Calculated Word Soup vs. Authentic Storytelling

Documentary Production

We cannot automate our way into trust. Authenticity is one thing no model can replicate.

The Invitation

It was a little alarming to receive an invitation to apply for a role helping AI agents learn how to replace video editors, or as they put it, "Collaborate with AI teams to improve next-generation video editing systems." Basically, they want video editors to train their AI agents on enough footage, cuts, and pacing decisions, so eventually the automated tool handles post-production on its own. 

But it’s not really artificial intelligence is it? “AI” is just a misnomer with hype. It’s Large Language Model (LLM) agents combined with computer vision model agents trained on data from human expertise and craft. The same structure was used to train self-driving cars. The human drives, the machine watches, the machine learns, and eventually the human is eliminated. 

These companies are asking us to document our own robotic replacements.

I did not pursue it, but it made me think hard about what we lose when we hand video editing to a machine. The current corporate delusion of trusting LLMs with serious decisions is already showing its limits, with results that are mainly shaped by the first prompt.

Word Calculators Generating Canned Fakeness

LLM-generated content has the tendency to generate vague, generalized statements that feel personally meaningful, in the same way horoscopes feel accurate. It's the Barnum effect. A lot of LLM content right now sounds resonant and novel, but it is drawn from the same pool of calculated word soup, regurgitated at scale. 

We recognize that uneasy feeling the second we encounter it: reading marketing copy that sounds super polished but says nothing, watching creepy advertisements that have all the right parts but leave us unmoved. Audiences are getting saturated with it, but they are also getting better at detecting even the best Diffusion models generated media. That hollowness of what is obviously LLM-generated content has a canned fakeness that is the opposite of trust. Yet corporations keep pushing to use LLMs, with great faith that it will improve, seemingly without consideration for the audience’s response. Instead of asking:  Do people disengage? Do they lose confidence in the organization? Do they share it less? Is anyone really buying it? The problem is,people are still buying the stock, at least for now.

But it’s not just the canned fakeness issue, it's also the ethics issue. Independentartists,authors, andmusicians are taking legal action against LLM companies over models trained on work they never consented to sharing. So would AI companies use their automated video production tools to also steal from existing films? It seems to be the trend.Diffusion models learn the statistical relationship between text descriptions and visual patterns across millions of images. So when you prompt an image model, it is not drawing, it is reconstructing images from patterns learned across millions of existing images, which is why the stolen work argument is so central to image and AI video specifically. Video generation models had to be trained on existing footage, and unlike text which has some fair use gray area, visual likeness and style are much harder to separate from the original work.

The Urge to Automate Storytelling

Film producers have been using formulas for years, from Joseph Campbell's Hero's Journey to the Blake Snyder beat sheet. Hollywood studios were greenlighting films based on whether they hit the beats. In the effort to find faster, cheaper ways to produce something that felt like a real story, they were just repeating a version of what was done before. The formula reduced risk short term but hollowed out the product long term. Streaming disruption, COVID, and shifting audience habits accelerated the collapse, but the hollowness was already there.

The industry reflected it. TriStar Pictures was scaled back significantly. New Line Cinema lost its independence and was folded into Warner Bros. DreamWorks has had multiple restructurings. Relativity Media filed for bankruptcy twice. Several mid-tier studios that specialized in formula driven content have either closed or been absorbed into larger conglomerates. This broader pattern is clear: the middle is collapsing. Big tentpole franchise films still make money. Small independent specific films are finding audiences. The formula driven middle, the movies that cost a lot but underperform at the box office, is where the losses are concentrated.

Contrastingly, independent studios like A24 have been outperforming the formula blockbuster companies because audiences are saturated with the redundancy of beat sheet produced films. People recognized the hollowness and started choosing films that were uncomfortable, specific, and deeply human over ones that are predictable to the point they could guess what was going to happen next.

While audiences are growing ever more aware of formulaic content, it is hard to imagine that AI filmmaking will lead anywhere different. The companies sending those job offers to train their systems are building toward the same conclusion the formula studios reached. If it is anything like what we have seen with writing and imagery, it would feel even more soulless. 

LLM Filmmaking vs. Documentary Storytelling

Documentaries have their own formulas. The talking head interview with b-roll cutaways. The three act problem, struggle, resolution structure. The hero's journey applied to a real person. The opening with a shocking statistic. The redemption arc. The underdog story. The institutional exposé. The Ken Burns pan across a still photograph, voiceover, repeat. A lot of documentary content in institutional video, nonprofit impact films, university research videos, follows those containers so closely that the specific human story inside gets flattened by the structure around it. 

The question is whether the filmmaker is using the structure to serve the story or using the story to fill the structure. Documentary done well would resist its own formulas the same way a good narrative film is now resisting the beat sheet. If it is rooted in specific people, specific places, specific moments, it naturally resists an automated formula by finding structure in what actually happened.  Real life spontaneously creates the unguarded moment, the unlikely outcome, the truth that is stranger than fiction. It is better than any formula, but it costs something that cannot be automated: presence. You have to show up. You have to wait. You have to build enough trust with a subject that they let you see something real. 

Meanwhile, “AI” content is the fast food of media creation. Convenient, cheap, and everywhere, but nobody is proud of it. Worse, if we keep trying to shortcut the cost of presence, we end up with content that costs us trust. We cannot automate our way into connection. The attempt to do so produces the exact opposite of what we want and need. 

The Opportunity

With the surge of LLM-created content, authentic storytelling is becoming more rare, which means it is becoming more valuable. We have to remember that we already tell stories better than any LLM ever will, even if we train them, because our stories are based on lived experience. As tempting as it might be to rely on an LLM, the best media is from our own skill, expertise and lived experience. That is what creatives should be spending time developing, not teaching computed models to do it for less. Author Joanna Maciejewska put it best when she said, “we want AI to do the laundry so that we can do art, not the other way around.”

The institutions most committed to human development, like universities, have the most to gain from investing in real stories. Their credibility is built entirely on the idea that human minds matter. But for all mission-driven organizations willing to invest in human created content, creating higher quality content will make their organizations stand out in a sea of growing LLM media. Especially as the audience demand for quality increases. This is the opportunity.

Your Story Deserves Presence

Aeilea Media creates documentary-driven video and strategic visual content for nonprofits, universities, and mission-driven organizations. If you're ready to invest in content that builds trust,let's talk →