Most people still think AI agents fail because models aren’t smart enough, but I’m starting to think the bigger bottleneck is coordination infrastructure. That’s why @OpenLedger ’s AutoClow direction caught my attention. What’s quietly changing is the shift from manually operated AI workflows toward automated on-chain coordination between agents, datasets, and execution layers. I’ve been watching how more activity inside decentralized AI ecosystems depends on repetitive verification, attribution, and settlement tasks that humans simply can’t scale efficiently. The market keeps focusing on flashy AI outputs, while infrastructure handling autonomous interaction may end up capturing the real long-term value. If #OpenLedger can make agent coordination smoother through automation layers tied to attribution and execution, $OPEN could become connected to machine-driven network activity instead of purely speculative trading cycles. That changes the economics entirely. This isn’t about launching smarter AI agents. It’s about building the coordination rails autonomous AI economies may eventually rely on.

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