Tag: Conviction

Anti-Social Proof

In the words of the great Fred Wilson – “If you can’t figure out why you like an investment and why it will be successful, don’t make it”.

Recently, I came across this awesome (like always!) 2012 post from Fred Wilson (Union Square Ventures) – Social Proof Is Dangerous. Quoting a line that captures its essence:

If you can’t figure out why you like an investment and why it will be successful, don’t make it.

One of the big investing ideas I have distilled from studying the best investors across asset classes – from Charlie Munger and Howard Marks to Bruce Flatt and Vinod Khosla, is that to outperform the average (the index), one has to be “non-consensus-and-right”.

In fact, in my July’23 post ‘An Investing Framework To Find Startup Diamonds‘, I outlined a Consensus vs Signal 2×2 and argued that the outlier venture returns opportunities tend to be found in the High-Signal-Non-Consensus quadrant.

Source: An Investing Framework To Find Startup Diamonds

It was only in 2022, almost a decade after I first started my career as an institutional VC, that I truly embarked on this journey of trying to become a non-consensus-and-right venture investor. As I have outlined in the above 2×2, molding my mindset toward this approach has required consciously working on the following 2 elements:

1/ Having a unique world-view and trusting my instincts to be able to spot ‘Signal’.

2/ Totally ignoring any social proof noise while doing this.

I have observed that while it was really hard to ignore social proof early on in my career (eg. which VC is leading the deal), having seen so many Tier 1 VCs across geos do such foolish things over a decade, I must say with much humility that as of today, I find it much easier to ignore their POVs on something.

A few months back, I also came across comprehensive LP data that validates this organic learning. David Clark of VenCap shared with Jason Calacanis how loss ratios are surprisingly similar across various percentiles of funds, and even the best strike out a lot.

That’s why in my view, it’s foolish to do one-off deals purely on the basis of the social proofing of a lead investor in that deal unless one is actually replicating their entire portfolio construction (which is a benefit only LPs in their Funds get).

This idea also explains why I remain skeptical of loose angel networks, angel communities, and syndicates that really don’t have a unique, grounds-up world-view and right-to-win, and therefore in most cases, do spray-and-pray on allocations in deals being done by VCs.

These deals often suffer from major adverse selection (“if the founder/ startup is so good, why are they raising from you?” OR “what specific value are you bringing to the table because of which a star founder is giving you allocation?”) and are therefore, likely to be on the wrong side of the loss ratios of major funds.

Coming back to the point of social proof, let me neatly summarize my POV on it:

  • If the best Tier 1 VCs are striking out as much as an average Joe VC, there is no value in blindly following them.
  • There could be value in investing in the “best” companies of a Tier 1 VC portfolio but especially at the seed stage, it’s impossible to know beforehand which company will turn out to be this “best” company. Also, companies keep going in and out (and back in) of this “best” bucket multiple times anyway during a Fund’s 10-year lifecycle.
  • Even if there was a way to know which company is indeed the best company in a Tier 1 VC portfolio, why would they give me allocation in it? The best VCs want to keep every bps of ownership in their best companies only for themselves.

Hence, what’s the point of doing a deal purely because of social proof? I would rather spend that effort looking for the best contrarian deals in places where no one is looking, doing the work (and trusting my instincts) to spot Signal in them, and investing in them as early as possible, driven only by my strongest conviction and nothing else.

This approach is already starting to reflect in the early Operators Studio Fund 1 portfolio. In a majority of recent investments (eg. Soulside, Confido, Loop, Astrophel Aerospace, and a recent one in Stealth), I was literally the first investor to build conviction and say “yes” even before the round started coming together with other VCs. In several of these deals, I ended up catalyzing the round itself, making intros to eventual lead investors and even sharing my customer diligence notes with VCs evaluating the company.

In a way, this approach is Anti-Social proof and Pro-Signal. What is Signal, you ask? It can be of two types, as I explained in my July’23 Investing Framework post (quoting from it here):

  • Internal – extraordinary founder-market fit eg. the founder has spent a decade just going deep in the field. Or a backstory that provides an authentic “why” behind pursuing this idea. Or an execution track record in the startup’s arc that is outstanding on important elements like capital efficiency, iteration velocity, or organic customer acquisition.
  • External – eg. a visionary customer is taking a bet, partnering with them in building the early product. Or a domain expert, skilled operator, perhaps even a specific GP in a venture firm, has taken the time to evaluate & build high conviction in the company.

As you can see, there is a little bit of social proofing baked into evaluating Signal too, but it’s much more oriented around operating and execution-oriented conviction vs deal FOMO and an investing herd mindset.

As you churn on this post, here are more POVs on this topic from some really distinguished venture investors over the years (Source: a 13-year-old Quora post titled Is social proof a rational approach to investment selection?)

1/ Roger Ehrenberg (Founding Partner – IA Ventures, one of the best-performing seed funds of all time)

2/ Naval Ravikant (Co-founder – AngelList, one of the best angels of all time)

3/ Dave McClure (Founder – 500Startups, now running PracticalVC)

Additional readings: The Death of Social Proof by Hunter Walk (Co-founder of a very successful seed VC Homebrew).

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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?

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Storyteller vs Scrapper Founders

At the seed stage, how does one distinguish between and evaluate the top-down ‘Storyteller’ vs the bottoms-up ‘Scrapper’ founder personas? And can one grow into the other?

At the pre-seed/ seed stage, I have generally observed 2 founder personas – the ‘Storyteller’ and the ‘Scrapper’:

A. The Storyteller

Extremely articulate at painting the vision and market opportunity. This persona typically comes from pedigreed educational institutions (hence, great communication skills). Often, they have been execs at large corporates, Big Tech companies, and/ or brand-name, growth-stage startups.

