# Web3 x AI Agents: Landscape, Integrations, and Foundational Challenges

arXiv: https://arxiv.org/abs/2508.02773 · HTML: https://mlsanity.com/paper/2508.02773/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 84 references that are in the map.
- First posted on arXiv 4 Aug 2025.

## Builds on (most cited first, 25 of 25)

- [Lost in the Middle: How Language Models Use Long Contexts](https://mlsanity.com/paper/2307.03172/) (2023)
- [A Survey of Large Language Models](https://mlsanity.com/paper/2303.18223/) (2023)
- [A Survey on Large Language Model based Autonomous Agents](https://mlsanity.com/paper/2308.11432/) (2023)
- [LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigation](https://mlsanity.com/paper/2409.20550/) (2024)
- [Slither: A Static Analysis Framework For Smart Contracts](https://mlsanity.com/paper/1908.09878/) (2019)
- [IPFS - Content Addressed, Versioned, P2P File System](https://mlsanity.com/paper/1407.3561/) (2014)
- [Towards an Understanding of Large Language Models in Software Engineering Tasks](https://mlsanity.com/paper/2308.11396/) (2023)
- [GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis](https://mlsanity.com/paper/2308.03314/) (2023)
- [Securify: Practical Security Analysis of Smart Contracts](https://mlsanity.com/paper/1806.01143/) (2018)
- [Vulnerability Detection with Fine-grained Interpretations](https://mlsanity.com/paper/2106.10478/) (2021)
- [Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives](https://mlsanity.com/paper/2310.01152/) (2023)
- [When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We?](https://mlsanity.com/paper/2309.05520/) (2023)
- [Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications](https://mlsanity.com/paper/2403.16073/) (2024)
- [Manticore: A User-Friendly Symbolic Execution Framework for Binaries and Smart Contracts](https://mlsanity.com/paper/1907.03890/) (2019)
- [SoK: Decentralized Finance (DeFi) Attacks](https://mlsanity.com/paper/2208.13035/) (2022)
- [RMCBench: Benchmarking Large Language Models' Resistance to Malicious Code](https://mlsanity.com/paper/2409.15154/) (2024)
- [An Overview on Smart Contracts: Challenges, Advances and Platforms](https://mlsanity.com/paper/1912.10370/) (2019)
- [Finding The Greedy, Prodigal, and Suicidal Contracts at Scale](https://mlsanity.com/paper/1802.06038/) (2018)
- [Eliza: A Web3 friendly AI Agent Operating System](https://mlsanity.com/paper/2501.06781/) (2025)
- [Decentralized Governance of Autonomous AI Agents](https://mlsanity.com/paper/2412.17114/) (2024)
- [Smart Contract and DeFi Security Tools: Do They Meet the Needs of Practitioners?](https://mlsanity.com/paper/2304.02981/) (2023)
- [FORGE: An LLM-driven Framework for Large-Scale Smart Contract Vulnerability Dataset Construction](https://mlsanity.com/paper/2506.18795/) (2025)
- [Smart Contract Security: a Practitioners' Perspective](https://mlsanity.com/paper/2102.10963/) (2021)
- [DAOs of Collective Intelligence? Unraveling the Complexity of Blockchain Governance in Decentralized Autonomous Organizations](https://mlsanity.com/paper/2409.01823/) (2024)
- [From Firms to Computation: AI Governance and the Evolution of Institutions](https://mlsanity.com/paper/2507.13616/) (2025)

## Built on by (most cited first, 1 of 1)

- [Distributed Legal Infrastructure for a Trustworthy Agentic Web](https://mlsanity.com/paper/2603.06884/) (2026)

## Abstract (arXiv)

The convergence of Web3 technologies and AI agents is a rapidly evolving frontier that is reshaping decentralized ecosystems. This paper presents the first comprehensive landscape analysis of the intersection between Web3 and AI agents, examining five critical dimensions: landscape, economics, governance, security, and trust mechanisms. Through an analysis of 979 capitalized Web3-AI agent tokens at a 1 September 2026 cutoff, compared with a cohort of 275 tokens collected at 6 April 2025, we develop a taxonomy and systematically map the current market landscape (RQ1), identifying distinct patterns in project distribution and capitalization. We complement the token frame with on-chain measurement of the agent standards layer: 530,266 ERC-8004 identity registrations across 16 chains and 432,913 x402 settlements on Base. We then investigate four integration domains: AI agents in decentralized finance (RQ2), governance (RQ3), security (RQ4), and Web3 trust mechanisms for agent reliability (RQ5). Infrastructure dominates the landscape in both project count and capitalization; value is highly concentrated (Gini 0.938), and the archived cohort lost 36.4% in capitalization over seventeen months despite token population growth. The agent standards layer shows adoption at scale, but economic throughput remains limited. Across integration domains, AI agents extend DeFi trading and make continuous security auditing affordable, while agents in governance remain largely a blueprint. These findings outline critical considerations for future research toward robust, intelligent, and trustworthy decentralized systems with AI agent interactions.