In an interview with CNBC-TV18, Das remarked, “If you examine the history of the Valley, nearly all significant companies have stemmed from a single revolution… for our era, it’s undoubtedly what generative AI can achieve for us.”
Das, who came to Menlo after co-founding Glean—a $7 billion AI enterprise startup—asserts that venture capital now encompasses much more than just financial investment. “Founders are seeking partners who provide not only capital but also moral and emotional support, helping them persist through challenges,” he stated.
Describing himself as a VC with a founder’s mindset, Das believes his hands-on experience at Glean—spanning engineering, product development, sales, and hiring—granted him valuable insights into building a company from scratch. “My time at Glean crystallized for me—this is truly how companies are formed.”
Originally from Kolkata, Das aspired to work in Silicon Valley from a young age. After studying computer science at Cornell and contributing to Google Search, he left the tech giant to help launch Glean. Initially, venture capital wasn’t on his radar. However, he soon recognized that his startup journey provided a unique perspective to aid early-stage companies.
His entry into VC stemmed from the belief that founders benefit significantly from investors who grasp product development, hiring, and technology—not merely finance. “Early-stage venture involves more than analyzing spreadsheets. It’s about knowing how to launch a company,” he explained.
Below is the excerpt from the interview.
Q: Could you share your backstory—Cornell, Google, Glean, and now Menlo? How did you get here?
Das: I grew up in Kolkata. My aspiration was always to come to the Valley and work as an engineer. Growing up, I admired companies like Google, which was a cornerstone of the internet. That was my dream.
At Cornell, I pursued computer science, later joining Google to work on search—a childhood dream. However, over time, I realized the opportunities the Valley offers extend far beyond working for a large corporation. I felt compelled to launch a startup, which is when I crossed paths with Arvind, leading me to join the founding team at Glean.
Q: Would you say that was the best decision you made?
Das: Absolutely. Glean turned out to be a phenomenal decision. It became a $7 billion entity. Observing its growth from about five people when I joined to nearly a thousand now was incredible. It’s at Glean that I truly understood—this is how businesses are built.
Post-Glean, I recognized a gap in the investing realm; few understand the intricacies of building a company. Initially, I hadn’t intended to enter venture capital. However, my experience in engineering, product development, hiring, sales, and marketing at Glean revealed to me how businesses are structured.
While starting my own venture made sense, I realized it could be more impactful to assist multiple companies in navigating their challenges. That’s how I transitioned into venture capital, a sector often populated by business school graduates focused solely on finance.
This isn’t how early-stage venture capital functions—you often don’t have extensive data to analyze. What’s essential is an understanding of technology, hiring practices, and company initiation. I believed I could excel in this, which led me here. It’s been about a year and a half, and I’m thoroughly enjoying it. Working with nascent companies is immensely fulfilling.
Q: Do you consider yourself a VC with a founder’s mindset?
Das: I do. Founders often face an intimidating journey, navigating it for the first time, often in solitude or with just one other person—it can be isolating. It’s an all-consuming job, leaving them unsure of where to turn for help. Their investor often becomes their sole ally.
If an investor comprehends that journey, empathizes with it, and possesses the requisite skills, we can collaborate effectively to help the company flourish. So yes, that’s an accurate description of myself.
Q: In light of Menlo’s “All In on AI” slogan, how do you perceive this focus? How do you approach it differently?
Das: Historically, significant companies in the Valley have emerged from pivotal shifts. We experienced the internet era, the dot-com boom, followed by cloud and mobile growth. Each seismic shift transformed the nature of companies that could arise.
Each era cultivated dominant, recognized companies. For our era, it’s undoubtedly about the potential of generative AI. Numerous new companies are emerging, but this technological shift diverges from previous ones—instead of merely easing product development and distribution, AI reshapes fundamentals.
In today’s AI landscape, investing requires a profound grasp of technology and talent, particularly at the early stages. That’s where we come in.
At Menlo, I collaborate closely with three exceptional individuals: Tim Tully, the former CTO of Splunk; Josh Redfern, the ex-Chief Product Officer at Atlassian; and Matt Groening, who built and sold a billion-dollar enterprise.
In observing founders today, access to capital has evolved. It was once a niche industry, but now there’s abundant capital available. Exceptional founders recognize this and seek partners for their journeys—those who provide moral and emotional support, standing alongside them in the trenches as they establish their businesses.
That’s where we differentiate ourselves. We grasp these nuances, which becomes evident in our early interactions with founders. Recently, I spoke with an early-stage founder who remarked, “I feel like I’ve skipped an hour of conversation because you just get it.”
And I replied, “Naturally, we understand this intimately.” He expressed, “With other VCs, I feel compelled to explain everything. With you, it’s a pleasure to talk.”
This, we believe, sets us apart. While investment experience is certainly valuable, combining it with operational expertise allows us to stand out in a landscape filled with numerous companies.
Q: There are countless companies, yet some are outliers. You’re backing some of these exceptional firms. Let’s discuss Anthropic and the investments you’re making there—a $65 billion valuation with the latest capital raise. What captivates you about Anthropic?
Das: Anthropic embodies numerous exciting prospects. Worldwide, many aspire to be software engineers; computer science reigns as one of the most sought-after majors today—if not the most popular. This shift has transpired over the last 15 years.
In the ’90s, the prestigious career paths were often banking or consulting. Transitioning over time, computer science became the aspiration, attracting immense talent.
What excites me most about Anthropic is the emergence of a reality where machines can perform many functions traditionally reserved for software engineers. This represents a monumental shift in our perception of technology’s future.
Recently, while analyzing a 100MB Excel file that took two minutes to open, I utilized Anthropic’s product, Claude Code. I instructed it to execute a cohort retention analysis based on a dollar, transaction, and customer perspective.
This is a task that typically requires a week for an MBA associate. The software completed it in two minutes, producing elegant graphs. If that’s not captivating, I don’t know what is.
As children, this was our aspiration—to achieve our goals without needing to code. That’s the core of the excitement.
Q: It’s both enchanting and alarming. Anthropic’s team warns of a potential white-collar bloodbath. In this context, will computer science remain attractive? Will MBA associates continue to be relevant? What do you think?
Das: Indeed, it’s quite concerning. Every technological transformation sparks trepidation. Predicting the future, especially in this space, is challenging—any attempt can lead to embarrassment. I’m uncertain about what will unfold in the coming weeks.
All the forecasts, model evolutions, and intelligence advancements—these remain unknowns.
Nonetheless, reflecting on history, humans typically adapt and discover new paths following monumental shifts. Are there risks? Is the future of white-collar jobs uncertain? Perhaps. However, one could argue that even if a hundred people aren’t needed anymore for a task but rather ten, those ninety individuals might pursue new, productive endeavors—benefiting society as a whole.
A topic everyone discusses—yet remains unknown—is the timeline for generative AI to impact productivity and GDP. I believe it’s on the horizon.
Change requires time, but I frequently engage with companies accomplishing more with fewer personnel than ever. We’re witnessing billion-dollar enterprises with substantial revenue run by fewer than ten individuals. Just five years ago, a similar company would have required 250 to 500 employees.
This amplified productivity alone fills me with optimism about the future.
Watch the accompanying video for the entire conversation.
