What are the biggest challenges first-time founders face while building a startup?
Startups are not a “single input – output” model, they are like a “multivariable – complex” model. Most of the time founders are not ready for this because developing this fundamental clarity needs time, you need to fail multiple times, it is an internal process which a founder needs to go through. Also, focus on basics (product, customer, and market) seems to be missing, while a lot of focus seems to be on shiny things (capital access, valuation) without realizing that capital will only follow if you focus on product and customer, and this will eventually open many gates.
How can entrepreneurship education become more practical and outcome-driven?
Legacy education institutions have an important role to play in the society with taxpayers’ support, and they will continue to do so, particularly, in fields like frontier research, and innovation. Entrepreneurship survives on commercialization at scale, and customer access – this requires good understanding of risk and access to risk capital. I don’t think traditional educational institutions are built for this. Most traditional institutions are looking for “repeatable and replicable” programs. Major challenge with an entrepreneurship journey is that it is not repeatable and replicable, what works for one founder in a sector, stage, time, will most likely not work for another founder. We need to build new age institutions to reimagine entrepreneurship programs, legacy institutes already have the physical infrastructure. We are trying to execute this through Mentor Sprints – we are jointly developing entrepreneurship programs with top private and public universities.
How is AI changing the way early-stage founders build and scale businesses?
I have always looked at technology as a horizontal theme in businesses. Similarly, I look at AI as another productivity layer for legacy businesses and startups. Some interesting themes which we have been exploring: Is software as an asset class investable in the AI age? Building MVP is easier then ever so how do we evaluate? Early-stage founders are replying on AI to automate clunky parts of the business model, but they need to be careful that it must translate into better customer experience. In other words, there must be someone willing to fund those tokens at the end of the day. Currently, I am noticing increased founder focus on sustainable economics with AI integration, and this trend is likely to continue across sectors.
What should founders focus on before approaching investors for funding?
Founders should understand that typical professional investor is evaluating a range of opportunities at any given time for capital deployment. You need to imagine the risk – return graph, and imagine range of opportunities, equity, debt, real estate, commodities etc. Startups are at the highest point of the risk – return graph, and you must have some distinction and differentiation in your product to really get the attention from professional investors. In some situations, this distinction and differentiation can also come through execution, but it is hard to prove this in case you are a first-time founder, and there is no track record. Founders need to be obsessed with building the ability to communicate distinction and differentiation at the level of their offering.
Looking ahead, what do you expect India’s startup ecosystem to look like over the next five years?
My very first interaction with the private investing ecosystem in India was right after the global financial crisis in Q42008. Looking back, we have come a long way, currently ~US$ 3bn is being deployed per quarter to startups across stages in India. Looking ahead, I expect this ecosystem to further deepen, in terms of market depth, currently VC AUM as percentage of GDP is very low compared to China, and US. I expect more risk capital will be available at idea and seed stage. Also, more investors will be able to exit through IPOs, that is the ultimate test because capital must rotate within the ecosystem. We have witnessed several IPO stories over the last few quarters, fitting well into this narrative.
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