The Complete Guide to Generating Video with AI

Most people's first AI video attempt is one line of text and a hope. Sometimes that works. More often, what comes back doesn't match what was actually in your head, not because the tool is bad, but because "a dog running on a beach" leaves far too much open for it to guess at.

Here's the full process for getting a shot that actually looks like what you pictured, from planning it out to editing the final result together.

1. Know what you're actually making

An AI-generated ad, a short story, a product demo, a quick social clip, each of these wants something different from you before you generate a single frame. An ad might need a clean product shot with specific framing. A short story might need consistent characters across several scenes. Figure out which one you're making first, since it decides almost everything else on this list: length, style, and how much control you'll actually need.

2. Plan the shot in detail before you prompt

This is the step that separates a usable result from a lucky one. Before you open a video tool, write out what you actually want: the subject, the setting, the action, the mood, and anything specific about how it should look. "A dog running on a beach" leaves the model guessing at everything. "A golden retriever running along the shoreline at sunset, sand kicking up behind it, warm orange light" gives it something real to work with.

If you're not sure how to put that into words, talk it through with Claude or ChatGPT first, either works fine for this. Describe the shot roughly, even messily, and ask it to help you turn that into a clear, detailed prompt you can actually use. Coming into the video tool with a ready-made prompt beats improvising one on the spot almost every time.

3. Decide the length up front

Shorter clips are more controllable and cheaper to generate, and it's much easier to keep a 4-second shot coherent than a 60-second one. Longer generations are more likely to drift, a face that shifts slightly, an object that wasn't there a second ago, small inconsistencies that get more likely the longer the clip runs. Decide roughly how long you need the final piece to be before you start, since that shapes whether you're generating one clip or planning to stitch several together.

4. Think about camera angles and movement

Static shot, slow pan, zoom, a tracking shot following the subject, these all read completely differently to a viewer, even if they couldn't tell you why. Decide on purpose rather than leaving it to whatever the model defaults to. A static shot reads calm and observational. A slow push-in reads tension or focus. Naming the camera movement you want in your prompt, rather than leaving it out, is one of the easiest ways to make a generated clip feel intentional instead of random.

5. Decide: pure text-to-video, or start from a reference image

If you need a specific character, product, or scene to carry through consistently, whether that's across one clip or several, starting from a reference image gives the model something concrete to anchor to instead of reinventing the look each time. If you're fine letting the model imagine the whole thing freely and consistency across multiple shots doesn't matter, pure text-to-video is simpler and faster. Know which one your project actually needs before you start generating, switching approaches partway through usually means starting over.

6. Pick the right tool

For most people getting into AI video, use OpenArt. It gives you one subscription across more than 100 image and video models instead of paying for several separate tools, so you can match the model and quality tier to what a specific shot actually needs rather than being stuck with one option for everything.

Two features are worth knowing about specifically. If step 5 pointed you toward a reference image, OpenArt's character tool holds a face, outfit, and look steady across scenes and angles, genuinely one of the stronger consistency tools available right now. And if you're planning something longer with multiple scenes, OpenArt's Director tool turns a plain-language description of the whole video into a script, storyboard, and finished multi-scene video, up to five minutes, using your saved characters to keep everything consistent throughout.

7. Generate in clips, usually short ones

Most of the time, you'll get better, more consistent results generating in short clips and stitching them together rather than fighting for one long perfect take, since drift and small errors get more likely the longer a single generation runs. That said, it's not an absolute rule, depending on the tool and what you're making, a longer single generation can work fine, especially for simpler shots with less happening in them. Treat "generate short" as the safer default, not a hard limit.

8. Review specifically for AI video's tells

Before you move on, watch the clip back specifically looking for the things that give AI video away: hands or faces that warp or morph, objects that flicker or shift slightly between frames, details that are consistent in one moment and wrong in the next. These are easy to miss on a casual watch because the overall motion looks convincing, but they're exactly what an audience notices first. Catching them now is cheaper than catching them after you've already built an edit around the clip.

9. Edit and stitch it together, if that's relevant

If you're working with more than one clip, or the piece needs music, pacing, or transitions, a real edit pass still matters, AI video generation gets you the raw footage, not the finished piece. Not every project needs this though, a single short clip for a quick social post might genuinely be done the moment it looks right, so treat this step as "if appropriate" rather than mandatory for everything you make.

10. It gets better with practice

The gap between your first attempt and your tenth is usually bigger than the gap between different tools. You'll get faster at spotting what a prompt is missing, better at predicting how a model will interpret a phrase, and quicker at noticing which shots need a reference image and which don't. Treat the first few generations as learning how the tool thinks, not as a judgment on whether AI video works for what you're trying to make.