The Startup Validation Playbook with Alexey Sapozhnikov

On the Predictable Revenue Podcast, host Collin Stewart spoke with Alexey Sapozhnikov, founder of cybersecurity startup Andeavour, about how he validated his idea before writing a single line of code.

His approach was simple: talk to customers first.

The Myth of the Brilliant Startup Idea

Many founders think the hardest part of building a startup is building the product. But the real challenge comes earlier: proving the problem actually matters.

When Alexey started exploring the idea behind his cybersecurity startup, Andeavour, he didn’t begin by writing code. Instead, he spoke with potential customers. Dozens of conversations focused on one thing: understanding where existing cybersecurity tools were failing and what problems teams were still struggling with.

Eventually, one conversation produced the signal every founder hopes for: “If this product is ready, I want to buy it.”

That moment mattered more than interest or compliments. It showed that the problem wasn’t just interesting, it was worth paying to solve.

Spotting Opportunity in Overbuilt Products

The idea behind Andeavour started with two observations.

First, AI was about to reshape cybersecurity. Many security products were beginning to incorporate AI capabilities, changing how threats are detected and analyzed.

Second, most enterprise security tools are massively overbuilt.

Companies often buy large, expensive security platforms packed with features they rarely use. These tools try to solve every possible problem, which makes them complex, costly, and difficult to manage.

Alexey saw an opportunity in that gap.

Instead of building another giant platform, Andeavour would focus on small, targeted tools, each designed to solve a specific cybersecurity problem. The goal was simple: deliver the functionality companies actually need, without the cost and complexity of a full enterprise suite.

As Alexey described, many companies today pay for the whole cow when they only need a glass of milk.

Validation First: The YC Rule That Matters

Alexey follows a simple principle often repeated by Y Combinator: if you think you have a great idea, go get a customer.

Before building anything, he focused on validation. That meant having dozens of conversations with potential users across the cybersecurity space.

The goal wasn’t to pitch a product. It was to understand the problem.

Alexey asked about workflows, frustrations, and where existing tools were falling short. These conversations helped test whether the pain he identified was real or just theoretically interesting.

Because there’s a trap many founders fall into.

People will often say a problem sounds interesting. They might even say they would use a solution someday. But that doesn’t mean it’s a priority.

Real validation requires commitment. Someone willing to spend time evaluating the product. Someone willing to introduce you to other buyers. Ideally, someone is willing to pay.

As Alexey puts it: “The best validation is the paycheck.”

Why Most Founders Fail at Validation

Many founders struggle with validation conversations for a simple reason: they don’t actually want to have them.

Instead of exploring the problem, they jump straight into selling the product. But that approach defeats the purpose of validation.

Alexey compares it to visiting a doctor who prescribes surgery before asking what’s wrong. “Imagine going to the doctor, and they say you need surgery before asking what hurts.”

Good validation works the opposite way.

Start by understanding the pain. Ask how the problem affects the customer’s day-to-day work. Learn how they’re currently trying to solve it and where existing tools fall short.

Only after you understand the problem should you introduce a possible solution.

Because early-stage sales isn’t about convincing people to buy. It’s about discovering whether the problem is real in the first place.

The First Customer Moment

Andeavour’s first real buying signal came after roughly 20 validation conversations.

At a cybersecurity event in Tel Aviv, Alexey spoke with a potential customer about the challenges security teams were facing and how existing tools were falling short.

About ten minutes into the conversation, the buyer said something every founder hopes to hear:

“If the product is ready, I want to buy it.”

The conversation itself was short. But the moment wasn’t accidental.

Those twenty earlier conversations had helped Alexey refine how he talked about the problem, what language resonated, which pain points mattered most, and how teams were currently trying to solve them.

By the time he reached that customer, he wasn’t guessing anymore. He could clearly articulate the problem and the value of solving it.

Sometimes the breakthrough conversation only takes ten minutes. But it’s usually built on twenty that came before it.

The AI Startup Advantage: Small Teams, Huge Output

One of the most striking parts of Alexey’s story is the size of the team behind Andeavour. The company launched with a small group and still operates today with roughly ten employees.

That would have been difficult to imagine a decade ago. Building a cybersecurity product traditionally required large engineering teams and significant capital.

AI tooling is changing that equation.

According to Alexey, a team of five to ten engineers today can achieve the output that once required fifty or sixty developers. Tasks that used to take weeks, from prototyping to testing, can now happen dramatically faster.

This shift gives founders a major advantage.

Small teams can bootstrap longer, validate ideas without raising large amounts of capital, and reach meaningful revenue before scaling headcount.

In other words, the barrier to building serious software companies is lower than ever.

Why Product-Market Fit Is a Spectrum

One of the most important lessons from Alexey’s experience is that product-market fit isn’t binary.

Many founders treat it like a switch. You either have it, or you don’t. In reality, it’s a spectrum.

Early on, product-market fit shows up as signals rather than certainty. Customers repeatedly describe the same problem. They’re willing to test an early version of the product. Some may even offer to pay before the product is fully built.

Over time, those signals become stronger.

More customers report the same pain. Sales conversations become easier. Prospects actively search for solutions like yours. Eventually, the dynamic flips.

Instead of founders pushing the product into the market, the market begins pulling the product out of them. That’s when you know you’re approaching real product-market fit.

Bootstrapping vs. VC: Choosing the Right Path

Alexey has experience building both venture-backed startups and bootstrapped companies. His view is simple: neither path is inherently better.

The right approach depends on what you’re building.

Some products require significant upfront investment and are better suited for venture capital. Others can grow more gradually and reach revenue without outside funding.

What’s changing the equation today is AI.

New tools are dramatically increasing the productivity of small teams, allowing founders to build and test products faster than ever before. As a result, startups can validate ideas and reach early revenue with far fewer resources.

That shift gives founders more flexibility.

They can bootstrap longer, maintain more ownership, and approach investors later from a position of strength, often with customers, revenue, and proof that the problem is real.