$18B AI CEO: How to Build a Million-Dollar Business in the Age of AI
Marina Mogilko (host), Andrey Khusid (guest), Marina Mogilko (host), Marina Mogilko (host)
In this episode of Silicon Valley Girl, featuring Marina Mogilko and Andrey Khusid, $18B AI CEO: How to Build a Million-Dollar Business in the Age of AI explores miro’s CEO on building fast, trusted products in AI era Miro’s CEO Andrey Khusid recounts how a simple browser whiteboard evolved into a platform used by 100M people, scaling via delightful UX, virality, SEO, and later enterprise sales—especially accelerated by the pandemic.
Miro’s CEO on building fast, trusted products in AI era
Miro’s CEO Andrey Khusid recounts how a simple browser whiteboard evolved into a platform used by 100M people, scaling via delightful UX, virality, SEO, and later enterprise sales—especially accelerated by the pandemic.
He argues that AI has commoditized building and shortened planning horizons: companies should commit on ~6-month cycles and avoid pretending they can forecast beyond ~12 months amid rapid model and platform shifts.
In an AI-flooded product landscape, he emphasizes that fundamentals still rule—real problem-solving, high-quality execution, rapid iteration, and strong brand/trust—because “nice-looking” is no longer differentiating.
Khusid demos Miro’s AI Canvas as “multiplayer AI,” aiming to collapse weeks of post-meeting work into hours by integrating AI into team workflows; he predicts vertical AI will scale fast and that consolidation will come within 18–24 months.
Key Takeaways
Start with a real problem you personally feel.
Miro began as Khusid’s need for a shared space to collaborate with remote clients. ...
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Distribution follows delight: build an organic flywheel first.
Early Miro growth came from product experience optimized for collaboration invites (virality) plus SEO; only after those channels worked did they layer more intentional marketing and enterprise sales.
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In AI, fundamentals still matter—PMF and quality are the moat.
AI makes shipping cheaper and faster, but not automatically “best in class. ...
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Brand and trust become the differentiator in a flooded market.
As software becomes easier to replicate, Khusid sees “trust” and “lovemark” status as critical. ...
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Aim for a deliberate failure rate to push boundaries.
He suggests a 50–70% success rate across experiments (and even acquisitions), leaving ~30% to fail—so the portfolio includes both safer bets and true moonshots.
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Iterate solutions relentlessly; don’t confuse ‘wrong solution’ with ‘no problem.’
When experiments fail, diagnose whether the underlying problem is real but the implementation is off. ...
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Stop long-range certainty theater; plan in 6-month increments.
Khusid argues the pace of LLM and ecosystem change makes >12-month prediction unreliable. ...
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Win by knowing where you have ‘permission to play’ and ‘permission to win.’
In crowded AI markets, clarity on your unique advantage determines whether you’ll stand out or get pushed into an irrelevant corner. ...
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The next productivity leap is ‘multiplayer AI,’ not solo prompting.
Miro’s bet is collapsing project cycles by embedding AI into team workflows—turning workshops into outputs (summaries, plans, prototypes) during the session, not weeks later.
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Vertical AI will scale fast—then consolidate quickly.
He highlights legal, coding, and marketing as ripe for end-to-end reinvention via agents. ...
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Notable Quotes
““The one thing that we didn’t predict is AI.””
— Andrey Khusid
““You can’t predict from my perspective, more than 12 months.””
— Andrey Khusid
““If you want to build something big, you need to move really fast.””
— Andrey Khusid
““Trust is the new currency.””
— Marina Mogilko
““For me, there are three types of names… name… brand… and then… lovemark.””
— Andrey Khusid
Questions Answered in This Episode
Miro’s early flywheel relied on virality + SEO—what specifically did you design in-product to maximize invites without feeling spammy?
Miro’s CEO Andrey Khusid recounts how a simple browser whiteboard evolved into a platform used by 100M people, scaling via delightful UX, virality, SEO, and later enterprise sales—especially accelerated by the pandemic.
Get the full analysis with uListen AI
You mentioned a 50–70% experiment success rate: how do you define ‘success’ for a product experiment (activation, retention, revenue, NPS), and over what time window?
He argues that AI has commoditized building and shortened planning horizons: companies should commit on ~6-month cycles and avoid pretending they can forecast beyond ~12 months amid rapid model and platform shifts.
Get the full analysis with uListen AI
In practice, how do you determine whether an initiative failed because the problem isn’t real vs. the solution/UI isn’t right yet?
In an AI-flooded product landscape, he emphasizes that fundamentals still rule—real problem-solving, high-quality execution, rapid iteration, and strong brand/trust—because “nice-looking” is no longer differentiating.
Get the full analysis with uListen AI
You said you can’t predict beyond 12 months—how do you reconcile that with enterprise customers who demand longer roadmaps and procurement certainty?
Khusid demos Miro’s AI Canvas as “multiplayer AI,” aiming to collapse weeks of post-meeting work into hours by integrating AI into team workflows; he predicts vertical AI will scale fast and that consolidation will come within 18–24 months.
Get the full analysis with uListen AI
What are concrete signals that a company has ‘permission to win’ in a category (data advantage, workflow lock-in, distribution, compliance, brand)?
Get the full analysis with uListen AI
Transcript Preview
You built Miro, used by 100 million people worldwide. Would you say you'd do the same in 2025?
I would definitely focus on- [beep]
This is Andrey Khusid, CEO and co-founder of Miro. He took a simple whiteboard idea and turned it into an $18 billion company. But in the past few years, the way he builds has flipped completely. Why?
The one thing that we didn't predict is AI.
And that's changed everything, even for him.
You can't predict from my perspective, more than 12 months.
What do you think is gonna happen in 12 months?
I don't know.
AI made building easy. The world is now overflowing with products.
If you want to build something big, you need to move really fast.
Mm.
You need to understand who you are, what you are passionate about.
In the new era, the rules are simple and brutal, and only those who know the main secret will survive. The rest, they'll disappear. Andrey, welcome to Silicon Valley Girl. You built Miro, used by 100 million people worldwide. Let's talk about how entrepreneurship has been changing in the past few years. So Miro is this dashboard-
AI innovation workspace. [chuckles]
Okay, but, like, initially, it was a mind map, right?
It, it was a whiteboard. We started with-
Whiteboard
... a simple idea of-
Yeah
... bringing a whiteboard into a browser.
Pretty simple idea, which grew to become an almost $18 billion company. If somebody who's starting out today, and has a simple idea, how do they rationalize around how big it could get?
When I started the company, I haven't thought about, like, how big it can be. I was just thinking about how I can solve the problem that I have, uh, because before this business, I was running a creative agency. We had customers who were in the same city with us, and then we had customers who were remote from us. I saw as an opportunity is to have s- uh, that shared space, where you can collaborate with customers who are remote, and that's how we kind of came up with a simple idea of bringing whiteboard into a browser. And that time, like, the only goal I had is, uh, to get to break-even business as fast as possible. So I had a team of 10 people, and we were trying to build, um, this product, and then we were rebuilding it, uh, after we figured out some of the early kind of, uh, signals that what we originally built is not working, actually. So everything that we were doing is just trying to build the product that will get to the break-even point, and then we saw that a lot of people were quite excited about the product, and we started to think how we can scale. But again, it was not like we had this ambition to build a multi-billion dollar company then.
But have you ever had that ambition, or it was just-
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