1Mby1M Virtual Accelerator AI Investor Forum: Ihar Mahaniok, Geek Ventures (Part 5)

Sramana Mitra: Let me ask you an interesting question. We have companies like this in our portfolio—really interesting, exciting companies. There is a question these companies have to answer: which go-to-market strategy, which business model do they go with? Do they sell software to clients, or do they sell services to end customers? Because in many cases, they could do either.

Ihar Mahaniok: That’s a very good question. To me, the right answer depends on where you have better sales connections, experience, and where your sales pitch lands better.

For example, if you know many accounting firms, it might be better to sell accounting software to them. They already know you, and you may have a reputation there.
But if you’re building accounting software and don’t know many accounting firms, yet you know many general startups, then it might make more sense to sell accounting services to those startups instead.

In general, we don’t like to invest in companies that still need advice on high-level go-to-market questions. We prefer to invest in companies that already know their go-to-market approach and have an unfair advantage there.

My advice to founders is: think about where you have an unfair advantage in go-to-market.
Today, writing software has become easier and more automated, so it’s less of a differentiator. Your main differentiation is your go-to-market network and sales.
You should think about where your special advantages are and go after those customers.

Sramana Mitra: Great answer. I’ll add another nuance to how our companies are making this decision.
They’re also thinking about exit strategy.
The complete vertical, ground-up approach is new and often has less exit potential than building pure software or software-service companies, which tend to have easier exit paths.
That’s also a consideration people are making.

Another factor is the timeline for AGI—whether it happens in three, five, ten, or twenty years. Each of those possibilities leads to very different strategies.

Ihar Mahaniok: Right. I don’t know when AGI will happen, or even if it will.
From a VC perspective, what’s important is that AGI is still about thinking.
Even if AGI happens, or doesn’t, we want to invest in companies that have a moat that doesn’t depend purely on thinking.

For every company we invest in, we think about how it would compete against future OpenAI solutions that may have much better AI. The key question is: does the workflow look unique?

For example, an AI company in healthcare might already have solved regulatory and integration challenges—that’s a strong moat.

Sramana Mitra: Integration is a good moat.

Ihar Mahaniok: Exactly. Integration and solving regulatory issues create barriers that smarter models can’t easily overcome.
Another moat is connections and knowing people—having their data, relationships, and customer base.

You could hire Einstein as your head of sales and he might fail, not because he isn’t smart, but because he lacks the right connections and experience.
Connections are a big part of what we value—they’re tied to data moats.

Sramana Mitra: Good point. The data moat is also becoming tricky because of synthetic data, which is now easily available and accessible.
Data used to be a strong moat, but that’s starting to come into question.

This has been a great conversation, Ihar. Thank you for coming. We’ll have you back.

Ihar Mahaniok: Thank you, Sramana. Nice to meet you. I really enjoyed this discussion.

Sramana Mitra: Same here. Thank you.

This segment is part 5 in the series : 1Mby1M Virtual Accelerator AI Investor Forum: Ihar Mahaniok, Geek Ventures
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