The AI Concierge: institutional design for recording, reconnection, and mutual growth at SPring-8-II

Synchrotron experiments generate not only data but also a continuous stream of tacit branching judgments: which sample to continue with, when to reprioritize batch groups, how to interpret ambiguous results. These judgments are rarely recorded, because the same documents that could capture them simultaneously serve as instruments of performance evaluation. This paper proposes a minimum operational specification (MVIS) for the AI Concierge, an institutional support layer comprising eight elements: capture pathway, AI-generated candidate draft, human confirmation, tier assignment, knowledge-steward review, consent and notice, provenance, and reconnection output. The structural prerequisite is the institutional separation of an accountability layer (proposals and reports) from a knowledge layer (decision branches, negative results, interpretive uncertainty). The MVIS is grounded in two worked examples drawn from actual beam-time branching episodes at BL13XU, with mandatory content-type labels distinguishing source-supported facts from illustrative content and unavailable data. A boundary comparison against well kept logbooks, electronic laboratory notebooks, metadata catalogues, FAIR infrastructure, and retrieval-augmented generation systems clarifies what the AI Concierge adds and what it does not claim to replace. Governance rules for role separation, re-identification risk management, and staff contribution evaluation-decoupled from protected-record content and count-are specified alongside the specification itself.