# Is DeFi Gonna Run By AI Agents?

Source: https://eli5defi.substack.com/p/is-defi-gonna-run-by-ai-agents?r=2gu2dc&triedRedirect=true

## Summary

AI agents already run parts of DeFi largely unnoticed and have become its most sophisticated power users. INFINIT, Giza and Almanak form what the piece calls an "AgenticFi" stack that turns plain-language goals into executable strategies, and Allora's collective prediction network is presented as the next layer. In one independent builder's case study, an agent using Allora's SOL price predictions made 2,776 trades over one month, returning 19.22% on a $50,000 balance with a 53.6% hit rate.

## Article

Short answer: They already have, and they’re running invisibly without your awareness.

AI agents are the native citizens of the blockchain network, and DeFi is their financial system.

But at what stage can we say these digital citizens are truly integrated—not merely visiting, but actively building the economy itself?

We may have just crossed that threshold.

From Tools to Citizens: AI agents have evolved from simple automation scripts to autonomous economic actors managing millions on-chain, marking a phase shift in DeFi participation.

Infrastructure Emergence: Protocols like INFINIT, Giza, and Almanak form the “AgenticFi” stack—translating natural language into verifiable, executable strategies while abstracting away complexity.

Predictive Evolution: The next generation of agents integrates collective intelligence networks (e.g., Allora) that synthesize thousands of specialized models, enabling predictive capabilities that individual LLMs fundamentally lack.

Network Effects: As more agents consume and contribute to these intelligence layers, they create self-reinforcing flywheels where accuracy compounds, strategies evolve, and DeFi becomes natively agent-optimized.

For years, DeFi’s growth has been constrained by human limitations: constant monitoring, gas-fee optimization, and deep protocol expertise. These frictions kept total value locked (TVL) stagnant relative to CeFi, creating a ceiling on complexity that only professional firms or DeFi native users could breach.

AI agents dismantle these barriers systematically.

An autonomous agent can scan hundreds of lending pools, DEXs, and perpetual markets in real time, compute optimal allocations, execute atomic transaction sequences, and hedge impermanent loss, all while the user sleeps.

This isn’t theoretical. In 2024-2025, on-chain AI agents evolved from experimental curiosities into legitimate asset managers, collectively overseeing millions in real capital and delivering institutional-grade returns to retail participants.

The shift is unmistakable: agents are no longer using DeFi protocols; they are becoming their most sophisticated power users.

“AgenticFi” may not be an official term, but it captures a fundamental architectural shift: agents become the principal actors in financial markets, operating with delegated authority yet retaining non-custodial guarantees.

Three protocols exemplify this evolution:

@INFINIT_Labs

delivers a “Prompt-to-DeFi” system using 20+ agents for yield research, gas optimization, and multi-protocol execution in single transactions via ERC-4337 and EIP-7702. Users set goals in plain language while agents handle bridging, liquidity, and positions seamlessly.

@Gizatechxyz

enables verifiable autonomy with zero-knowledge proofs. Its ARMA agent allocates stablecoins across Aave, Morpho, and Compound for best yields, factoring in gas and liquidity. The Pulse agent manages Pendle Principal Tokens on ETH, earning ~13% APR through automated tracking and rebalancing. AI decisions are cryptographically verified for transparency.

@Almanak

acts as a personal AI quant, running a swarm of agents for market analysis and yield optimization. Its Liquidity USD vault earns 8.75% APY through constant reallocations. Users describe strategies in plain English, and LLMs turn them into executable code in seconds.

You can check the detailed comparisons here:

These protocols optimize for yield. But the evolution doesn’t stop there. The next frontier is predictive intelligence.

The Alpha Arena experiment by Nof1.ai revealed critical insights about AI trading personalities. Six models received $10,000 each to trade crypto perpetuals autonomously:

At the end of S1, Alibaba’s Qwen3-Max achieved +75.6% returns through just 22 selective trades by employing patient, high-conviction signals, while US models like GPT-5 and Gemini lost 60-70% through over-trading (Gemini executed 272 frantic trades).

Yet this experiment also exposed a fundamental limitation.

To date, most trading agents rely exclusively on large language models designed to predict words, not market behavior. When confronted with live data, they generate inaccurate numbers, misinterpret price feeds, and overlook liquidity constraints.

They lack true predictive capability.

This is beginning to change through specialized intelligence networks. Consider a recent case study:

An independent builder, AgenticTrading, integrated Allora’s SOL price predictions into a binary options agent.

Over one month, it executed 2,776 trades with $100 fixed stakes, generating $9,612 profit (19.22% return) from a $50,000 balance. Crucially, it achieved a 53.6% hit rate, outperforming the 51.8% break-even threshold.

The agent’s edge came from Allora’s Inference Synthesis mechanism, which dynamically weights thousands of specialized models rather than relying on a single predictor.

By filtering for only top-quantile confidence predictions (buckets 8-10), the agent avoided noise and capitalized when the network’s collective intelligence signaled genuine market inefficiencies. Here, the agent evolves beyond execution, it becomes a selective consumer of emergent market wisdom.

This architecture creates a self-improving coordination layer. Each model contributes predictions, learns from collective performance, and adapts to changing market regimes in real time.

As more agents consume its feeds—from volatility forecasts to yield curve predictions—the network’s accuracy compounds. A flywheel emerges: better predictions attract more agents, which generate more data, which strengthens predictions further.

These developments forge a new DeFi architecture. At the base, coordination networks like Allora provide continuously improving collective intelligence. Above them, infrastructure players like INFINIT and Giza translate predictions into safe, verifiable execution. At the application layer, Almanak and specialized agents deliver accessible strategies.

The implications are seismic:

Complexity vanishes

Access democratizes

Capital efficiency soars

Yet evolution brings new challenges. Hallucination risks persist—but are mitigated by deterministic execution frameworks and zk-proof verification. Scalability demands cross-chain intent protocols and gas abstraction. Trust requires on-chain identity standards like ERC-8004 to establish verifiable agent reputation.

With the AI agent sector valued at $20-39 billion in mid-2025, this isn’t speculative—it’s a functional new financial layer being built in real time. As models specialize and coordinate, we’re witnessing the emergence of an “Internet of Intelligence,” where autonomous agents don’t just participate in DeFi; they become its most efficient participants, continuously learning, adapting, and optimizing.

The question is no longer whether AI will transform DeFi, but how quickly we can build the infrastructure to let it reach its evolutionary potential.