When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale.
In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation metrics for at-scale production guardrails. He will also share how they treated prompts as version-controlled code, built robust tests for every component using those prompts, and created a CI/CD pipeline that ensured a high-confidence one-click production deployment.
Through this real-world case study, you’ll walk away with practical, battle-tested techniques you can immediately apply to your own LLM-powered SaaS solutions!
You will learn:
- How to apply proven techniques that ensure LLM outputs remain reliable and consistent at scale 🎯
- Why seeded testing (with temperature 0) is crucial for reproducibility and quick customer feedback iterations, and how to introduce variations to simulate real-world inputs you will face in production 🚀
- Why Ben and his team avoided using LLM-based evaluations for determining accuracy in production, and what they implemented instead 💡
- How to harness an iterative, test-driven approach—combined with human oversight—to drive continuous accuracy improvements 🛠
Register today to save your seat for this exciting webinar!
📆 April 9th, 2025 at 11:00 AM PST, 2:00 PM EST, 7:00 PM BST
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