Changing Talent Assessments with Video Games ft. Gianluca Ferremi

On the Predictable Revenue Podcast, Collin Stewart sat down with Gianluca Ferremi, CEO and Co-founder of WisePath, to unpack a deceptively simple question: why do so many hires fail?

Gianluca’s answer challenges the default narrative. Nearly half of new hires don’t work out, and most failures have nothing to do with technical ability. This points to a deeper issue.

It’s not a talent problem, it’s a measurement problem. Because if you can’t measure how people actually behave, you can’t predict how they’ll perform.

The Hidden Reason Hiring Fails

Hiring didn’t suddenly get worse during the pandemic, what changed was our ability to see the problem.

For years, the system appeared to work because it was optimized for signals that are easy to evaluate: resumes, credentials, and technical skills. These inputs are structured, comparable, and scalable across large candidate pools.

But they are also incomplete.

They tell you what someone knows, not how they operate. And in most roles, performance is far more dependent on how someone thinks, communicates, adapts, and handles pressure than on what they can demonstrate in a controlled assessment.

The pandemic exposed an already existing problem. 

When environments became more volatile and less structured, the gap between technical capability and real-world performance became impossible to ignore.

The result is a pattern most companies know too well: candidates are hired because they meet the measurable criteria, and let go because they fall short in areas that were never properly evaluated.

Soft Skills Are the Real Differentiator

If hiring failures were only about skills, the fix would be simple: train more, test better, raise the bar. But that’s not how performance actually works.

In sales, there’s a simple principle: you don’t create demand, you uncover unmet needs. The job is to understand what’s already there and align the solution to it.

The same logic applies inside a company: People don’t fail in isolation, they fail in context.

An employee can be highly capable and still underperform if the environment doesn’t match how they think, communicate, or operate. Put that same person in a different team, under a different manager, or in a role that better fits their strengths, and the outcome changes completely.

That’s why performance is so often misdiagnosed.

It’s treated as a reflection of capability when it’s actually a function of fit.

Until you understand both sides of that equation, you’re evaluating how well people happen to fit the system you’ve put them in.

The Insight Behind WisePath

If performance depends on behavior, the next question is simple: How do you actually observe it?

Most companies rely on interviews, assessments, and structured tests. But all of these share the same flaw: they’re artificial environments where the candidate knows they’re being evaluated, and that changes everything.

The moment you know you’re being tested, you stop being yourself. You optimize for the “right” answer, you manage perception, you perform. What you get isn’t real behavior, it’s a polished version of it.

That’s why traditional assessments are inherently biased. 

They don’t measure how someone actually operates day to day, they just measure how well someone can simulate competence in a controlled setting.

But real ability shows up when there’s no script, no obvious right answer, no pressure to perform for an evaluator. It shows up when people forget they’re being measured.

Why Video Games Work (The Contrarian Bet)

So if you want to understand how someone actually behaves, you need an environment where they stop performing and start acting naturally.

That’s where the contrarian bet comes in: Video games, because they create the exact conditions traditional assessments can’t.

Just a dynamic environment where decisions have consequences and problems need to be solved in real time. And, critically, no pressure to impress anyone.

That combination changes behavior.

People stop optimizing for perception and start optimizing for outcomes. They experiment, adapt, react, and reveal how they actually think.

Games don’t measure what you say you’d do, they measure what you actually do.

And because the environments are complex, often more complex than day-to-day work, you get a clearer signal of how someone handles ambiguity, pressure, and trade-offs, not in theory, but in practice.

Product-Market Fit Moment

A lot of ideas sound compelling in theory, but product-market fit is where the conversation changes. 

Early on, every discussion starts the same way: you’re explaining why the problem matters? Why do existing approaches fall short? Why should anyone care? That’s the grind. But at some point, the dynamic flips.

Customers don’t need to be convinced that the problem exists, they’re already feeling it. The conversation moves past why this matters and into how we use this.

That’s when you know something has shifted.

For Gianluca, the signal was simple: price was no longer the objection.

Instead of pushing back, customers already had a budget in mind. Instead of debating the premise, they wanted to understand the implementation. Where it fits in their hiring process, how quickly could they roll it out?

Product-market fit isn’t when people say your idea is interesting, it’s when they’re ready to act on it. And when that happens, everything downstream gets easier, because product-market fit doesn’t just validate the product, it multiplies every go-to-market effort that follows.

GTM Lessons (This is where founders get value)

Getting to product-market fit is one thing, figuring out how to get in front of customers is another. The first customers didn’t come from scalable channels, they came from the network.

That’s not unique, but it’s unavoidable. 

When you’re introducing something new, especially something that challenges how people think about hiring, trust matters more than reach. Warm introductions open doors that cold outreach won’t. But that only gets you started. 

What actually drove volume early on was events.

The product has a built-in advantage: it creates curiosity. “Using video games to assess candidates” is just unexpected enough to start conversations. People want to see it, understand it, and challenge it.

That curiosity is a double-edged sword… Handled well, it pulls people in, handled poorly, it makes the product sound like a gimmick. Which is why messaging becomes critical.

If your product sounds crazy, distribution isn’t your first problem, positioning is. You have to do the work to frame the problem clearly before you introduce the solution. Otherwise, people dismiss it before they understand it.

The takeaway is simple: early on, how you explain the product matters as much as the product itself. Because if people don’t take it seriously, they’ll never get far enough to see that it works.

Bigger Trend (Tie to AI)

All of this becomes more urgent when you look at where the market is heading.

For years, technical skills were the primary filter. They were scarce, hard to acquire, and easy to justify as a hiring benchmark. That’s changing fast.

AI is rapidly commoditizing hard skills… Tasks that once required specialized knowledge can now be performed, assisted, or fully handled by faster, cheaper systems.

Which means the value of those skills is compressing. What doesn’t compress the same way is human behavior.

Those aren’t easily automated, and they don’t show up on a resume. 

So the bottleneck shifts.

It’s no longer about whether someone can do the job, it’s about how they operate when doing it. As AI makes technical skills cheaper, human behavior becomes the only real edge.

Conclusion

The hiring playbook most companies rely on was built for a world where technical skills were scarce and stable. That world is gone.

As AI lowers the cost of execution, the advantage shifts to how people think, adapt, and operate in real environments, not how they perform in controlled ones.

The companies that figure out how to measure that will hire differently. And over time, they’ll outperform the ones that don’t.

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