Technical Documentation

Everything you need to understand how Writers Factory works under the hood. This is the system architecture that powers AI-assisted novel writing.


The Two-Stream Approach

The pedagogical foundation of Writers Factory—separating research from story to enable creative discovery.

PHILOSOPHY

The Two Streams

Why we separate research (interest) from skeleton (intent)

The Intersection

How skeleton meets research—the Connection Point workflow

The Two-Track Architecture

The separation of Researcher (Kitchen) and Architect (Meal)


Writing Stages

The four stages of the Writers Factory workflow.

ARCHITECT

Architect Mode

Build your Story Bible with AI guidance

VOICE

Voice Calibration

Train the system to write like you

DIRECTOR

Director Mode

High-velocity scene generation

EDITOR

Editor Mode

Polish prose and ensure consistency


Research Preparation

What you do before the course starts—building your research in NotebookLM.

START HERE

Getting Started

The unified writer's workflow

STAGE 1

Story Development

The 25-question interview that builds your skeleton

NotebookLM Deepening

Enrich your story with research ingredients

Deepening Prompts →

Copy-paste prompts for prose extraction

Genre Calibration

Teaching the system your genre's rules

Concept Generation

Turning ingredients into 5 novel concepts


Research Notebook Templates

Seven specialized notebooks for building your research library in NotebookLM.

The Arena

Competition, sports, and conflict settings

The Speculation

Science fiction and fantasy worldbuilding

Beliefs & Worldviews

Philosophy, religion, and ideology themes

Literary Roots

Literary traditions and influences

The Voice

Prose styles and narrative voices

Visual Language

Cinematic and visual aesthetics

The Rabbit Hole

Deep research obsessions


System Overview

Understand how Writers Factory works under the hood.

ISP INTRO

Building a Writer's Brain

Why NotebookLM is your research assistant and creative partner

Context Engineering

The new prompt engineering—it's all about context

GraphRAG

Knowledge graphs for narrative consistency

Data Architecture

Three-system architecture: Research + KB + Story

LLM Models

Multi-model orchestration and routing


Technical Reference

Deep dives for Architect Track students who want to understand the implementation.

Scene Scaffolding

How the scaffold prompt is assembled from multiple sources

GraphRAG Architecture

Knowledge graphs for narrative consistency

Research Pipeline

Three-system architecture and data flow

Agent Instructions

How to communicate with AI agents effectively

LLM Orchestration

Multi-model routing and capabilities

Anti-Patterns

Common mistakes and how to avoid them

Source code access is available to Architect Track participants.


ISP Course Results

Findings from the January 2026 ISP course — what we learned generating 73,000 words across 4 manuscripts.

NEW

Course Findings

8 discoveries about AI novel writing from 60 scenes across 2 languages

Scene Scaffolding

How the scaffold prompt is assembled from multiple sources

Context Engineering

Why context matters more than the model you choose


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