Everyone talks about $OPEN's Proof of Attribution. Fair. But I keep thinking about the three tools sitting underneath it that most people scroll past.
Datanets are community-owned datasets with verifiable provenance anyone can contribute, anyone can build on them. ModelFactory lets you fine-tune AI models without writing a single line of code. OpenLoRA deploys thousands of fine-tuned models on a single GPU, cutting infrastructure costs by a number that sounds made up until you look at it twice.
Together these aren't features. They're a full builder pipeline. Data in, trained model out, deployed at scale all on-chain, all with attribution embedded at every step.
The projects that win infrastructure bets usually aren't the ones with the best story. They're the ones developers actually stay on. The tooling has to be good enough that leaving costs more than staying.
That's what I'm evaluating with OpenLedger right now. The narrative is clear. The question is whether the developer experience matches it. That answer comes from usage numbers, not whitepapers.
Still watching the on-chain activity closely.