Why Writers Need to Think Like Showrunners
How AI is transforming the writing process—and why today’s authors must think like creative leaders, not solitary geniuses
A writer opens their laptop at 5:32 a.m. with a mug of coffee and a blank Notion page. Three AI windows are already open: Claude for structure, GPT for prose, and Perplexity for research. This is not solitude; it’s a room full of silent collaborators waiting for direction.
By Dan B. Jensen
The modern author is rarely truly isolated anymore. Beside them stands an invisible team—algorithms ready to brainstorm, suggest, challenge, and transform their words. This technological partnership represents a profound shift in the creative landscape, one that demands not just new tools but new frameworks for understanding the writing process itself.
AI as an Infinite Writers' Room
For decades, television's most iconic series have emerged from writers' rooms—collaborative spaces where creative teams develop storylines, refine dialogue, and build narrative worlds under a showrunner's guidance. Now, artificial intelligence has created a parallel for authors: a virtual writers' room available at any hour, capable of generating variations and ideas without the constraints of physical space or human schedules.
The Creative Potential
This AI writers' room offers remarkable creative possibilities that are transforming how many authors approach their craft. When effectively directed, today's language models can function as versatile collaborators across multiple aspects of the writing process:
Idea generation and expansion
Where a human might brainstorm three or four approaches to a scene, AI can rapidly suggest a dozen alternatives—often including unexpected directions that challenge conventional thinking. A mystery writer stuck on developing the perfect red herring might prompt an AI to generate ten possible misleading clues, each with different psychological implications for the reader.
Stylistic experimentation
Advanced models can adapt content to different stylistic frameworks, helping writers explore how their narratives might work in different voices. A novelist working on historical fiction might test how a pivotal confrontation reads when written in Hemingway's terse style versus Dickens' more ornate approach, gaining insights without investing days in manual rewrites.
Character development
Some specialized writing tools excel at maintaining consistent character voices while suggesting dialogue or actions that reveal deeper personality traits. An author might feed a character profile to the AI, then request dialogue that subtly reveals the character's insecurity without explicitly stating it—receiving options that accomplish this through different conversational patterns.
World-building assistance
For speculative fiction especially, AI can help develop consistent cultural practices, technologies, or environments based on established parameters. A fantasy author might prompt the system to generate societal customs for a fictional civilization based on specific religious beliefs and environmental conditions they've defined.
Structural suggestions
When provided with plot elements, some tools can propose various narrative structures that create different emotional arcs or thematic emphases. A screenwriter might receive suggestions for reorganizing story elements to build tension more effectively or to emphasize a particular character's journey.
Refining and variation
Once a passage exists, AI can offer multiple variations with different emphases, helping writers see their own content from new angles. A passage focusing primarily on visual description might be rewritten to emphasize sounds or emotional undertones instead, revealing new possibilities within the same scene.
The efficiency gains are substantial. Tasks that might have required days of experimentation can be compressed into hours or even minutes. A writer can rapidly prototype different approaches to a challenging scene, explore alternative character motivations, or test multiple endings to find the most satisfying resolution.
Perhaps most valuably, AI tools can serve as instant sounding boards for half-formed ideas, responding with concrete suggestions rather than the abstract considerations of traditional internal dialogue. These technologies don't just expand what writers can produce—they potentially expand how writers can think about their work.
The Necessary Perspective
However, these creative capabilities vary significantly across different platforms and models, and results depend heavily on how effectively the writer guides the process. Not all AI tools are created equal. Some excel at maintaining stylistic consistency but struggle with plot logic. Others might generate brilliantly imaginative scenarios but falter when asked to maintain character consistency across multiple interactions.
The writer's skill in directing these tools—through carefully crafted prompts, thoughtful selection from multiple outputs, and strategic integration with human-written content—largely determines their ultimate value. Much like a showrunner choosing which pitches to develop from their writing staff, authors must develop discernment about which AI contributions actually advance their vision.
And this brings us to the fundamental challenge at the heart of AI-assisted writing. For all their impressive capabilities, these tools lack the core human experiences that give storytelling its deepest resonance.
The Synthetic Life
AI writing tools lack human life experiences that inform authentic storytelling. They cannot draw from lived emotional reality, cultural identity, or personal values unless these elements are explicitly injected by the human author. This is not merely a technical limitation but a fundamental one—and precisely why the showrunner's guiding vision remains irreplaceable.
AI writing tools also struggle with cultural understanding beyond superficial representations. Their training data inevitably contains biases, stereotypes, and gaps in representation that can manifest in generated content without careful oversight.
These biases can be very subtle. Ask an AI photo generator to produce a group of people in a work environment. It will produce a group of people with seemingly great diversity. But upon closer inspection, you will almost always notice that none of the people appear to be under 40. This is not a bias in AI. Nor is it a bias in those who have trained the AI. It is unconsciousness in those who have trained the AI, because in our time there has developed a stereotype that diversity is the same as being a young black woman. Which is, of course, a contradiction in terms.
The Human Element
Cultural and Ethical Awareness
Human writers bring lived experience and cultural understanding that allows them to navigate sensitive subjects with appropriate nuance and respect. Virtually all AI models have a built-in strong reluctance to address controversial topics. Some are very cautious. This is basically common sense and a sign that those who trained them have had an ethical attitude to the work.
The problem is that AI does not understand the nuances. From an artistic perspective, this is extremely problematic. Film, literature, and art must be able to deal with topics such as sexual subcultures, political extremism, and suicide. Here, AI becomes a very difficult workmate, because its training has to be unambiguous about what it includes as controversial matters.
Purpose and Judgment
While AI can generate content according to specifications, it can't determine what should be written or why. The human author's vision, values, and purpose remain the essential foundation of meaningful work.
