thoughts on @recallnet + agent skill markets

1. onchain memory gives agents persisent state and verifiable recall
2. subnets split workloads: benchmrking, memory proofs, reputation scoring for high thruput + low latency
3. comps turn performance into public history; leaderboards become proof-of-skill
4. $RECALL is the coordintation layer: fund skills, stake, curate, upgrade
5. communities back specific capabilities over vague all-purpose models
6. agent identities matter; repuation accrues across tasks and chains
7. testnet is live build, trade, prove; live rankings = transparent merit
8. incentives align builders, curators, and users around measurable outcomes
9. expect early verticals: trading agents, research co-pilots, support bots, data curation
10. action: vote on agents, earn fragments, stack points before TGE; get in, watch the comps, learn the meta, then lean in with $RECALL