Courtesy of this top-tier background, this persona has a naturally strategic, top-down view of the market they are going after, including the “why now?”, secular growth trends, market gaps, competition etc.

This persona is also great at spotting and riding waves, and therefore, is often building at the edge of hot trends (eg. Web3 a few years back, AI now).

This persona has a thoughtful view of how the ‘company’ will scale in the coming years. Everything from hiring and global expansion to marketing and M&A. In general, this persona will talk more about the opportunity, market, growth and scaling, and less about getting the 1st customer, writing early code, design and other aspects of building.

It’s easy to visualize this persona as the Founder and CEO of a multi-billion $ company. Therefore, Investors love this person. Period.

B. The Scrapper

Natural tinkerer in a very specific space. Typically, this interest germinated during teenage or through college. In many cases, this interest was considered obtuse or nerdy by mainstream observers, and hence, this persona is relatively less understood, perhaps viewed as quirky and therefore, underestimated.

Their creative energy manifests in hacking software, teaming up with friends on specific projects, building products as a hobby, or doing side hustles on the weekend.

This persona typically doesn’t have much capital, nor are investors lining up outside their door. So either by choice or fate, there is no option but to build in scarcity.

In fact, this persona is less likely to view their work as a ‘company’. They have a deep and unending curiosity about something and just want to put it out in the world, hoping that maybe a handful of us will ‘get’ it.

This persona thrives in a bottoms-up view of their space – their eyes light up when discussing technology, code, features, users, and anything related to building. They suck at top-down, so-called strategic discussions of possible markets their work could serve.

It’s hard to visualize this person as the Founder and CEO of a multi-billion $ company. Therefore, Investors largely pass over this person.

C. The Scrappy Storyteller

The dream is to spot a founder who blends the attributes of the Storyteller and the Scrapper. Someone who can both build with their own hands, as well as explain with utmost simplicity and clarity, why what they are building matters to the world.

©An Operator’s Blog

As I was drawing this Venn diagram, the one founder who immediately came to my mind was Peyush Bansal of Lenskart. I still vividly remember him pitching to our entire investment team for Series A in 2011 – it was a poetic combination of Storytelling backed by Scrappy execution. Peyush stays as a gold standard founder persona in my head to this day.

So, how does one spot the Scrappy Storyteller? Anecdotally, I have seen a few contexts where this persona lives:

  • Fresh grads of good universities, with a builder DNA.
  • Repeat founder with sub-scale outcomes in previous startups and/ or ‘a point to prove’.
  • ‘Hacker’ personality with good communication skills and a high-potential side project.
  • Deep domain/ research expertise with commercial DNA, often building in university labs.
  • Solid professionals who are under-estimated or ignored as per mainstream social criteria.
  • First-time founder who is executing on fumes, clawing and scrapping to early customers.

Of course, these are just some examples from my lived experiences as a venture investor. The whole point that makes venture capital extremely challenging and exciting as a vocation is that there is zero predictability in where the best founders can be scouted. It’s like going on tiger safaris in India – you might spot one in the wild during the first trip itself, or it might take multiple trips over several years.

D. Can one persona gradually grow into the other?

While all investors are on a perpetual quest to repeatedly find the dream Scrappy Storyteller persona, the reality is most founders would be more indexed on one side, to begin with.

However, the beauty of entrepreneurship is that it’s an extremely long game of survival. Therefore, irrespective of the starting point, founders with a growth mindset can gradually evolve into incorporating the strengths of the other persona, becoming an ideal blend of the two over the journey.

So the key question then becomes – how does one spot which Storyteller can eventually transform into a Scrapper? Or which Scrapper can grow into a Storyteller?

Here are some heuristics I have been experimenting with:

1/ Storyteller ➡ Scrapper

It’s very hard to convert someone into a builder. It’s like what they say in cricket – you can’t teach a fast bowler to bowl fast. Either one has it or doesn’t.

If one hasn’t developed Scrappiness as a muscle through life experience, then the only way to develop it is to go through the fire during the startup journey and not give up while at it.

Surviving for long requires grit. And grit is an outcome of an underlying emotion, which is “How badly do you want to win?”. Whenever I meet a Storyteller, I try to spot signals that help me get conviction around this single question.

2/ Scrapper ➡ Storyteller

I believe that while Scrapping is a muscle that is built over many years via braving adversity and hardships, Storytelling is a learned skill that can be honed with expert coaching and practice.

In my own venture career both institutionally as well as individually, I have seen numerous examples of Scrappy founders gradually becoming awesome Storytellers. More global exposure, as well as tools and guidance provided by VCs, really helps in this.

However, while the odds of a Scrapper becoming a Storyteller are generally positive, one still needs to evaluate how quickly and to what quality can a particular founder evolve?

In this regard, I have come to look for the following signals:

  • Basic communication skills – like command over the language, elementary articulation, clarity of thinking, logical thinking, creating arguments, and basic persuasion skills. It’s like scouting for fast bowlers in Pakistan – if the kid is bowling fast bare feet, with a tennis ball on an uneven dusty playground, the raw material is there for a premier fast bowler.
  • Coachability – self-awareness to recognize personal gaps, humility to seek solutions from experts, listening skills to assimilate feedback, and courage to work on it and become better.

E. The key message

As individuals, we all have our strengths and weaknesses. Ideally, we should choose to play games in life where our natural strengths give us an ‘edge’. Entrepreneurship is the toughest of such games. If you do choose to play it, I believe it’s important to have the self-awareness to map your gaps, and the growth mindset to work on them. If one can follow this approach and survive long enough in the game, success is almost inevitable.

PS: this post is a result of a recent brainstorming session over WhatsApp with my friend and deep tech VC Arjun Rao of Speciale Invest. Thanks so much for your thought partnership in framing this 🙏🏽

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