Vijay Krishnan, a seasoned entrepreneur, and AI expert, embarked on a remarkable journey from his roots in India to the heart of Silicon Valley. This blog post delves into his experiences, academic background, early fascination with artificial intelligence, and the evolution of his entrepreneurial endeavors.
From pursuing a degree in computer science at IIT Bombay to cofounding a successful startup and eventually becoming the founder of Turing, Vijay’s story is a testament to the intersection of passion, perseverance, and foresight.
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Early Days in India and Journey to Stanford
Born in India, Vijay Krishnan’s childhood was marked by exposure to various cities. This exposure helped him gain a diverse perspective from a young age.
He pursued his bachelor’s degree in computer science with a specialization in machine learning at IIT Bombay, around 20 years before the current AI hype.
The early signs of machine learning’s potential intrigued him. This interest sparked in him a passion for probability, statistics, mathematical modeling, and other similar concepts.
Vijay’s expertise in machine learning earned him a coveted spot at Stanford, marking the beginning of his U.S. journey. At Stanford, he further honed his skills and delved into the world of artificial intelligence, even before it became a mainstream buzzword.
The Fascination with AI
During his academic journey, Vijay’s fascination with AI stemmed from the practical applications of machine learning concepts. He witnessed early signs of AI’s capabilities in text categorization, basic NLP, speech tagging, and more.
Classifying different datasets was another area that piqued Vijay’s interest. This intersection of his mathematical curiosity and pragmatic aspirations played a key role in shaping his future endeavors.
Despite these inclinations, Vijay recalls that he didn’t want to become a pure mathematician back then.
Vijay did extensive research into machine learning. During his time at Stanford, he also had his well-cited papers accepted in several conferences and journals.
As a part of the next step, he planned to go to grad school and do research on the applications of machine learning to problems in text, information retrieval, and NLP. Thus, he applied to a bunch of good universities with strong PhD programs.
Eventually, Vijay got accepted into Stanford and was fascinated by its high density of the smartest researchers in the world. During his time at Stanford, he met a lot of world-renowned faculty members and authors whose textbooks are used in computer science classes.
Graduating from Stanford and Venturing into the Unknown
After grad school at Stanford, Vijay joined Yahoo’s AI team. However, during his time there, he was consumed by the idea of launching his own startup. The decision to leave a reputable position in a notable company and venture into entrepreneurship wasn’t met with universal approval.
However, Vijay had never been subject to social influences and social pressure. Moreover, being in the right environment further spurred his interest in entrepreneurship.
Vijay concedes that if he had gone to another reputed school like MIT instead of Stanford, he would not have gotten the kind of exposure in a short timeframe to understand what it takes to translate good technology and good ideas into viable businesses.
Thus, driven by a desire to pursue the American dream and fueled by his passion for AI, Vijay took the plunge into the unknown.
First Startup: Pivots and Challenges
Vijay’s first startup, a personalized content recommendation technology company, went through a series of pivots and rebrands at the beginning. This, of course, is a common occurrence for many entrepreneurs finding their footing.
In Vijay’s opinion, founders should avoid pivoting as a company, if it’s possible. They should, instead, de-risk things with a five-year view of how the world will likely change. Pivoting ends up destroying some value in the process, and it’s always more desirable to march on and execute the original business plan.
Next, Vijay’s startup went on to focus on the B2B content recommendations and was successfully acquired. He considers the entire experience of getting visibility and running the full cycle of a company from start to finish as invaluable.
As Vijay points out, achieving failure or success with a company has several aspects, with various factors influencing the outcome. Founders may not learn much along the way if they fail outright.
But, if they go through a fairly difficult time and somewhat bumpy ride but manage to make it to the other side, that’s the real learning experience.
Entrepreneurs can also learn what works, what doesn’t work, and what creates value by looking at the experiences of fellow founders around them. Vijay shares that this process helped him learn at a much deeper level, which is very different from learning entirely from books.
Thus, the challenges and lessons learned during this period, including the importance of market focus and adaptability, laid the groundwork for future success.
Acquisition and Time at Foundation Capital
Post his first startup’s acquisition and integration, Vijay took some time off and decided to take a look at what things were like on the other side of the table.
Subsequently, he joined Foundation Capital as an Entrepreneur in Residence, gaining exposure to the venture capital side of the business. Vijay recalls how the folks at Foundation Capital were always helpful and brainstorming different ideas to work on.
Learning Lessons for the Inception of Turing
The learning process of how to validate a concept and incubate it would eventually become the basis for Turing. Vijay underscores the importance of having an “A+ market” for startups.
He defines an “A+ market” as one with customers who love a product, even if it’s a crude MVP, and are willing to spend money on the product because it solves a crucial pain point for them.
Simply put, capturing an A+ market is about addressing a specific, severe pain point with a product or service that customers are willing to pay for.
Vijay also learned that once founders raise capital, they step into the sprint mode and spotlight, with everyone measuring how fast they are growing.
Vijay explains how he spent a lot of time talking with different customer clients to understand the ins and outs of various businesses. During this period, he dived deeper into recruiting and IT businesses of varying sizes and got to know how unit economics work.
He also shared that having close friends in related industries who were comfortable sharing insights was very helpful. Vijay recalls having had more than 100 conversations with execs of large companies, prospective clients, and various other valuable sources during this time.
