This topic covers the toolkits, agent frameworks, marketplaces and security practices used to build autonomous on‑chain fund managers — AI agents that monitor markets, execute trades, rebalance portfolios, handle custody interactions and record auditable actions on blockchains such as Polygon or runtimes like OKX OnchainOS. It’s timely in 2026 because agent orchestration, private LLMs, retrieval‑augmented generation (RAG) and decentralized compute have matured enough to enable continuous, programmatic fund operation while regulators and auditors require stronger governance and traceability. Key components include agent frameworks and marketplaces where strategies and components are composed and exchanged; developer platforms that turn documents and signals into operational knowledge; and enterprise LLM and model hosting that provide private, compliant inference. Representative tools: AutoGPT for building and running autonomous agent workflows (self‑hosted or cloud), LlamaIndex for RAG and document agents, Vertex AI and Google Gemini for managed multimodal models and scale, Cohere and IBM watsonx for private/custom LLMs and embeddings, and StackAI for no‑/low‑code agent deployment and governance. AI‑integrated wallet tooling demonstrates how agents securely interface with on‑chain custody. Practical challenges and trends include verifiable execution (on‑chain logs, attestation), oracle design for trusted market inputs, multi‑party governance (multi‑sig, timelocks, human‑in‑the‑loop approvals), model risk management, and composability across decentralized infrastructure. The landscape favors modular stacks: LLMs + RAG for strategy reasoning, agent runtimes for orchestration, and blockchain smart contracts for execution and audit — all governed by security, compliance and interoperability standards increasingly demanded by institutions.