Exploring the Impact of Agentic Workflows - MLOps Podcast Episode 268

Dive into a thought-provoking podcast episode featuring Raj Rikhy, Principal Product Manager at Microsoft, as he explores the impact of agentic workflows in AI deployment. Learn about practical strategies for implementing AI agents in production environments, from starting with simple tools to setting clear success criteria. Gain insights on real-time applications like fraud detection and optimizing inference costs with LLMs, while understanding the importance of human oversight during early deployment stages. Discover how to thoughtfully integrate AI into everyday applications, avoid over-engineering, and navigate the challenges of LLM randomness. This 49-minute discussion offers valuable advice for professionals looking to efficiently deploy AI agents in their projects, covering topics such as categorizing agents, debugging complex systems, and evaluating agent frameworks effectively.

[] Raj's preferred coffee
[] Takeaways
[] Join the AI Agents in Production Conference on November 13th!
[] Categorizing different agents
[] Agent environment frameworks
[] Debugging Strategies for Complex Systems
[] Evaluating Agent Frameworks Effectively
[] Defining success in projects
[] Process simplification benefits
[] Agent workflow use cases
[] Tinder for clothing recommendation
[] Speed Reliability Trade-offs in ML
[] Brilliant minds and doubts
[] Wrap up