The Web3 + AI Daily #25
Today's agenda: can AI agents solve the stablecoin fragmentation, will confidentiality boost DeFi's adoption, and is AI really causing large-scale job loss?
Hello, everyone, and welcome to all newly-joined subscribers!
This is The Web3 + AI Daily, your definitive guide to the world of Decentralized AI (DeAI/dAI)! Today’s digest covers verifiable AI, LLM-enhanced blockchain validation and governance, AI agents autonomously transacting stablecoins, and confidential DeFi.
Thank you for being here! Let’s dive in.
What’s Hot in Web3 + AI?
EigenCloud Makes Verifiable AI Trendy
EigenCloud recently introduced EigenAI and EigenCompute, a new infrastructure that makes AI inference and computation verifiable and tamper-proof.
EigenCloud today launched EigenAI and EigenCompute on mainnet alpha, two services that bring verifiable computing to AI. This launch enables developers to leverage the scalability and flexibility of traditional tech infrastructure and frontier LLMs with the same security and transparency guarantees as smart contracts.
AI’s growing role in critical systems faces a major trust deficit, since users have no way of verifying whether AI outputs are genuine or unaltered, especially when models run as black boxes on centralized servers. EigenCloud addresses this through:
EigenAI: a verifiable LLM inference API compatible with OpenAI’s API. It ensures prompts, models, and responses are unmodified, solving key risks in traditional AI services. Using a breakthrough in deterministic LLM inference, EigenAI allows anyone to cryptographically verify that model outputs are authentic.
EigenCompute: a verifiable off-chain compute layer that enables developers to run complex agent logic in secure Trusted Execution Environments (TEEs). Future versions will add cryptoeconomic security and zero-knowledge (ZK) proofs for full verifiability and censorship resistance.
Together, the two tools form the foundation for autonomous, trustworthy AI agents capable of managing real-world tasks, like trading, payments, and prediction markets, with proof of correctness.
Leading partners in this endeavor are Coinbase, Google, Dapper Labs, Eliza Labs, and FereAI. They’re already building with EigenCloud, leveraging its cryptographic trust model to enable verifiable AI-driven applications.
Secret Network and Cintara Launch LLM-Powered Blockchain Validators
The AI-native Layer-1 blockchain Cintara has partnered with Secret Network Foundation to introduce validator nodes enhanced with LLM-powered AI inference and confidential computing. These AI validators go beyond mere consensus, as they can process intelligent workflows on-chain, while Secret Network’s privacy and compliance tools safeguard sensitive data.
The integration aims to fuse trust, privacy, and intelligence at the infrastructure level, allowing enterprises in regulated sectors (like finance, healthcare, supply chain) to run AI-driven operations on-chain without compromising compliance. Moreover, this deal marks a shift toward validator nodes that are not just guardians of consensus but agents capable of secure AI execution and smart decisioning, blurring the lines between blockchains and AI systems.
NEAR Foundation Builds AI Governance Participants
The NEAR Foundation is developing AI-powered “delegates” (or “digital twins”) that can vote on behalf of DAO members in governance processes, aiming to overcome low participation rates common in decentralized organizations.
These AI delegates would learn each user’s preferences via past votes, messaging, social channels, interviews, and then act accordingly when governance proposals arise. In early stages, the model will function like an advising chatbot; eventually, individual AI delegates could represent every DAO member.
The system will still include a “human in the loop” for high-stakes decisions (e.g. budget allocations or strategic pivots). To maintain trust, training of the delegates will be verifiable.
Web3 + AI Readings & Conversations
AI Agents Could Help Solve Stablecoins’ Fragmented Landscape
Bhaumik Kotecha, co-founder of Paxos Labs, suggested in a recent Cointelegraph op-ed that autonomous agents may be the solution to the widespread stablecoin fragmentation.
While the total market capitalization of stablecoins has exceeded $300B, the ecosystem remains highly fragmented across multiple issuers, such as Tether.io, Circle, and PayPal, as well as varying regulatory frameworks. In the meantime, AI agents capable of executing financial actions without direct human input could help solve this problem by dynamically reallocating liquidity between different stablecoins.
These agents would instantly shift to whichever token offers the most favorable conditions, such as lower transaction fees, stronger backing, or better yields. In doing so, AI could transform market fragmentation into a competitive advantage, driving issuers to improve their performance and transparency while equalizing liquidity across the ecosystem.
Is Confidentiality the Missing Link in DeFi’s Mass Adoption Quest?
Zama‘s Jason D. argues that confidentiality powered by Fully-Homomorphic Encryption (FHE) is the key to unlocking trillions in traditional finance for DeFi. Here’s why:
FHE allows data to be processed without decryption, enabling institutions to assess encrypted credit scores and execute private transactions on public blockchains. This technology supports uncollateralized lending, where smart contracts verify encrypted credit data, allowing borrowers to access funds without exposing sensitive information. Implementing FHE in DeFi could lead to private collateral pools, protection against front-running and MEV bots, and the evolution of lending protocols into confidentiality-first systems.
While challenges like encrypted liquidations, credit systems, and oracle compatibility remain, FHE offers a pathway to scaling DeFi to trillions without compromising trustlessness.
The Harshest AI Doomers Have Been Refuted
Let me conclude with a piece of news that’s not directly related to the Crypto x AI space, but has a deep significance for society’s perception of technology as a whole, and AI in particular.
A new Yale University and The Brookings Institution study finds that, despite widespread fears, artificial intelligence has not yet caused large-scale job losses. Three years after ChatGPT’s debut, U.S. employment patterns remain largely stable. Occupational changes have risen only slightly, suggesting that AI’s impact so far resembles earlier technological shifts rather than a historic disruption.
Researchers caution that “AI exposure” measures potential vulnerability, not actual AI use in the workplace, and that limited data on real-world AI adoption makes definitive conclusions difficult. Overall, the findings suggest that the long-predicted AI employment apocalypse has not yet materialized.
Thank you for reading! I hope you found this article insightful.
If you’d like to keep up with the latest developments at the burgeoning intersection of blockchain and AI, I invite you to subscribe.
And if you find value in my writing, consider supporting the newsletter. I’d greatly appreciate it.
The Web3 + AI Book Club is live on Fable. Follow the link below and come join our literary community.
I'm looking forward to connecting with fellow Crypto x AI enthusiasts, so don't hesitate to share your thoughts here or reach out on LinkedIn, Instagram, or Firefly.social.
Disclaimer: The content of this newsletter is provided for informational and educational purposes only. Nothing contained herein should be construed as financial advice or as a recommendation to buy, sell, or hold any of the companies or assets mentioned.
Please don’t take my views at face value. Instead, do your own research (DYOR), think critically, and share your perspective so we can challenge ideas, learn from one another, and arrive at better conclusions through thoughtful discussion.