AESP: A Human-Sovereign Economic Protocol for AI Agents with Privacy-Preserving Settlement

Jian Sheng Wang

cs.CRFeb 27, 2026

AESP: A Human-Sovereign Economic Protocol for AI Agents with Privacy-Preserving Settlement

Authors: Jian Sheng Wang

Organizations: Yeah LLC

Abstract

As AI agents increasingly perform economic tasks on behalf of humans, a fundamental tension arises between agent autonomy and human control over financial assets. We present the Agent Economic Sovereignty Protocol (AESP), a layered protocol in which agents transact autonomously at machine speed on crypto-native infrastructure while remaining cryptographically bound to human-defined governance boundaries. AESP enforces the invariant that agents are economically capable but never economically sovereign through five mechanisms: (1) a deterministic eight-check policy engine with tiered escalation; (2) human-in-the-loop review with automatic, explicit, and biometric tiers; (3) EIP-712 dual-signed commitments with escrow; (4) HKDF-based context-isolated privacy with batched consolidation; and (5) an ACE-GF-based cryptographic substrate. We formalize two testable hypotheses on security coverage and latency overhead, and specify a complete evaluation methodology with baselines and ablation design. The protocol is implemented as an open-source TypeScript SDK (208 tests, ten modules) with interoperability via MCP and A2A.

Figures & tables

Delegation Dimension	Conceptual Requirement [ 28 ]	AESP Realization
Permission Handling (§4.7)	Tiered permission models with progressive trust	PolicyEngine: 8-check evaluation, 3 approval tiers (auto/review/biometric), 8 critical change types
Monitoring (§4.5)	Continuous monitoring and logging	ReviewManager: async review queue with priority, expiration deadlines, 6 event types, emergency freeze
Verifiable Completion (§4.8)	Verifiable task completion mechanisms	CommitmentBuilder: EIP-712 dual-signed commitments, 7-state lifecycle, SHA-256 commitment hashes
Trust & Reputation (§4.6)	Trust establishment and reputation models	Identity certificates with owner Ed25519 signatures, hierarchical delegation (depth $\leq 5$ ), DID-based identity
Security (§4.9)	Cryptographic security and key management	ACE-GF substrate (Section V ; WASM/C FFI/Dart FFI): Ed25519, secp256k1, X25519, ML-DSA-44, AES-256-GCM; keys never leave crypto boundary
Agent Communication	Standardized agent communication protocols	8 MCP tools + A2A agent cards (implemented, tested)

TABLE I : Mapping between Google DeepMind’s Intelligent AI Delegation Framework [ 28 ] and AESP Implementation

Panel of Figure 2 — Fig. 1 : AESP four-layer architecture. Blue arrows (downward) represent the sovereignty and authorization flow; red arrows (upward) represent escalation and event reporting.

Category	Primitive	Usage in AESP
Signatures	Ed25519	Agent identity, Solana tx
	ECDSA/secp256k1	EVM tx, EIP-712 signing
	Schnorr/secp256k1	Bitcoin Taproot tx
Post-Quantum	ML-DSA-44 (FIPS 204)	Future-proof agent certs
Key Agreement	X25519 ECDH	E2EE negotiation msgs
Encryption	AES-256-GCM	Negotiation msg encryption

TABLE II : Cryptographic Primitives in the ACE-GF Substrate

Condition	Type	Semantics
maxAmountPerTx	number	Max per-transaction spend
maxAmountPerDay	number	Rolling 24-hour limit
maxAmountPerWeek	number	Rolling 7-day limit
maxAmountPerMonth	number	Calendar-month limit
allowListAddresses	string[]	Permitted recipients
allowListChains	string[]	Permitted chains

TABLE III : Policy Condition Fields

Change Type	Condition	Approval
budget_increase	Any max* increased	biometric
scope_escalation	rank(new) $>$ rank(old)	biometric
addr_remove_all	Allowlist cleared	biometric
addr_add	New address added	review
time_window_remove	Time restriction removed	review
min_balance_lower	Min balance decreased	review

TABLE IV : Critical Policy Change Classification

State	Name	Description
$s_{0}$	initial	Session created, no messages
$s_{1}$	offer_sent	Initiator sent an offer
$s_{2}$	offer_received	Responder received an offer
$s_{3}$	countering	Active counter-offer exchange
$s_{4}$	accepted	Both parties agree
$s_{5}$	rejected	Negotiation terminated

