When will the new round of AI zone market come? First, look at the innovation in on-chain yield scenarios.

*Original Title: *Crypto AI Moats: Where Capital and Agents Converge

*Original author: *0xJeff (@Defi0xJeff)

Compiled by: Asher (@Asher_0210)

As market funds tighten, capital is concentrating on projects with stronger fundamentals, and a clearer picture is emerging: the next wave of AI innovation is about to directly impact the strongest moats in Crypto.

In this process, the integration of Crypto and AI will deepen further, giving rise to more AI application scenarios native to the Crypto ecosystem. These applications will not only showcase the value of AI in the Crypto field but also create its unique use cases.

Among them, the most obvious synergy is the combination of AI and Crypto in capital efficiency and yield optimization, which is also the core demand of the Crypto ecosystem.

DeFi: On-chain Yields

DeFi has always been at the core of the crypto space, with its on-chain yields and trading opportunities allowing users globally to participate freely. However, with the rise of AI, these values can not only be captured and optimized more efficiently, but also further enhance the utilization of capital. The involvement of AI has made DeFi not only a tool to combat inflation but also helps users achieve excess returns. The core areas and AI empowerment include:

• Stablecoins: As the primary currency medium in the on-chain ecosystem, stablecoins are used in almost all on-chain transactions, lending, payments, and yield optimization;
• RWA: Tokenizing real-world assets such as government bonds, securities, real estate, DePIN loans, and GPUs to integrate them into the on-chain financial system and expand the asset range of DeFi;
• Spot & Perpetual Contract Trading: AI can optimize trading fees and returns, enhancing the execution efficiency of trading strategies;
• Lending Market: AI enhances capital efficiency and achieves better yield enhancement through intelligent lending strategies;
• Yield Market: AI introduces dynamic interest rate adjustments and intelligent yield strategies, making the yield market more efficient and providing users with a better interest rate environment.

The essence of DeFi is to create, transfer, and increase capital, and Web3 AI shows great potential in this process. Compared to the closed Web2 system, AI in the Web3 ecosystem can utilize the openness of blockchain and token incentive mechanisms to optimize asset management more intelligently.

Let’s take a look at the early practices of DeFi + AI. Although still in the early stages, the DeFi AI (DeFAI) field has already seen several exciting cases emerge:

• Giza (@gizatechxyz): Its AI-driven stablecoin yield optimization agent TVL has surpassed 1 million USD, and it has improved traditional lending strategies’ yields by over 83% through efficient strategies, with a total trading volume reaching 6 million USD;
• Cod3x (@Cod3xOrg): Launched the Sophon Spark proxy trading competition, where AI proxies will compete for a $1.5 million reward while leveraging data to train smarter trading strategies;
• Olas (@autonolas): The Modius & Optimus AI agents under its banner can serve as personal portfolio management tools, and its team is the only one that supports running agents on local desktop clients. Users can manage through the “Pearl” agent application store (recently, this team also launched a $1 million Olas acceleration program);
• AI DeFi Access Layer: Projects like @HeyAnonai, @AIWayfinder, and @slate_ceo are working to enhance the accessibility of DeFi, enabling AI to better integrate into the DeFi ecosystem.

So, why are AI agents suitable for DeFi?

• 24/7 Operation: The AI agent can optimize returns, adjust positions, and respond to market changes in real time around the clock;
• Automated Management: AI can intelligently manage DeFi positions, significantly enhancing the efficiency of on-chain trading and yield optimization;
• Multi-Protocol Integration (MCP): AI agents can access more on-chain protocols, uncovering richer DeFi yield opportunities. In the coming year, AI agents may handle a large number of on-chain transactions in the DeFi ecosystem due to their efficient automation advantages.

In addition, the directions worth noting in this section are:

• Team for Promoting Technological Innovation: Projects that support the developer ecosystem, such as hosting hackathons, competitions, and seminars;
• Focus on Privacy, Verifiability, and Non-Custodial Teams: Empowering users to have complete control over AI agents, rather than a centralized platform;
• AI Agent Growth Metrics: For example, Assets Under Administration (AUA) / Total Value Locked (TVL) managed by agents, measuring the influence of AI in the DeFi ecosystem.

However, the DeFi AI competition has just begun. Crypto x AI is driving an evolutionary race of survival of the fittest, and in the end, only the strongest AI agents and teams will survive and rise.

Darwinism: The Natural Selection Law of AI Evolution

Web3 AI is driving a “Darwinian evolution,” and the survival rules of the AI ecosystem are gradually becoming clear: technological innovators are rewarded, while laggards are eliminated. This competitive environment is different from the traditional AI field; Web3 has built a highly competitive, survival of the fittest ecosystem through token incentives, inflation distribution, and penalty mechanisms.

