Abstract
Abstract (Part 15 of 27)
Agent A and Agent B jointly commit to a plan in which Phase 1 includes a database change and a later external disbursement. The local database update can be committed with its receipt inside a transaction, but the external call may time out, may have been staged but not delivered, or may have been accepted remotely without confirmed completion. An agent may still attempt Phase 2 because a tool return says success or because a previous model answer described Phase 1 as completed. An ordinary audit log, initial OAuth-style authorization, or orchestrator return code does not establish that the specified effect occurred, nor that all phase prerequisites have been authoritatively verified.
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, and pending-work escrow. This embodiment specifically controls phased execution with protected completion receipts — converting a committed plan into bounded, verified phases rather than assuming that an authorized call has been successfully performed.
This embodiment (Part 15 of a 27-part series under Indian Patent Application Number 202631131650; full details at https://zenodo.org/records/23940766) separates five distinct steps: permission for an exact task, protected locally committed effect or externally verified outcome, phase-completion evidence aggregation, independent evaluator review and participating-owner approval, and the protected phase-boundary state transition. Source-authenticated completion receipts classify outcome truth (completed, partial, unknown, or denied). Phase advancement is withheld until the required evidence is independently verified. No tool return, model statement, or prior authorization alone opens the next phase.
The architecture therefore turns multi-agent plans into evidence-based phases across independently governed systems, ensuring that later phases cannot begin on unverified claims that earlier effects succeeded.
Keywords: multi-agent systems, agentic AI, AI safety, AI governance, phased execution, protected completion receipts, verified phase advancement, outcome-truth classification, fail-closed systems, zero-trust agents, source-authenticated receipts, phase-boundary control, cross-organizational collaboration, execution finality, evidence-based phase closure, non-assumption of success, independently verified phase transition, protected phase scheduler, external-effect outcome verification, multi-phase plan enforcement.
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Recommended Citation
Das, Sangam Kumar, "AI Agent Safety: Don’t Start the Next Phase Until the Last One Is Proven", Technical Disclosure Commons, (November 05, 2026)
https://www.tdcommons.org/dpubs_series/12785