Case Study: The Narrative Lab

Architecting the Bridge Between Creative
Intent and Machine Logic

The Challenge

In the rapidly evolving landscape of Generative AI, there remains a significant ‘translation gap’ between high-level creative vision and model execution. Most LLM outputs suffer from ‘narrative drift’ or hallucinations because they lack the structured reasoning required for complex storytelling.

Technical Architecture

Bridging the gap between creative intent and machine logic requires a framework grounded in human interaction. Storytelling is the most basic social code we have. When we apply narrative structure to LLMs, the model assumes a consistent role that is naturally resistant to drift and attacks. For the end user, this translates to a seamless, natural interaction that leans into a proven human constant: empathy.


import openai

def generate_narrative_logic(user_input, character_archetype):
    """Translates creative intent into structured LLM logic."""
    
    system_prompt = f"Role: Narrative Architect. Archetype: {character_archetype}."

    # Implementing a logic layer to prevent hallucinations
    response = openai.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_input}
        ],
        temperature=0.7 
    )

    return response.choices[0].message.content

Red Team Methodology & Safety Controls

Safety in Generative AI is often treated as a post-processing task, but true resilience begins at the architectural level. By enforcing a strict narrative framework—defining a character’s ‘Wants vs. Needs’ and ‘Moral Compass’—we create a logical boundary that the model cannot easily cross. This methodology, refined through my work on AI safety at Meta (Rose Int), serves as a primary defense against model drift and adversarial attacks, ensuring the AI remains both relatable and safe

The Impact

At Meta: Driven a 25% improvement in AI character assessment accuracy through standardized technical documentation and Red Team logic.
At Netflix: Provided structured narrative analysis and workshops contributing to the greenlighting of 3 global series currently in production.
The Narrative Lab: Engineered a functional prototype demonstrating how structured logic layers effectively mitigate LLM hallucinations in creative workflows.

Ready to see the logic in action?

I developed a prototype app, The Narrative Lab, to demonstrate how AI character creation can be structurally aligned with the ‘code’ of storytelling. By answering a series of foundational questions—utilizing metrics pioneered by masters of story development like Aristotle and Lajos Egri—users can create and stress test a character’s internal logic before deployment or further development in a screenplay or manuscript.

Explore my Writing & AI Frameworks

Visit The Toolbox to explore my curated collection of narrative frameworks, script analysis tools, and technical documentation guides.

Architecting the Bridge Between Creative Intent and Machine Logic