Many teams building Large Language Model (LLM) apps get stuck in "Proof-of-Concept Purgatory." They build flashy demos with tools like ChatGPT, OpenAI API, or LlamaIndex—but these quickly gather dust as the systems hallucinate, become inconsistent, or fail to scale.
There’s a better way: Evaluation-Driven Development (EDD).
Turn your LLM demo into a system that scales, debugs, and improves over time.—using proven software engineering workflows adapted for modern AI.
LLM-powered apps aren’t like traditional software. They’re non-deterministic, data-sensitive, and constantly evolving. Building them requires a new approach—one grounded in testing, monitoring, and iteration from day one.
In this free, concise 10-email course, you’ll learn how to:
Delivered clearly and practically—one email at a time.
This Evaluation-Driven Development framework has been battle-tested with teams at Netflix, Amazon, Meta, Ford, TikTok, Adobe, and the US Air Force—helping them escape endless iteration and launch production-grade LLM systems.
Whether you're shipping your first LLM feature or scaling a Generative AI product, this course will sharpen your approach.
Hugo Bowne-Anderson has taught 100+ engineers at companies like Netflix, Amazon, and the US Air Force how to build and deploy reliable LLM apps—combining software engineering principles with the realities of modern AI.
You’ll get the first email right away, and one every day after that.
No fluff—just real strategies for building LLM apps that work in the real world.
Sign up below to start your free 10-email course.