ep. 91. How a Maker-Turned-Product-Leader Keeps the Human in the Frame with AI
5 min read
Meet JD
Jean-Daniel (JD) LeRoy is a maker who loves solving ambiguous problems.
He grew up in the San Francisco Bay Area bringing ideas from his head into reality, prototyping ideas in CAD and fabricating them in his high school’s maker space. He built on that instinct at the USC Iovine and Young Academy, marrying his design craft with product development and HCI.
Soon after graduating, JD joined MIRA, an AR headset startup later acquired by Apple. There, he saw designers struggling to bring their ideas into this new spatial medium. They were stuck using Unity, a game engine built for developers, to prototype immersive experiences. He co-founded Playbook 3D to help designers bring their ideas to life more easily.
When generative image models emerged, text-to-image felt like a slot machine: you described a shot and hoped for the best. Playbook proposed a better way: combine AI’s strength in ideation and rendering with 3D’s precision and control. Block out a scene in 3D, frame a virtual camera to capture exactly the shot in your head, then let AI render the scene.
Wonder Studios, an AI-native film studio, saw Playbook’s approach to giving creators more control over their output and brought the team on board.
JD now works there across product, community, and operations, where he’s building agentic, human-in-the-loop workflows that take creators from concept through post-production. Through combining custom-trained models with open and closed source APIs, Wonder aims for generative AI to handle the heavy lifting while creatives stay in control.
Pace Vs. Taste
The rapid emergence of powerful AI image and video generation models has caught the filmmaking industry off guard.
“The pace of innovation, how often it’s changing right now—no one could have expected it. But it also makes it one of the most interesting times to be building in the space.”
Problems that plagued generative video two years ago, like character consistency and continuity across generated frames, have largely been addressed by improvements in foundational models, such as Google’s Nano Banana and ByteDance’s Seedance.
The gap that remains is specificity.
Models are statistically biased toward common outputs, which means a director with a unique creative vision won’t get there through prompting alone. As AI generation becomes cheaper and faster, what differentiates the output is storytelling and taste.
I asked JD for a definition: “Taste comes with the human experience. It’s the coming together of different inputs and serendipitous connections that we’ve made throughout our lives. Quality is a measure of taste.”
What that looks like in practice is creative direction in the AI era, having a deep enough vocabulary to prompt these tools effectively, understanding which models to stitch together in a specific order to achieve a particular output, knowing which clip to cut, which half to keep, which pieces to splice together.
Taste is also what separates work worth watching from what JD calls “slop machines”: pipelines pumping models to auto-assemble content with no curatorial judgment.
“Taste comes with the human experience. It’s the coming together of different inputs and serendipitous connections that we’ve made throughout our lives. Quality is a measure of taste.”
The Control-Efficiency Spectrum
JD frames the choice to use AI in film production as a spectrum between control and efficiency.
At the control end, AI is used at specific touchpoints within traditional production, such as filming with a physical camera and using AI for VFX. At the efficiency end, AI can run an end-to-end pipeline, like generating scripts, character breakdowns, and sequences of imagery.
“One side leans towards more human in the loop, with more critical decisions made by humans; the other is more of a ‘Ford factory’ type experience.”
Choosing where to operate on this spectrum is often an economic decision for studios, who tend to operate using a “pick two” framework of cost, time, and quality.
When a director’s vision cannot be compromised, the production remains procedural, relying on tried-and-true methods for blocking, world-building, and camera placement while utilizing AI for the “last mile”: tasks like dubbing, rendering, and stylization.
AI Skepticism Has a Timeline
Initially, JD faced significant resistance from Hollywood’s film industry. During his first year pitching AI-assisted production to traditional studio representatives, the response was a clear, hard “no.”
To bridge this gap, JD strategically based Playbook 3D in Los Angeles to operate at the intersection of Hollywood and Silicon Valley, ensuring he was physically present with traditional filmmakers.
JD built acceptance by humanizing the technology through community engagement.
“We hosted a lot of meetups where we would have creatives and technologists showcase what they were working on. It just started to show that there are some actual people behind these tools. It’s not just Silicon Valley pushing AI downstream to consumers in the world.”
Fast forward to March 2026: Netflix acquired InterPositive, Ben Affleck’s AI-powered film tools company, for an estimated $600 million. The industry has come a long way from a “hard no.”
Small Teams, Full Stack
The current film industry disproportionately favors green-lighting sequels and established franchises because they are viewed as safe investment decisions.
Historically, original IP has been expensive to produce and difficult to validate before committing significant capital, but AI-assisted production is fundamentally changing that math.
“With lower risk and lower investment, you can start to validate newer IPs or newer ideas that might find a niche audience on YouTube or Twitch beforehand, and eventually be produced all the way down to the full theater experience.”
These creators can use new AI tools to reclaim control over the entire process as “orchestrators”. JD noted, “With these tools today, small teams or individuals can do the full end-to-end filmmaking process,” marking a significant change in who has the power to bring a vision to life.
“With these tools today, small teams or individuals can do the full end-to-end filmmaking process.”
The AI Hype Check
I ask every practitioner I interview the same question: is AI overhyped or underhyped?
JD’s answer: “underhyped”.
That’s because it has yet to reach many subregions of the creative world that currently lack access to these tools. The most significant signal isn’t coming from the AI-native communities, but from the traditional practitioners who are realizing that exploring AI is no longer optional.
For all the people who already have a foundation in storytelling and filmmaking, JD’s recommendation is, “stay curious, join in on the dialogue, and try the tools out for yourself.”
While the initial move toward these tools may be driven by necessity, JD is optimistic about the outcome for those who lean in. He predicts that those who move past their initial hesitation will be pleasantly surprised by the opportunities available to AI-fluent creators.
“Stay curious, join in on the dialogue, and try the tools out for yourself.”
This interview has been edited for length and clarity. Opinions expressed are solely JD’s own and do not necessarily reflect those of his employer.
Three Takeaways
Building off JD’s insights, here are three takeaways you can apply to your own work:
Build for modular adoption. The pace of AI model improvement has outrun planning cycles. Build workflows where the core logic stays stable and the AI layer is interchangeable. When a better model emerges, you can adapt without rebuilding from scratch.
Taste cannot be automated. It’s built from lived experience: the inputs and serendipitous connections that compound over time. AI works by finding the statistical center of what already exists. By definition, its outputs are average.
Build community, not just products. JD’s meetups helped show filmmakers that real people were building these tools for them. The arc from resistance to adoption moves faster when the people who can most benefit from the technology feel like it was built for them.
Know a practitioner navigating AI in their work who should be featured here? Reach out to hello@sendfull.com
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