Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source

Let's cut through the hype: most AI agents never make it past the demo stage. The gap between a working prototype and a production-grade system comes down to one thing—evaluation. Without reliable metrics, you're guessing at what's working, what needs fixing, and whether your agents are actually improving. You'll learn how to: - Define custom metrics tailored to your use case - Calibrate LLM judges for cost-effective assessments - Track evaluation results over time to measure real progress Whether you're building LLM-powered apps or leading AI teams, you'll leave with actionable tools to move from proof-of-concept to production—with the transparency and reliability enterprises demand.