Glenn Gow, The Scaling Executive Coach and host of The Scaling Executive Podcast, interviews Bernardo Hernández, co-founder and co-CEO of Pensero AI, on the leadership shift that separates CEOs who scale from CEOs who stall.
The CEO who built the company is often the wrong person to scale it — unless they change. Bernardo Hernández has scaled companies across three decades, from co-founding Idealista to leading Flickr and Zagat inside Google, to engineering exits at Tuenti (acquired by Telefónica) and Verse (acquired by Block). His rule is direct: the skills that make you effective when you are small will actively work against you when you grow. The CEO who survives scaling is the one who recognizes which version of themselves the company needs right now, and who makes that shift before the company forces it.
When scaling pressure hits, the highest-leverage move is not product, not capital, not market timing. It is a fundamental change in how the CEO leads.
This episode is for CEOs who have achieved early traction and are now asking whether their personal operating style is keeping pace with company growth — or quietly holding it back.
Key Takeaways
- The skills that make a CEO effective at 10 people — speed, scrappiness, doing everything — actively hurt performance at 50 or 100 people. Scaling requires a deliberate shift in operating mode, not just adding headcount.
- CEOs lose visibility into execution not because they stop paying attention, but because the data to support good decisions has never existed in their function. Measurement infrastructure is what closes the gap between perception and reality.
- AI adoption inside companies is moving slower than technology development — not because of resistance, but because business culture and internal processes are not yet redesigned to absorb it. CEOs who assume technology rollout equals productivity gain will be disappointed.
- The best signal that a CEO has done their job is sitting in a leadership team meeting and realizing every person in the room is better at their role than the CEO would be.
- CEOs who bring boards a clear set of execution metrics — resource efficiency, risk identification, roadmap fidelity — extract more strategic value from those conversations than CEOs who report on narrative alone.
How CEOs Must Shift from Hunter to Coach as Companies Scale
You started by doing everything. You had to. At an early-stage company, the CEO who refuses to get in the weeds does not survive. Speed matters more than structure. Hustle matters more than hierarchy.
But that operating mode has a ceiling. When you cross it, the same behaviors that made you effective start making you the bottleneck.
Bernardo Hernández describes the shift plainly:
“The person that you need to be when you’re small, you need to be almost like a hunter and you like it. Everyone is doing everything, building whatever needs to be built at the beginning. And then as you scale the organization, you need to be more of a mentor or a coach. You just need to hire the right people and let them execute properly.”
The word “let” matters. Many CEOs hire the right people and then fail to let them work. They stay in the details. They second-guess. They require too many check-ins. The hiring decision was right. The releasing decision never happened.
Hernández describes what the scaled CEO role actually looks like:
“You just need to be there like a spiritual leader that is just like providing them with whatever they need for them to execute.”
That is a different job description than most CEOs are operating from.
The practical test: when your company crosses 30 to 50 people, look at how you are spending your time. If you are still the person solving functional problems, you have not made the shift. Your job at that point is to hire people who solve those problems better than you would, remove whatever is in their way, and hold the culture together while they work.
Hernández puts the hiring mandate in stark terms: “At that point you need to start hiring people even better than you — people that you can even work for — and just let them execute.”
I sat at my own leadership team table as a CEO and realized the same thing. Every person in the room was better at their function than I was. For a moment, that felt like a problem. It is not. It is the goal. That is what scaling looks like from the inside.
Why CEOs Lose Visibility Into Execution — and What Measurement Does About It
Most CEOs believe they have a reasonable read on what is happening inside their company. They have conversations. They attend standups. They read reports.
The belief is understandable. The belief is often wrong.
Hernández has watched this play out across three decades of building companies. His observation: the problem is not attention. The problem is the absence of infrastructure that makes the truth visible.
“I’m a huge believer in measuring everything that you’re doing so you can actually have an educated decision. Sometimes you think you’re perceiving anything that is going on. That is true. That’s true for certain things. But for others, you need metrics. You need KPIs.”
