When people talk about AI video generation, they often reduce it to a technical process: type in a prompt, wait a few seconds, and you get a video. But anyone who has spent real time with these tools knows the truth: creating something that feels intentional, cinematic, or beautiful requires far more than typing words. It requires taste, design sense, and an understanding of how to work with — and around — the limitations of current systems.
For context, I put together a short Sora video of Pikachu in a forest — a simple, documentary-style shot. My goal was to capture a sense of magic and liveliness, with just a touch of nostalgia.
Why Taste Matters More Than Technology
AI video systems are powerful, but they are also blunt instruments. They can generate movement, textures, and lighting, but they don’t know the difference between clumsy motion and cinematic motion, or between chaotic visuals and composed imagery. That’s where taste comes in.
Taste is knowing when to hold back, when to simplify, when to direct the focus toward subtlety instead of spectacle. It’s what makes the difference between something that looks like a random clip and something that feels like it belongs in a documentary.
Design Sense as Direction
Good design isn’t about piling on features — it’s about restraint, clarity, and intention. The same applies to AI video. You’re not just describing “what” you want to see, but how it should be experienced.
In filmmaking, directors use camera angles, lighting, and pacing to tell stories. In AI video generation, those choices still matter — but you translate them into conceptual direction rather than physical equipment. The AI doesn’t make those decisions for you. You still have to decide whether the scene feels static or alive, whether it conveys intimacy or distance, and how it should unfold for the viewer.
Working Within Limitations
Here’s the reality: today’s AI systems can’t do everything. They struggle with consistency, with complex motion, with fine control over small details. Instead of fighting these limitations, the creative approach is to adapt to them.
That means leaning into what the system is good at — atmosphere, mood, texture — and designing around what it struggles with. It means using stillness when smooth animation isn’t possible, or cinematic camera movement to create emotion without relying on character action. It’s about turning constraints into stylistic choices.
Prompt Engineering as Creative Mediation
Much has been written about “prompt engineering,” but I see it less as engineering and more as creative mediation. You’re standing between the world you imagine and the tool’s capabilities, finding the right balance of direction, restraint, and emphasis to coax the system toward your vision.
The best prompts aren’t about magic keywords. They’re about clarity, intent, and the ability to think like a designer: what should be emphasized, what should be excluded, and how to frame the experience in a way the AI can reliably reproduce.
Post-Processing
AI-generated video is rarely perfect on the first try. Models can introduce awkward timing, visual noise, or jarring transitions. But with careful post-processing — refining cuts, stabilizing shots, correcting color, and designing audio atmospheres — the work can evolve from an interesting clip into something that feels intentional and alive. Adding sound design, in particular, transforms perception: the rustle of jungle leaves, distant bird calls, or the low hum of ambience can anchor even a simple shot in reality.
The Human Role in AI Creation
Good AI videos are a product of choices: to simplify, to lean into cinematic perspective, to treat limitations as opportunities for style.
That’s why AI video generation isn’t replacing creativity — it’s testing it. It asks us to bring taste, design judgment, and adaptability to every project. The AI may generate the pixels, but we are still the ones who direct the vision.
And that’s the art of it — or at least, as close as we get (for now).