Make a Lightweight RAG Evaluation Table
Explore how to design and use a lightweight evaluation table to systematically improve retrieval-augmented generation (RAG) workflows. Learn to record queries, results, and changes that tie pipeline behavior to specific fixes, ensuring grounded answers and appropriate refusals in AI support systems.
An evaluation table is the smallest operating artifact that turns a RAG-enabled support workflow into something we can improve on purpose. Each row records what we asked, what the retrieval step returned, what the draft answered, and the next change we made. The point is not a score; it is evidence that ties pipeline behavior to a specific fix. This lesson defines that judgment precisely, walks through filling one row end to end, and builds a small but deliberately varied question set to run it against.
This table also forces a key distinction. A retrieval hit means the right policy chunk showed up in the top results. Grounded means the draft’s claims are supported by text in those retrieved chunks, or the draft refuses when the policy text does not support an answer. ...