He traces the history of transparency across business functions. Sales went from gut feel to real accountability when Salesforce arrived. Marketing went from guesswork to measurement when Google and Google Analytics arrived. Finance went from lagging signals to real-time visibility when Oracle and enterprise resource platforms arrived.
Each function made the same transition: from theater of perception to accountable data.
Engineering has not made that transition. Until very recently, the CEO had almost no reliable visibility into what the engineering team was actually producing, how effective the work was, or whether the investment was returning results.
“For engineering management, we were still in that place of lack of transparency. It was really hard to know what the engineering team was doing. Do I have the right people? Are they working on the right things? Why am I going slow? How’s the quality of the code that I’m producing? How effective is the use of AI? All those questions were very hard to answer, especially when you go over 30, 40, 50 engineers within your organization.”
This matters to any scaling CEO whose largest cost center is engineering. The conversation in the board meeting is almost always about the product roadmap. Engineering execution is assumed. That assumption is where the gap lives.
The fix is not more meetings or more check-ins with your engineering lead. The fix is measurement infrastructure. The first question to ask when scaling stalls is not “what is wrong with our engineers?” It is “do we have any reliable data on what they are producing, and what standard are we holding that output against?”
Why AI Adoption Inside Companies Is Moving Slower Than the Technology
Most of the AI conversation inside executive teams is about technology choices. Which tools. Which models. Which vendors.
Hernández reframes the question — but starts with the size of what AI represents:
“AI is the holy grail of computer science. I’ve been doing tech for 30 years and I’ve been waiting for this moment my entire life. It’s the moment when software is learning. We don’t need to program software — it’s programming itself.”
That excitement comes with a clear-eyed observation about pace. The technology is moving fast. Business adoption is not.
“I don’t think the business adoption is going to happen as fast as we think. And it’s primarily because of us. I think we’re not built for fast changes.”
Hernández points to Anthropic’s own research as confirmation. The data showed that adoption is moving slower than anticipated — not because organizations are hostile to AI, but because the internal practices, processes, and cultures required to absorb it have not been redesigned.
This is the CEO’s problem to solve, not the CTO’s. Technology rollout without process redesign produces frustration, not productivity. The question CEOs must ask is not “have we deployed this tool?” It is “have we redesigned the workflow this tool is supposed to improve?”
How CEOs Should Build AI Strategy Around Flexible Architecture and Niche Applications
The second error most scaling CEOs make on AI is waiting for a dominant platform before committing. That platform is not coming — not in the form the internet or the browser provided.
“I think we’re going to see faster adoptions in the small niches. It’s going to be very simple, powerful models that they’re going to bring the largest productivity gains. And the combination of all of those is where it’s going to really change.”
For the scaling CEO, this means two things. First, build flexibility into your architecture so you are not locked to one stack as the underlying technology shifts. As Hernández puts it: “Whatever you build needs to be flexible enough to adapt to an ever-changing tech stack underneath.”
Second, identify the specific workflow inside your company where an AI application will produce a clear, measurable result, and build from there. Do not wait for a comprehensive platform strategy. Find the niche. Prove the gain. Expand.
