The part that stayed with me from the OpenLedger $OPEN #OpenLedger @OpenLedger task was how the two beneficiary groups — AI builders and data contributors — are on very different timelines, even though the pitch presents them as arriving together. Builders get immediate utility: ModelFactory works today, no-code fine-tuning works today, OpenLoRA deploys models without heavy infrastructure overhead. That value is front-loaded and doesn't depend on the Proof of Attribution flywheel spinning. Contributors are different. Their rewards only materialize when models built on their Datanets are actually queried at scale — but DeFiLlama shows annual protocol revenue sitting at $693K with fees down 23% in the past week, which suggests inference demand is still light. The design is coherent; the sequencing just matters more than the framing admits. Builders come in, build on the infrastructure, models sit waiting. Contributors have already uploaded, already contributed, already earned their attribution records… and are now waiting on demand that hasn't fully arrived yet. Whether that gap closes depends entirely on whether the builders who showed up actually ship products people use.