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Alexander Pack

Alexander Pack is Co-Founder and Managing Partner of and Co-Founder and Board Member of Imperii Partners. His career has spanned venture capital, investment banking, technology, and policy, with an increasing focus on , infrastructure, and other emerging technologies. [1]

Education

Pack earned his BA in Philosophy, Politics, Economics, and History from Wesleyan University. [2]

Career

Pack began his career in Legislative Policy at the United States Senate from 2011 to 2012 before moving into the private sector as a Product Marketing professional at McGraw-Hill Education from 2012 to 2013. He then worked as a Product Manager at Microsoft from 2013 to 2014 and served as a University Lecturer through a teaching fellowship with Princeton in Asia in Hong Kong in 2014. He subsequently worked in fintech venture capital at Arbor Ventures from 2014 to 2015 and joined AngelList as a Partner from 2015 to 2016, focusing on early-stage technology investing. From 2016 to 2018, Pack was Director of Network Investing at Bain Capital Ventures, where he established the firm's network investing program and expanded its investments into seed and early-stage companies, cryptocurrency, and open-source infrastructure software. He then co-founded Dragonfly Capital and served as Managing Partner from 2018 to 2020, working across the U.S. and China on investments in the cryptocurrency sector. During this period, he also served as a Senior Advisor to Huobi Global from 2020 to 2021. In 2019, Pack co-founded Imperii Partners, an investment banking and advisory firm focused on companies operating across and AI, where he remains a Board Member. In 2021, he co-founded and became its Managing Partner, focusing on venture investments in , AI, and other emerging technologies. [3]

Interviews

Modular ETH

In December 2024, Pack appeared on Empire to discuss architecture, valuation, and prospects for institutional adoption. He argued that development had placed too much emphasis on decentralization while relying on networks to address scaling, and that the resulting modular architecture had reduced fees and network revenue in the short term, contributing to pressure on valuation while supporting longer-term ecosystem development. Pack examined how networks are valued through factors such as market share, , and network effects, noting continued dominance despite competition from chains such as . He also argued that modularization had increased competition among tokens and shifted some value away from , while Ethereum remained an important institutional network because of its security, developer base, and established ecosystem. The discussion further considered role as a monetary asset, given that activity and many applications remain denominated in , as well as the potential for new , , cryptographic advances, AI, and privacy technologies to reshape the market. Pack expected continued venture funding and development across infrastructure, potentially extending existing market cycles and creating further changes in the relative position of major networks. [4]

Panels

Autonomous Capital

In October 2025, Pack participated in a panel at alongside Amjad Masad of Replit, of Selini, and of , moderated by Irene Wu, discussing the intersection of AI, , and autonomous capital. The panel examined how autonomous capital could evolve from algorithmic trading strategies into systems in which independently manage capital and execute activities onchain, while also considering earlier visions of decentralized, AI-managed services. Pack and the other panelists discussed the risks associated with autonomous agents, including exploit attribution, vulnerabilities in trusted computing environments, hardware dependencies, and the difficulty of assigning responsibility within complex decentralized systems. They also considered the relationship between AI and crypto talent, regulatory constraints, infrastructure requirements, and potential to attract technical talent through early financial incentives. The discussion concluded with the possibility of using -based incentives to connect human and machine intelligence, including applications such as decentralized contests and incentive-aligned software infrastructure, while emphasizing the importance of developing technically simple and understandable products. [5]

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