Practical AI
The most technical AI podcast that stays accessible. Great for practitioners.
3 episodes curated
Episodes
Building Reliable AI Workflows That Don't Break
Chris Benson and Daniel Whitenack discuss practical techniques for building AI workflows that maintain quality over time. Error handling, validation, human oversight patterns, and monitoring strategies for production AI systems.
RAG in Production: Lessons from Real Deployments
Retrieval-Augmented Generation is the most important AI architecture pattern for enterprises. This episode covers real production RAG systems — what breaks, how to measure quality, and the chunking strategies that actually work.
Fine-Tuning vs Prompting: When Each Makes Sense
A practical decision framework for when to fine-tune a model versus optimizing prompts. Includes cost analysis, quality comparison, and the exact scenarios where fine-tuning delivers meaningful improvements over prompt engineering alone.