Eli Hua and other "crypto veterans" shifting to AI are not simply chasing a trend, but signaling a fundamental restructuring of Web3 investment logic from "speculating on coins" to "investing in infrastructure." AI is not an add-on to Web3 but is becoming its new operating system.

How will AI reshape Web3 investment logic?

1. Narrative upgrade: from "Financial Lego" to "Intelligent Agent Economy"

Past Web3 investments valued DeFi's "money Lego," but now capital (such as Eli Hua's newly founded OpenX Labs) focuses more on the chemical reaction between AI and Web3:

AI needs Web3: solving data rights confirmation, decentralized computing power (DePIN), and trustworthy verification of model outputs (ZKML).

Web3 needs AI: introducing AI Agents as on-chain "new users," enabling automated trading and risk management, upgrading on-chain activities from "human-driven" to "machine-driven."

2. Valuation anchor: from "token price" to "real utility"

Altcoins relying solely on "community consensus" to pump will accelerate to zero. By 2026, funds favor sectors with real cash flow or computing power backing:

DePIN sector: decentralized computing networks (like Akash, Aethir), with token value anchored to actual GPU rental income.

AI Agent economy: investing in autonomous trading and DAO governance-enabled intelligent protocols, focusing on their automation productivity.

3. Capital flow: from "sprinkling pepper" to "focused爆破"

VC funds are shifting from purely investing in public chain ecosystems to the intersection of AI and Web3. Eli Hua emphasizes "those who don't understand AI will be淘汰," reflecting a re-pricing of technological barriers—only teams with AI infrastructure capabilities can survive the cycle.

How practitioners can find their position?

1. Skill restructuring: become "AI integrators," not just "pure coders"

Pure Solidity developers will see their competitiveness decline in the AI era. Future high-paying roles will require multidisciplinary talent:

Technical side: mastering AI Agent development, ZKML (Zero-Knowledge Machine Learning), on-chain data analysis.

Product side: designing "human-machine collaboration" economic models, such as AI agent wallets and DeFi strategy robots.

2. Role evolution: from "trader" to "ecosystem builder"

If you understand technology: don’t just focus on secondary market K-lines; participate in open-source AI×Web3 projects or DePIN network building, accumulating verifiable on-chain contributions (Proof of Work).

If you are an investor: like Eli Hua, expand your view from secondary markets to primary infrastructure (such as decentralized computing power, data markets), which is the real boom zone of this cycle.

3. Mindset adjustment: embrace "small teams + AI leverage"

AI lowers the startup threshold. Practitioners should leverage AI tools (like code generation, intelligent research) to improve efficiency, build lean teams, and focus on solving specific problems (such as cross-border payments, content rights confirmation), rather than blindly issuing tokens.

Cycle response strategies

Short-term (1-2 years): use AI tools to optimize research and risk control, maintain low leverage amid macro uncertainties (like high interest rate environments), and focus on projects with actual income, such as AI+DePIN.

Long-term: view AI as a new factor of production. Future Web3 giants are likely teams currently building "trustworthy AI infrastructure."