1Mby1M Virtual Accelerator AI Investor Forum: Yanev Suissa, SineWave Ventures (Part 2)

Sramana Mitra: Very true. This is very true. I want to underscore that you should not raise money at the highest valuation you can, because you’re pricing yourself out of the exit market and out of further fundraising. If you don’t meet milestones that are that aggressive and far ahead of the curve, you will be stuck.

Yanev Suissa: It happens even to the greatest companies. I was one of the three earliest investors in Databricks. It’s a fantastic high-growth company and one of the biggest players in the industry, but they’re not public for a reason. One of the biggest reasons is they were always ahead of their valuation. The public markets don’t play that game, and later-stage investors don’t always play it either. You have to be careful.

Sramana Mitra: There’s a term some of you may know: zombiecorn. Unicorns that have become zombies. They cannot find an exit, they’re not growing fast enough, and they cannot raise more money. This is what happens if you raise money at too high a price.

Yanev Suissa: At the end of the day, it’s about building a great business. All the “they raised at this much so we need to raise at this much,” or “the price is the most important thing”—none of that matters as much as building your business. Returns will come for you and for your investors.

Sramana Mitra: A little footnote: 96% of exits in our industry are under $100 million. Be careful about raising so much money that you price yourself out of the bulk of exits.

Switching gears, you’ve talked a few times about your thesis. Can you summarize your investment thesis for entrepreneurs right now?

Yanev Suissa: I’ll give you that in two parts: our broad investment thesis and then the AI piece, which I know you’re particularly interested in.

My background is that I was a senior official under the Bush and Obama administrations, and then at NEA. I’m still one of the only VCs who was senior at a top venture fund and also senior in the public sector. We invest early-stage in companies where the public sector is one of many sales verticals, and we open up that market. I always say “baby Microsoft, not baby Lockheed,” or “baby Databricks, not baby Lockheed.” Companies that are commercial, where we can help with commercial business and also open up a billion-dollar public sector business for the same technology.

AI is part of our thesis—it’s not the only part—and it has always been part of the thesis even before everyone else was paying attention.

In AI, there are a few things people should build toward. You often see reactivity rather than forward-thinking adventure, but you have to think ahead.

Some of those things are access and reliability—consistency in that access. How does a business ultimately get value and make smart decisions from the tech you’re providing? I say nowadays: if I want a banana, I don’t care if there are a thousand AI developers in the back room or a monkey—I just want a banana. If you’re not giving the business what it needs in the exact form it needs it, you’re going to have trouble. Too many companies build tech for the sake of tech rather than for business use.

Sramana Mitra: Solutions looking for a problem. Doesn’t work.

Yanev Suissa: Exactly. You have to be secure and scalable, cross-platform, able to integrate, and multimodal. Another capability people don’t always think about is collaborative sensing: can you develop real memory? Can you become adaptive?

Every great startup addresses a current need but also has a vision for the future and can adapt. Databricks is a good example—it started with real-time analytics based on Spark and then expanded, integrated with analytical tools, adjusted to AI, created a marketplace, and moved into other areas. They were architected for that. You have to architect for a future-proof system.

Things are moving so quickly that you can become obsolete fast. You have to innovate for the markets but also innovate ahead of tech itself. Tech is changing as fast as markets and customers.

The last point is that you need to be built for an autonomous computing infrastructure. You must be able to access different infrastructure but also think about the most efficient use of it. You hear about superintelligence—it’s a huge opportunity and we have investments there—but sometimes for a business use case you don’t need superintelligence; you need a specific function for a specific set of tasks. You have to think about compute power, efficiency, time, and latency in advance. What you’re building must match business ROI.

One Million by One Million (1Mby1M) is the first global virtual accelerator in the world, founded in 2010 by Silicon Valley serial Entrepreneur Sramana Mitra. It offers a fully online entrepreneurship incubation, acceleration and education resource for solo entrepreneurs and bootstrapped founders working on tech and tech-enabled services ventures. 1Mby1M does not charge equity, offers an AI Mentor available 24/7 in 57 languages, and offers a compelling alternative to Y Combinator and other equity accelerators.

The Accelerator Conundrum is a multipart series that challenges the prevailing wisdom of the tech startup ecosystem that entrepreneurs should Blitzscale out of the gate. Written by Sramana Mitra, the Founder and CEO of One Million by One Million (1Mby1M), the world’s first global virtual accelerator, it emphatically argues that a better strategy is to Bootstrap First, Raise Money Later, focus on customers, revenues and profits. 1Mby1M’s mission is to help a Million entrepreneurs reach a million dollars in annual revenue and beyond. Sramana’s Digital Mind AI Mentor virtually mentors entrepreneurs around the world in 57 languages. Try it out!

This segment is part 2 in the series : 1Mby1M Virtual Accelerator AI Investor Forum: Yanev Suissa, SineWave Ventures
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