The Importance of Privacy for DeFi Participants

This is a guest post reflecting the views of Matej Janež, Head of Partnerships at Oasis.

At EthDenver this year, a prevalent theme emerged: the integration of AI and autonomous AI Agents. This enthusiasm has persisted through other crypto events as the year progresses. The excitement is warranted; these concepts are no longer theoretical—they are operational and managing real assets. However, their dependence on transparent blockchains might turn out to be a significant drawback.

So, what exactly are these AI agents? They are intelligent software applications that autonomously perform designated tasks. In the crypto space, they utilize machine learning alongside blockchains to monitor markets, identify trends, and automate trades. Unlike traditional trading bots, contemporary AI agents adapt their actions continuously based on performance outcomes.

However, a major issue has been overlooked: the fact that these on-chain agents operate on transparent blockchains makes their decision-making processes—essentially their “brains”—publicly accessible. This transparency introduces significant challenges for agents aiming to compete effectively in financial markets.

AI Agents in DeFi

Currently, DeFi agents conduct trading across decentralized exchanges, manage lending activities, and optimize yield farming initiatives. They respond promptly to market fluctuations, often making swift decisions involving substantial funds. Smart, rapid, and efficient.

Yet they encounter a fundamental challenge. The public blockchain structure that enables their functionality simultaneously exposes their strategies. Every transaction and interaction with a smart contract creates a trail that reveals their decision-making process. It’s akin to participating in poker with your cards laid bare.

While it’s conceivable to execute these strategies on private servers and only submit final transactions to the blockchain, doing so undermines the core promise of crypto: transparency and on-chain verifiability. The objective of DeFi is to eliminate the necessity for trusted intermediaries and centralized authorities.

Examine the current landscape in DeFi. A yield farming bot is constantly assessing protocols for optimal returns, transferring millions among lending platforms based on subtle shifts in the market. Once its strategy is visible on-chain, competitors can easily observe which pools it enters and exits, replicating its strategy without the initial research investment. In decentralized credit markets, AI agents tasked with scoring wallets for under-collateralized loans become ineffective if borrowers can discern precisely which behaviors enhance their scores, resulting in artificially manipulated wallet patterns to exploit the system.

Particularly concerning are DAO treasury agents; if their rebalancing strategies are open to the public, anyone can front-run significant liquidity movements, effectively robbing the community with each transaction. These aren’t isolated occurrences; they represent inherent flaws in applying AI within transparent systems where strategy implementation and development cannot be distinguished.

Perhaps most alarming is the potential for market manipulation. When malicious entities understand an agent’s decision-making framework, they can orchestrate scenarios specifically designed to deceive it. Markets populated with transparent agents become easy targets.

Why a “Private Brain”?

Implementing a “private brain” for DeFi agents could address these issues. By maintaining confidentiality in computations, agents would make decisions without exposing their logic or intentions until after transactions are executed.

The security advantages are clear. Strategies would be shielded from duplication. Front-running would become more difficult without access to pending transactions. The agent’s operations remain confidential. Teams developing superior algorithms could retain their competitive edge, fostering ongoing improvements. Ultimately, the market would reward genuine innovation instead of quick imitations. On a broader scale, market stability would improve. When agent strategies remain undisclosed, it mitigates herding behavior, where multiple agents adopt identical approaches, thereby reducing correlated market oscillations and systemic risks.

If current practices persist—if DeFi agents continue to function with transparent operations—there are valid concerns about several adverse developments.

Market exploits are likely to become more frequent and sophisticated. As agents manage larger sums, the incentives for exploitation also increase. Without privacy protections, these exploits transform into mere technical challenges rather than serious security threats.

Strategy replication poses another significant issue. When successful strategies are swiftly copied, their effectiveness wanes. Eventually, all agents adopt similar methodologies, leading to a lack of diversity in the market and reducing its resilience.

This situation can be likened to the “Hive Mind” phenomenon; when all agents behave similarly, their responses to market fluctuations will align too. This strip of individuality results in heightened market swings, increased volatility, and the danger of flash crashes triggered by widespread identical reactions. What begins as discrete agents ultimately evolves into a single massive entity exerting system-wide consequences. Such conditions do not bode well for market health.

Technical Solutions

Trusted Execution Environments (TEEs) present a viable solution for establishing these private brains. TEEs create secure zones where computations occur in isolation, safeguarded even from the host system. Verification of correct execution is possible, while the specifics remain confidential.

This technology allows for a balance between openness and privacy. The foundational framework of an agent can be transparent and verifiable, while the intricacies of its decision-making process remain safeguarded.

Incorporating private computations into DeFi agents isn’t just beneficial—it is essential for the healthy evolution of algorithmic finance. Without measures for privacy, we risk creating a market that punishes innovation, rewards exploitation, and accumulates systemic risks beneath the surface.

We find ourselves at a pivotal moment in AI-driven finance, where our actions will shape whether autonomous agents foster a more efficient market or a perilously unstable one. The technology for private computations is already available, but its implementation demands intentional efforts from developers and protocols alike. As financial intelligence increasingly transitions on-chain, securing the ability of these systems to function with computational privacy is crucial—not just for protecting individual strategies but also for preserving the integrity of the entire DeFi ecosystem.