Jeff Feng

Jeff Feng is a venture investor and a co-founder of , a layer-one designed for efficient digital asset exchanges.


Feng graduated with a B.S. in Business Administration from the University of California, Berkeley. [1]


Feng's tech career began at UC Berkeley due to its cost-effectiveness for in-state students. Around 2014, Feng researched the world of , initially exploring with due to the complimentary electricity available in dorms and to earn money to pay his tuition. His interests extended beyond crypto during his university years, leading him to launch startups in various sectors such as education and healthcare. Post-graduation, Feng gained experience in the corporate sector at Goldman Sachs as a technology investment banker, providing insight into the challenges of large tech companies and the associated bureaucratic hurdles. [2]

In 2020, Feng left Goldman Sachs to work at the VC firm CO2, where he engaged in fintech, software, and crypto investments, contributing to the growth of companies like Fireblocks, , and X Stripe. Around the same time, he began collaborating with his co-founder, , with whom he shares a decade-long working history building and funding tech start-ups, eventually leading to the co-founding of in 2022. [2]


The Sei Network

In a November 2023 interview with Voice of Crypto, Feng discussed how Sei works and what the company works toward in the space. When asked about how he sees blockchain adoption in five years, he started with a simple explanation of what Sei is, beginning with its foundation and thesis: [3]

“The simple way to think about Sei is we only have one thesis, that's it. What you'll find as a style of myself, the rest of the team, the foundation is to cut through as much of the noise in blockchain as as possible and get to exactly what matters the most. So there's so much sort of hype, so much flock, so many narratives that people spend at different points of excitement. It's really difficult to cut through all of the excitement.”

“The simple thesis of Sei is we believe that the core value proposition of all blockchains is just the exchange of digital assets, period. That is it. Many other things may excite people, but at the end of the day, what ends up moving a big part of the industry is exchanging some kind of digital asset. It could be an , a token, a gaming asset, a real estate asset—doesn't matter; it's exchanging some kind of asset. Then the question becomes, if you look at all of the successful apps so far on , they all end up routing back to exchanging assets

He then went on to talk about how changing the infrastructure of asset exchange would be a major influence on the future of trading as a whole, stating: [3]

“People say have a lot of product-market fit. Their product-market fit is as a trading pair; it's like the thing that you sort of swap out of. So that's going to be the big, big problem that if Sei's infrastructure is able to solve will unlock a huge, huge part of the industry. So the easy way to think about the value pop is if you build any kind of today, the tradeoff is insurmountable. If you wanted to go to a , the user experience difference between that and, like, is, like, a laughing matter. It's like how big it is. If Sei is successful in solving this problem, there's no trade-off.”

Feng also cleared up misconceptions about Sei’s infrastructure and explained the critical aspect of asset trading on networks like Sei. He said: [3]

“The reality is the exchange of assets is so critical to every possible type of application. One of the common misconceptions of Sei is it's like a very finance-focused piece of infrastructure, but people don't quite realize that trading is general purpose. If you're building a game, if you're building an NFT, if you're building a social app, the exchange of assets is just as critical to that application as it is to broader DeFi. Yeah, you need to exchange the gaming assets; it's critical to the user experience.”

He also shared his thoughts on the implementation of AI in Web3 networks: [3]

“Where things get really interesting with AI is how do you incentivize people to provide the inputs needed to build these robust, production-ready models. To do the simple manual workers of labeling photos, labeling data, labeling words—how do you incentivize people to do that with participation, with tokens, with ownership in the eventual end product? So that's probably the area that is most practical, makes sense, where you can kind of see step by step where the incentives start coming into place.”

“How do you allow the exchange of those kinds of tokens and digital assets that are used to incentivize manual behavior to easily be exchanged? And that's going to drive more and more people to be incentivized to label simple data. An easy example is like a web 3 scale AI. Okay, Scale AI employs a huge labor force to label data, or you can incentivize that same labor force with ownership in the network with tokens. That's one of the easiest, sort of low-hanging fruits that we're excited about, we're excited about funding.”

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Jeff Feng

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Edited On

March 11, 2024


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