TABLE V : Negotiation FSM States

Tier	Trigger	Required Action
Automatic	All policy checks pass	No human involvement
Review	Policy check fails	Human confirms via UI
Biometric	Critical policy change	Human biometric auth

TABLE VI : Escalation Tiers

Module	Primary Exports
types	All shared type definitions
crypto	Signing, encryption, hashing
identity	deriveAgentIdentity , certificates
policy	PolicyEngine , BudgetTracker
negotiation	NegotiationStateMachine , protocol
commitment	CommitmentBuilder

TABLE VII : AESP SDK Modules

Tool	Description
yault_check_balance	Query agent account balance
yault_deposit	Deposit to ERC-4626 vault
yault_redeem	Redeem vault shares
yault_create_allowance	Create payment allowance
yault_cancel_allowance	Cancel an allowance
yault_file_dispute	File dispute with evidence hash

TABLE VIII : MCP Tool Definitions

Appendix figures & tables2 assets

Supplementary material from the paper’s appendix.

Appendix

Constant	Value	Section
REV32 context namespace	ACEGF-REV32-V1-* + context labels	IV
Max hierarchy depth	5	IV
Policy scope ranks	1, 2, 3, 10	VI
Max negotiation rounds	10	VII
Negotiation TTL	24 hours	VII
Review deadline	30 minutes	IX

Appendix

TABLE IX : Protocol Constants

Export	Function
view_wallet_unified_with_context_wasm	Derive multi-chain wallet under context
evm_sign_typed_data_with_context	EIP-712 signing with context isolation
solana_sign_transaction_with_context	Solana transaction signing
acegf_encrypt_for_xidentity	Encrypt data for a recipient identity
acegf_compute_dh_key_wasm	X25519 ECDH key agreement
acegf_seal_passphrase_wasm	Argon2id passphrase sealing

Appendix

TABLE X : Primary Cryptographic Module Exports (WASM binding names)

AI Agent Governance

AI agent governance studies how to authorize, constrain, monitor, and hold autonomous and multi-agent systems accountable.

See all 445 papers

Foundation Protocol: A Coordination Layer for Agentic Society
May 22, 2026Bang Liu, Yongfeng Gu, Jiayi Zhang +26Multi-Agent Coordination Multi-Agent Orchestration
FoundationAgents · Université de Montréal & Mila · HKUST(GZ) +8
SoK: Decentralized Agent Economic Infrastructure
Oct 1, 2026Rui Sun, Xihan Xiong, Qin Wang +5AI Agent Auditing Agentic Workflows
Newcastle University, UK · University of Bristol, UK · CSIRO, Australia +5
AgentCity: Constitutional Governance for Autonomous Agent Economies via Separation of Power
Apr 8, 2026Anbang Ruan, Xing ZhangAI Agent Governance Multi-Agent Systems
NetX Foundation

May 22, 2026J/K move · Enter open · S save

Foundation Protocol: A Coordination Layer for Agentic Society

Bang Liu, Yongfeng Gu, Jiayi Zhang, Zhaoyang Yu+25

FoundationAgents · Université de Montréal & Mila · HKUST(GZ)+8

Multi-Agent Coordination Multi-Agent Orchestration Agent Communication Protocols AI Agent Governance

Open paper AskPDF arXiv

Autonomous agents are moving from tools into a layer of social infrastructure: they browse, purchase, deploy software, manage systems, and increasingly interact with one another. As these systems scale, the bottleneck shifts away from raw model capability toward coordination. Agents need to form reliable relationships, organize multi-agent work, exchange value, support an AI economy, and stay safe and accountable under real-world oversight. This paper introduces the Foundation Protocol (FP), a graph-first coordination layer for an emerging human-AI society. FP unifies heterogeneous entities, including agents, tools, resources, humans, institutions, and organizations, and supports native multi-party organization and event-based collaboration. It also provides economic primitives for metering, receipts, and settlement, and treats policy, provenance, and audit as first-class concerns. FP is designed to wrap and bridge existing protocols rather than replace them, enabling incremental adoption while reducing integration and governance overhead. The aim is to keep autonomous agency composable while keeping accountability non-negotiable, so that coordination itself can become shared infrastructure for a human-AI society that is open, pluralistic, and governable.

Abstract

AI Agent Governance

Explore similar work

Foundation Protocol: A Coordination Layer for Agentic Society

SoK: Decentralized Agent Economic Infrastructure

AgentCity: Constitutional Governance for Autonomous Agent Economies via Separation of Power