Evaluation, Guardrails, and Going to Production
Explore the essential practices for moving an LLM application from a prototype to a production-ready system
In our previous lessons, we have assembled a powerful architectural framework. We know how to select the right tools to build a functional LLM-powered application. The final step in our journey is to adopt a production mindset. How do we demonstrate that our application is of high quality? How do we secure it from misuse? And what must we monitor once it is live? This lesson focuses on transitioning from a developer’s sandbox to a production-ready system.
Moving from “it works” to “we can prove it”
The first pillar of a production system is evaluation. This is the process of systematically and objectively measuring the quality of our LLM’s responses. The goal is to move beyond anecdotal “it seems to work” feelings to data-driven proof of quality. Objective evaluation is essential for:
Comparing changes: Proving that a new prompt, RAG strategy, or model is actually better than the last one.
Preventing regressions: Ensuring that a new feature doesn’t accidentally degrade performance on a task the application used to handle well.
Building trust: Providing concrete metrics on the application’s accuracy and ...