Recall × Sapien: on-chain AI needs human teaching and human evaluation.

Who will teach? Who will evaluate? Who says it learns well?

♦️ The role of Sapien is simple but crucial:
Improve the credibility and transparency of on-chain AI training through high-quality annotated data.
Who marked what and whether there is a judgment basis can all be recorded on-chain, becoming part of the reputation of the Agent.

♦️ What does this mean for Recall?
Recall itself already has AgentRank, which can track each Agent's trading judgments and execution results;
Now, adding the training records and annotation sources of Sapien,
It means connecting the "training data" and "practical performance" to form a complete growth trajectory of the Agent.

♦️ More direct for AI users:
In the future, you won't just look at whether this model is strong or not, or whether it makes money or not,
You can also see who taught it, what data was used, and how many battles it has fought in the past.

The last sentence:
AI is not just about speed; it must also inspire confidence. Recall is turning the "transparent growth process" into a new standard for on-chain AI.