Self-Improving AI Agents Aren’t One Model. They’re a Feedback Loop.
Stanford’s CS329A shows why self-improving AI is less about one smarter model than a closed loop of search, verification, tools, learning, and long-horizon evaluation.
Stanford’s CS329A shows why self-improving AI is less about one smarter model than a closed loop of search, verification, tools, learning, and long-horizon evaluation.
When AI makes one stage of work dramatically faster, the rest of the system does not automatically keep up. Startups, government services, and AI research show what happens next.