The Autoresearch track — automated AI research, verifiers, memory harnesses for long-running research agents, and multi-agent research villages.
Accessible with the Engineering pass and above.
As AI agents take on increasingly complex development tasks, the critical challenge has shifted from generation to verification. Hallucination is not a temporary bug. Evidence suggests that as models grow more capable, failures become more frequent and more convincing, making cognitive surrender among human reviewers an acute risk. This talk introduces a three-stage discipline for responsible agentic development, Guide, Verify, Solve, and argues that rigorous verification infrastructure is both a safety requirement and a competitive advantage. Counterintuitively, code quality matters more in an agentic world: clean, low-complexity codebases make agents faster, cheaper, and more reliable, while technical debt compounds at machine speed.