How to Trust AI Agents on the Web: Proof, Stake, and Smarter Safeguards

Kari Jaaskelainen

06 Nov 2025 — 1 min read

The "agentic web" is coming: billions of AI agents that buy, sell, and collaborate online. But who - and what - do we trust?

This study compares six ways agents earn trust:

Brief: verifiable profiles/IDs
Claim: self-declared skills
Proof: cryptography and hardware attestations
Stake: collateral with slashing/insurance
Reputation: feedback and social graphs
Constraint: sandboxes and capability limits

Pure claims or reputation often fail with LLM agents (prompt injection, hallucination, sycophancy, deception). No single tool is enough.

Recommendation: design "trustless-by-default" systems. Use Proof and Stake to gate high-impact actions; add Brief for discovery/identity and Reputation for social signals; keep tight Constraints around what agents can do.

The paper benchmarks emerging standards - Google's A2A, Agent Payments Protocol (AP2), and Ethereum's ERC-8004 - on security, privacy, cost/latency, and resistance to Sybil/collusion/whitewashing.

For builders and policymakers, it offers actionable design guidelines for safer, interoperable agent economies. Read: http://arxiv.org/abs/2511.03434v1

Paper: http://arxiv.org/abs/2511.03434v1

Register: https://www.AiFeta.com

AI Agents AgenticWeb Web3 Security Cryptography Reputation Trust LLM ProtocolDesign Ethereum

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