Context Engineering: The New Prompt Engineering
“The AI revolution isn’t about bigger models. It’s about context.”
For the last two years, the industry has been obsessed with Prompt Engineering—the art of whispering the right magic words to get a good result.
But for a novelist building a 100,000-word manuscript, “magic words” aren’t enough. You need state. You need memory. You need consistency.
This course introduces the next evolution of AI interaction: Context Engineering.
The Core Shift
Prompt Engineering is static. It asks: “How do I phrase this question?”
Context Engineering is dynamic. It asks: “What information does the model need right now to answer this question correctly?”
An LLM (Large Language Model) is inherently stateless. It has amnesia. Every time you talk to it, it’s meeting you for the first time. To write a novel, we have to cure that amnesia. We do this by dynamically assembling a “Payload” of context for every single interaction.
The Architecture of a Muse
In the Writers Factory, we implement Google’s “Context Engineering” framework to turn a stateless chatbot into a stateful creative partner.
1. Sessions (The Workbench)
Think of a Session as your messy desk while you’re working. It holds the immediate conversation, the current scene draft, and your temporary notes. It is fast, chaotic, and temporary.
- In the App: This is your “Ideation Chat” or the current “Drafting Tournament.”
2. Memory (The Filing Cabinet)
Memory is where we store the “Truth” of the story. It is organized, searchable, and persistent. When you finish a session, the important facts are extracted and filed away here.
- In the App: This is the Knowledge Graph. We don’t just save text files; we save relationships. Mickey KNOWS Alice. Alice IS_IN The Casino.
Types of Context
To engineer a muse, we must manage two distinct types of memory:
Declarative Memory (“Knowing What”)
These are the hard facts of your world.
- Character names, eye colors, backstories.
- The rules of your magic system.
- The plot points of Chapter 3.
How we engineer it: We use RAG (Retrieval-Augmented Generation) to pull specific facts from your NotebookLM research and inject them into the prompt.
Procedural Memory (“Knowing How”)
This is the “muscle memory” of your writing style.
- Your sentence rhythm.
- Your preference for “show, don’t tell.”
- Your specific tone (e.g., “Noir Cynicism”).
How we engineer it: We run Voice Tournaments. When you pick a winning draft, we extract the mathematical patterns of that text and save them as a “Style Vector.” Future prompts are instructed to match that vector.
The Writers Factory Approach
We are not just writing prompts. We are building a Context Engine.
- The Input: You ask for a scene.
- The Assembly: The system pauses. It queries the Knowledge Graph:
- Who is in this scene? (Retrieves Character Nodes)
- What just happened? (Retrieves Previous Scene Summary)
- What is the tone? (Retrieves Style Vector)
- The Payload: It packages all this into a massive, invisible context window.
- The Generation: Only then does it ask the AI to write.
The result? The AI doesn’t hallucinate. It doesn’t forget your main character’s name. It writes like you, because we engineered the context to make it impossible for it to be anyone else.
“You are Tony Stark. The Context Engine is the suit.”
Deep Dive: The Systems Behind the Magic
Want to understand the specific systems that power the Context Engine?
| System | What It Does | Learn More |
|---|---|---|
| GraphRAG | Turns your story into a computable graph of relationships. Calculates tension, tracks setups and payoffs, detects contradictions. | GraphRAG: The Living Brain |
| Voice Calibration | Runs a tournament where AI models compete to match your voice. The winner becomes your permanent style reference. | Voice Calibration System |
| Narrative Dashboard | Real-time visualization of tension levels and pacing. Tells you when your story needs more conflict or resolution. | Narrative Dashboard |
| Director Mode | The 6-step scene creation pipeline: Scaffold → Structure → Generate → Compare → Enhance → Complete. | Director Mode Pipeline |
These systems work together during every scene generation, ensuring consistency across all dimensions: facts (Graph), voice (Calibration), structure (Dashboard), and workflow (Director).