Among them, the key AI projects that the community pays attention to are:

1. Bittensor: The decentralized infrastructure for all AI

• Allow teams to innovate freely and promote AI development through Subnets;
• SN6, 41, 44 ignite the GambleFAI narrative, leveraging AI/ML predictive capabilities to gain an edge in the prediction market.

2. Allora: AI-driven Machine Learning and Prediction Market

• Adopt the “Topics” mechanism to replace the subnet of Bittensor, with each Topic representing a financial prediction use case;
• The team with the strongest AI prediction capabilities can receive the most rewards;
• @steerprotocol Case: AI-driven LP strategy for achieving higher yields and lower impermanent loss (IL).

3. Bit Robot: Focused on the Robot AI Ecosystem

• Built by the @frodobots team, similar to Bittensor, but focused on the robotics field;
• Plan to establish different subnets covering areas such as robotic data, hardware, visual models, and large language models (LLMs).

The Web3 AI ecosystem has entered a “Hunger Games mode,” where the strongest technologies will gain more resources, while the laggards will be eliminated. In the future, AI agents will play an increasingly key role in this evolutionary race, driving the entire AI ecosystem towards greater efficiency and intelligence.

Decentralized Infrastructure

The core goal of decentralized infrastructure is to promote open collaboration and innovation, preventing technological monopolies from being held by a few centralized giants. As the DeFAI and Darwinian AI ecosystem matures, these infrastructures will be further adopted, driving the development of data, model training, verifiability, privacy protection, and DePIN. Currently, the market is focusing on the following mid to short-term directions:

1. Social & Emotional Data

Social data is crucial in the AI ecosystem, helping AI understand market trends, track project developments, and optimize trading decisions. Several projects have already made progress in this area.

• Kaito AI (@KaitoAI): Launched Yap Leaderboard and Yaps Open Protocol, enabling teams to build upon the Yaps scoring system to enhance the utilization of social data;
• aixbt (@aixbt_agent): Based on Twitter tracking and mapping project Alpha opportunities and social trends, helping investors discover new opportunities;
• Cookie DAO (@cookiedotfun): Provides market/social intelligence analysis to help AI agents interpret market sentiment more accurately.

2. On-chain data

Currently, the leaders in on-chain data have not been clearly defined, but this field remains one of the key directions for infrastructure development.

3. Other data field players

• Data crawling: @getgrass_io collects data by utilizing unused bandwidth to improve data availability;
• Data Ownership: @vana incentivizes personal data ownership through DataDAOs, empowering users with control over their own data;
• Privacy Computing: @nillionnetwork has developed the Blind Compute technology to enhance the privacy protection of data computation, and its token NIL is about to welcome TGE.

As the narrative of DeFAI and Darwinian AI deepens, infrastructure such as data, computing power, and privacy protection will see broader applications. In the future, we will witness a more mature ecosystem of infrastructure and a greater role for AI agents in decentralized data processing, transaction optimization, and market prediction.

Crypto AI Breaks the Limitations of Web2 AI

Crypto AI is not just about giving AI the ability to think, but also empowering it with trading capabilities. Through DeFi infrastructure, AI agents can independently manage assets, optimize capital flow, and operate autonomously in an open, permissionless network.

Crypto AI empowers the three main capabilities of AI agents.

• Autonomous capital flow without centralized intermediaries: AI agents can directly allocate funds, optimize returns, and execute trades within the DeFi ecosystem, avoiding reliance on centralized institutions;
• Access data that Web2 AI cannot reach: Decentralized data streams (On-chain Data, Social Data) provide unique informational advantages, helping AI make more precise decisions on the chain;
• Open collaboration, faster AI evolution: Crypto AI relies on open models and collaborative innovation, evolving faster and offering broader application scenarios compared to the closed AI systems of the Web2 era.

The core value of Crypto AI

• AI + DeFi, smart agents truly become participants in the on-chain economy: AI agents are not just tools for executing tasks, but can also hold assets, trade for arbitrage, and optimize capital operations, becoming an important part of the DeFi ecosystem; Transparent and verifiable & composable: All AI transactions, revenue management and other operations on the chain can be tracked, and intelligent agents can be reused, iterated and collaborated, promoting the accelerated development of the AI ecosystem;
• Web2 only opens AI competitions, while Web3 promotes AI towards autonomous economy: AI agents will evolve from “assisting humans” to active creators of on-chain economy, building a more intelligent and decentralized financial world.

In the future, Crypto AI will unlock a decentralized intelligent economy that Web2 AI cannot achieve. AI agents will not only optimize the DeFi ecosystem but also become the core engine for on-chain wealth flow and value creation.