At the Google I/O conference last week, a discussion brought together filmmaker Darren Aronofsky, DeepMind CEO Demis Hassabis, and director Eliza McNitt to explore the future of storytelling in the age of AI. It wasn’t just the new apps that sparked buzz – though there were plenty – but what really stood out to me was Ancestra, McNitt’s latest film and the first outcome of the Primordial Soup x DeepMind collaboration.

In a setting like this, the conversation could have easily fallen into familiar binaries: hype versus fear, replacement versus enhancement. But instead, it spotlighted something subtler – and far more important. Through Ancestra, McNitt showed that AI isn’t dragging creativity down. It’s lifting it into new dimensions. 

What interested me most wasn’t how AI can replicate what we already know how to do, but how it lets us do things we’ve never done before. 

And that’s where I found myself repeating a thought I keep returning to: there is no such thing as “best practice” in AI-assisted storytelling – only “best fit.” That mindset, I believe, matters far beyond filmmaking.

Ancestra. The Story Begins.

Ancestra is a short film inspired by the day McNitt was born – an emergency C-section that nearly claimed both her and her mother’s lives. It’s a story that is both intimate and difficult to visualize. Without generative AI, the film would have struggled to render the metaphysical, embryonic, and cosmic dimensions of that moment. But with early access to Google DeepMind’s Veo 3 and Flow tools, McNitt was able to reimagine the invisible forces surrounding her birth – cosmic imagery, symbolic renderings of life formation, and scenes that go far beyond what any camera could capture.

“To be honest, I never thought about telling the story of the day I was born – but here we are.”

The film was created using a hybrid pipeline: live-action performances by SAG-AFTRA union actors, full film crew production, and AI-generated videos.

What makes Ancestra meaningful isn’t the unique collaboration or novelty of the technology. It’s the contextual precision with which the technology was used.

Making the Invisible Visible

One of the film’s most powerful creative decisions was the creation of a digital baby – Baby Eliza. Instead of using a real infant on set, which sometimes raises both ethical and logistical challenges, McNitt trained Veo on photographs of herself as a newborn. These were taken by her late father, a renowned photographer, and used to generate scenes that felt emotionally authentic and personally resonant.

To deepen that emotional fidelity, McNitt used a style-transfer tool to infuse the output with her father’s distinct photographic style. The result was not just technically impressive – it felt like the scenes were shot by someone who loved her. In doing so, McNitt extended her family’s artistic legacy into a future-facing medium.

She also used AI to visualize sequences that would be nearly impossible to capture with traditional tools – like a baby’s heartbeat in utero or stylized representations of cellular life and cosmic metaphors. In Ancestra, generative video became not just a visual aid, but a poetic lens for memory, imagination, and emotion.

Start with the Story, Not the Tool

What’s clear from McNitt’s approach is that she didn’t begin with the question “What can Veo do?” She began with a story only she could tell. The technology followed the narrative – not the other way around. That distinction matters.

AI should never dictate creative direction. It should amplify the storyteller’s intent. And what works for one story may not work for another. The way AI fits into the creative process is entirely dependent on the context – the story, the team, the moment, the constraints. In Ancestra, AI was used sparingly, intentionally, and only when it added emotional or narrative value.

AI Didn’t Reduce the Need for a Team – It Transformed the Roles

McNitt described the creative process as “a lot of nightmares” at times – referring to the unpredictability and rough edges of working with early-stage generative models. But rather than resisting that chaos, she leaned into it. She treated it as an expressive medium, not a polished product. Her job as a filmmaker was to shape and interpret the outputs, not expect perfection from them.

“It’s been very interesting to create and see what comes out when you embrace that chaos.”

The production of Ancestra involved over 165 people, including 15 dedicated “generators” – artists who guided Veo’s outputs. This marks a shift in how we think about creative teams. Prompt engineers, AI visualists, and model trainers are becoming as integral to the filmmaking process as cinematographers and editors. McNitt didn’t reduce her team – she redefined it.

Rethinking the Creative Process in the Age of AI

What McNitt’s process reveals is that generative AI doesn’t come with a playbook. You can’t Google your way to meaning. You can’t outsource intuition. Creative judgment still comes from the human – what to keep, what to discard, what to shape, and what to feel.

And as AI tools move further into the worlds of writing, music, design, advertising, and architecture, the temptation will be to chase standardization. To build templates. To copy what worked elsewhere. But the lesson from Ancestra is this: AI isn’t a shortcut to creativity. It’s a prompt for maturity.

There is no right way to use AI. Only a right-for-this way. The only real “best practice” is knowing your intention, your audience, your story – and using AI only when it serves those things.

Human storytelling is not a protocol. It’s a pulse. AI should follow that beat – not override it.