Abstract
Abstract (Part 27 of 27)
A customer-facing AI agent initiates a two-organization transaction. Organization A authorizes a ledger effect and Organization B authorizes inventory release, subject to A having actually completed its effect. A ledger commit succeeds, but the response is lost. The agent retries, B accepts an old or fabricated receipt, and a customer may be charged twice or an item released without settlement. A second case arises when an external device or payment service times out after receiving an operation whose actual outcome cannot be observed. A third arises when cancellation is described as reversing a previously committed effect. These are different failures: uncertainty of remote observation, missing cross-domain dependency enforcement, and confusion between authority for a new effect and history of a past effect. Cryptographically authenticated messages do not make a distributed transaction globally atomic.
Difference from earlier parts: Earlier embodiments control the joint plan, the freeze, evaluation, next-actor selection, role reconfiguration, selective communication, the next-move passport, Finality Sink enforcement, substitute selection, pending-work escrow, verified phase advancement, actual-outcome feedback, independent evaluator integrity, cross-domain partition recovery, protected session closure, cross-organizational supervisor appointment, independent evaluator appointment, cross-domain trust and policy compatibility, leaderless coordination, self-expiring supervisory authority, dynamic multi-organization membership, and purpose-bound selective evidence. This embodiment specifically controls multi-domain protected execution finality — the native multi-domain effect boundary where each separate resource independently admits an exact authorized operation, required predecessors are verified, partial chains are recoverable, and composite evidence differs from renewed effect authority.
This embodiment (Part 27 of a 27-part series under Indian Patent Application Number 202631131650; full details at https://zenodo.org/records/23940766) coordinates a plurality of independently administered agent-controlled resources without presuming global atomicity. A protected owner-derived manifest identifies every mandatory native effect and its causal prerequisites. Each owning domain separately verifies a phase- and operation-bound authorization at a protected resource gate, records preparation without confusing it with completion, checks current native state and policy at commit, atomically consumes a locally bounded grant with the native effect where supported, and issues an authoritative source receipt. Successor operations are admitted only upon independent verification of required receipts. Transport loss, uncertain external processing, and partial completion are preserved as explicit states; unauthorized retry is blocked until native-source reconciliation. Compensation, if possible, is an independently authorized new effect rather than an assumed rollback. Composite evidence completion requires all authorized mandatory operations, whereas the resulting completion record remains non-executable.
The architecture therefore ensures that multi-domain AI-agent transactions remain independently enforceable at each resource boundary, without treating a lost message, a timeout, or a cancellation request as proof that an effect did or did not occur.
Keywords: multi-agent systems, agentic AI, AI safety, AI governance, multi-domain execution finality, protected execution commitment, conditional effect authorization, fail-closed systems, zero-trust agents, partial-outcome reconciliation, cross-organizational recovery, execution finality, authoritative source receipt, independently controlled recovery, non-global atomicity, unauthorized retry suppression, compensation as new effect, composite evidence completion, resource-side authorization, distributed transaction recovery.
Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Recommended Citation
Das, Sangam Kumar, "AI Agent Safety: A Lost Reply Does Not Mean the Payment Failed", Technical Disclosure Commons, (November 05, 2026)
https://www.tdcommons.org/dpubs_series/12797