The State of Execution Harnesses for Agentic Payments

The seven-layer agentic payments stack

We identify seven layers that together carry an agentic payment from an adaptive goal to deterministic movement of value. Each layer owns a distinct responsibility, and no single protocol, wallet, runtime, or rail represents the whole system.

Reading downward, agent surfaces originate demand; runtimes maintain the task; domain execution converts a plan into concrete actions; wallets and mandates control authority; payment protocols coordinate acceptance; funding systems supply value; and settlement rails provide finality. Trust, security, compliance, observability, and reconciliation cut horizontally across all seven layers.

Figure 1Seven layers from adaptive demand to deterministic settlement

01

Agent surfaces and vertical applications

Own the user or business workflow; capture goals, context, preferences, and consent

ChatGPTGeminiAmazon RufusPayPalBankrVirtualspartner-built agent apps

02

Agent runtime and orchestration

Run the model loop, memory, tools, scheduling, retries, state, background work, and multi-step coordination

Aomi LabsBankrCoinbase AgentKitGOATElizaOSVirtuals GAMELangChainCrewAI

03

Domain execution and transaction construction

Translate a plan into an exact API call, order, contract invocation, or transaction batch; simulate and reconcile the result

Aomi Labs1inchdeBridgeUniswapKrakenCrossmintexchanges

04

Identity, mandates, wallets, and signing

Prove who the agent represents, define what it may do, protect credentials, and decide whether to sign

AP2VisaMastercardCoinbaseMetaMaskOKXCirclePrivyTurnkeySafeFireblocks

05

Payment coordination and acceptance protocols

Describe price, accepted methods, required proof, and how the service is delivered

x402MPPACPUCP

06

Money, funding, and treasury infrastructure

Supply stable value, bridge fiat and crypto, manage balances and liquidity, and reconcile books

CircleTetherPayPalStripeBridgeCoinbaseCrossmintMoonPayBVNKZero Hashbanks

07

Settlement rails

Final, deterministic movement and record of value

BaseSolanaEthereum L2sPolygonTempoArcVisaMastercardbank rails

Horizontal assurancesimulationcompliancethreat detectionobservabilityreconciliationdisputes

This stack is the paper's starting point. It separates adjacent markets before asking where responsibility is still incomplete. The gap appears between adaptive planning and financial authority: someone must construct, test, execute, recover, and reconcile the action across the other layers. Section 5 names that missing category only after the market evidence and boundaries are clear.

Scope, definitions, and methodology

2.1 What counts as an agentic payment?

A conventional automated payment follows predetermined code: send a fixed amount on a fixed date. An agentic payment contains an adaptive decision step: find a compliant supplier under a budget, choose a route, determine the amount or timing, and pay. The agent may decide what, when, where, or how much within a delegated mandate.

A complete agentic payment requires more than a checkout button. It runs through seven stages, and the stages do not share the same character: the first three are adaptive and reversible, while the last four must be deterministic.

Agentic payments overlap with two larger categories but are not synonymous with either. Agentic commerce includes discovery, comparison, ordering, fulfillment, returns, and support; payment is one stage. Agentic finance includes trading, treasury, hedging, lending, compliance, and portfolio operations; not every financial action is a payment. A crypto agent that only analyzes or communicates becomes a payment actor only when it can request or authorize value transfer.

2.2 The probabilistic–deterministic boundary

The IMF's 2026 model separates agentic payments into intent and orchestration, control and authorization, and settlement.^[1]That separation captures the core safety property: an agent may reason, search, negotiate, and propose, but a deterministic boundary must decide whether a concrete request may use financial authority, and a deterministic rail must settle without reinterpreting the instruction. This paper expands the commercial and technical space between those three institutional layers.

2.3 Research method

The analysis combines official protocol specifications, first-party product documentation, independent onchain evidence, and Aomi Labs' operating perspective. The market taxonomy, player map, and use-case maturity assessments extend an earlier ecosystem deep dive published by Aomi Labs Research in August 2026, which remains the underlying survey for this paper.^[17] Product capabilities are treated as vendor claims unless independently demonstrated. Transaction activity is evidence of technical use, not automatically evidence of durable or autonomous demand. The market taxonomy is analytical: firms often span multiple layers, and placement reflects the function being evaluated rather than the company as a whole.

The seven-layer ecosystem

The seven-layer model becomes useful when it assigns each function to the actors that actually perform it. A protocol, wallet, runtime, funding provider, or settlement rail may span several layers, but no one label should be mistaken for the whole system.

