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 AI, blockchain technology, and intelligent agents – where the primary focus shifts to user intentions and automated functionalities.

AI’s Rapid Integration into Web3

According to DappRadar, 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 — all happening instantaneously. Notably, by June 26, 2025, investments in AI-driven projects had soared to $1.39 billion, already exceeding the previous year’s benchmarks.

Chris Dixon effectively highlights that AI and blockchain technology are closely intertwined. 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.”

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”, leading to innovative user engagement and automation trends within the finance sector.

Transitioning from Applications to Intelligent Agents

The future landscape is straightforward in concept but challenging to actualize: users express their desires, and autonomous agents manage the intricate backend processes—including data analysis, risk evaluation, and settlement—ultimately 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 notes that developer tools are progressing rapidly, with frameworks like elizaOS 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.

The Challenge of Fragmentation in Web3 Data

For agents to function efficiently, they rely on precise, real-time data. However, Web3 remains divided by various chains and data formats. 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.

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

Key Insight: 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.

AI Agents: A Perfect Match for Decentralized Finance (DeFi)

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

• Trade and adjust portfolios based on pre-set criteria (“liquidate assets if market volatility hits X”).
• Identify risks (unusual patterns, oracle discrepancies) and factor them into trade decisions.
• Engage in arbitrage and market making across various platforms without cumbersome user interfaces.
• Manage governance (draft initiatives, assess outcomes) using consensus from both on-chain and off-chain communities.

Recent academic research regarding AI agents in DeFi aligns with these anticipated roles, linking decision-making of autonomous agents to intricate market dynamics and governance structures. Similarly, influential figures like Buterin suggest positioning AI as a participant within crypto markets, seamlessly integrating into financial systems.

The Rise of Chat-Driven DeFi Platforms

Below is a selection of innovative chat-centric or agent-first platforms demonstrating the diverse possibilities, from user-friendly bots to intention-driven systems:

• HeyElsa: An AI crypto co-pilot that simplifies actions like routing and exchanging assets across chains with an intuitive voice or text interface. Think “just outline your needs, and Elsa manages the rest.” Projected Unique Feature: integrated voice and chat functionality paired with enhanced security through MPC (Multi-Party Computation).
• Kuvi.ai: Promoting the idea of Agentic Finance, its motto, “Don’t trade, just shout out,” facilitates straightforward execution of trades in DeFi through natural dialogue. Projected Unique Feature: comprehensive intent communication linking finance, identity, and gaming sectors.
• Igris.bot: Specializes in destination-based exchanges: users specify desired outcomes (“achieve 2 ETH on Base”), and the bot analyzes the best route, sources, and fees. Projected Unique Feature: focus on achieving user-specified outcomes while minimizing user decision fatigue and optimizing available portfolio liquidity.
• Defi App: Facilitates explicit intent-based trades, efficiently routing tasks across diverse decentralized exchanges (DEXs). Projected Unique Feature: enabling native intent-driven execution where external solvers compete to provide optimal trade routes.
• AskGina.ai: Functions as an AI wallet companion capable of reviewing user holdings and executing transactions through chat commands; available as both a web application and a mini-app. Projected Unique Feature: a chat-based interface that comprehensively understands user portfolios and presents tailored insights.

Infrastructure Needs for the Agentic User Experience

As intelligent agents emerge as the new user interface, infrastructure must evolve to meet machine requirements:

• Programmable Data Framework: cross-chain integration leading to unified schemas, real-time data replication, and deterministic APIs consumable by AI agents.
• Low-Latency Computation: triggers for fluctuations in price/volatility, evaluation of agent policies, and preliminary trade assessments.
• User Identity & Permissions: wallet-secured permissions, cryptographic confirmations (“proof of identity”), and safety structures around agent autonomy—a link to blockchain’s inherent strengths.
• Safety Features: Vitalik Buterin’s observations point towards essential components like restricted APIs and emergency triggers to ensure user safety.

Importance of Timing and Integration

The emerging intent-focused design is gaining traction: users input goals, while agents take care of the underlying technical tasks. The current model of manually navigating across bridges, DEXs, and dashboards is unsustainable for mass adoption. A redesign isn’t solely about a better interface; it’s about crafting accessible pathways for ownership and programmable data so that various agents—not merely a few super-apps—can offer real user value.

As significant trends develop, they tend to “enhance and support one another.” AI injects innovation and operational efficiency, while crypto provides frameworks for ownership and motivation. Furthermore, the introduction of new devices (ranging from phones to wearables) will create a comprehensive user experience, effectively merging these functionalities as agents.

Final Reflections

If the last era revolved around “read-write-own,” the forthcoming phase emphasizes “act”: software taking action on behalf of the user. In the realm of DeFi, this translates to agents that accurately interpret user intent, assess risks, and facilitate settlements across fragmented markets both swiftly and securely. The leading solutions won’t simply focus on attractive user interfaces; they will prioritize strategic architecture and create programmable data layers alongside incentive structures to enable agents to flourish on a grand scale.