too much of consensus expectations around a negative event, it somehow reduces the probability and/or the intensity of that negative event.

Let’s play out some thought experiments on this…

#1 Inflation

In 2022, the market (including the Fed) had a consensus expectation that inflation would remain sticky and continue to rapidly increase, thus explaining the steepest rate hikes in history.

However, given this widespread expectation, both consumers and businesses likely started to proactively tighten their belts, managing demand, reducing costs, and improving productivity to increase supply. The combined impact of this proactive action perhaps brought down inflation much faster than the Market expected?

#2 Recession

The market expected that given the steepness of rate hikes and how that has played out in the past, a recession was imminent. This widespread expectation likely prompted both individuals and businesses to proactively become more fiscally prudent, improve their productivity, and essentially, start doing more with less. These efforts perhaps contributed to avoiding a recession and creating a soft landing instead?

#3 Google

Post the launch of ChatGPT in Nov’22, the market held a consensus expectation that Google’s search business would be rendered irrelevant in the new chat-based AI paradigm. The stock hit a 52-week low in early’23, with the likes of Brad Gerstner (Altimeter) proclaiming that Google’s monopoly was over.

However, the rise of OpenAI and negative market expectations likely woke up Google from its slumber, forcing the management to focus, play its hands in AI (Bard, investment in Anthropic), and do some tough belt-tightening (unprecedented series of layoffs and org. flattening from a company that has been considered as a safe haven for employment over the last 15 years).

#4 Crypto

With the SBF scam, and the SEC cracking down on Coinbase and Binance, many thought that the US is completely closed for business in Crypto. In fact, I remember this being explicitly mentioned in one of the All-In Podcast episodes. However, less than a year after these events, the US has approved Bitcoin ETFs, bringing crypto to the mainstream as a legit asset class (read my post “Bitcoin ETFs and The Challenges of Digital Gold“). As it turns out, the SEC crackdowns were not to shut down Crypto but to clean it up so that it could come into the mainstream.

Connecting the dots…

It seems like widespread negative expectations have a tendency to catalyze a chain of mitigating actions by various stakeholders. In this era of social media, this happens even faster than expected. Perhaps, the human behavior of “loss aversion” creates a sense of urgency, precipitating tough decisions and better execution.

Modeling future scenarios…

Let’s use this mental model to run a few more thought experiments on things the market has negative expectations on right now.

#1 AI taking away jobs

The market has a widespread narrative that AI will end up taking away most knowledge jobs as we know them. However, workers are already aware of this shift and are working to counter it eg. upskilling themselves, starting side hustles to create financial buffer etc.

In parallel, universities are already realizing that their coursework might be outdated soon. They are frantically working to upgrade content, get more AI practitioners involved, and introduce coursework that requires “building” as a way to learn.

Enterprises too, are keenly aware of how a post-AI world will require a different set of skills and are already starting to re-train and upskill employees. Further, in less than a year of ChatGPT’s launch, govts. across the world are proactively thinking through the socio-economic ramifications of AI, including how to stay nationally competitive as well as re-distribute wealth in an increasingly unequal world.

Contrary to current market expectations, all this could create a positive surprise on productivity and job creation in an AI-driven world.

#2 China

The market has overwhelmingly negative expectations of China, including how Xi is taking the country back to its communist roots, the population is de-growing and it’s getting geo-politically discarded by the West.

However, this multitude of adversities could actually rally the CCP to undertake path-breaking reforms, the general population to become more productive, and the country generally coming together more effectively to come out of this mess. Again, more likelihood of a positive surprise from here on.

#3 San Francisco

The market consensus is that San Francisco is America’s Gotham City, a decaying region that the next generation of talent is unlikely to choose to live in.

However, these dire circumstances are already putting massive pressure on local political leaders, forcing corporate leaders like Marc Benioff to speak up against how the city is being run, large budget deficits bringing administrative incompetence to the fore, and the city’s residents finally deciding to speak up and drive political change. I won’t be surprised that all this drives a positive change in SF faster than anyone expects.

#4 Commercial real estate

I watched the recent 60 Minutes episode that talked about how commercial real estate is getting decimated in cities like NY, with even marquee buildings at all-time-high vacancy rates. The market has a consensus expectation that work will become overwhelmingly remote and the concept of offices will cease to exist.