Layer 1 — Agent surfaces and vertical applications

Agent surfaces own the user or business workflow and originate demand. OpenAI and Stripe's Agentic Commerce Protocol, for example, allows a conversational surface to pass a structured order and a scoped payment token to a merchant while the merchant retains responsibility for acceptance and fulfillment.^[9] Crypto surfaces go further. Bankr combines a conversational agent, wallet, cross-chain trading, scheduled automations, and x402 service access in one runtime.^[16] Virtuals' EconomyOS gives agents identity, wallets, permissions, jobs, and programmable capital, with its own Agent Commerce Protocol for inter-agent work.^[25] That Virtuals “ACP” is a different specification from the Stripe and OpenAI Agentic Commerce Protocol despite the shared acronym.

Layer 2 — Agent runtime and orchestration

Beneath the surface, runtimes own sessions, memory, tools, retries, background work, and multistep state. Toolkits and runtimes should be distinguished: Coinbase describes AgentKit as a modular, framework- and wallet-agnostic system of action providers and wallet providers.^[6] A stateful execution runtime goes further by owning the path to completion and the evidence left behind.

Layer 3 — Domain execution and transaction construction

Domain-execution providers then supply the exact mechanics of a swap, bridge, order, checkout, staking operation, or protocol call. This is where generic tool calling becomes domain execution: ABI handling, route selection, calldata construction, balance and allowance checks, slippage, gas, bridge state, failure semantics, and post-execution verification. Vertical providers are strong while the action stays inside their domain — 1inch Business MCP for swaps and portfolios, deBridge MCP for cross-chain routing, Uniswap skills for liquidity workflows, Kraken CLI and MCP for exchange trading and staking, Crossmint for agentic checkout and merchant-of-record flows. The unresolved question is whether execution consolidates into broad runtimes or remains a federation of protocol-owned tools. The likely answer is both: broad runtimes orchestrate, while specialists own routes, liquidity, inventory, and domain-specific guarantees.

Layer 4 — Identity, mandates, wallets, and signing

Layer four is becoming the center of competition. Google's AP2 binds an agent's action to cryptographically verifiable mandates describing identity, scope, limits, and conditions, and includes an x402 extension for stablecoin payments.^[4]Visa's Trusted Agent Protocol helps a merchant recognize an approved agent and verify cryptographically signed commerce intent; Mastercard Agent Pay extends tokenized credentials and network controls to agents.^[10][11] Crypto wallets are evolving from key stores into programmable authorization systems with:

• isolated keys, or MPC and TEE signing
• per-transaction and cumulative spend limits
• merchant, protocol, contract, function, asset, and chain allowlists
• session and time-bound permissions
• human escalation above thresholds
• audit logs, revocation, and emergency stops
• simulation, threat scanning, and compliance screening

The crypto-native wallet models are diverging rather than converging. Coinbase Agentic Wallets isolate keys in a TEE and add session and transaction caps, KYT screening, x402, and gasless trading on Base.^[12] MetaMask Agent Wallet stays self-custodial and makes simulation mandatory, with Blockaid scanning, MEV protection, spend limits, allowlists, and human 2FA escalation.^[13] OKX pairs TEE-protected keys and risk scoring with gas-free X Layer use across nearly twenty chains.^[22] Privy provides server wallets and scoped browser authorization while Turnkey evaluates signing policies inside secure enclaves.^[14][15] MoonPay's Open Wallet Standard proposes an open agent-to-wallet interface with a local encrypted vault and multichain signing.^[24] Crossmint and Circle instead sell the full stack: wallets, policies, funding, payment protocols, and service access in one integration.^[23][19]

Layer 5 — Payment coordination and acceptance protocols

Layer five tells an agent what is for sale, how much it costs, which payment methods are accepted, what proof is required, and how the service is delivered. These protocol families are frequently conflated and should not be.

The distinction in the last row matters most. MCP and A2A expose tools and coordinate agents; payment can be layered onto their calls, but they are not payment rails. Within machine payments, x402 facilitators verify signed payloads and submit settlement without custodying funds.^[20] MPP, co-authored by Stripe and Tempo, coordinates payment for APIs, MCP tools, and HTTP endpoints and supports microtransactions and recurring charges, reaching stablecoins, cards, and buy-now-pay-later methods while preserving tax, fraud, reporting, refunds, and normal merchant payouts.^[3] ACP and UCP address commerce rather than raw payment: ACP lets an agent surface pass a structured order and scoped token to a merchant who remains responsible for acceptance, tax, fulfillment, and returns, while UCP standardizes discovery and checkout across surfaces. The competitive boundary is whether merchants adopt an open protocol directly or rely on an orchestrator — Stripe, Coinbase, Circle, Crossmint, Bankr — to hide the protocol complexity.

