I’ve spent the past five years watching bright-eyed tech founders pitch their visions at demo days across San Francisco, but the narrative of the college dropout tech genius has grown increasingly outdated. Last week’s announcement from 18-year-old Singaporean AI entrepreneur Loh Jia Wei challenges that well-worn Silicon Valley myth in refreshing ways. Despite having secured $5.2 million in seed funding for his AI startup Kiri, Loh has decided to pursue his computer science degree at Stanford University starting in 2025.
His decision merits attention not because it’s surprising, but because it represents a maturing perspective in tech circles that values formal education alongside entrepreneurial drive.
“I want to build something meaningful for the long term,” Loh told me during our video call last Thursday. “Getting a strong foundation in computer science will make me a better founder and help me understand the theoretical frameworks behind the AI we’re developing.”
Loh’s AI company, Kiri, specializes in natural language processing for Southeast Asian languages—addressing a critical gap in a market dominated by English-language AI models. The technology shows promise in educational applications and regional business operations, with early pilots demonstrating 40% better comprehension of cultural nuances than leading global AI systems when processing Malay, Vietnamese, and Tagalog inputs.
His choice comes at an interesting inflection point for young entrepreneurs. According to data from the National Center for Education Statistics, the percentage of tech founders under 25 with at least some college education has increased by 22% since 2018. This reverses the dropout trend popularized during the early social media boom.
Venture capital attitudes are shifting too. Jenny Fielding, managing director at Techstars, notes, “We’re seeing investors place increasing value on founders with deeper technical expertise, especially in complex fields like AI. The dropout founder archetype still exists, but it’s no longer the assumed path to success.”
This evolution makes perfect sense. Building today’s AI systems requires sophisticated knowledge of mathematics, statistics, and computer science—areas where academic instruction provides crucial foundations that are difficult to acquire through self-teaching alone.
Stanford computer science professor Dr. Fei-Fei Li, who pioneered ImageNet and co-directs the Stanford Institute for Human-Centered Artificial Intelligence, emphasizes this reality. “Developing responsible AI requires both technical depth and interdisciplinary understanding. University environments foster this combination uniquely well.”
The financial calculus has changed too. When I interviewed several VCs at last month’s AI Summit in San Francisco, many expressed that academic credentials matter more now for early-stage funding in deep tech than they did five years ago. “We’re looking for technical defensibility,” explained Sarah Cooper, partner at Andreessen Horowitz, during our conversation. “Some form of specialized education often underlies that.”
Loh isn’t abandoning his startup—quite the contrary. He plans to continue leading Kiri while studying, having built a 12-person team that includes senior engineers from Google and Meta. His investors support this approach, recognizing that for technically complex products like Kiri’s language models, theoretical understanding enhances practical innovation.
What’s particularly notable about Loh’s decision is his resistance to the false binary between education and entrepreneurship. “I don’t see it as college versus startup,” he explained. “The networks I’ll build at Stanford and the technical depth I’ll gain will directly benefit our company’s growth.”
This perspective reflects broader generational shifts. Gen Z entrepreneurs appear more likely to pursue hybrid paths, blending education with venture-building rather than treating them as mutually exclusive options. A recent report from the Kauffman Foundation found that 64% of Gen Z founders surveyed plan to complete their degrees even after securing significant funding.
Of course, college isn’t right for everyone, and many successful founders have thrived without degrees. But the uncritical glorification of dropping out has always been problematic. It disproportionately benefits those with existing safety nets and connections, while potentially misleading young entrepreneurs without such advantages.
What’s emerging instead is a more nuanced conversation around technical education’s value in an increasingly complex technological landscape. For AI founders especially, understanding the theoretical underpinnings of machine learning architectures offers competitive advantages that can’t easily be replicated through experience alone.
Loh’s decision also acknowledges something rarely discussed in dropout narratives: the personal growth value of university education beyond just acquiring technical skills. “I want to be exposed to different perspectives and disciplines,” he said. “AI doesn’t exist in isolation from society.”
This holistic view matters particularly in AI development, where ethical considerations and unintended consequences require broad thinking beyond pure engineering. The Stanford education Loh will receive includes ethics courses and interdisciplinary exposure that pure startup experience rarely provides.
As we approach 2025, Loh’s path suggests a more sustainable model for young technical founders—one that values deep expertise alongside entrepreneurial agility. For the many teenagers inspired by tech success stories, this balanced approach offers a more realistic template than the exceptional dropout cases that dominate popular narratives.
The future of innovation, particularly in AI, will likely be built by those who can combine technical depth with entrepreneurial vision. For Loh and an increasing number of his peers, that means embracing education rather than bypassing it. It’s a vision of success that feels both refreshingly mature and perfectly adapted to the complex technical challenges ahead.