However, this rock-bottom could perhaps force developers and landlords to innovate and re-think what the concept of an “office” should be going forward. And, even force cities to upgrade regulations on how urban buildings can be converted to mixed-use. Irrespective of technology, the human need to connect and collaborate with others, as well as be outdoors to refresh and re-energize, remains the same.

Closing thoughts…

Of course, these are just probabilistic thought experiments. As a disciple of Howard Marks, I am always wary of forecasting. However, this working theory that consensus negative expectations often end up seeing a surprise on the positive, is a useful mental model. It helps in not getting overly carried away with the crowd’s narrative, thinking through the likelihood of various scenarios playing out, and positioning yourself optimally.

How Much of Success is Skill vs. Luck?

Is our life a game of Chess or Monopoly? Can we use our skill to control outcomes, or are we at the mercy of luck?

I layer the work of Michael Mauboussin on top of my own life experience, to understand modern reality and suggest ways we can tilt the playing field in our favor.

Since entering 1st grade, my older son has been really into two different kinds of games – Chess and Monopoly. As expected, I am his default opponent whenever he feels like playing either one. Especially on weekends, when he assumes I have nothing better to do anyway!

Anyway, I have noticed an interesting behavioral pattern over many weeks of playing. While my son hates losing in general (need to rewire him on that), he is relatively calmer in accepting defeat at Chess. But when he gets defeated at Monopoly, he totally loses his marbles.

After experiencing several instances of this behavior, I had to ultimately sit him down and explain how Chess is a game of skill while Monopoly is a game of luck. Of course, it’s hard for a 6-year-old to understand the difference, but I think he got the gist of it when I told him the difference between thinking through a Chess move and rolling the dice in Monopoly.

This explanation seems to be working so far. While it helped restore a much-needed weekend peace in my household, it also brought me back to the ‘Skill-Luck Continuum’ framework by one of my favorite finance practitioners, academic and author Michael Mauboussin. Both as a parent and venture investor, I feel this is a good opportunity to do a refresher on MM’s work untangling skill and luck, as well as apply his lens to my own life experience.

Key Source – The Success Equation: Untangling Skill and Luck by Michael Mauboussin (Talks at Google, July 2014).

A. Definitions

Straight out of a dictionary, skill is defined as the ability to use one’s knowledge effectively and readily in execution or performance. Essentially, having perfect skill means the ability to re-create the same performance each time across repeated rounds of a game.

Luck, on the other hand, is much harder to define. The dictionary defines it as a force that brings good fortune or adversity or favoring chance. However, I like the 3 conditions outlined by Mauboussin, that need to be satisfied for luck to be at play:

1/ Operates for an individual or organization.

2/ Is either good or bad.

3/ It’s reasonable to expect that a different outcome could have occurred.

An awesome thought test by MM for this is – “Can you lose this game on purpose?”. If it’s 100% yes, it’s perfect skill. If not, there is definitely some luck involved.

B. The Continuum

All outcomes in life are a mix of skill and luck. So all professional and personal games that we play can be plotted on a skill-luck continuum, with the extreme left being 100% skill and the extreme right being 100% luck. Anything in the middle is a blend.

C. Insights from the Modern World

MM highlights the following insights regarding the interplay of skill and luck in today’s world:

1/ Outliers require both extreme skill and extreme luck – that’s when the likes of Michael Jordan, Bill Gates, and Warren Buffet become what they did.

2/ Mean-reversion* – on the 100% skill side, there is no reversion to the mean. On the 100% luck side, there is a complete reversion to mean.

*Mean-reversion means an outcome that is far from average will be followed by an outcome with an expected value that is closer to the average.

3/ Paradox of skill – in the modern world, as skill improves, the role of luck becomes even more important. Across diverse areas such as sports, business, and money management, it has been observed that the difference between the very best player and the average player has been steadily going down compared to the previous generation. For eg., in the Olympic marathon, the time difference between the 1st place and the 20th place has come down from ~39 mins in 1932 to 5-7 mins as of today.

Standard deviations of baseball batting averages, managers generating excess returns over the benchmark, and the quality of physical or digital goods have all been steadily declining.

Absolute skill has never been higher while relative skill has never been narrower, thus increasing the role of luck in the modern world.

