AI Training · Sora & Generative Video

AI Video Production Training: Sora & Generative Video

Generating one striking clip is easy. Turning that into a repeatable stage of your production pipeline, brief to storyboard, motion prompting, continuity, review, and a provenance-tagged handoff to your editor, is the harder work. It stays plain about what generative video can and can't do today.

modules: 6
hours: 12

A generative-video shoot runs on paperwork nobody pictures when they picture generative video: creative briefs, shot lists, storyboards, take logs, consent forms, and a provenance trail that has to survive to the final export. Skip any one of those and the failure shows up downstream instead of up front. A cameo gets pulled into a spot with no signed release. A character's jacket changes color halfway through a scene and nobody catches it before the edit. A clip goes out with no record of what generated it or who was supposed to check it.

None of that is exotic to video production. A shoot already runs on shot lists and continuity notes. The craft doesn't change because the frames come from a model instead of a camera. Generative video adds speed: a director can try six versions of a move before lunch, provided someone still plans, names, and checks each shot before it reaches an edit.

This program builds that workflow directly: brief to scene breakdown and storyboard, then motion prompting, iteration, and continuity across a run of shots, ending in a review rubric and a provenance-tagged handoff to an editor. Sora leads the exercises because most teams already have access to it, but the shot-planning and review habits carry over to whatever tool replaces it next year. Stills stay out of scope here: our AI image creation and design training already owns still-image prompting and brand image systems, and this page sits inside the wider AI training catalog alongside it.

One good clip doesn't make a workflow

A single striking clip is a demo. A team still needs a shot list and a scene brief before anyone renders a frame, plus a way to hold continuity across the cut.

Shot type and camera movement, first

Useful generative video starts with shot type, camera movement, framing, and pacing, described the way a production team already talks about a shoot.

How do you hold a face steady for six shots?

A character's jacket changes shade halfway through a scene. A prop goes missing between two shots. Holding a look steady across a cut takes reference frames and fixed constraints. It also needs the naming and version discipline a traditional shoot already runs on.

Consent comes first

Putting a person's likeness into a shot or using client footage raises a consent question. Publishing a generated clip brings a rights question before the shot ships. A workflow needs a place to log that decision on the record.

Morphing hands are a motion problem

Morphing limbs and broken physics are motion problems a still-image review process was never built to catch. Drifting continuity is another.

01
What generative video can and can't do yet
90 minBeginner
Participants get a plain-language, hype-free picture of what tools like Sora can and can't do today, set against traditional production and static image generation. Everything after this module builds on that shared baseline.
What still breaks: hands, physics, long shots, and small text
Sora against other text-to-video and image-to-video tools, without favoring one interface
Social cuts, concept previz, ads, and product teasers are where the wins show up fastest
No team should promise guaranteed photorealism or a long-form narrative film from this yet
A traditional production timeline changes shape here, but it doesn't disappear
02
Access and roles for a safe studio setup
90 minBeginner
Before anyone generates a shot, the team sets up access, roles, and guardrails: what a cameo requires, what the usage policy rules out, and how provenance gets kept from the first generation.
Setting up access and workspace conventions for the tool
Why a cameo feature needs consent on paper first
Reading the usage policy
Content credentials and the visible watermark, and why they matter
Setting an approved-input rule so client footage stays out
03
From brief to shot list
150 minIntermediate
Teams turn a creative brief into a scene breakdown and a shot list built for generation. Then they practice describing each shot in the camera language a prompt actually understands.
Turning a brief into a scene breakdown and shot list
Shot type, camera movement, framing, and pacing as prompt vocabulary
Reference images and starting frames to anchor a look
Sequencing shots so a cut can breathe against neighboring footage
Scoping to this quarter
04
Motion and iteration across a continuous cut
150 minIntermediate
Participants build an iteration loop for motion the way a director works a take. Change one variable. Diagnose the miss, then hold character, wardrobe, and setting steady across several shots.
Prompting motion and camera movement
One variable, one change
Remix and iteration tools that refine a shot without a restart
Holding character and wardrobe steady across several settings
Naming the recurring failures, from morphing to temporal drift
When to regenerate or edit around it, and when to drop the shot
05
Review and the handoff to editing
120 minIntermediate
A generated shot isn't a finished asset yet, so this module builds a review rubric and a clean handoff package an editor can drop straight into a timeline.
Setting quality criteria before generation starts
A review rubric: brief fit, continuity, motion, brand risk
Packaging clips and provenance metadata for the edit
Working generated shots into an edit timeline next to live-action
A human check before a shot enters the cut
06
Provenance and rights for a governed pilot
120 minAdvanced
The last module makes responsible use routine. It keeps a provenance record from prompt to export and gives the team a place to route rights and consent questions. A pilot with clear cost visibility closes it out.
Keeping a provenance record from prompt to final export
What a workflow can document, and what only legal counsel can clear
Disclosure norms for AI video across different platforms
Running a pilot with a champion model and honest cost tracking
A capstone that plans, generates, reviews, and hands off one shot

What you will learn

Tell where generative video earns its place in your pipeline
A shot list and storyboard built for generation
Prompt motion and camera movement
Spot a bad take fast
Iterate one variable at a time
Run a shot through the review rubric before it ships
Keep a provenance record from prompt to export
Know who signs off on rights, consent, and likeness

Who should attend

Video producers and content-production teams
Social and brand video creators
Marketing and creative agencies making client video
Anyone briefing a shoot from a script or a deck
Editors who now get generated footage in their bin

Plan on about 12 hours, usually spread across two days or broken into half-day blocks around a live production schedule. Onsite and live-online sessions run the same workshop syllabus, adjusted to your approved tools and asset rules.

Format: Onsite or live online
Duration: 2 days (about 12 hours, can be split into half-day sessions)
Group size: Up to 16 participants per group
Language: English or Turkish
Materials: Shot-list and storyboard templates, prompt workbook, and a provenance and review checklist
Certificate: Certificate of completion

Zeo started in 2011 and now works out of San Francisco, Istanbul, Ankara, and Lisbon. We run Copilot Academy and organize Digitalzone, an international digital marketing conference. This program draws on the 10+ years of consulting and training work behind that, applied to corporate AI adoption.

2011founded in Istanbul
10+years of consulting and training experience
3offices: San Francisco, Istanbul, Ankara, Lisbon

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Send over what your team produces and which tools or assets are cleared. Then show us where rights or review tend to get stuck. We build the exercises and the workflow around exactly that.

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AI Video Production Training: Sora & Generative Video