How to utilize AI agents in decentralized finance (DeFi) platforms

March 8, 2025

Key takeaways

AI agents in DeFi are self-operating apps that can help navigate by optimizing trading, adding risk management and market analysis without human intervention.
These agents integrate with DeFi platforms through smart contracts, offering automation for tasks like portfolio rebalancing, yield farming and enhanced security.
AI trading agents adapt to real-time market conditions, identifying trends and executing trades 24/7 across multiple platforms.
Despite their potential, AI agents face challenges such as reliance on high-quality data, regulatory uncertainties and vulnerability to security risks.

Imagine a world where trading is no longer limited to human financial knowledge and capacities. In this world, machines don’t just execute trades but also adapt and continuously optimize strategies on their own. This isn’t the distant future; it’s the reality emerging in decentralized finance (DeFi) today, thanks to AI agents.

AI agents are self-operating software programs that can make decisions independently, without human interaction. They use machine learning algorithms to refine their processes and adapt continuously.

In traditional finance, AI has already transformed trading, risk management and customer service. In DeFi, where trust is built on code, not intermediaries, AI has opened new avenues for autonomy, transparency and effectiveness.

This article will explore what AI agents are and how to utilize AI in DeFi platforms.

How AI agents power DeFi

AI agents are like helpful robots that live inside DeFi platforms and manage finances. They’re integrated with smart contracts and decentralized applications (DApps), which function like regular apps but instead are run on a blockchain.

Some DeFi platforms have AI agents integrated into them. These agents can work with decentralized exchanges (DEXs) and lending platforms to make trading easier, smarter and safer for users. However, some apps or bots must be downloaded to start interacting with an AI agent.

For instance, an AI agent could monitor interest rate trends in Aave, optimizing lending strategies. If the interest rates for borrowing assets on Aave drop below a threshold, the AI could automatically rebalance your portfolio, shifting your assets to a more profitable lending market.

In contrast, some platforms offer AI services through subscriptions. You pay a small fee, and the AI takes care of tasks like automatic trading or rebalancing your portfolio without needing you to do anything.

AI agents often work through smart contracts, which are like self-executing agreements that run automatically when conditions are met. There is no need to trust an intermediary; everything is handled by code, making transactions safe and automatic. Here’s how it works:

Predefined rules: The AI agent interacts with a smart contract containing predefined conditions (e.g., “buy Bitcoin if the price drops to $40,000”).
Real-time data analysis: The AI continuously monitors market conditions, user preferences or risk factors and feeds this data into the smart contract.
Automatic execution: When the conditions are met, the smart contract executes the transaction instantly, whether it’s a trade, loan adjustment, or portfolio rebalancing.

Architecture of AI agents

Did you know? According to CoinGecko, interest in AI agents has surged, with the market cap of this niche growing by 222% to over $15 billion by the end of 2024.

Different ways to use AI in DeFi

AI agents in decentralized finance are transforming how users manage their assets, from trading and market analysis to risk management and security. These AI-powered tools enhance DeFi platforms and help users save costs by reducing the need for professional financial firms.

AI agents for crypto trading

AI agents are taking the role of traders by automating their daily routines. While traditional bots follow pre-set rules, AI trading agents learn from market patterns and adapt their strategies in real time.

They monitor price fluctuations of cryptocurrencies, identify trends and execute trades 24/7, ensuring that your portfolio is always managed with up-to-date information. They can spot arbitrage opportunities and optimize buying/selling decisions across multiple platforms.

For example, an AI-powered trading agent might execute complex multi-step trades, taking advantage of price differences between various DEXs and ensuring that opportunities are not missed.

AI agents for risk management

Risk management in the risky DeFi world can be daunting, but AI agents can help manage it. With the ability to continuously monitor market volatility, liquidity, and borrower credit risk, AI agents provide a more accurate and real-time risk assessment than traditional systems.

In DeFi lending, for example, AI agents examine a borrower’s history on various platforms and offer customized collateral and loan terms based on real-time inputs.

AI agents for crypto market analysis

AI agents can process vast amounts of data. By scanning the price history of cryptocurrencies, social media sentiment and economic indicators, these agents are constantly learning and adapting to predict market trends. As a result, they can spot emerging trends, forecast price movements and even identify the next big DeFi project.

With this information, traders and investors can stay ahead of the curve, making more informed decisions and avoiding risky markets.

AI agents for enhanced security

Security is one of the significant topics in DeFi, and AI agents can become crucial in helping detect fraudulent activities. They can analyze patterns to identify unusual behaviors, such as rapid, large withdrawals or trades that could signal a breach.

