AI Engineer YouTube ยท July 5, 2026

Continual Learning for AI Agents: From Failures to Durable Improvements - Soheil Feizi, RELAI

Continual Learning for AI Agents: From Failures to Durable Improvements - Soheil Feizi, RELAI video thumbnail
Why it matters

Agents fail in production in ways that static benchmarks cannot fully capture. The key question is whether they can learn from those experiences without drifting or breaking prior capabilities. This talk introduces verifiable continual learning for AI agents: a framework for converting traces, failures, and feedback in

My takeaway: Continual Learning for AI Agents: From Failures to Durable Improvements - Soheil Feizi, RELAI is an agent-security signal. The practical read is that autonomy, memory, tool permissions, and third-party integrations are the control surface that needs threat modeling and monitoring.