For years, CEOs have been given the same advice.
Find one problem. Solve it exceptionally well. Then expand.
It’s simple. It’s disciplined. And for a long time, it was the right way to build.
Kriti Sharma followed that playbook too. In fact, she believed in it deeply.
“Even two years ago, I would have said… find one problem and solve it really well.”
But something has changed.
Not gradually, but in a way that forces a complete rethink of how companies scale.
“I no longer think it… we can solve multi-dimensional problems as long as we stay focused on the same few customers.”
That shift is subtle at first glance, but it has profound implications. It changes how you approach product-market fit, how you prioritize problems, and how you think about growth in an AI-driven world.
Build From the Work, Not the Data
Many companies still begin their AI journey the same way they approached earlier waves of technology. They start with data, assuming that if they collect enough of it and structure it properly, insights will follow.
Kriti takes a very different approach.
Instead of beginning with data, she begins with the work itself. Not abstract workflows, but real people doing real jobs in real environments.
“To truly solve the problems, you have to work alongside these people who are doing the work.”
That might mean standing in a manufacturing plant, riding along with field technicians, or observing how operators interact with systems that have been in place for decades. It’s immersive, and at times uncomfortable, but it reveals details that would otherwise remain invisible.
An application that looks perfect in a demo might fail immediately if it can’t be used with safety gloves. A system designed for constant connectivity becomes useless in environments without reliable internet access.
These are not edge cases. They are the reality.
When you build from the work instead of the data, your product naturally aligns with the way people actually operate. That alignment is what creates real traction.
Why Three Customers Matter More Than Thirty
There’s a tendency, especially in early-stage companies, to chase volume. More prospects, more pilots, more markets.
Kriti pushes in the opposite direction.
She focuses on a very small number of customers at the beginning, often just three.
“Focus on the first three customers… you start to see patterns and then scale.”
What happens within those first few relationships is far more valuable than broad exposure. With three engaged customers, you begin to see repeatable problems emerge. You notice where needs overlap and where they diverge. You understand what is essential and what is incidental.
This is where the thinking begins to shift.
Instead of narrowing your focus to a single problem, you start to recognize that those same customers are dealing with multiple interconnected challenges. Historically, solving all of them at once would have been impractical. It would have required too many resources and too much time.
AI changes that equation.
With the right tools and approach, it becomes possible to address several dimensions of a problem simultaneously, without losing focus. The key is not expanding to more customers, but deepening your engagement with the ones you already have.
Product-Market Fit Shows Up in Unexpected Ways
Most CEOs look for product-market fit in metrics. Growth rates, retention curves, revenue expansion.
Those signals matter, but they often lag behind something more telling.
Kriti described a moment that captures this perfectly.
“Two of my customers told me this week they want their business to run like ours.”
That statement goes beyond satisfaction. It reflects a shift in mindset.
When your customers begin to model their own operations after yours, you’re no longer just solving a problem. You’re influencing how they think about their business. You’re shaping their future state.
That level of alignment is difficult to manufacture. It comes from consistently delivering value in a way that resonates at both a functional and strategic level.
Letting Go Becomes a Requirement, Not a Choice
As companies grow, the role of the CEO evolves, often in ways that feel counterintuitive.
In the early stages, success comes from being deeply involved. You understand every detail, every decision, every trade-off. That level of control is necessary.
But over time, it becomes a constraint.
Kriti is clear about what needs to happen next.
“You don’t hire the best people on the planet and tell them how to do their job.”
Letting go is not about stepping back entirely. It’s about shifting where you apply your energy. Instead of managing execution, you focus on building the team, setting direction, and identifying the next set of challenges worth solving.
In fast-moving environments, especially those shaped by AI, this shift becomes even more critical. The pace of change is simply too high for centralized control to be effective.
AI Changes Where You Spend Your Time
When Kriti talks about AI, she doesn’t describe it as a feature or a capability. She describes it as a multiplier.
“I have personally immersed myself completely into an AI-first working culture… it makes me perform like 10 of me.”
That doesn’t mean working longer hours or pushing harder. It means reallocating effort.
Tasks that once consumed large portions of the day, such as documentation, analysis, or follow-up planning, can now be handled by AI systems. These systems operate continuously, often producing insights or recommendations overnight.
The impact is not just efficiency. It’s focus.
With routine work handled elsewhere, teams can spend more time on the problems that actually require human judgment and creativity. In Kriti’s case, that often means working directly with customers to capture knowledge that would otherwise be lost.
She shared one example that illustrates this well.
“I can hear a bearing fail from 30 feet away… figure out how to capture that before I retire.”
That kind of expertise is difficult to document and nearly impossible to replace. AI creates an opportunity to preserve and scale it, but only if you’re close enough to the work to recognize its value.
Adoption Has Less to Do With Technology Than You Think
There’s a common narrative that traditional industries are slow to adopt new technologies. Kriti sees it differently.
In her experience, the hesitation is not about resistance to change. It’s about relevance.
“I don’t believe at all that they’re slow moving… once they see the value, it’s a different conversation.”
When conversations start with technology, they tend to stall. When they start with real problems, they move quickly.
That distinction matters.
If you walk into a manufacturing company and talk about AI agents, you may not get far. But if you demonstrate how your solution helps them navigate supply chain disruptions, manage workforce transitions, or respond to pricing volatility, the discussion shifts.
It becomes practical. Immediate. Necessary.
A Different Way to Think About Scaling
Kriti’s perspective doesn’t reject the fundamentals of building a company. Focus still matters. Discipline still matters. Execution still matters.
But the boundaries have expanded.
AI allows you to solve more than one problem at a time, provided those problems are grounded in the same customer reality. It enables you to move faster without sacrificing depth, and to scale capabilities that were previously constrained by time and resources.
For CEOs, this requires a shift in mindset.
- Go deeper with fewer customers before expanding outward
- Build alongside users instead of relying on assumptions
- Focus on outcomes, not the underlying technology
- Use AI to amplify your strengths, not replace them
I’ve seen many leaders struggle with this transition. The old rules are still familiar, and in some cases still useful, but they no longer define the limits of what’s possible.
I’m Glenn Gow. I coach CEOs who are navigating these changes in real time.
The companies that win will not be the ones that adopt AI the fastest. They will be the ones that rethink how they build, how they focus, and how they scale.