Furthermore, AI agents can monitor smart contracts to detect vulnerabilities before they are exploitedexploiting them, ensuring the platform’s security.

AI agents for yield farming and staking

As yield farming and staking pools can be highly lucrative, constant monitoring of gas fees, rewards, and interest rates for optimization is required. AI agents are adept at determining the most profitable pools to stake or farm tokens, switching strategies on the fly to compound returns. They can ensure that your assets always work for you, even when you are not actively controlling them.

AI agents as personalized financial assistants

By acting as personalized financial assistants, AI agents can help users navigate the complexities of DeFi. They can suggest the best investment opportunities, provide portfolio advice and help users optimize their assets while saving costs — without requiring in-depth crypto knowledge.

Additionally, some agents can assist with taxes and financial research, making it easier to navigate the accounting field. This creates a more inclusive DeFi ecosystem where newcomers can participate and make informed decisions.

Intersection between Artificial Intelligence and blockchain

Let’s focus on creating an AI agent for portfolio management in DeFi. This AI agent will help manage and optimize your cryptocurrency holdings in a decentralized way.

Did you know? In decentralized autonomous organizations (DAOs), AI agents can be leveraged to provide data-driven feedback and recommendations on governance proposals. From processing onchain information, sentiment within the community, and economic statistics, such agents help DAO participants make more informed decisions.

AI agent for portfolio management in DeFi: Step-by-step guide

This section explains how to create an AI agent for DeFi portfolio management that autonomously optimizes asset allocation, rebalances holdings and leverages yield farming opportunities through smart contracts.

Step 1: Define portfolio management goals

Start by defining what you want your AI agent to achieve with your crypto wallet. Common portfolio management goals include:

Rebalancing: Ensuring the portfolio stays aligned with the desired allocation (e.g., 50% Bitcoin (BTC), 30% Ether (ETH) and 20% stablecoins).
Risk management: Adjusting allocations based on market conditions or volatility.
Diversification: Ensuring the portfolio is spread across a variety of assets to minimize risk.
Yield optimization: Allocating assets to maximize returns through yield farming or staking opportunities.

Your AI agent will analyze your portfolio and automatically rebalance it on a regular basis every month to keep your crypto allocation within the desired percentages, adding stablecoins when volatility is high or increasing exposure to promising altcoins during a bull market.

Kingsley Advani tweet

Step 2: Choose the data

Your AI agent will need market data to make informed decisions. For portfolio management, the data includes:

Price: Real-time and historical data of various cryptocurrencies.
Market conditions: Volatility, liquidity, market trends, etc.
DeFi opportunities: Information about yield farming, staking and lending rates.
Risk metrics: Data on market risk and volatility levels.

Use APIs like CoinGecko or CoinMarketCapto to fetch real-time price and market data. Get information on available yield opportunities from Yearn.finance or Aave.

Step 3: Build or choose an AI model

For portfolio management, a reinforcement learning model might be most appropriate. The AI will learn and adapt its actions based on rewards or penalties. This allows the agent to optimize the portfolio over time by evaluating the performance of different assets and adjusting allocations accordingly.

What the model does: The AI learns from past portfolio performance and current market conditions to suggest the optimal mix of assets.

The AI will monitor market fluctuations, adjusting asset allocation by moving funds into stablecoins during high volatility or switching into high-yield opportunities when market conditions are favorable.

Step 4: Develop smart contracts for automation

To implement portfolio rebalancing and other tasks autonomously, write smart contracts to handle actions like swapping assets, staking or yield farming based on the AI’s recommendations.

What the smart contract does: The smart contract will handle transactions like moving assets between wallets, rebalancing portfolios, staking tokens or withdrawing funds from yield farming pools.

So, write a Solidity smart contract that automatically moves your holdings based on the AI’s instructions. For example, if the AI detects that your portfolio has too much ETH and insufficient BTC, the smart contract will automatically swap some Ether for Bitcoin.

Step 5: Integrate AI with the DeFi platform

Use a blockchain interaction library like web3.js or ethers.js to connect your AI with the DeFi protocols. This allows the AI to send transactions to DeFi platforms like Uniswap or SushiSwap to swap tokens, Aave for lending/borrowing or Compound for yield farming.

The AI could determine that a particular stablecoin pool offers the best yield and instructs the smart contract to swap a portion of your crypto holdings for the stablecoin and stake it in the pool.

