Chao Thao ✉️ Email · 🔗 LinkedIn · 💻 Portfolio
The first show I production-coordinated at Netflix was a union series with big scripts — stunts, dance, music, and minors. The kind of show where the production office and the stage need to be in lockstep, or the day falls apart.
Early in that show, our doc approvals were becoming a bottleneck. I started asking my UPM and ADs how they wanted approvals to work. The answers were consistent: quick access, readability, and the ability to make changes in real time. So I proposed we try Google Sheets.
That sounds small now. In 2018, on a union show, it wasn't. UPMs and ADs come to a production married to the templates they trust, and for good reason — those templates have been refined over hundreds of shows. What I was proposing was a workflow change, not a tool change, and the hesitation was real. What got us there wasn't a mandate. It was matching their existing call sheet line by line, building a central hub both sides could work in, and proving over the first few weeks that the new way was faster without being less rigorous.
I think about that experience a lot now when I think about AI in production.
Here's what I keep noticing, and what I haven't seen named clearly enough: everyone is already using it. Coordinators are drafting memos with it. Marketing producers are using it to speed localization briefs. Editors have plugins in their workflows that didn't exist eighteen months ago. There is no top-down rollout coming. AI is entering production the way Google Sheets entered my call sheet workflow — sideways, person by person, problem by problem, with leadership formalizing policy long after the practice has spread. That's how production has always absorbed new tools.
Studio leadership has also begun publicly discussing fewer entry-level production roles over the next several years. That forecast lands hardest on producing students, because the assistant coordinator and PA roles I came up through are the same roles most exposed to AI-assisted tooling. Which raises a question I keep turning over: what is a producing program for in a world where information access is free? A student today can take a producing course from Sundance, a camera class from a working DP on YouTube, and a project management cert from Google, all before lunch. A big part of higher education's value used to be access. Access is mostly free now, while the cost of a paid program has gone the other direction. The programs that adapt will be the ones that double down on what they uniquely offer: judgment, network, and the safety to fail in front of people who'll catch you. Those are real, durable advantages. And they matter more now, not less.
I don't have a clean answer. I have observations from a decade in physical production and from teaching and translating faculty workflows in higher ed. I have honest uncertainty about where this is all heading. Particularly around how guild and non-guild work will diverge as AI tools spread, and how producing students will navigate a path I myself wouldn't recognize from when I started.
What follows is a working draft of a 6-week module I've been sketching out, built as an advanced elective for producing students who already have foundational training and are ready to layer AI fluency on top of it. It's spec work, not a deployed curriculum. The point isn't to prescribe what producing programs should do. The point is to share what I'd want to teach if I were doing it now, and to open a conversation with the faculty, producers, and program designers already wrestling with these same questions. If you're in any of those chairs and any of this resonates (or doesn't), I'd genuinely like to hear from you.
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📌 A working draft of how I'd structure an advanced producing elective if I were teaching it now. Assumes students already have foundational producing coursework and some production experience. Built as a 6-week module, flexible enough to live as a focused unit inside a full-semester producing course, or as a standalone intensive in a workshop, summer, or extension program. Each week assumes ~3 hours of contact time plus an assignment. The arc moves from framing to development to production to delivery to the producer's responsibility layer.
Weekly rhythm: each class opens with students presenting the previous week's assignment for instructor and peer notes, as a group discussion. Producers have to defend their choices in real time; the module practices that skill every session.
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Introduced in Week 1, the anchor project runs through the full term. Students choose a real project they want to make, one of their own shorts, features, or series ideas, and each week's exercise builds a piece of the package. The pitch package itself develops across multiple weeks rather than in one sprint, so students experience how a pitch actually evolves through production. By the end of the term, students leave with:
The goal isn't a polished thesis project. The goal is a producer's package strong enough to share with collaborators, financiers, or festivals, plus the lived experience of using AI tools as part of a real producing workflow rather than a classroom exercise.