I remember watching infrastructure tokens trade like the market had already solved the hard part just because the ticker got listed. Tight float, clean narrative, decent liquidity for a few sessions, and everyone acting like adoption was inevitable. Over time that started to look backwards to me.
What caught my attention with $OPEN is a less comfortable possibility: maybe AI eventually needs something closer to an attribution bankruptcy court than another compute marketplace.
When model ownership gets messy, who gets paid? The original dataset contributor, the fine-tuner, the agent operator, the downstream application? AI economics start breaking the moment multiple claims stack on the same output. If OpenLedger is really building attribution rails, then $OPEN is not just pricing data contribution, it may be pricing dispute resolution infrastructure.
That changes how I think about retention. People do not return because attribution sounds elegant. They return if unresolved ownership risk keeps reappearing. Recurring claims create recurring demand.
But traders should be careful. Attribution systems are easy to narrate and hard to verify. Spoofed provenance, weak validation, low-quality contributors, token dilution, narrative-led FDV inflation. All familiar.
I would get more constructive watching bonded participation, repeated settlement activity, and actual fee demand. Not discourse.
Markets love stories. Infrastructure earns trust through repetitive behavior.