4/ Convexity in payoffs – convexity means for a small change in quality, there is a huge change in payoff. From tennis grand slam prize money to Big Tech market caps, the modern world is littered with winner-takes-all dynamics wherein the gap between the payoffs of the #1 and #2 ranked players is really wide, even though their absolute skills are relatively similar.

D. Suggested Approaches For Skill vs. Luck Games

MM recommends the following two approaches for each end of the continuum:

1/ ‘Practice’ for skill-heavy games

This is where Malcolm Gladwell’s famous 10,000 hour rule applies. More inputs lead to better skills that in turn, are directly correlated to better outputs.

2/ ‘Process’ for luck-heavy games

You can’t improve your luck, you can only manage it. The idea is to focus on what’s in your control.

A good way is to design a process that improves your odds, and play only when you have an ‘edge’. For example:

In poker, place small bets most of the time to avoid ruin, but go all-in when the hand is strong.
Choose to play only against weak opponents.
When faced with a strong opponent, change the rules of the game (see my post on AI wars ‘David (Microsoft) vs Goliath (Google)‘).
Iterate by running small experiments (check out the Business Model Canvas by Steve Blank).
Invest in inefficient markets.
Have an adequately diversified portfolio.

E. Applying to My Life Experience

Let me plot various games from my own life on MM’s skill-luck continuum:

1/ Writing

In any creative field, it’s extremely hard to pick winners. J.K. Rowling was rejected by multiple publishers. Classics like Star Wars and Jurassic Park initially struggled to get greenlit by studios for several years.

An exec at Time Warner had this to say during a guest lecture in MM’s class at Columbia Business School:

We have no idea what’s going to be a hit. We try and run numbers, or apply formulaes, but we really have no idea whether it will work.
Exec at Time Warner

While writing as a creative art is mostly a skill, luck also plays a role in what eventually becomes popular. For eg., even an average work of a popular author will generate more sales than the great work of an unknown author (check out my post ‘The Success Flywheel‘ for more on this phenomenon).

My approach: focus on Practice. Put in reps and continuously learn from observation and feedback.

2/ Venture investing

Classic early-stage venture capital (in today’s terminologies, that would be anything from pre-seed to Series A) is ruled by power laws (see my posts ‘Conviction vs Randomness in Venture Investing‘ and ‘Only Need To Get a Few Right!‘ on this). Given the high levels of uncertainty at this stage of company building, the eventual outcome is a widely distributed set of probabilities. Ergo, picking is really hard.

Data also corroborates this view. In this Venture Unlocked podcast by Samir Kaji, Miriam Rivera of Ulu Ventures cited data from Horsley Bridge that shows for the absolute top-tier of funds like Sequoia and Benchmark, a mere 4.5% of their companies have generated ~2/3rd of all their returns.

Of course, the track record of funds like Union Square Ventures and Benchmark where they have repeatedly beaten benchmark returns across decades of multiple vintages, also suggests that some VCs have more skill than others.

If I had to put venture capital as an industry on the continuum, I would give a higher proportion to luck relative to skill in the blend.

My approach: focus on Process. Respect power law. Identify and double-down on your ‘edge’. Take enough shots at the goal. Ensure asymmetric upside (when you win, you win big).

3/ Public market investing

I have no hesitation in calling myself, as well as many of my successful peers, major beneficiaries of the post-’08 ZIRP decade. For cusp Millennials like us, our peak career years coincided with a never-seen-before era of loose monetary policy, leading to a worldwide economic boom and asset inflation. I am not sure if I will see another decade where the economies of the US, China, and India are all ripping at the same time.

Of course, there was still some skill at play wherein a few were better positioned than others to take advantage of this wave, and they did. But still, a rising tide lifts all boats, as everyone who worked in tech over the last decade would testify to.

With respect to public markets, I totally agree with what Howard Marks says in his 2014 Memo ‘Getting Lucky‘:

But in investing, it’s hard to know what will happen and impossible to know when it will happen. Many things influence performance other than (a) investors’ hard work and skill and (b) the market’s dependable discounting of information about the future. Luck-randomness, or the occurrence of things beyond our knowledge and control – plays a huge part in outcomes.
Howard Marks (Getting Lucky)

So, while the inherent randomness in the world ensures that successful investing requires significant luck, a skillful investor is right more often, over a long period of time.

