The Big Picture
Autonomous AI can act on blockchains usefully, but only if planning is separated from signing and every intent is checked by verifiable policy before funds move.
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The Evidence
A clear progression of five integration patterns runs from read-only advisors to fully autonomous signers, each increasing trust and risk. integration patterns six-stage pipeline where errors compound across layers. Standards and interfaces are the critical levers: a Transaction Intent Schema and a Policy Decision Record can enforce a separation of duties and reduce catastrophic on-chain failures. A survey of 20 production systems shows the landscape is fragmented and missing robust, standardized guards for high-autonomy workflows. separation of duties
Data Highlights
1Analyzed 20 representative platforms drawn from an initial pool of 85 publicly documented systems
2Defined a five-part taxonomy mapping agent authority from read-only analysis to autonomous signing
3Modeled a six-stage agent-to-chain pipeline (observe, reason, plan, authorize, execute, verify) to pinpoint where failures compound
What This Means
Engineers building AI-driven wallets and trading bots need these patterns to avoid automated loss and ensure auditable decisions. Security and operations teams should adopt intent and policy artifacts to gate signing and speed incident response. Product leaders and architects can use the taxonomy to choose the right trade-offs between convenience and safety when delegating authority to agents. intent and policy artifacts
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Learn MoreKeep in Mind
The survey relies on publicly documented systems and may miss proprietary or rapidly evolving implementations. Proposed standards (intent schema and policy records) require industry adoption and tooling to be effective in practice. Real-world adversarial testing under live market conditions remains limited and is needed to validate defenses against transaction ordering and mempool attacks. adversarial testing
Methodology & More
A systematic review maps how autonomous AI agents link to blockchains and why that matters: as agents gain the ability to build and submit transactions, the potential rewards rise alongside irreversible risks. The work organizes agent-to-chain interactions into a six-stage pipeline—observe, reason, plan, authorize, execute, verify—so teams can see where bad inputs or flawed reasoning turn into financial loss. A five-part taxonomy describes common integration patterns, from advisory agents that only read data to fully autonomous signers that can move funds without human intervention. The analysis used a reproducible screening protocol and compared 20 platforms from a larger pool of 85 publicly documented systems to surface common gaps: inconsistent tool interfaces, weak separation between planning and signing, and brittle authorization controls. Practical recommendations include adopting a Transaction Intent Schema to express goals in a structured, auditable way and a Policy Decision Record that proves an intent passed policy checks before signing. For engineers, the takeaway is actionable: keep creative planning and deterministic signing separated, require verifiable policy attestations, use multiple independent data sources, simulate transactions before sending, and log verification loops so memory is only updated after confirmed finality. These steps lower the chance that a manipulated input or marketplace adversary leads to irreversible loss. six-stage pipeline Policy Decision Record log verification loops simulate transactions before sending
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Credibility Assessment:
Single author with no affiliation or h-index information; arXiv preprint with no citations.