Like an AI startup, Theory Ventures wants to use huge checks and supplies of data to beat competitors.
Tomasz Tunguz said that in launching Theory Ventures, he already has a 30-year plan for the business. The crux of it: to influence tech investors to take a more thesis-driven approach—effectively, making big bets in a small number of companies.As AI enchants Silicon Valley with its ability to analyze and distill massive quantities of data, Tomasz Tunguz is building a venture capital shop to match the occasion.
The longtime investor has raised $230 million for his new firm Theory Ventures, a single-partner operation supported by some 10,000 lines of code to help automate his work, and a series of 30-page manifestos on the key areas in which he plans to invest. “We want to be the deepest in a particular space,” he told. “Having that mentality of being a student and preparing lots of research is how we’re looking to differentiate.
For Tunguz, the focus areas are data, web3 and machine learning, where he’s getting hands on — playing around with AI tools like ChatGPT to write blog posts, GitHub’s Copilot to write code and LangChain to create a chatbot for his notes. In each area, he has ambitions to outmuscle blue-chip venture firms from the get go with big checks. Theory will apportion its funds into only about one dozen startups, he said.
“I really admire the model of having the courage in your convictions to really back up a truck behind a founder.”last year from Redpoint Ventures, where he had spent the previous 14 years . His former employer had separate investment vehicles for early and growth investment phases. Tunguz, who worked on the early-stage segment, did not have sway on the firm’s investment decisions at later rounds.
The Belgium-born investor also describes Theory as an opportunity to return to his entrepreneurial roots. At 17, after moving around Europe and the Americas with his family due to his father’s finance job, Tunguz launched his first company in Chile selling software to lawyers. Upon graduating from Dartmouth in 2004, he worked as an early employee at software company Appian (which
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