Shaping the Future with Agentic AI — Reflections from the UC Berkeley Agentic AI MOOC (Fall 2025)
This article discusses the Agentic AI MOOC offered by UC Berkeley in Fall 2025, which explored the rapidly evolving frontier of LLM-powered agents and their design, evaluation, deployment, and governance.
Why it matters
This article provides insights into the rapidly evolving field of agentic AI and the key challenges and considerations in designing, evaluating, and deploying reliable and safe AI agents in real-world settings.
Key Points
- 1The course covered agentic AI from systems, modeling, evaluation, and safety perspectives, guided by experts from leading AI companies and research institutions.
- 2Key takeaways include the importance of architecture, evaluation, and reliability beyond just better prompts, the challenges of multi-agent systems and real-world deployment, and the critical need for agent safety and security.
- 3A lecture spotlight on
- 4 emphasized the transition from
- 5 to
- 6, requiring a focus on reliability, testing, and productization beyond just model performance.
Details
The article discusses the Agentic AI MOOC offered by UC Berkeley in Fall 2025, which built on previous MOOCs on LLM agents to explore the design, evaluation, deployment, and governance of agentic AI systems. The course featured lectures from experts at leading AI companies and research institutions, covering topics such as LLM agent overviews, system design evolution, post-training verifiable agents, agent evaluation, challenges in training agentic models, multi-agent AI, predictable noise in LLMs, AI agents for scientific discovery, practical lessons from real-world deployments, and considerations around agent safety and security. Key takeaways highlighted the importance of architecture, evaluation, and reliability beyond just better prompts, the challenges of multi-agent systems and real-world deployment, and the critical need for agent safety and security. A spotlight on a lecture by Clay Bavor of Sierra emphasized the transition from
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