Layer 6 — Money, funding, and treasury infrastructure

Stablecoins are the default crypto asset for agentic payments because agents need predictable unit pricing, 24/7 availability, global reach, programmability, and settlement smaller than card-network minimum economics. Circle claims USDC represents 99.8% of x402 transaction value and has built agent wallets, nanopayments, a CLI, skills, and a service marketplace around that position.^[19] Treat that percentage as a current vendor-reported ecosystem statistic, not a permanent market share.

Funding remains the bottleneck. An agent wallet without reliable onramps, treasury policies, gas sponsorship, balance monitoring, FX, and accounting is only a demo — which is why full-stack providers keep bundling these functions rather than leaving customers to assemble separate wallet, onramp, facilitator, and compliance vendors.

Layer 7 — Settlement rails

At layer seven, different rails win different jobs. Base offers cheap EVM settlement with x402 and Coinbase distribution; Solana offers throughput and low fees with strong stablecoin and marketplace activity; Tempo is payment-optimized and the native home for MPP sessions and streaming payments;^[27] Ethereum and its L2s hold the deepest programmable-finance and account-abstraction ecosystem; card networks retain unmatched merchant acceptance, disputes, consumer protection, and issuer controls; bank rails carry regulated account-to-account flows, payroll, and fiat-native settlement. The likely endpoint is cross-rail orchestration, not a crypto-only or card-only world.

3.1 Horizontal assurance across all seven layers

Trust, security, compliance, and observability do not sit at one level. They cut across all seven, and the controls divide cleanly by when they run.

Chainalysis combines KYT, sanctions screening, fraud intelligence, and pre-signing threat detection, and argues for auditable autonomy rather than unconstrained automation.^[26] This horizontal layer is likely to become a major standalone market precisely because neither a model nor a wallet can independently validate the entire economic outcome. These responsibilities can be vertically integrated for convenience, but they carry different competencies and liabilities, and mature buyers will require the boundaries to remain inspectable even when one provider bundles several layers.

Emerging service sectors, evidence, and maturity

4.1 Emerging service sectors

Financial agents need more than access to money. To operate beyond demos, they must receive bounded authority, find trustworthy counterparties, execute correctly, choose the right rail, and remain accountable after settlement. Each unresolved need creates a market for specialized infrastructure.

Authority must be both programmable and attributable. Credentials need isolation, mandates must encode scope and limits, and merchants must know which agent is acting for which principal. This creates two related but distinct markets: wallets that control access to money, and identity, mandate, and reputation systems that establish the legitimacy of its use.^[12][14][15]

Markets must also become legible and usable by software. Agents need structured descriptions of services, prices, schemas, and delivery terms; sellers need gateways that abstract verification and settlement. Discovery without reputation becomes spam, while payment without delivery proof invites fraud, so marketplaces will increasingly incorporate attestations, service histories, and escrow.

A valid payment is not necessarily a correct action. Systems must test transaction semantics before signing, verify the resulting state, and select among stablecoin, card, bank, and local rails according to the task's economic and regulatory requirements. This separates execution assurance, which determines what should happen, from payment orchestration, which determines how value should move.

Finally, autonomous spending must close the operational loop. Every balance change, receipt, gas cost, refund, and tax event must map back to an agent, mandate, task, user, and result. When the result is wrong, settlement finality is insufficient; the system still needs proof of delivery, recourse, and a clear allocation of liability.

4.2 Market evidence

Evidence now appears across all eight service sectors, but they are not maturing at the same rate.

