Nathan Wangliao Yinan, CEO and cofounder of Singapore-based AI startup Havana, shares his journey from McKinsey consultant to AI entrepreneur in a candid interview with Business Insider. After spending nearly three years at McKinsey starting in 2018, Yinan left the consulting giant in 2021 at age 27 to join an AI startup, eventually cofounding Havana, which specializes in AI agents for student recruitment and enrollment teams.
Yinan’s transition from the prestigious consulting firm to the startup world was far from smooth. He moved from a “huge office with all kinds of perks” to a coworking space with just two other people, admitting he told his founder in the first month that he considered returning to McKinsey because the uncertainty “feels too scary.” The psychological challenges of startup life proved to be the most significant hurdle, more than learning product development or sales strategies.
At McKinsey, Yinan gained valuable skills including navigating senior clients, running efficient meetings, and ruthless prioritization. These capabilities translated well to his current role selling AI solutions to universities. However, he also had to unlearn several consulting habits that hindered startup success. The most critical was the tendency to overanalyze and wait for comprehensive data before making decisions—a luxury startups cannot afford.
“Consultants are trained to overanalyze and rely on data to figure out the most optimal solution,” Yinan explained. “In a startup, when you’re trying to make decisions, you’ll never have enough data. You just have to have the guts to do one thing.”
Before founding Havana, Yinan spent two years at another Singapore-based AI startup leading go-to-market strategy. That company was acquired in 2023, after which he launched Havana. The AI agent technology his company develops helps educational institutions streamline their recruitment and enrollment processes, addressing a significant operational challenge in higher education.
Yinan emphasizes that managing one’s psychology is the most important skill for startup founders, more crucial than technical or business capabilities. He notes that maintaining morale amid uncertainty and avoiding comparisons with peers in more stable careers requires constant mental discipline. As a non-technical founder in an AI company, he’s also had to become more vocal and confident in presenting viewpoints to customers daily.
Key Quotes
I was told that the most important and hardest thing in a startup is managing my own psychology. It’s not learning how to build a new product or how to sell.
Nathan Yinan reflects on the key lesson from his startup journey, emphasizing that mental resilience matters more than technical skills when building an AI company. This insight challenges conventional wisdom about what makes successful tech entrepreneurs.
Consultants are trained to overanalyze and rely on data to figure out the most optimal solution. That’s OK for big companies. In a startup, when you’re trying to make decisions, you’ll never have enough data.
Yinan identifies a critical habit he had to unlearn from his McKinsey days. This observation highlights the fundamental difference between consulting methodology and the rapid experimentation required in AI startups, where waiting for perfect information can be fatal.
Maybe I should just go back to McKinsey because this feels too scary. I don’t know if the company will be around in a year.
Yinan’s honest admission about his first month at an AI startup reveals the psychological toll of leaving prestigious consulting for the uncertainty of the tech world. This vulnerability resonates with many professionals considering similar career pivots into AI.
Now, I don’t feel like I have to have all the knowledge. I’m comfortable taking risks and making decisions.
Describing his evolution as an AI startup founder, Yinan demonstrates the mindset shift necessary for success in the fast-paced AI industry, where decisive action often trumps exhaustive analysis.
Our Take
Yinan’s journey illuminates a critical challenge facing the AI industry: translating traditional business expertise into startup success. While consulting firms like McKinsey produce analytically rigorous professionals, the AI startup environment demands a fundamentally different operating mode—one that prioritizes speed, risk-taking, and psychological resilience over comprehensive analysis.
His focus on AI agents for education is particularly noteworthy. While much attention goes to consumer AI applications, B2B solutions for sectors like higher education represent substantial market opportunities. Universities face significant operational challenges that AI can address, making this a pragmatic application area.
The psychological dimension Yinan emphasizes deserves more attention in discussions about AI entrepreneurship. As the AI industry matures, success will increasingly depend not just on technical capabilities but on founders’ ability to navigate uncertainty, maintain conviction, and execute rapidly—skills that traditional career paths may not adequately develop.
Why This Matters
This story provides valuable insights into the growing AI startup ecosystem in Asia, particularly Singapore’s emergence as a regional AI hub. Yinan’s experience highlights the talent pipeline from consulting firms to AI entrepreneurship, showing how traditional business skills translate—and sometimes hinder—success in the fast-moving AI industry.
The focus on AI agents for education represents an important application area as institutions seek automation solutions for administrative tasks. This reflects broader trends of AI adoption in non-tech sectors and the practical implementation of AI tools beyond consumer applications.
For aspiring AI entrepreneurs, Yinan’s candid discussion of the psychological challenges and necessary mindset shifts offers practical guidance. His emphasis on speed over perfect information and comfort with uncertainty reflects the realities of building AI companies in a rapidly evolving landscape. The story also illustrates how AI startups are attracting talent from prestigious firms, potentially reshaping career trajectories for ambitious professionals seeking to participate in the AI revolution rather than just advise on it.