As an operator-angel, I consciously follow a “tech-generalist, founder-first” style of investing. It both suits my background (which is very cross-sectoral & cross-functional) as well as helps me cast a wide-enough net.

I believe one of the core advantages of being a solo investor is not being boxed in a niche fund strategy or sector focus. As tech evolves rapidly across geos, I like the freedom to be able to seek out the best founders in whatever vertical they might be building in, as well as be opportunistic in terms of participating across stages & in special situations too. This is the model that the likes of Elad Gil & Jason Calacanis have followed.

Of course, one has to still identify the game where one has an “edge” in, to have the best odds of outlier returns. For me, that’s focusing on what I call the “Global Indian” founder persona. It includes:

(1) India based founders building for the world (eg. cross-border SaaS, enterprise, deeptech etc.), and

(2) Indian immigrant/ Indian-origin founders building tech cos. in large markets like the US & SE Asia.

This is the persona where I have high-quality access, where I am able to understand & relate to the founder’s journey & motivations, as well as add value with empathy, given I am myself a Global Indian.

With this strategy, I end up with a massive top-of-the-funnel of deals across a wide variety of sectors, stages, geos & check sizes. Over the last few months, I have been trying to think of some sort of a screening framework to be able to quickly figure out where a new investment opportunity fits in my deal universe. Ideally, this framework should help easily visualize a deal’s preliminary fit with my strategy, before taking it into deeper diligence & running my entire check list on it (my core IP!).

While any such framework can involve many types of vectors, I have been experimenting with a “consensus vs signal” 2×2.

Deal Screen	Consensus	Non-Consensus
High-Signal	(2)	(4)
Low-Signal	(1)	(3)

These vectors abstract out 2 important elements of venture investing:

• Consensus – what is the investor-crowd’s opinion on whether this startup* makes sense or not.
• Signal – what is the quality of people** who believe in the startup & have skin-in-the-game.

*”Startup” here means an amalgamation of team, market & product.

**”People” here includes founders, employees, customers, existing investors etc.

Let’s look at what each of the quadrants in the 2×2 mean:

(1) Low-Signal-Consensus – these companies lack high quality operating signals around the business and who the investor-crowd agrees will find it hard to make it big. A typical example would be an idea stage founder with no educational or career spike, going after an established (highly competitive?) market but with weak founder-market fit, and yet to demonstrate any early validation or traction around the startup’s hypothesis.

These opportunities will usually have negligible investor interest. When I come across such companies, my instinct is to first check if I am seeing any positive signal that the crowd is missing. This could be a behavioral characteristic of the founder, something from their personal backstory or from their startup journey so far. Idea is to see if there is some sort of high-quality leading signal hiding in plain sight.

If I sense a likely positive signal, I try and maintain a thread with the founder over coming months, attempting to see if subsequent execution can help build some conviction.

Note: most cold inbounds on LinkedIn, as well as startups from college incubators/ accelerators/ b-plan competitions fall in this bucket.

(2) High-Signal-Consensus – these companies have high quality signals around team pedigree, investor interest, customer traction etc., and who the investor-crowd agrees are potential winners. A typical example would be a repeat founder building in an established market that is universally understandable, has a large TAM and a past history of large outcomes.

While these deals are understandably hot, high investor FOMO around them creates 2 risks:

• High entry valuations, bringing down future returns.
• Because these deals look so obviously good on paper, it drives investors to overlook asking hard questions around the business. Does the repeat founder have fit with the space? Is there hubris at play from past success? Is the company being over-capitalized & therefore, not being set up for capital efficiency?

Therefore, whenever I see a High-Signal-Consensus deal, my antennas go up & I consciously try to keep FOMO at bay while increasing the rigor of the evaluation process.

Note: most deals that I see in angel syndicates or groups fall in this bucket.

(3) Low-Signal-Non-Consensus – these companies lack high quality operating signals around the business. But interestingly, the investor-crowd also doesn’t have a consensus yes/ no view on it yet. Reasons could be the space is esoteric so hard to understand, team’s background is non-traditional, or location is non-top-tier, founder is bad at pitching etc.

While looking at these opportunities, I am conscious of these being potential “non-consensus traps” – companies that look good to someone trying to invest against the crowd just for the sake of it, without building first-principles conviction.

I have an inherent positive bias for underestimated founders & overlooked assets. That’s why I try to be consciously careful in this bucket of startups as with experience, I have learned that bad companies are in most cases, just bad companies.

(4) High-Signal-Non-Consensus – these are the opportunities we as venture investors live for. They are highly non-consensus, with the investor-crowd struggling to access, understand, evaluate risk and build a positive view on them. Yet, these startups have high-quality leading signals, which could be external and/ or internal.

• External – eg. a respected investor, sometimes a domain expert, has taken the time to evaluate & build high conviction around the company. Or a visionary customer is taking a bet, partnering with them in building the early product.
• 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.

This quadrant is the hardest to source for and requires having a really differentiated network of relationships (for referrals) and a personal brand that attracts interest from these types of founders.

When I meet startups in this quadrant, I immediately get to work, spending time with the team & together unboxing every facet of the market. Generally, these deals have relatively less investor FOMO so I can take the time to run my conviction-building process with rigor.

The risk in this quadrant, and purely from my personal investing style & behavior perspective, is that I tend to get positively biased on them very quickly. After many such experiences, I now consciously play devil’s advocate during the evaluation process. Btw this is where running a rigorous conviction building process and avoiding a trigger-happy mode really helps.

Hope you found this screening framework interesting & perhaps helpful for your own venture process. Of course, evaluating an early-stage venture opportunity is much more multi-dimensional than this. But having such a framework really helps in effectively allocating bandwidth while managing high volume deal flow.