The Scaling CEO’s Framework: What Changes at Each Stage
| Principle | What it means in practice | Named evidence from this interview |
| Hunter to coach | The CEO’s operating mode must shift from doing to enabling. The trigger is when the company needs specialization more than it needs generalism. CEOs who do not make this shift become the bottleneck. | Hernández scaled Tuenti to an exit acquired by Telefónica by building and then stepping back from execution — the company’s sellable scale required a team that could run without the founder in the details |
| Hire above your ceiling | The right hire at scale is someone you could work for, not someone you manage. CEOs who hire people they can outperform produce a team with a ceiling at the CEO’s own skill level. | Hernández: “You need to start hiring people even better than you — people that you can even work for — and just let them execute.” |
| Measurement closes the perception gap | CEOs who believe they have visibility without data are operating on theater. Every function that gained accountability did so through a measurement tool, not through more meetings. | Hernández traces this pattern through Salesforce (sales), Google Analytics (marketing), and Oracle (finance), identifying engineering as the last function to receive this infrastructure — the gap Pensero AI was built to close |
| Architecture before AI commitment | Because the AI technology stack is changing faster than business adoption, any AI investment must be built on a flexible architecture rather than a locked stack. | Hernández: “Whatever you build needs to be flexible enough to adapt to an ever-changing tech stack underneath.” |
| Niche before platform | AI productivity gains will come from specific workflow applications, not from a single platform shift. CEOs who wait for a dominant platform will wait too long. | Hernández: “It’s going to be very simple, powerful models that they’re going to bring the largest productivity gains.” |
Quotes from This Episode
- “The person that you need to be when you’re small, you need to be almost like a hunter and you like it. Everyone is doing everything, building whatever needs to be built at the beginning. And then as you scale the organization, you need to be more of a mentor or a coach. You just need to hire the right people and let them execute properly.” — Bernardo Hernández, Co-Founder and Co-CEO, Pensero AI
- “You just need to be there like a spiritual leader that is just like providing them with whatever they need for them to execute.” — Bernardo Hernández, Co-Founder and Co-CEO, Pensero AI
- “At that point you need to start hiring people even better than you — people that you know you can even work for — and just let them execute. I think that’s the secret of scaling.” — Bernardo Hernández, Co-Founder and Co-CEO, Pensero AI
- “I’m a huge believer on measuring everything that you’re doing so you can actually have an educated decision. Sometimes you think you’re perceiving anything that is going on. That is true. That’s true for certain things. But for others, you need metrics. You need KPIs.” — Bernardo Hernández, Co-Founder and Co-CEO, Pensero AI
- “I don’t think the business adoption is going to happen as fast as we think. And it’s primarily because of us. I think we’re not built for fast changes.” — Bernardo Hernández, Co-Founder and Co-CEO, Pensero AI
Frequently Asked Questions
How should a CEO change their leadership style as the company scales?
When a company is small, the CEO must act as a direct executor — doing whatever the business needs, moving fast, and filling every gap. When the company scales past 30 to 50 people, that operating mode becomes a liability. Bernardo Hernández, who scaled companies from Idealista through Flickr, Zagat, Tuenti, and Pensero AI, describes the required shift as moving from hunter to coach: hiring people who are better at their functions than the CEO is, then removing obstacles so those people can execute. CEOs who do not make this shift become the bottleneck, not the builder.
What is the biggest blind spot CEOs have when they think they understand what is happening inside their company?
The blind spot is confusing perception for data. CEOs who rely on conversations and intuition to gauge company performance are operating on what Hernández calls the “theater of perception.” Every business function that gained real accountability — sales through Salesforce, marketing through Google Analytics, finance through Oracle — did so because a measurement tool replaced perception with data. When a CEO feels confident about engineering output or team productivity without a measurement system behind that confidence, the perception is likely outrunning the reality.
How should a CEO approach AI adoption inside their company without getting locked into the wrong technology?
Two principles apply simultaneously. First, the underlying AI technology stack is changing faster than most organizations expect, so any system built on it must have a flexible architecture that can swap out components as better options emerge. Second, the human and process side of adoption is moving slower than the technology. Hernández points to Anthropic’s own research showing adoption is behind projections — not because of resistance, but because internal practices have not been redesigned to absorb AI effectively. The right entry point is a specific, high-value workflow where AI produces a measurable result, not a company-wide platform strategy.
CEOs Work with Glenn Gow to Scale Their Companies by Scaling Themselves First
Glenn Gow is The Scaling Executive Coach — he coaches ambitious executives into the CEO seat and CEOs into successful exits. With 25 years as a CEO and 5 years in venture capital, Glenn helps leaders scale their companies by scaling themselves first. If this conversation was useful, you can apply for executive coaching with Glenn Gow or apply to be a guest on The Scaling Executive Podcast.
