I help creative organizations direct AI instead of drowning in it. Universities, studios and in-house creative teams bring me in to train their people, build curriculum that scales, and design the production systems that keep human judgment in charge.
Five signs I use to read what AI is doing to creative work. Each has two readings that pull against each other, and neither one cancels the other. Most organizations are living inside that pull, which is where the friction, the fear and the opportunity sit.
Technical skill is getting cheap and taste is getting scarce, yet taste is trained by making. The ability to choose rises in value, and the eye that chooses well still comes from the hands.
Shows up astaste, judgment, selection, omission
What to doBuild a practice that sharpens your taste and makes it visible. Lean into your weird. Get known for it.
Value used to sit in owning a finished asset. More and more of it sits in circulation: who carries an idea, who remixes it, and who keeps coming back.
Shows up asnetworks, publics, cultural gravity
What to doProtect the core. Design the rest to travel. Decide whether you are building a fortress or a movement.
Large, role-based crews give way to small teams with outsized reach. When the machine can supply the hours, the scarce input becomes direction.
Shows up assmall crews, scale, the one-person studio
What to doUse the machine to scale a vision you already have. It will not supply one.
Script, shoot, edit is a line. A world is a system you return to: characters, lore and assets that hold together across formats and keep producing stories.
Shows up aspersistence, lore, reusable universes
What to doStop making one-offs. Invest in what can carry many stories.
The audience stops sitting in the dark. It talks back, makes things, and expects to be let in.
Shows up asparticipation, community, feedback loops
What to doDesign the loop. Build with the people who show up.
The product is not proof.
When a machine can produce competent output on demand, the finished thing stops telling you who understood anything. My work circles one problem: what still counts as evidence of learning, of expertise, of authorship and of intention, and how to teach people to produce it.
Classrooms, studios, brand teams and labs. I build the thing, run it with real people, and keep what survives contact with them.
Director of Media Entrepreneurship and Innovation, teaching across the business and arts colleges. Originated the early concept and technology vision for what became CMII, and wrote the core curriculum for its Media Entrepreneurship program. David Cheshier led the institutional work that brought it into being.
Built an agentic scripting system for StudioNow inside Coca-Cola, developed AI production methods, and trained producers to work with generative tools and AI creative talent.
A one-day intensive where participants develop, direct and screen original short films with generative tools. Ten full-day intensives run so far for industry professionals. People understand AI fastest by making something with it and watching it in a room together.
“Astonishing. Like it or not, AI is here, and it is something every filmmaker needs to understand.”
Tom Luse, Executive Producer, The Walking Dead
Co-teaches the AI and creativity module of the 2026 Founderz × Microsoft AI and Innovation certificate: imagination, creative direction, and producing work that rises above the statistical average.
Founder and director of a peer-reviewed journal for immersive media, built with the Immersive Experience Alliance, where she also directs programming.
A chapter on creative intention, judgment and expertise in human and AI collaboration, for an Edward Elgar volume on pedagogy in the age of AI edited by Michael A. Peters and J. Owen Matson.
Keynotes, workshops and executive sessions. Each one leaves the room with a framework they can argue with and something to try on Monday.
The sign list, live. What is moving in creative labor, authorship, production systems and business models, and how to navigate each shift.
What counts as evidence of learning, skill and authorship when the finished output can be generated. For educators and anyone who hires.
Authorship, taste and direction when stories and images arrive instantly.
How creative leaders shape abundant machine output through intention, standards and judgment.
Designing AI systems around human judgment instead of reorganizing people around the machine.
Faculty workshops, AI curriculum, assessment that survives generative tools.
Generative Storytelling Labs, pipeline design, crew training.
Agentic production systems, producer training, creative strategy.
The questions underneath the work. I do not have the answers yet, and I am suspicious of anyone who claims to.
What becomes scarce when competent production is nearly free?
What happens to expertise when machines can imitate everything it visibly produces?
What happens to attention under infinite generation?
Who owns the systems, who gets paid, and where does the leverage pile up?
What do authorship and intention mean once human and machine agency are tangled together?
Who am I talking to inside my own head, and does that change when the machine talks back?
I helped build internet infrastructure at Georgia State, then joined Mindspring as one of its first forty employees, when the commercial internet was still a rumor. Since then the frontier has kept moving: computing, cinema, immersive media, blockchain, entrepreneurship, generative production, artificial intelligence. I keep following it.
I studied philosophy, computer science and filmmaking, in that order, and use all three every week. I make things, teach things and break things, and I trust the experiment over the forecast.
Send the context, the audience, the timing, and what would make it useful. I will tell you plainly whether I am the right person for it.
