AI Self-Improvement Techniques - Training, Evaluation, and Optimization for Real-World Performance

Explore advanced AI agent development through this 19-minute conference talk that demonstrates how to train, evaluate, and optimize AI systems for enhanced real-world performance. Learn practical techniques including system prompt updates and meta-prompting strategies that improve agent memory and adaptability. Discover how continuous feedback loops and contextual optimization can dramatically boost the efficiency and effectiveness of even smaller AI models in production environments. Gain insights from real-world implementations at major companies like Spotify and Uber, understanding common development challenges and proven solutions for creating more capable AI agents through self-improvement methodologies.