My approach: focus on Process. Acknowledge how hard it really is to beat the index. Respect randomness. Act as a permanent owner of businesses. Benefit from compounding. Remember that you only need to get a few right.

4/ Parenting

This is the hardest game to analyze. As parents, we all strive for control – the ability to craft, almost guarantee, our kids’ destiny. We read books, talk to other parents, listen to podcasts, hound teachers, and constantly iterate on what is and isn’t working. We continuously gather skills and tools in our yearning to discover the ‘playbook’.

The reality, however, is much harsher. There is no playbook for nurturing humans. There is just too much unique context, too many variables, too many uncertainties, too many externalities – basically, too much randomness. In this dynamic, it’s essentially a fool’s errand to predict anything.

I loved a thought that I recently read on X, and which was also echoed by a few other parents in our school community – “parents can only hope to give a modicum of downside protection to their kids. They can’t guarantee the upside”.

Approach: focus on Process (and Philosophy). Acknowledge the uncontrollables. Let it be organic.

F. TL;DR

Layering the work of Michael Mauboussin on top of my own life experience, here’s what I am netting out to on this topic:

All games in life are a blend of skill and luck.
The modern world is highly random and the future, for the most part, is unknown and unknowable.
Ergo, barring a few specific games, most of modern life is highly influenced by luck.
On top of this, payoffs are getting increasingly convex, courtesy of power laws.
Given these realities, an effective approach to life is to focus on the ‘process’ over outcomes (see my post ‘Conquering Uncertainty, Dhoni & Vinod Khosla Style‘).
Work to discover your ‘edge’ and back it up with deliberate execution that tilts the odds in your favor just a little bit each day.

Conquering Uncertainty, Dhoni & Vinod Khosla Style

What does Cricket legend MS Dhoni have in common with Silicon Valley legend Vinod Khosla?

Both believe in breaking down ambitious goals into achievable Base Camps. Here’s how you can use this idea to manage uncertainty in your own life.

One of my favorite sportspersons of all-time is former India cricket captain MS Dhoni. Not because he won every title there was to win during an illustrious international career, but because I learnt the importance of “process over results” by observing him. India winning the 2011 Cricket World Cup under Dhoni’s leadership had a major impact on me personally at the time. I ended up gorging everything he had to say about his philosophy & approach to both cricket & life.

Post that milestone win, I started trying my best to adopt Dhoni’s playbook of “showing up every day & doing the small steps well” as one of the core elements of my value system. Here’s a quote of his that captures this idea really well (paraphrasing a bit for clarity):

What if this happens? What if we don’t win the game? What if we don’t get selected?

Worry about the “controllables”. Focus on taking care of them.

If we don’t get the desired results, we’ll improve. We’ll change our plans. We’ll execute better and we will get another chance to prove ourselves.

Thinking about the result never gives you the result. Yes, you may have a target in mind but what’s more important is taking care of the small steps in life. What needs to be done, what I am supposed to do, what extra I can do. That is what will help us achieve the target.
MS Dhoni

Fast forward a few years, as I was building my startup 0-to-1, I found most thinking models I had experientially grasped as an operator & investor till then were completely failing me in this new chapter. I was wading through risk & uncertainty the level of which I had never experienced before. This was causing immense personal stress & I figured that I better search for some sort of a new philosophy that could help me reframe my approach before I tapped out in the first round itself.

This is when I chanced upon this insightful chat between Vinod Khosla and Sam Altman. Vinod is known for not mincing his words. While he spoke on several interesting topics, what really stayed with me was the concept of “Base Camps”. Here’s how Vinod explained it (paraphrasing for clarity):

If you have a large vision, say you are looking to climb Mount Everest, it’s never a straight line. You get to Base Camp, Camp 1, Camp 2, Camp 3 and so on.

The right approach is to be obstinate about the vision (getting to the top of Mount Everest) but be flexible on the tactics as things change. When you zig and zag, when you pivot.

You could easily set up Base Camp at the wrong place (revenue, customers, investors) such that it doesn’t help you get to Everest. Or you could work a little longer, a little harder, and set up Base Camp at a place that helps you eventually get to Everest.
Vinod Khosla

This idea of Base Camps really resonated with me, especially as I then connected it back to Dhoni’s philosophy of breaking down a large goal into small, “controllable” daily steps and focusing on executing them to your best ability.

