Core Capital Partners Managing Partner Kam Thindal says AI growth is being held back by talent shortages, not compute limits.
As capital continues to pour into AI, the assumption has been simple: whoever controls the infrastructure — compute, data centers, chips — wins. But Kam Thindal, Managing Partner at Core Capital Partners, says the real constraint isn’t hardware. It’s people.
“Everyone’s talking about CapEx like it’s a cheat code to AI dominance. It’s not. Infrastructure’s useless without the talent to deploy it properly,” says Kam Thindal.
While much of the attention is on the arms race between hyperscalers, foundation model startups, and GPU suppliers, Thindal points to a quieter issue unfolding behind the scenes: teams can’t hire fast enough to keep up with the resources being deployed.
Talent is Becoming the New Compute
Thindal notes that companies backed by $100M+ in funding are struggling to fill senior infrastructure and machine learning roles. That gap, he argues, is where execution risk creeps in.
“You can throw capital at chips. You can’t easily throw capital at technical leadership that moves models into production culture,” he says. “That’s where we’re seeing the real separation between hype and delivery.”
This perspective is shaping how Core Capital is approaching its AI bets: looking not just at what companies plan to build, but who’s actually in the room doing the building.
Hiring as a CapEx Constraint
In Thindal’s view, talent is no longer just an HR issue — it’s directly affecting capital efficiency. Teams that can’t hire are stuck with idle compute or delayed product launches, extending burn and pushing out revenue timelines.
“It’s not the number of GPUs that matters anymore. It’s who’s running them,” he says.
Getting the Financial Model Right
Behind the scenes, Aman Thindal, Core Capital’s CFO, plays a critical role in assessing whether teams have the operational discipline and cash runway to withstand the current hiring crunch.
Aman’s background in managing growth-stage budgets and evaluating long-range technical capex plans helps Core pressure-test whether a company’s scaling plan is actually executable, not just aspirational.
The Core Capital approach is focused on substance: real hiring pipelines, realistic product timelines, and teams that understand that capital alone doesn’t build a company.
What Comes Next
As the AI market matures, Kam Thindal believes companies will start differentiating not on model size or token count, but on speed of execution and stability of engineering culture.
“The advantage will go to teams who can actually ship,” he says. “That’s not about who raised the biggest round. It’s about who can turn capital into working code.”
Emerging tools, including blockchain-based credentialing systems, may also help streamline technical hiring by verifying expertise across borders.
This industry announcement article is for informational and educational purposes only and does not constitute financial or investment advice.