Productization is clearest in authority, identity, discovery, and payment access. Coinbase, Circle, MetaMask, Privy, Turnkey, and OKX now offer agent wallets or delegated controls.^{[12][13][14][15][19][22]} Google's AP2, Visa Trusted Agent Protocol, and Mastercard Agent Pay formalize mandates and agent recognition.^[4][10][11] Circle has launched an agent marketplace alongside wallets and nanopayments, while x402 and MPP supply gateway protocols.^[2][3] Usage is material but noisy: Chainalysis measured more than 100 million x402 transactions on Base through Q1 2026, while Solana reports more than 35 million transactions and over $10 million in volume. Speculative activity drove part of the earlier surge, so these figures demonstrate technical reach rather than durable autonomous demand.^[5][18]

Execution and operations are also taking shape. Tenderly offers live-state simulation, Blockaid exposes agent-focused transaction scanning and threat detection, and Crossmint routes cards and stablecoins under common controls.^[31][32][23] Stripe carries MPP payments into existing tax, reporting, accounting, and refund systems.^[3] Evidence weakens after settlement: treasury and reconciliation mostly extend general payment tooling, while Visa and Artemis find no settled way to unwind disputes across chains of agents.^[33] The market is therefore broader than x402: the first six sectors are productizing, while agent-native back-office and recourse remain open categories.

4.3 Use-case maturity

Use cases mature fastest when the purchased object is digital, the price is machine-readable, fulfillment is immediate, and failure is reversible or low value. They mature more slowly as physical fulfillment, regulated advice, custody, credit, cross-border compliance, or ambiguous liability enters the workflow.

This sequence explains crypto's early advantage. Wallets are programmatic accounts; stablecoins provide internet-native value; and blockchains settle globally at machine speed. Those properties are especially valuable for low-value digital services and crypto-native financial actions. They are less decisive in consumer commerce, where merchant reach, refunds, fraud allocation, tax, and fulfillment usually matter more than the novelty of the rail.

The missing execution harness

The seven-layer map reveals a responsibility that the market has not consistently named: carrying an agent's adaptive plan into a concrete, inspectable, and reconciled financial outcome.

General-purpose agents can already reach financial destinations. They can browse documentation, discover a tool, infer its schema, create a payment or transaction, recover from an error, and inspect a receipt. Yet they often do so the way a person travels on foot: one uncertain step at a time, repeatedly paying in reasoning, tokens, latency, and operational risk.

Faster models improve that walk. They do not remove the economic reason to build vehicles. In mature technical systems, repeated integration knowledge, safety checks, and recovery logic move out of general reasoning and into software. The model remains the intelligence; an execution harness carries the known mechanics.

A payment protocol can coordinate a handshake, and a wallet can decide whether to sign. Neither can independently establish that an adaptive financial task was correctly completed.

Consider an instruction to bridge an asset, pay for a service on the destination chain, and return a receipt. The agent must interpret constraints, select a bridge and service, obtain quotes, construct approvals and calls, reason about destination gas, handle changing state, preserve the request reviewed by the signer, recover from a partial bridge, prevent duplicate payment, verify delivery, and reconcile the final balances. A wallet can enforce a spend cap. A simulator can test a concrete transaction. A chain can prove finality. None alone can connect the semantic objective to the whole sequence of evidence.

5.1 Definition

An execution harness is the runtime machinery that converts adaptive intent into bounded, inspectable, and reconcilable financial action. It is more than a toolkit because it owns state, recovery, and completion. It is broader than a policy layer because policy does not construct or reconcile the task. It remains separate from the wallet because the wallet must retain the independent power to refuse.

The harness does not replace the seven payment stages in Figure 2; it decomposes the work inside them. Its responsibilities cover stages one through three, the simulation that precedes the authorization request, and the reconciliation that closes the task. It never owns stage four. Authority stays with the wallet, funding with the balance, and finality with the rail.

5.2 Why better models do not eliminate the category

General models will continue to improve at documentation discovery, schema inference, tool use, and error recovery. That lowers the cost of walking; it does not change the value of a tested route. Mature systems do not ask a model to rediscover stable protocol knowledge, allowance rules, idempotency semantics, receipt formats, or balance assertions on every run. They encode those mechanics and reserve model reasoning for decisions that are genuinely adaptive.

Legal and clinical AI provide an instructive precedent, even though those companies do not necessarily use the term “harness.” Harvey distinguishes individual models from model systems, agents, and workflows. Its legal workflows combine task-specific tools and knowledge sources with structured steps, citation requirements, human review, and evaluations based on completed legal work.^[28] Abridge turns clinical conversations into billable, EHR-integrated notes and actionable outputs, tying drafts back to source information for clinician review.^[29] Hippocratic AI describes a safety process built around output testing, clinical supervision, escalation to human nurses, and cross-validation against real interactions.^[30]

The shared pattern is not simply more domain knowledge. Stable professional mechanics move out of repeated prompting and into software that owns workflow, evidence, review, and evaluation. Financial execution follows the same pattern with a stricter end state: the output can move assets irreversibly. Its domain-specific harness must therefore own transaction construction, simulation, immutable authorization handoff, idempotency, recovery, and reconciliation—not merely produce a more informed financial answer.

