{"id":46046,"date":"2025-09-05T19:58:54","date_gmt":"2025-09-05T19:58:54","guid":{"rendered":"https:\/\/www.bitrabo.com\/discover\/?p=46046"},"modified":"2025-09-05T19:58:54","modified_gmt":"2025-09-05T19:58:54","slug":"discover-why-ai-agents-are-revolutionizing-defi-now","status":"publish","type":"post","link":"https:\/\/www.bitrabo.com\/discover\/discover-why-ai-agents-are-revolutionizing-defi-now\/","title":{"rendered":"Discover Why AI Agents Are Revolutionizing DeFi Now"},"content":{"rendered":"\n

The evolution of technology often unfolds through interconnected phases. We’ve seen a significant shift with the rise of mobile, social networks, and cloud computing, shaping recent technological trends. Now, we are stepping into a new era dominated by <\/i>AI, blockchain technology, and intelligent agents<\/i><\/a> \u2013 where the primary focus shifts to user intentions and automated functionalities.<\/i><\/p>\n

<\/span>AI’s Rapid Integration into Web3<\/span><\/h2>\n

According to DappRadar<\/a>, in the past year and a half, AI technology has transitioned from being a mere novelty to a foundational component in the crypto ecosystem. Large language models (LLMs) now assist in summarizing governance discussions, while automated agents manage investments and strategies on-chain \u2014 all happening instantaneously. Notably, by June 26, 2025<\/strong>, investments in AI-driven projects had soared to $1.39 billion<\/strong>, already exceeding the previous year\u2019s benchmarks.<\/p>\n

Chris Dixon effectively highlights that AI and blockchain technology are closely intertwined<\/strong>. While traditional AI systems lack necessary features like ownership and secure identity, blockchains provide a solution, enabling a more open and efficient market for computational resources, data, and content. Dixon aptly states, “AI requires blockchain’s computational capabilities<\/strong>.”<\/p>\n

From a broader perspective, the industrial implications of AI complement this transformative shift. NVIDIA’s CEO, Jensen Huang, articulates that AI heralds “a new industrial revolution”<\/strong>, leading to innovative user engagement and automation trends within the finance sector.<\/p>\n

<\/span>Transitioning from Applications to Intelligent Agents<\/span><\/h2>\n

The future landscape is straightforward in concept but challenging to actualize: users express their desires, and autonomous agents manage the intricate backend processes<\/strong>\u2014including data analysis, risk evaluation, and settlement\u2014ultimately performing the required actions. Investigating the potential of “the Agentic Web” reveals a connected environment where agents can compensate each other for data and services, collaborate through smart contracts, and autonomously conduct transactions without human intervention. IKANGAI<\/a> notes that developer tools are progressing rapidly, with frameworks like elizaOS<\/strong> that link LLM agents to wallets for executing decentralized finance actions based on natural language instructions. This hints at a future where applications operate as orchestrators of intelligent agents.<\/p>\n

<\/span>The Challenge of Fragmentation in Web3 Data<\/span><\/h2>\n

For agents to function efficiently, they rely on precise, real-time data. However, Web3 remains divided by various chains and data formats<\/strong>. Current methods for indexing and accessing blockchain data vary significantly, making robust inquiries a complex issue that often involves specialized indexing systems and pipelines, sometimes required anew for each blockchain.<\/p>\n

Services like Goldsky<\/strong> and The Graph<\/strong> are attempting to bridge these gaps, emphasizing the urgency for solutions that provide cross-chain mirroring<\/a>, real-time data streams, and adaptable subgraphs to meet the demands of complex applications\u2014particularly those led by autonomous agents. Various studies reinforce the negative impacts of fragmentation<\/a> on risk management and user experience within decentralized finance.<\/p>\n

Key Insight:<\/strong> if the user interface evolves into an input space for intentions, all the necessary computational tasks will shift to a programmable data layer designed to standardize on-chain and off-chain contexts, offering reliable APIs for agents and enabling swift computations across multiple chains.<\/p>\n

<\/span>AI Agents: A Perfect Match for Decentralized Finance (DeFi)<\/span><\/h2>\n

DeFi operates on machine-friendly principles: transparent ledgers, adaptable liquidity, and easily integrable contracts. This framework makes it an ideal environment for autonomous agents<\/strong> to:<\/p>\n