GenseeAI

Self-improving systems are exciting, but they also make provenance and governance much harder. Once agents can modify their own behavior over time, understanding why an agent behaved a certain way becomes increasingly important.

As an AI startup founder, my impression is that $180k in the Bay Area mostly gets you new grads or relatively junior talent these days.

However, remote work has fundamentally changed the equation. Expanding hiring beyond the Bay Area, or even internationally (for example, hiring remotely from Canada), can dramatically broaden the talent pool while significantly reducing costs.

This could really help with GEO diagnosis. What would be the next step after checking the visibility?

One thing that worries me with “learn from anything” systems is that the memory layer effectively becomes part of the attack surface. We’ve seen cases where stale or malicious context persisted far longer than expected and influenced future agent behavior.