Exploring Friend.tech: A Rising DeSo App Making Waves in Crypto

Key Takeaways

  • Friend.tech, a decentralized social media (DeSo) app, has quickly gained over 64,000 users and more than 24,000 ETH in trading volume since its beta launch on August 11.
  • Operating on Coinbase’s Base layer-2 network, Friend.tech allows users to buy shares of friends and influencers, granting access to private chats, which distinguishes it from traditional social media platforms.
  • The app has generated significant revenue, with $1.42 million in fees within a 24-hour period and total revenue of $1.88 million, alongside over 724,000 transactions involving 64,500 unique traders.
  • Despite its early success, there are concerns about the long-term viability of Friend.tech’s model, with comparisons being made to previous DeSo projects like BitClout, which faced substantial challenges.

Decentralized Social Media (DeSo)

In the world of blockchain and cryptocurrency, new players are constantly emerging. The latest newcomer is Friend.tech, a decentralized social media (DeSo) app that has quickly gained traction. With over 64,000 users and more than 24,000 ETH in trading volume since its beta version launch on August 11, Friend.tech is raising eyebrows.

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Coinbase Base Layer-2 Network

Friend.tech operates on Coinbase’s Base layer-2 network, offering a distinctive feature that sets it apart from traditional social media platforms. Users can purchase shares of their friends and influencers, gaining access to private chat conversations. This new and unique concept has drawn both interest and skepticism from within the crypto community.

BitClout

However, some analysts and influencers are raising concerns about the long-term sustainability of Friend.tech’s model, with comparisons to previous DeSo projects, like BitClout, which faced many challenges and essentially collapsed, are also being made.

Revenue Generating Model

The stark rise of Friend.tech is undeniable. Within a very short period after its launch, the app has garnered substantial attention and engagement. In addition to its already large user base, Friend.tech has generated remarkable financial figures. It generated $1.42 million in fees within a 24-hour span and has accumulated a total revenue of $1.88 million. Over 724,000 transactions have been executed on the platform, involving 64,500 unique traders.

Friend.tech

The future of Friend.tech is still uncertain. As it gains more and more traction while generating trading volumes, questions linger about whether it will become a long-term phenomenon in the crypto space or encounter challenges similar to its predecessors. The crypto community is watching closely to see how Friend.tech’s journey unfolds and what impact it could have on the broader landscape of decentralized social media platforms.

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Jeff Sekinger
Jeff Sekinger | Wealth Strategies

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Bingham Zhou, CFA, has over 15 years of experience as a quantitative researcher. His expertise spans systematic equity strategies, CTA trend-following, and interest rate proprietary trading in both U.S. and Asian markets. He holds advanced degrees from MIT, Carnegie Mellon, and Yale.

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Greg Doscher was a CFO for many years who built out many quantitative strategies and investment tools to manage and enhance risk adjusted returns in the company’s pension plan. Prior to joining Nurp, he consolidated his skills in coding and discretionary trading to develop a comprehensive and fully automated algorithmic trading system deployed across 200+ futures markets and cryptocurrencies that encompassed all of the trading strategies he had honed over the last 22 years in finance

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Marcin was Head of Quant IT at the USD 4bn+ CERN Pension Fund, where he spent nearly a decade building quantitative asset allocation systems and implementing algorithmic investment strategies for a multi-asset institutional portfolio.Before joining Nurp Marcin was also Senior Quant Strategist at Evooq, a Swiss-based fund managing four strategies across equities, gold, and equity derivatives.Marcin holds a degree in Computer Science an MBA from the University of Geneva and the Certificate in Quantitative Finance (CQF).

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Abhay has worked with Nurp since 2022. As a Product Strategist, he focuses on building, refining, and commercializing algorithmic trading strategies. He brings seven years of experience in financial trading – combining macro research, technical analysis, quantitative strategy development, and market psychology. Alongside his work at Nurp, Abhay also serves as an Investment Analyst at Orca Capital. Before entering financial markets professionally, he spent eight years at IBM, including three years in the AI & data division as a Delivery Lead managing complex implementation projects.