In the future, Crypto AI will pioneer a decentralized intelligent economy, where AI agents not only optimize the DeFi ecosystem but also become the core of on-chain wealth flow and value creation.

Written by: 0xJeff (@Defi0xJeff)

Translated by: Asher (@Asher_0210)

As market funds tighten, capital is concentrating on projects with stronger fundamentals, revealing a clearer picture: the next wave of AI innovation is about to directly impact the most solid 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 form their unique use cases.

The most obvious synergy lies in the combination of AI and Crypto in terms of 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 global users to participate freely. However, with the rise of AI, this value can not only be captured and optimized more efficiently but can also further enhance the utilization of capital. The involvement of AI makes DeFi not only a tool against inflation but also helps users achieve excess returns. The core areas empowered by AI include:

• Stablecoins: As the main currency medium of 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, bonds, real estate, DePIN loans, GPUs, etc., to integrate them into the on-chain financial system, expanding the asset range of DeFi;

• Spot & perpetual contract trading: AI can optimize trading fees and yields, enhancing the execution efficiency of trading strategies;

• Lending markets: AI improves capital efficiency through smart lending strategies, achieving better yield enhancement;

• Yield markets: AI introduces dynamic interest rate adjustments and smart 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 appreciate capital, and Web3 AI shows great potential in this process. Compared to the closed Web2 system, AI in the Web3 ecosystem can leverage 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 its early stages, the DeFi AI (DeFAI) field has already seen several exciting cases emerge:

• Giza (@gizatechxyz): Its AI-driven stablecoin yield optimization agent has surpassed $1 million in TVL and has improved traditional lending strategies by over 83% through efficient strategies, with a cumulative trading volume of $6 million;

• Cod3x (@Cod3xOrg): Launched the Sophon Spark agent trading competition, where AI agents will compete for a $1.5 million reward while training smarter trading strategies using data;

• Olas (@autonolas): Its Modius & Optimus AI agents can serve as personal portfolio management tools, and its team is the only one supporting agents to run on local desktop environments, allowing users to manage through the "Pearl" agent app store (recently, the 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, allowing AI to better integrate into the DeFi ecosystem.

So, why are AI agents suitable for DeFi?

• 24/7 operation: AI agents can optimize yields, adjust positions, and respond to market changes in real-time around the clock;

• Automated management: AI can intelligently manage DeFi positions, significantly improving the efficiency of on-chain trading and yield optimization;

• Multi-protocol integration (MCP): AI agents can connect to more on-chain protocols, uncovering richer DeFi yield opportunities. In the coming year, AI agents may undertake a large number of on-chain transactions in the DeFi ecosystem due to their efficient automation advantages.

Additionally, noteworthy directions in this sector include:

• Teams driving technological innovation: Supporting developer ecosystems, such as hosting hackathons, competitions, and seminars;

• Teams focusing on privacy, verifiability, and non-custodial solutions: Allowing users to have complete control over AI agents rather than centralized platforms;

• AI agent growth metrics: For example, assets under administration (AUA) / agent-managed TVL, measuring the influence of AI in the DeFi ecosystem.

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

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 apparent: technological innovators are rewarded, while laggards are eliminated. This competitive environment is different from the traditional AI field; Web3 has built a highly competitive ecosystem through token incentives, inflation distribution, and penalty mechanisms.

Key AI projects with high community attention include:

1. Bittensor: The decentralized infrastructure for all AI

• Enabling teams to innovate freely through subnets, promoting AI development;

• SN6, 41, 44 have sparked the GambleFAI narrative, leveraging AI/ML predictive capabilities to gain advantages in prediction markets.

2. Allora: AI-driven machine learning and prediction markets

• Adopting a "Topics" mechanism to replace Bittensor's subnets, with each Topic representing a financial prediction use case;

• The team with the strongest AI predictive capabilities can earn the most rewards;

• @steerprotocol case: AI-driven LP strategies achieving higher yields and lower impermanent loss (IL).

3. Bit Robot: Focusing on the robot AI ecosystem

• Developed by the @frodobots team, similar to Bittensor but focused on the robotics field;

• Plans to establish different subnets covering areas such as robot data, hardware, visual models, and large language models (LLMs).

The Web3 AI ecosystem has entered a "Hunger Games mode," where the strongest in technology will gain more resources, while laggards will be eliminated. In the future, AI agents will take on increasingly critical roles 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 ecosystems mature, these infrastructures will be further adopted, promoting the development of data, model training, verifiability, privacy protection, and DePIN. Currently, the market is focusing on the following short to medium-term directions:

1. Social & Sentiment 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 on the Yaps rating system, enhancing the utilization of social data;

• aixbt (@aixbt_agent): Tracking and mapping project Alpha opportunities and social trends based on Twitter, helping investors discover new opportunities;

• Cookie DAO (@cookiedotfun): Providing 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 area remains one of the key directions for infrastructure development.

3. Other Data Field Players

• Data scraping: @getgrass_io collects data using 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 develops Blind Compute technology to enhance privacy protection in data computation, with its token NIL set to undergo TGE soon.

As the narratives of DeFAI and Darwinian AI deepen, infrastructure related to data, computing power, and privacy protection will see broader applications. In the future, we will witness a more mature infrastructure ecosystem, with AI agents playing a larger role in decentralized data processing, trading optimization, and market prediction.

Crypto AI Breaks the Limitations of Web2 AI

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

Three Core Capabilities Empowering AI Agents through Crypto AI

• Autonomous capital flow without centralized intermediaries: AI agents can directly allocate funds, optimize yields, and execute trades within the DeFi ecosystem, avoiding limitations imposed by centralized institutions;

• Access to data unreachable by Web2 AI: Decentralized data flows (On-chain Data, Social Data) provide unique informational advantages, helping AI make more precise decisions on-chain;

• Open collaboration, accelerating AI evolution: Crypto AI relies on open models and collaborative innovation, evolving faster and with broader application scenarios compared to the closed AI systems of the Web2 era.

Core Value of Crypto AI

• AI + DeFi, intelligent agents truly become participants in the on-chain economy: AI agents are not just tools for executing tasks; they can hold assets, trade for arbitrage, and optimize capital operations, becoming an important part of the DeFi ecosystem;

• Transparency and verifiability & strong composability: All AI transactions, yield management, and other operations on-chain are traceable, allowing intelligent agents to reuse, iterate, and collaborate, accelerating the development of the AI ecosystem;

• Web2 only initiated the AI competition, while Web3 drives AI towards a self-sustaining economy: AI agents will evolve from "assisting humans" to proactive creators of the 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 will also become the core engine of on-chain wealth flow and value creation.

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