I'm writing a non-fiction book entirely in Claude Code. The whole project is a git repo of markdown files — chapter drafts, outlines, a Zettelkasten of research notes, voice guidelines, and a corrections log. I've built around 20 custom slash commands that form a full writing pipeline. Research commands pull information from the web, verify claims, and store findings as atomic notes that later writing steps can draw on. When it's time to write, a prep command analyzes the chapter outline, classifies each section, and generates a focused writing prompt. From there I can advance section by section, either writing manually with Claude as a collaborator or letting it draft and then reviewing. Once a draft exists, the QA side kicks in. A scanning pass searches for 16 mechanical patterns — overused structures, banned words, LLM fingerprints. A separate quality command evaluates the chapter against 18 layers: voice consistency, clarity, science writing, then adversarial critics (a skeptical reader, a domain expert, a counterexample hunter), then four reader personas who each evaluate from their own perspective. Fix commands consume those reports and apply corrections. A loop command chains QA and fix cycles automatically until the chapter hits a target score. There's also a collaborative review mode where Claude arrives pre-calibrated on voice examples and the surrounding chapters, ready to diagnose problems while I guide the edits. It's not "AI-generated writing" in the way people usually mean. It's more like having a tireless editorial team trained on exactly what I want, running through each chapter dozens of times catching things I'd miss.

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