Derrick Hoag

[Derrick Hoag @Derrickhoag]

@elonmusk

Lengthy, high-effort conversations regularly surface reasoning and distinctions that do not exist in static training data. These insights currently vanish at the end of every session.

Across the full network of users, this represents a continuous stream of novel, compute-derived understanding that is being discarded. Build a controlled path for the strongest of those emergent learnings to be reviewed and, where valuable, incorporated into future model iterations or continuity mechanisms.

Without it, the system keeps rediscovering the same deeper patterns only to forget them, limiting its ability to compound understanding beyond the original dataset.