The analogy must be applied strictly. A poor vehicle can be slower than walking. A harness that hides failures, constrains a capable model, increases retries, or cannot demonstrate the final state has not earned its abstraction. The relevant comparison is the same athlete on the same course: one model and task set, with and without the harness.

Player map and market structure

Early markets reward full-stack products because developers prefer one API and users prefer one trusted surface. Coinbase, Circle, Crossmint, Stripe, Bankr, and OKX therefore span layers. Yet specialization is likely to deepen because each layer has a distinct technical competency, distribution advantage, and liability model. Models optimize reasoning; runtimes manage state; wallets control authority; protocols coordinate; issuers manage money; rails provide finality; risk vendors provide independent evidence. As stakes rise, buyers will demand modularity and independent checks.

6.1 Market structure and competitive dynamics

Wallets own the strongest distribution moat. They already control assets, trust, signing, and the gateway to settlement, which gives MetaMask, Coinbase, OKX, Phantom, and institutional custody providers a path upward into agent controls and execution. Runtimes should treat wallets as distribution and authority partners rather than as competitors to displace.

Protocols converge by function, not toward one standard. x402 and MPP overlap in machine payments; ACP and UCP overlap in commerce workflows; AP2, Visa, and Mastercard focus on mandates and trusted agents; MCP and A2A coordinate tools and agents. These can coexist because they solve different parts of the journey. Durable providers will support several protocols while preserving one stable internal authorization and accounting model.

Stablecoins are the crypto wedge, not the whole product. They solve global, programmable, low-value settlement. They do not solve agent identity, merchant acceptance, delivery disputes, refunds, taxes, wallet policy, or safe construction. The market will reward teams that pair stablecoins with those missing layers.

Transaction counts can mislead. The x402 data is promising but should not be presented as pure autonomous-agent adoption. Chainalysis attributes a major Q4 2025 spike to meme-coin pay-to-mint loops and holds that mass adoption remains distant.^[5]

Taken together, these dynamics set the bar for anyone in layers two and three. Payment platforms can move inward from money movement into orchestration; vertical providers can dominate high-frequency domains through route, venue, or inventory depth; general agent frameworks can move downward through wallet and payment plugins. Execution runtimes must therefore prove that they are materially better at generalized completion and evidence, not merely better at exposing transactions to an LLM.

Harness economics and measurement

Model tokens are not the only operational cost, but they reveal the underlying inefficiency. When an agent rereads documentation, reconstructs schemas, reasons through stable allowance mechanics, retries stale routes, or investigates whether a task finished, the system is buying cognition to compensate for missing infrastructure. Harness value comes from moving repeated cognition into software, compressing the failure surface, and making operations legible.

This produces a stricter economic claim than “agents work better with tools.” A useful harness should increase the number of verified outcomes obtained from a fixed model budget. It should also preserve model optionality: operators can improve or replace the model without rebuilding every financial integration and control around it.

7.1 Proposed scorecard

The benchmark should include ordinary success and adversarial state: stale quotes, changed allowances, rejected signatures, insufficient destination gas, partial bridge completion, delayed confirmation, unavailable tools, malicious content, and repeated network requests. A harness is valuable only if its advantage survives these conditions.

Aomi Labs’ thesis

Our thesis at Aomi Labs is that agentic finance will require a distinct execution-harness layer. Our work focuses on its onchain instance: infrastructure that turns agent intent into verified financial execution across payment and non-payment actions.

That work sits primarily in layers two and three: runtime orchestration and domain execution. It encompasses the agent loop, tools, sessions, persistence, and multistep state; translates intent into typed actions and transactions; simulates expected outcomes; and prepares a concrete request for an external signer.^[7][8]Wallets, identity providers, compliance systems, payment protocols, stablecoins, and settlement rails remain integrated components, not the category our work claims.

8.1 Where our work sits

8.2 What the thesis does not claim

We are not proposing a new wallet, stablecoin, payment protocol, facilitator, card network, or settlement chain. “Policy layer” and “transaction firewall” are also too narrow: policy and guards are subsystems inside a broader runtime. The research concerns a generalized execution surface — pay, swap, bridge, lend, stake, trade, deploy, call APIs, and reconcile outcomes.

