based16z × Thread Guy

Hyperliquid became based16z’s defining trade after he recognized its superior product and exceptional founder before an investable token existed.Rare asymmetric setups—not frequent activity—powered positive crypto years despite a 25%–30% win rate, while oversized positions and 40x leverage damaged realized returns.Whop marks his shift toward positive-sum equity and products, but permanent holding remains unresolved.

Thread Guy × Mert × Illia Polosukhin × ZK Dragon × Tulip King

Current AI advances have not meaningfully weakened the factoring or elliptic-curve problems securing major blockchains, leaving cryptographic resilience intact for now.Smart-contract hacks appear the more immediate loss risk, while cheaper formal verification and adaptable schemes at Zcash and NEAR contrast with Bitcoin’s rigidity if a breakthrough emerges.

Avi Felman × Arthur Hayes

BitMEX found product-market fit in a crowded spot-exchange market by pairing high leverage with perpetual swaps as Bitcoin rose.Hayes says it exited without losing customer funds, but the insurance fund’s disposition remains unresolved.He sees government support for AI firms as a possible crypto catalyst, while Flop Network remains a speculative bet on cheap compute and agent growth.

Michael Arrington

Michael Arrington frames AI panic, sovereign debt, geopolitical tension, and institutional decay as overlapping Fourth Turning symptoms, not one clean “doom” event.He argues US labs cannot slow AI development while China may continue racing; Bitcoin could hedge institutional risk and become autonomous AI’s native transaction layer, while founder psychology and capitulation inform bear-market entry.

Ansem × FaZe Banks

Ansem views the selloff as the first meaningful pullback since late June, with Bitcoin’s $75,000 level deciding whether the bullish structure remains addable despite rates and war risk.His 70/30 barbell pairs high-conviction spot holdings with speculative onchain and perpetual trades, recycling exceptional gains while limiting the risk of one meme trapping the portfolio.PUMP, HYPE and STRK offer near-term catalysts through revenue, platform execution and privacy or quantum-resistance narratives, but their asymmetric targets remain contingent on broader adoption beyond crypto’s existing bubble.

Jordi Alexander × Justin Bram × Taiki Maeda × Dim Selk

Zcash was the panel’s highest-conviction, highest-fragility trade, with Taiki calling it “the coin of the cycle” as Project Tachyon approaches.Crowding across ZEC, HYPE, Lighter and NEAR leaves buybacks weak and downside unresolved, while Variational’s Q4 TGE, $4 billion-plus daily volume and 32% airdrop offer a competing catalyst amid expected market dispersion.

DeFi Dad × Nomatic × Kyle

Capital is concentrating in businesses with usage, revenue and tokenholder alignment, as Hyperliquid’s roughly 99% buyback model raises token-economics and disclosure standards.Kyle favors Venice’s VVV and selected digital-asset treasuries, while expecting a K-shaped cycle where roughly 90% fail and strong alts can rise even if BTC ranges around $90,000-$100,000.

邵艾伦 × 孙宇晨

核心不是押中单一赛道，而是把健康、工作与决策沉淀为可迁移数据，用多模型交叉分析并持续调参。机会集中在数据密集且处理不足的领域，AI基础设施、生物健康金融、全球支付与Agent结算可受益于更低的搜索、分析和交易成本，但波场规模、合规与采用仍待验证。

Ceteris × Jason × Yan × Kevin × Jose × Guy Young

Tokenized real-asset perpetuals could expand crypto derivatives from a $2.5–3 trillion base toward a $150 trillion market, with Guy Young expecting non-crypto contracts to surpass crypto derivatives in open interest within 24 months. 24/7 access, leverage, and liquidity extend reach beyond US brokerage accounts and could keep capital on-chain through cycles, while DEX cost advantages remain tempered by Ethena’s preference for CEX hedging and dollar insurance funds.

Jason Yanowitz × Santiago Roel Santos

AI’s narrative dominance masks a possible crypto bull market, as Yano reports revived interest after 18 barren months and tokens that have increased 50 times.Anthropic’s reported $1 of revenue per $60 of compute, possible ARR stabilization, and customer switching leave frontier-model economics unresolved, while 1 gigawatt of AI capacity costs $50–60 billion.Falling inference costs could strand capacity or trigger Jevons’ paradox, as LPs seek crypto’s growth-stage fintech opportunity as a countercyclical alternative to crowded AI.