Step 6: Backtest and optimize the strategy

Before deploying the AI agent, backtest it using historical data to simulate how it would have performed under various market conditions.

Backtesting: Run the AI model using past market data to see how it would have adjusted the portfolio.
Optimization: Adjust the model based on backtesting results to ensure it meets your portfolio goals and risk tolerance.

You could run the AI agent with historical data from the past two years, simulating market crashes and rallies, to see how well it rebalances the portfolio and minimizes losses or maximizes gains.

Step 7: Launch and monitor the AI agent

Once the AI is trained and the smart contracts are deployed, you can launch your AI-powered portfolio manager.

Regularly check that the AI performs as expected and that the smart contracts execute correctly. You can set up alerts for significant changes or portfolio adjustments.

For instance, you might want to monitor how often the portfolio rebalances, ensuring the AI isn’t making unnecessary changes or accumulating high gas fees due to frequent swaps. You can also track the performance of your yield farming and staking efforts.

Drawbacks of AI agents

While AI agents in the crypto space are gaining traction, much of the current excitement remains speculative. Researchers caution that many AI agent projects have yet to prove their utility beyond hype.

One of the biggest concerns is their reliance on real-time, high-fidelity data. Errors or data manipulation can lead to unintended decisions with serious financial consequences.

Mike Cahill from the Pyth Network highlights that AI agents require ultra-low-latency price updates, ideally sourced directly from first-party providers like exchanges, to reduce risks from outdated or manipulated data.

While interest in AI-related crypto projects has surged, much of the AI agent niche remains speculative. Although some projects address practical challenges, the rapid development of Chinese AI models also adds competitive pressure that may lead to a sell-off among crypto AI projects, according to Sygnum Bank.

Additionally, while AI enhances security, it also introduces new risks. If not properly secured, AI systems can become targets for malicious actors. Moreover, flaws in algorithms could be exploited, making security a top priority for any AI-powered DeFi platform.

The regulatory environment of AI in DeFi is still nascent. Regulators and governments are concerned about algorithmic bias, data privacy and accountability. Resolving these concerns is crucial for AI to be implemented in DeFi on a large scale.

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Lingering lung disorders 5 years post-COVID: Here’s what to know

Reporters News Wire

March 8, 2025

The COVID-19 pandemic engulfed the U.S. five years ago this month, leaving not only lingering mental health effects but also long-term physical symptoms.

One of those included a condition known as post-COVID pulmonary fibrosis, which involves scarring of the lungs that can worsen over time and may require a lung transplant, according to pulmonologists.

Early infection caused extensive inflammation in many different body systems, noted Dr. Scott Scheinin, MD, director of lung transplantation for Mount Sinai Health System in New York City.

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“Once they cleared that infection, a lot of people were left with some amount of lung tissue being destroyed,” Scheinin told Fox News Digital during an interview.

Post-COVID pulmonary fibrosis involves scarring of the lungs that can worsen over time and may require a lung transplant. (iStock)

Scheinin provided medical care on the frontlines in New York City in the first wave of the pandemic.

“The early COVID experience in New York was the worst thing I’ve ever experienced in my life. It was just horrible,” he recalled.

One patient’s story

One of Scheinin’s patients was a pastor in his mid-50s who was infected with COVID-19 in March 2020.

Pastor Benjamin Thomas of East Meadow, Long Island, spent nearly 100 days in the hospital — 54 of which were on a ventilator — and six weeks in a medically induced coma.

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He was discharged in July 2020 with an oxygen tank. Despite overcoming the initial infection, Thomas’ condition deteriorated.

In 2022, the pastor noticed that his daily activity tolerance diminished dramatically and he required more oxygen for simple tasks.

The inflammatory response sparked by early mutations of the novel coronavirus led to scarring of lungs in many individuals. (iStock)

“I couldn’t take a shower for more than 30 seconds without being on oxygen,” he told Fox News Digital in an interview.

Scheinin said the pastor had no underlying conditions before contracting COVID. A lung biopsy showed that Thomas’ symptoms were consistent with post-inflammatory pulmonary fibrosis due to the COVID-19 infection.

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Thomas’ story was remarkable in that he survived the first bout with COVID, but two years later, his lungs had deteriorated so badly from the scarring that he needed a double lung transplant, Scheinin shared.

After spending seven months on the wait list, Thomas opted to settle for one lung since that would be faster than waiting for two. His surgery was performed on Feb. 28, 2023.

“The flu and any other illness would be exacerbated because of the underlying scarring of the lung.”