As a founder, this idea helped me to disconnect from the stress of achieving a far-out goal, the path to which is understandably fuzzy at this stage, and instead divert my energy towards thinking through:

1/ What’s my next Base Camp? And;

2/ What should I be doing today to get to it?

Focusing on large & far-out goals naturally leads to a heightened sense of uncertainty, which triggers fear-related emotions. However, once you break down the goal into a series of Base Camps & focus only on the next one you need to get to, it dramatically brings down uncertainty, making the immediate path less blurry & abstracting a set of daily controllables that one can focus on.

This approach helps bring down overall stress in the system, thus making it easier to start what I call the Progress Flywheel:

The vision (goal) can still be in the back-pocket, easily referenceable for inspiration on an ongoing basis. However, daily execution is only focused on the controllables that can help get to the next Base Camp. That’s it, no more, no less!

This idea can also be applied to other contexts like fitness, learning a new skill or building new relationships at work. Essentially, this is one of the core approaches behind persevering at anything where the goal is long-term, the path is fuzzy, and overall, the endeavor has high perception of uncertainty & risk.

The idea of Base Camps is at the heart of the milestone-based financing mechanism that Silicon Valley has mastered as an approach to deploying risk capital.

I believe this idea is also at the core of “living in the moment”, often cited as the key to happiness (whatever that is!).

Through the highs and lows of life, I have discovered that the best way to decrease daily stress & internal conflict in your life is to focus on a one-two combo comprising of an ultra-long-term “Mission” + the next immediate “Base Camp” on that Mission. Avoid anything in between those two, the intermediate planned future, as that’s where stress lives.

The Bunches Principle: why things go right or wrong all at once

What’s common between Nvidia’s recent massive stock jump, Zoom’s unprecedented user growth during the pandemic, SVB’s blow-up in a week & network effects of Calendly?

It’s a phenomenon I call the Bunches Principle, & it poses both risks & opportunities. Here’s how you can be on its right side.

Probably the biggest news of last week was the major pop in Nvidia stock. After an AI-fueled earnings update that massively surpassed market expectations, its stock price rose by 24% in a single day (May 25), taking its market cap close to $1Tn.

While this was happening, I went back to check how the stock has moved since the company IPO’d in 1999 (see chart below). Interestingly, the stock remained flat for almost a decade starting 2006, before growing ~9x between 2016 and 2018, then dropped again in late 2018 before 10x’ing again in the next 3 years. More recently, Nvidia’s stock has been up 235% since its two-year low in Oct’22, beating out the performance of any other S&P 500 company since then.

Nvidia’s stock performance reflects a phenomenon that I see frequently play out in the world at-large, and especially in complex-dynamic systems like financial markets, technology innovation, growth of young companies etc. I call it the Bunches Principle – it states that both good & bad things tend to happen in bunches.

Some examples of the Bunches Principle at play:

1/ Driven by the pandemic lockdown, Zoom’s daily meeting participants rose from 10Mn on Dec 31, 2019 to 200Mn on Mar 31, 2020 and 300Mn on Apr 21, 2020. That’s 20x growth in 3 months flat! This translated to steep revenue growth as shown below:

2/ SVB was a top 20 bank in the US by assets, a category leader in servicing the venture space, and had crossed $40Bn market cap in Nov’21. Even with a downturn in public markets, it had a ~$17Bn market cap on Feb 28, 2023. From there, it went bust in a week and was put under FDIC receivership on Mar 10 (see collapse timeline below).

3/ I see a frequent pattern in enterprise software/ SaaS startups wherein it can take several years for a product to grow from 0 to $1Mn+ ARR (especially when run bootstrapped or with minimal capital infusion), but then, $1Mn ➡ $100Mn ARR happens in a fraction of that time (see chart below). Case in point is Calendly’s timeline – the company was largely bootstrapped in its initial phase, raising only a small $550k seed round in 2014. Tope Awotona (who is a solo founder, to top it all – I mean this company is riddled with narrative violations at all levels!) ran it super-frugally for the next 7 years, getting the company to ~$100Mn ARR in 2021 and only then raising the 2nd round of…wait for it…$350Mn at a cool $3Bn valuation.