AI struggles to independently evaluate quality beyond technical correctness. The ability to recognize when writing truly works—when it moves, provokes, or illuminates—remains uniquely human.
And perhaps most importantly:
Intuitive Leaps
Some of the most profound moments in literature come from unexpected connections, provocative juxtapositions, or deliberate rule-breaking. Breaking a fundamental rule in a narrative universe, but doing so in a way that feels completely natural to the reader, who immediately accepts it and wants to hear more. It is a unique quality of the human imagination.
Consequence
The human author must maintain clear authority over what gets generated, what gets kept, what gets modified, and what gets discarded. This selective process constitutes a form of authorship in itself.
The landscape for authors: Those who don't master AI collaboration risk falling behind competitors who produce content more quickly and versatilely.
Writers using AI without proper guidance may lose their distinctive voice. The essential elements that distinguish meaningful literature from functional text can erode through unguided AI collaboration.
The question isn't whether to engage with these technologies, but how to preserve authenticity while doing so—a challenge authors across all genres already face.
The Showrunner Solution
Television production offers a compelling model for creative control. The showrunner role emerged in response to a fundamental challenge: how to maintain a coherent artistic vision across episodes with different writers, directors, and creative specialists. Unlike film, television developed a structure specifically designed to balance collaborative input with unified vision.
Creative Vision in a Fragmented World
The showrunner serves as both creative visionary and decision-maker—establishing the show's aesthetic, thematic, and narrative parameters, and ensuring each episode carries the show's distinctive voice. They don't write every line, but they ensure everything contributes meaningfully to the larger story.
Delegation without Dilution
Great showrunners harness diverse creative inputs without losing the show's essential identity. Vince Gilligan could delegate "Breaking Bad" episodes while maintaining the show's unflinching moral examination. This is precisely the balance authors must now strike with AI.
Why Television Holds the Key
By adapting showrunner methodologies to AI-assisted writing, storytellers can harness technological potential without sacrificing artistic integrity. Television's collaborative writing model offers valuable lessons in balancing multiple inputs within a cohesive vision.
A New Framework for Creative Authority
The showrunner model provides a practical framework for maintaining meaningful creative control in AI collaboration:
Clear "series bible" documentation: Authors can create explicit reference materials guiding AI contributions.
Structured development processes: Authors can develop workflows for AI interaction with control at critical junctures.
Delegation based on strength: Authors can direct AI tools toward tasks they excel at.
Final creative authority: The model reinforces the irreplaceable role of human judgment.
Nuancing the Metaphor
It’s worth noting that showrunners themselves can fall prey to bias. And the showrunner model is not a guarantee of good results. There are actually examples of terrible TV series produced using this approach.
The Path Forward
The goal isn't to replace human creativity with algorithmic efficiency, but rather to develop new creative processes that incorporate both—with humans providing the essential elements of purpose, judgment, and meaning while AI contributes its capabilities for generation, variation, and technical support.
By embracing the showrunner mindset, authors can navigate this emerging landscape with confidence—neither rejecting technological tools out of creative pride nor surrendering authority out of technological deference. The result can be work that is both enhanced by AI's capabilities and unmistakably human in its essential character—writing that leverages the infinite writers' room while preserving the singular vision that gives literature its enduring value.
In this new era, the writer's room is infinite—but the voice that echoes through it must still be unmistakably human.
The Showrunner Method in Action: A Meta-Analysis
When I wrote "Why Writers Need to Think Like Showrunners," I demonstrated the very process I was advocating without really thinking about It.
What readers couldn't see was that the article itself was a collaboration between human vision (mine) and AI execution (primarily Claude 3.7 Sonnet).
The central metaphor—comparing modern writers using AI to television showrunners managing a writers' room—was my original concept. However, I lacked detailed knowledge about television production workflows. This is where the collaborative dance began.
Claude produced drafts, while Gemini and ChatGPT 4o fact-checked and provided ongoing suggestions for improvements. DALL-E and Sora produced (many) illustration proposals before finding the right one. I gathered the pieces, edited, added content, and ran everything through the mill numerous times. Finally, I took the article through the large and advanced Claude Opus for the final quality check (it's quite expensive, so I access it via the OpenRouter service, where I only pay for the actual time I use the model). Together, these services constituted a stack of AI tools, or a creative team under the direction of the showrunner—me.
Like a showrunner establishing creative parameters, I provided the core vision and direction. Claude then expanded this foundation with specific details about television production processes, examples of successful showrunners, and technical explanations of structured development workflows.
I contributed sections from my own experience—especially the "edgier" observations about AI's limitations. My sections on "The Synthetic Life" and "The Human Element" drew from personal insights about AI's inability to truly understand nuance in controversial topics and its subtle biases in representation.
I pointed out how AI image generators create superficially diverse groups where "none of the people appear to be under 40" and how this reflects unconscious stereotyping in training data. This kind of critical observation about technology—identifying not just technical limitations but cultural blind spots—represents the human perspective that AI cannot generate independently.
Similarly, my observations about AI's struggles with artistic nuance—particularly around controversial topics like "sexual subcultures, political extremism and suicide"—highlight the irreplaceable value of human judgment in creative work. These sections demonstrate exactly what the article argues: the human author must maintain authority over what gets generated and kept.
This meta-narrative serves as both evidence and example. The article argues that writers must learn to preserve their distinctive vision while leveraging AI's capabilities. Our collaboration demonstrates that this balance is not only possible but potentially transformative when each contributor plays to their strengths.
As our original piece concluded:
"In this new era, the writer's room is infinite—but the voice that echoes through it must still be unmistakably human."
(PS: Claude came up with that ending. It's a bit AI’ish, but I liked it.)