All this research and experience helped him develop the Turing thesis better. Vijay and his Turing co-founder, Jonathan Siddharth, spent many months going deeper and deeper into their business concept while evaluating other ideas around applications of AI and machine learning.
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Founding Turing
Vijay and Jonathan were now ready with a company that had the potential to become a unicorn or even the next Google. A strong factor they had going for them was that Turing offered an excellent founder-market fit.
At their prior startup, the duo worked with talented software developers in Russia, Poland, Serbia, China, Romania, and the Middle East.
They had a Silicon Valley team that was supplemented by a distributed team of really talented software developers in different parts of the world. Insights from this experience gave Vijay and his cofounder key insights about the state of global software talent.
Vijay refers to a phrase that Peter Thiel uses all the time, “secrets.” By this, he means a truth that can be the basis of a multibillion-dollar business, which most founders don’t understand.
Vijay and his co-founder had a strong intuition regarding what quality of talent existed, at what price, and how they could be sourced.
They also knew how talent could be vetted and how to make the remote collaboration function. This, essentially, was their “secret”.
At the time, most people did not believe in their thesis, and a lot of venture capitalists said it could never work. However, Vijay opines that everyone should experience first-hand how the process works.
While the duo could not have predicted the pandemic, they did predict that continuing talent shortages would force companies to go down the remote hiring route. They also suggested that companies that became early adopters would gain a competitive advantage.
Vision Behind Turing
Vijay’s current venture, Turing, emerged from a deep understanding of global talent dynamics and the potential of remote collaboration. The vision behind Turing is grand – it is a platform rivaling the impact of major tech giants, connecting top-tier global talent with companies worldwide.
As Vijay explains, Turing is a two-sided platform. On one hand, software developers from countries around the world can sign up and take programming tests. These tests are in various tech stacks, soft skills, and leadership skills and help build a detailed profile of them.
The value proposition for programmers is that if they’re really talented and live anywhere in the world, they can still be plugged into the very best job opportunities in the United States and the world at large.
This value proposition is very appealing in a lot of countries globally, particularly in developing countries.
The value proposition for clients is that Turing can help them with very high quality by cost ratios in the context of remote hiring or if they wish to have fully managed software projects run for them.
Turing provides a high-value proposition because it draws from a global talent pool, and the rigorous vetting process ensures that companies hiring with us have a superstar team comprising the top 1% of software developers across the world.
These companies can hire software developers in any capacity, either managing them directly with remote hiring or in a fully managed software project. At the end of the day, they get very high-quality work at very reasonable costs.
Fundraising and Scaling Turing and Market Dynamics
Turing has raised about $150M in funding. As Vijay explains, capital can be a great multiplier since it can spur high growth rates and higher company valuations.
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As Turing scales, the challenges shift towards maintaining innovation and adapting to constant change. The emphasis on capital efficiency comes naturally from the sound unit economics of the business, avoiding the pitfalls associated with capital-intensive models.
Lessons for Aspiring Entrepreneurs
Vijay’s journey provides invaluable lessons for aspiring entrepreneurs. Focusing on an “A-plus” market, understanding market dynamics, and prioritizing growth is fundamental. The importance of speed, adaptability, excellent unit economics, and a keen eye for market insights cannot be overstated.
Founders come across many attractive opportunities in the world, but to have an alpha, they must try to do something novel. But to hire for this novel role, there needs to be a very high degree of first-principle thinking, which is very challenging.
Whereas large corporations have well-oiled machines, startups are building something novel and wish to achieve and maintain high growth rates. To do that, they need a fair amount of constant innovation. At every growth stage, they need to think about how to get to the next stage.
As Vijay explains, Turing is not a pure tech business but also has added operations, such as understanding various countries and complexities that can present an attractive opportunity. In addition, he also underlines the importance of achieving capital efficiency, but not at the expense of growth.
Conclusion:
Vijay Krishnan’s journey from India to Silicon Valley is a testament to the power of passion, continuous learning, and a strategic approach to entrepreneurship.
As the founder of Turing, he stands at the forefront of reshaping the global talent landscape, demonstrating that the fusion of technological expertise and market understanding can lead to groundbreaking success.
Listen to the full podcast episode to know more, including
- Vijay Krishnan’s journey from IIT Bombay to Stanford reflects a lifelong passion for AI, ignited by early exposure to probability, statistics, and mathematical modeling.
- Leaving a secure position at Yahoo, Vijay ventured into entrepreneurship, driven by a desire to pursue the American dream and explore the untapped potential of AI.
- Vijay’s first startup witnessed multiple pivots, emphasizing the importance of adaptability and market focus in navigating the unpredictable entrepreneurial landscape.
- An acquisition and tenure at Foundation Capital provided Vijay with a comprehensive understanding of the entire business cycle, from startup inception to acquisition.
- Turing’s vision extends beyond a remote talent platform; Vijay envisions it as a global giant, rivaling tech giants like Google and Microsoft in reshaping the future of work.
- The success of Turing is rooted in sound unit economics, emphasizing capital efficiency without compromising on rapid growth.
- Vijay underscores the importance of market-first thinking, emphasizing speed and growth rates in a rapidly evolving technological landscape.
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