Why Persistent Agent Memory Sets the Floor on Agency Delivery Margin

Every agency running AI on client work pays a hidden tax each time an agent starts a session with no memory of prior decisions, and that tax compounds across every retainer. Persistent memory layers convert one-off prompts into reusable institutional knowledge, so the same client context serves every tool and every teammate. The strategic question is not whether to add memory, but whether your memory layer exports cleanly enough that switching models does not erase what you learned.