Consensus and Non-consensus: Counter-cyclical Directions in a Bear Market
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Consensus and Non-consensus: Counter-cyclical Directions in a Bear Market
When there is no answer within the circle, one should look beyond it.
Navigating Web3 tides with focused insightsThe primary market has been quiet for far too long—there hasn’t been anything new in sight. Yet theoretically, for VCs, a bear market is precisely the time to enter countercyclically. Based on this belief, I traveled to Singapore in June to discuss current directions with many old and new friends, uncovering both prevailing consensus and dissent within the industry, while also crystallizing my own thoughts. After an internal sharing session, I’ve turned these reflections into writing for broader discussion—and I welcome project founders and fellow VCs to exchange more ideas. Due to length constraints (i.e., it was simply becoming impossible to finish otherwise :P), this piece will focus on the overall framework. If time permits later, I can dive deeper into specific sub-sector observations and judgments.
1. Consensus: What Everyone Generally Agrees On
1.1 Two Main Investment Approaches: 1) Financial projects returning to fundamentals; 2) Massive opportunities at the application layer
Currently, there are two dominant investment strategies. One returns to blockchain’s original nature—financial applications—investing in RWA, insurance, payment rails, bank-like protocols, derivatives, stablecoins, etc. This trend began emerging after Hong Kong’s Wanxiang Conference but has become increasingly common lately. There are two angles here: first, innovation within the industry is limited, while financial applications represent already-validated areas that offer stability and cash flow. Second, the narrative around compliance is strengthening, raising the likelihood of mass adoption, essentially betting on future inflows of large-scale capital and their revenue potential.
The other approach is betting on the application layer. More and more funds are now focusing on applications—even those previously focused on infrastructure are undergoing a paradigm shift. There are many reasons, but the most important one, in my view, is that crypto itself does not have high technical barriers. Once one project demonstrates technical feasibility, competitors can quickly pivot. A chain’s core competitiveness lies in its ecosystem, not its technology, and traffic remains the key driver of the industry. As infrastructure matures, what ultimately draws users in will be real applications, and true value will accumulate at this layer. Ultimately, super apps will choose their preferred infrastructure and hold final decision-making power—a story we’ve already seen play out with Dydx. (I’ll explore application-layer opportunities further in future articles.)
1.2 Industry growth is slowing down—how to act under tightening liquidity is a question every VC must answer
Cheap capital fuels soft-tech development; bubbles drive the emergence of new industries. While slightly absolute, it's undeniable that the rapid evolution of tech over the past decades owes much to post-WWII capital surplus. For a small market like crypto, the clearest example is how DeFi Summer emerged from the Federal Reserve’s monetary easing. Now, amid tightening liquidity, both traditional VCs and crypto VCs face the same challenge: when the tide recedes, how do you navigate?
1) On investing: Most funds may adopt a strategy of investing less—when uncertain, don’t invest; when borderline, still don’t invest. But if you do invest, go big: once a project meets your bar, place meaningful bets. In a bear market, stock up on ammunition (so founders, push forward—we still have liquidity). Additionally, more crypto investors are turning attention to adjacent fields such as AI, semiconductors, and even biotech.
2) On post-investment: With fewer pre-investment activities, more effort can be directed toward post-investment support. Given crypto’s tight linkage between primary and secondary markets, sophisticated asset and project management is rising on more funds’ agendas.
2. Non-consensus: Where Big Disagreements Lie, So Do Big Opportunities
2.1 Crypto investing is reverting to traditional dollar-fund logic
As an emerging tech sector, crypto used to follow a tech-driven investment logic: deep understanding, identifying technological superiority early, and profiting from efficiency gains. But as the industry matures and shifts toward application-based evaluation, generalist dollar-fund approaches—focusing on teams and business models—are becoming more effective. Technology remains relevant, but is no longer the sole deciding factor. What matters more than technology itself is the new business models enabled by technological breakthroughs.
2.2 L2s vs. High-performance L1s
This might be the biggest non-consensus today. Even as L2s become politically correct, many new public chains remain ambitious, with fresh projects still securing funding. Indeed, going long on Ethereum via L2s appears the safest bet—after all, developers, communities, and capital are concentrated on Ethereum, which currently seems the most suitable decentralized platform… assuming external conditions stay constant. But should significant new capital or developer talent enter, the narrative could easily shift.