Now, two years after his lung transplant, Thomas says he no longer needs oxygen supplementation and is back to performing his daily pastoral activities at his church in Queens Village, New York, albeit at a slower pace than before.

The pastor has returned to long-distance driving and can now walk for about 30 minutes. He attributes his successful recovery to the efforts of his Mount Sinai medical team, his faith and prayers from his congregation.

What is post-COVID fibrosis?

A healthy lung allows for the normal exchange of gases, such as oxygen and carbon dioxide, when one breathes air, Scheinin told Fox News Digital.

The inflammatory response sparked by early mutations of the novel coronavirus led to scarring of lungs in many individuals.

Testing for this condition is relatively non-invasive, typically including a cat scan or X-ray to check for structural lung damage, as well as blood tests and a pulmonary function test. (iStock)

In certain cases, the doctor said, the lungs no longer function as well as they did before the infection.

“The normal gas exchange is impeded because now you have areas of the lung tissue that are scarred, and therefore they’re not functioning normally,” he said.

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“If it’s a small area, it may be insignificant and unnoticeable, but as more of the lung tissue becomes scarred, more of the normal lung function is destroyed, [and] the patient becomes short of breath.”

This could lead to future issues, especially if the patient is exposed to other respiratory ailments.

“The flu and any other illness would be exacerbated because of the underlying scarring of the lung,” Scheinin said. “I think it just makes the lungs more susceptible to injury.”

Symptoms, diagnosis and treatment

Symptoms of post-COVID pulmonary fibrosis can mimic other types of interstitial lung diseases, which are disorders that cause progressive scarring and inflammation of lung tissue.

If a person who previously had a COVID infection continues to experience shortness of breath, chronic cough and change in their exercise tolerance — or if they smoke or have an underlying condition such as emphysema — they should see their physician or a pulmonologist, according to Scheinin.

Risk factors for post-COVID pulmonary fibrosis typically include an underlying chronic condition, older age, and the use of mechanical ventilation during the acute phase of COVID. (iStock)

Testing for this condition is relatively non-invasive, typically including a cat scan or X-ray to check for structural lung damage, as well as blood tests and a pulmonary function test, the doctor told Fox News Digital.

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Not everyone infected with COVID will develop pulmonary fibrosis, and the condition can vary in severity and recovery, the lung specialist noted.

In some cases, a person may have been susceptible to developing lung fibrosis due to an underlying condition and the COVID-19 infection may accelerate the fibrotic progression.

It is important to get checked out by a medical professional if you have symptoms, a lung specialist said, especially shortness of breath. (iStock)

It is important to get checked out by a medical professional if you have symptoms, Scheinin said, especially shortness of breath.

Risk factors for post-COVID pulmonary fibrosis typically include an underlying chronic condition, older age, and the use of mechanical ventilation during the acute phase of COVID, according to previous studies.

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Researchers are investigating the use of antifibrotic medications to treat the condition, along with steroids and other anti-inflammatories that are currently used to treat other lung diseases.

Besides medications, treatment may also include pulmonary rehabilitation, exercise training and behavioral modifications, according to lung specialists.

Amy McGorry is a contributing health writer for Fox News Digital. Follow her on Twitter @amymcgorry.

Crypto execs weigh in on what to expect at White House summit

Reporters News Wire

March 8, 2025

With many crypto industry leaders and US government officials expected to gather at the White House in a matter of minutes, some are speculating that the event will explore regulatory clarity.

On March 7, US President Donald Trump is expected to address an audience of crypto company CEOs and founders to discuss regulatory policies, stablecoins and a proposed plan to establish a strategic crypto reserve in government. A senior White House official said prior to the event that the summit would not focus on taxes but rather “rolling back” policies put in place by the previous administration.

“While we’ll need to wait and see what concrete goals emerge from the summit, there’s optimism that it will continue building a regulatory framework that gives the US crypto industry what it desperately needed: clarity without strangulation,” Les Borsai, co-founder of Wave Digital Assets, told Cointelegraph.

“After years of watching innovation flee to friendlier jurisdictions overseas, this summit represents the first coordinated effort to reverse that talent drain and create both an immediate path to regulatory certainty and a long-term vision for blockchain’s role in America’s financial architecture,” Borsai added.

Trump announced the summit less than seven days ago. Executives from major crypto firms, including Ripple CEO Brad Garlinghouse and Coinbase CEO Brian Armstrong, have confirmed that they will be attending. Many are speculating that Tether CEO Paolo Ardoino, who posted on social media that he was in Washington, DC on March 6, could also visit the White House.