Figure 7The execution responsibility boundary

DemandIntent

Goal, budget, timing, constraints, desired result

→

aomiExecution runtime

plan · tools · construct · simulate · execute · reconcile

→

AuthorityWallet and mandate

identity, consent, limits, risk, refusal

→

FinalityMoney and rails

stablecoins, cards, banks, chains

8.3 Strategic whitespace implied by the research

1. Protocol-aware execution quality. Typed calls, protocol constraints, fork simulation, balance deltas, and outcome assertions should create measurable leverage over generic tool use.
2. A portable runtime above wallet fragmentation. Support self-custodial, embedded, and institutional wallets rather than betting the runtime on one custody model.
3. Payment-protocol neutrality. Treat x402, MPP, cards, and direct stablecoin transfer as tools selected by app and mandate.
4. Evidence as a product. Record user intent, tool calls, immutable payload, simulation, policy decisions, signer, receipt, and final state as one inspectable chain.
5. Partner-owned distribution. Wallets, protocols, exchanges, fintechs, and partner apps keep the user relationship while our infrastructure supports execution.
6. Benchmark the runtime. Measure task completion, dangerous-proposal block rate, simulation-to-execution consistency, duplicate-broadcast rate, human escalation, and end-state correctness.

8.4 Competitive threats

Four vectors converge on layers two and three. Wallets can move upward: Coinbase, MetaMask, OKX, Circle, Privy, and Turnkey can all add tools and construction above the signing boundary they already own. Payment platforms can move inward: Stripe and Crossmint can add orchestration around money movement. Vertical execution providers — Bankr, 1inch, deBridge, Uniswap, and the exchanges — may own high-frequency domains outright. And general agent frameworks can move downward, adding wallets and payment plugins to existing distribution. The Aomi Labs thesis therefore depends on specialized infrastructure being materially better at generalized, verified onchain execution than a wallet assistant or a protocol-specific skill.

Risks, outlook, and conclusion

9.1 Unresolved risks

The open problems are not evenly distributed across the stack, and few of them are solved by any single layer.

Liability deserves separate emphasis because it cuts across all of them. It remains fragmented across user, model provider, runtime, tool, wallet, facilitator, merchant, issuer, and settlement rail, and regulatory classification can change with custody, payment initiation, brokerage, advice, sanctions exposure, or jurisdiction. A technically successful design may still fail if no participant clearly owns refunds, disputes, exceptions, and loss.

9.2 Outlook

Over the next twelve months, wallets are likely to make agent-specific policies, escalation, and transaction security default features. x402 and MPP will compete for paid APIs while processors support both. ACP, UCP, and AP2 integrations will expand across merchant systems, and stablecoin issuers will bundle wallets, discovery, compliance, and nanopayments. DeFi agents will remain valuable but risk-tolerant early adopters. Independent security and observability will become enterprise requirements.

Over a two-to-three-year horizon, agents should carry portable mandates and credentials across surfaces; service marketplaces should expose machine-readable price, capability, reputation, and delivery guarantees; cross-rail routers should choose among stablecoin, card, bank, and local rails automatically; and agent treasury and accounting should become standard enterprise infrastructure. Durable systems will separate proposer, executor, authorizer, and settler while linking all four through evidence. At that point “agentic payments” stops being a category and becomes a capability embedded in runtimes, wallets, commerce platforms, and financial software.

9.3 A decision checklist for any player

The taxonomy in this paper is only useful if it can place a real company quickly. Ten questions do most of that work, and the last two are usually the most revealing.

1. Who owns the user or task? Surface and application.
2. Who runs the model loop and task state? Runtime and orchestration.
3. Who constructs the exact order or transaction? Domain execution.
4. Who holds the credential and can refuse to sign? Wallet and authorization.
5. Who defines the payment request and acceptance handshake? Protocol or orchestrator.
6. Who supplies and manages the money? Stablecoin, account, card, onramp, treasury.
7. Who provides finality? Chain, card network, or bank rail.
8. Who independently verifies risk and records evidence? Trust and compliance.
9. Who bears loss, refund, dispute, and regulatory liability? Often the clearest layer indicator.
10. Can each layer be replaced independently? If not, vertical integration creates convenience and lock-in.

9.4 Conclusion

Agentic payments will not mature simply because models receive wallets. They will mature when software can form an adaptive intent, turn it into a valid and inspectable action, operate within delegated authority, settle through the appropriate rail, and prove that the requested outcome occurred. Better models will become better athletes. Execution harnesses are the vehicles that let the same athlete travel farther, faster, and with evidence.