2.3 AI + Web3?
AI presents a tricky point: an industry born in the 1960s that has cycled through hype multiple times. Not long ago—mid-last year—it was still debatable whether AI constituted a real sector. Silicon Valley VCs were still debating whether to first invest in enterprise cloud migration, gather vertical data, then move to ML, and finally reach AI—the so-called three-step path. But once GPT-3.5 arrived, all skepticism vanished overnight, triggering a full-blown arms race across every fund. :P
Now, over half a year later, it remains unclear whether AI is a real sector or just another bubble. Echoing @Laobai’s Threads, beyond the repetitive debates on large models and applications, mainstream discourse is already exploring AGI through embodied intelligence (i.e., AI + robotics—you know how good Web2 is at coining concepts). Regardless, one thing is clear: this AI wave has delivered tangible UX improvements for end users. Whether it’s New Bing, Claude, or PoeAI, the experience feels meaningfully better (at least for me). As for the intersection of AI and Web3, I still believe there’s latent potential in leveraging long-tail resources. I’ll elaborate on this in a dedicated article later.
3. Reflections: Spotting Non-consensus Opportunities Within Consensus
3.1 Can Infrastructure Be an “App”?
We often liken infrastructure to utilities like water, electricity, or gas—worrying that once mature, it becomes commoditized and unable to capture high margins. But returning to first principles: if we’re betting on future business models, infrastructure—or blockchain as a tool—could still independently generate application scenarios. Think AI-specific chains, payment-dedicated chains, etc. In fact, doing one thing well is already a huge achievement for a blockchain. Though perhaps distant from today’s reality, such outcomes remain very possible.
3.2 What Is the Industry’s Primary Contradiction?
My answer consists of two points:
1) There aren’t enough high-quality assets on-chain.
If we bet on massive future capital inflows, the precondition is having on-chain yield-bearing assets that outperform even U.S. Treasuries and are accessible to large players. The current contradiction is twofold: first, asset liquidity is severely insufficient; second, there’s a lack of high-alpha yield-generating assets. For long-tail capital, however, finding suitable geo-arbitrage opportunities—deploying RWA in jurisdictions where centralized on/off-chain asset ownership is clearly defined—could indeed be a viable direction.
2) There is almost no consumption on-chain.
Most crypto users are effectively small B-end participants—with virtually no real C-end presence. The core motivation for most token traders is profit, and the vast majority of NFT holders maintain bullish expectations. Only a tiny fraction of true NFT enthusiasts hold digital images long-term regardless of price—becoming actual consumers. Without genuine consumption, the entire system remains a Ponzi scheme.
3.3 Is Web3’s upgrade compelling enough?
Leapfrogging theory: Due to the nature of technological change, developing countries possess a late-mover advantage. Advanced nations may find their technological progress locked into narrow ranges due to inertia. Under such conditions, latecomers can leapfrog ahead—this is the “leapfrog” process.
Recently, I’ve spoken with many professionals from traditional industries about Web3-driven upgrades. Their reaction? “Interesting—but not that interesting.” Yes, it’s akin to promoting QR code payments in a country where everyone already has credit cards. When the gains from a paradigm shift fail to outweigh switching costs, technological adoption becomes difficult. Similar to past cycles of innovation, developing countries, burdened by outdated systems, can easily surpass incumbents because the benefits of new technologies outweigh transition costs—enabling true breakthroughs. By this logic, if Web3 innovations are incremental, disrupting developed systems becomes unlikely—while greater opportunities may lie in developing economies.
3.4 Become an industry oracle—think outside the box
Crypto has evolved to the point where, due to its infrastructural nature, it can connect with various domains—IoT, finance, even daily life—creating diverse linkages. Often, solutions to crypto’s challenges lie outside the ecosystem. For instance, as discussed with @siyuan, Ethereum’s state explosion problem might ultimately be solved not by native crypto tech, but by declining physical storage costs—Moore’s Law solving a software issue.
When answers aren’t found within, look outward. Be an industry oracle—step back, gain higher perspective, and in this beta-less era, seek alpha.
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@JimsYoung_
