I’ve spent the last few weeks building and testing a RAG-based workflow for structural novel editing—specifically, trying to use a local LLM setup to analyze a full manuscript (100K+ words, 100+ scenes, multiple POVs) in a way that could meaningfully assist a Draft 1 -> Draft 2 revision.
The idea was not to generate prose or rewrite scenes, but to use AI as an analytical tool: something that could reconstruct structure, identify pacing issues, trace character arcs, and surface real editorial problems so that I, as the writer, could make better and faster decisions.
In theory, this is exactly what Retrieval-Augmented Generation (RAG) should enable.
In practice, it does not work. This post will explain why and what I plan to do next.
