How to Make Your First AI Video with SJinn, Step by Step

Your first AI video on SJinn takes about ten minutes, most of it spent thinking rather than clicking. The platform gives you several strong video models in one workspace, so the real skill is writing a good description and picking the right model for the shot. Here is the process, step by step, at the level SJinn's own pages support. If you have not yet skimmed what SJinn is and what it can make, do that first; it will make the choices below much clearer.

Step 1: Create your account and open the Workspace

Head to sjinn.ai and sign up. There is a free tier, so your first experiments cost nothing but time. Once you are in, open the Workspace, which is where your projects and generations live. You do not need to download anything; SJinn runs entirely in the browser.

Step 2: Decide the shot before you type anything

Write down, in one sentence, what should happen on screen. "A red paper boat floats down a rainy city gutter at night" is a shot. "A cool video about rain" is not. AI video models reward specifics: a subject, an action, a setting and a mood. Decide also whether you want the camera still, slowly pushing in, or tracking alongside the subject. You will put all of this into the prompt in the next step.

Step 3: Pick a model, or start from a Template

SJinn hosts several video models, and they have different strengths and credit costs. Seedance is the budget-friendly workhorse at 60 credits per second, and every paid plan includes Seedance 2.5 access. Sora 2 costs 80 credits per second, Veo 3 is the premium option, and Kling sits in the middle at 200 to 300 credits a clip. If choosing feels overwhelming, open the Templates section instead and start from a proven setup, then swap in your own subject. Not sure how the costs add up on your plan? Our SJinn pricing breakdown converts every model's price into plain numbers.

Step 4: Write the prompt like a film direction

A reliable prompt has four parts: subject, action, camera and style. For example: "A red paper boat floating down a gutter in the rain, camera tracking beside it at water level, cinematic night lighting, gentle and melancholic." Keep one action per generation. Asking for three events in five seconds muddles every model, not just SJinn's. Generate the clip, watch it fully, and only then judge it.

Step 5: Try image-to-video for more control

If text-to-video keeps missing your vision, flip the workflow. Generate the opening frame as an image first, using Nano Banana Pro or another image model, get it exactly right, then animate that still with the image-to-video tool, listed at 150 credits. This is the single most useful habit on the platform: a perfect first frame drags the whole clip up with it.

Step 6: Add voice, lip-sync and music

A silent clip often feels unfinished. SJinn connects to ElevenLabs for voiceover at 100 credits per 150 characters, offers image and video lip-sync so a face can speak your script, and generates music at 200 credits a track. Add these one at a time and re-check the result after each, so you know which layer helped and which one hurt.

Step 7: Polish and export

If the clip is a keeper but looks soft, the video upscale tool sharpens it at 150 credits per second. Paid plans remove the watermark, which matters if the video is headed for a client or a monetized channel. Before you spend credits on a long generation, test the same prompt as a short clip; a five-second proof tells you more than any preview image.

Three mistakes to skip

First, do not burn your best idea on your first generation; learn the controls on a throwaway shot. Second, do not stack every feature at once, because you cannot tell what went wrong. Third, do not judge a model by one bad prompt; rewrite the description once before switching engines. When you are ready to see how this workflow compares with dedicated single-model tools, read SJinn versus the other AI video generators.

That is the whole loop: describe, generate, review, refine. Your second video will be noticeably better than your first, not because the models changed, but because your prompts did. Save the descriptions that worked, because on SJinn a good prompt is a reusable asset, and the Skills feature exists precisely so you can bottle the workflows you repeat and run them again next week.