4/ I often say that while we think we are living in the age of innovation, our rate of shipping new groundbreaking technology is perhaps 10% of what the US achieved during World War 2. In 10 war-torn years between 1935-1945, here is a sampling of all the things that were invented in the country – Flu Vaccines, Penicillin, Jet Engines, Blood Plasma Transfusion, Electronic Computers, Radar, Atomic Bomb, Jeep, Superglue, Synthetic Rubber, Radar, Microwave Oven and many other spinoff products. It wouldn’t be an exaggeration to say that the foundation of modern life as we know it, was built in WW2.

What creates the Bunches Principle?

Within any complex-dynamic system, there are many interconnected & intertwined constituent elements, each of which is continuously evolving. As this system tries to achieve its stated goal or purpose, its constituent elements are both interacting with each other (“internalities”) as well as with external forces (“externalities”). On a shorter timeline, changes in these internalities & externalities are hard to observe, and often, can appear random or chaotic.

However, in some systems and at a specific point in time, these internalities and externalities combine in a unique way, sometimes called the perfect storm in everyday language, to create a tipping point. Beyond this point, the system makes explosive progress that can be either positive (towards the goal) or negative (away from the goal).

So, in the above examples:

Rapid acceleration of Generative AI via the launch of ChatGPT has created a positive tipping point in demand for Nvidia’s chips & data center products.
The pandemic literally drove the entire knowledge worker population on the planet to adopt video meetings, creating a positive tipping point for a consumerized, self-serve video conferencing product like Zoom (& then eventually for Teams & Meet as well).
Drastic interest rate increase by the Fed in less than a year (from 0.25-0.50% in Mar’22 to 4.75-5.00% in Feb’23) created a negative tipping point for SVB given it held a significant portion of its assets in long term treasuries that had to be marked-to-market to significantly lower levels, thus severely impacting its asset values & in turn, causing a bank run on it.
Calendly is a calendar scheduling product with in-built network effects given meetings are multi-sided. While these types of products have a cold-start problem and take a lot of initial heavy-lifting, once adoption reaches critical mass, a positive tipping point gets created for network effects to take over in a massive way. Same dynamic can also be seen in products like Slack.

What are the implications of the Bunches Principle for me?

Whenever we are operating in a complex-dynamic system, eg. the stock market, venture investing, building a new business, working in a pre-PMF startup, or even careers in general, we should be prepared to encounter the Bunches Principle & take decisions accordingly.

Some of these considerations could be:

1/ While holding a stock, as long as your conviction in the initial thesis holds & the business continues to make solid progress in the right direction, it might be worth holding on even if the stock stays flat, as a positive tipping point could be around the corner. See this pic via a tweet from Ian Cassel that I found worth bookmarking.

2/ In my experience, careers move in step functions, in what I call a “sow-reap” format. You sow for a few years, getting yourself to a tipping point where you reap significant rewards in bunches, post which another phase of sowing begins.

Therefore, it’s important to be patient enough during career journeys, in order to be on the right side of the Bunches Principle & catch those tipping points. Founders & venture investors, in particular, will appreciate this point given their careers involve putting in years of upfront work, with the belief that a giant payout awaits in the end.

3/ Watch out for small systemic risks that could be silently accumulating in important aspects of your life, potentially leading to a negative tipping point down the road. This could be neglecting health on a daily basis, various kinds of small debt piling up, not saving enough on a regular basis, over-exposure to one asset class, taking an important relationship for granted & not giving it enough care on a regular basis, having small but frequent burnout episodes at work etc.

4/ As you operate in various macro environments & external contexts, be aware of any negative tipping points that could be lurking within them. Things like the pandemic displacing life as we knew it, remote work destroying commercial real estate, geopolitical conflicts & their ripple effects coming to your door, regime changes leading to social unrest in your communities etc.

While it’s almost impossible to predict these, designing your life in an anti-fragile way with a margin of safety baked in, can go a long way in countering whatever the world throws at you. PS: for more thoughts on this, check out my post: Building an anti-fragile career (& life!).

In the ever-changing landscape of life and business, understanding and embracing the Bunches Principle empowers us to adapt, seize opportunities, and mitigate risks. So, as you venture forth, be aware of the bunches that surround you, for within them lie the seeds of both transformation and caution.

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