Dragonfly Fund IV sparks a candid playbook on building a crypto VC, covering fundraising, differentiation, winning deals, and surviving cycles.


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Promote with Leviathan NewsDragonfly, a crypto-focused venture capital firm, has closed Dragonfly Fund IV, a new $650 million fund, and is using the milestone to publicly outline a candid “playbook” for how to build and operate a crypto VC firm through volatile market cycles. Managing partner Haseeb Qureshi announced the close on X, noting that the fund was raised at a time when “spirits are low” and fear is high in the crypto market, and framed the new material as practical guidance on fundraising, differentiation, winning competitive deals, and surviving downturns. The new vehicle matches the size of Dragonfly’s previous fund and was raised amid what Dragonfly’s partners describe as a “mass extinction event” for crypto VC, with many firms struggling to raise capital as investor attention shifts toward AI and token prices remain depressed. Dragonfly’s decision to pair the Fund IV announcement with a transparent playbook matters because the firm is one of the more established crypto-native VCs, having backed over 160 companies and protocols across the industry, including names like Polymarket, Rain, Ethena, Avalanche, and others. Fund III, raised in 2022 during another period of market stress, produced some of Dragonfly’s strongest-performing deals, and the firm is explicitly positioning Fund IV to lean into similar contrarian deployment—arguing that downturns can be the best time to invest and that disciplined fund construction and clear differentiation are critical to surviving industry shakeouts. For founders and emerging managers, Qureshi’s shared “playbook” provides a rare, detailed look at how a large crypto VC thinks about LP fundraising, portfolio strategy, and competitive dynamics when capital is scarce, while for the broader market it underscores that significant institutional money is still being allocated to crypto infrastructure and applications despite cyclical bearish sentiment.
AI-generated background, compiled from web sources — not editorial content.

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