Sora is stunning but not quite usable? It's more of an inspiration toy than a production tool

After Sora was released, many people around me tried it out immediately. The visuals are indeed stunning—lighting, materials, physical interactions—it's on a completely different level from previous AI videos. But after using it for two or three weeks, a common feeling began to emerge: Sora is cool, but it still has a way to go before it's "usable."

This isn't to say its technology is lacking. Rather, for most teams creating short videos and commercial clips, what an AI video tool truly needs isn't "the occasional viral hit" but "consistent output every time." From this perspective, Sora is currently more of an inspiration toy than a production tool.

Entry barrier: Only the step of "opening the webpage" is low

Sora's usage is very straightforward. Type in a text prompt, wait a few dozen seconds, and you get a video. Watching demos feels like the future, but when actually running projects, the problems become apparent.

First, controllability is weak. For example, if you write "a golden retriever running on a beach, nice sunlight," Sora might give you a very lively dog, but as it runs, the dog's fur color changes, or an entirely unrelated person appears in the background. This randomness is fun for personal experimentation but a disaster for deliverables.

Second, the cost of modifications is high. Whenever a client says "make the scene a bit darker" or "have the dog move left," in Sora you can only regenerate the entire clip. It's not that you can't try, but every attempt is a gamble—gambling on whether this generation will be lucky. For a slightly longer shot, just tweaking parameters can consume half a day.

In comparison, many teams have already shifted their approach

This is why platforms like getsora2 are starting to attract more attention. Their logic is different: instead of "letting AI freely create," they let you "use AI to enhance what you've already shot."

Here's an example. You shoot some live-action footage, but there's a visible green screen or uneven lighting in the background. The traditional approach involves chroma keying and color grading—time-consuming and labor-intensive. But on getsora2, using AI to directly process the original footage, it understands your intentions, corrects unnatural lighting, and even replaces the background—the generated video style can remain consistent with the live-action footage. This is "controlled generation," not "random generation."

Another common scenario is e-commerce product showcases. You shoot a lipstick ad, and the client wants to see two versions with different shades in the model's hand. If you regenerate with Sora, the new video might feature a different model or the lipstick's texture could change. But with tools like getsora2, you can lock the original footage and selectively replace the product itself. When the final versions are edited together, there's no issue of "shot discontinuity."

Stability and efficiency are the real dividing lines

If we only compare the "visual ceiling of a single frame," Sora still leads. But video is a continuous medium—one stunning frame isn't enough; every frame must be usable. Sora has improved rapidly in long-shot consistency, but its control over specific details remains "coarse." It's hard to tell it "don't break the cup at the third second," and there's no mechanism for local post-generation edits.

Services like getsora2, on the other hand, choose a more pragmatic entry point: they don't touch the "from zero to one" pure generation but instead focus on AI enhancement "from shooting to editing." This means every modification is predictable, and the toolchain is closer to traditional video workflows.

Of course, this comes with trade-offs. getsora2 requires you to have source material upfront; it can't create a completely new world from just a text prompt like Sora can. If I need to produce a fully fantastical scene that's impossible to shoot in reality, I'd still open Sora. But if I need a video that must be delivered tomorrow, I'd prioritize a platform with higher controllability.

Recommendations for choosing

Ultimately, the choice doesn't depend on "which is more advanced" but on what kind of work you have at hand.

• For concept design, mood boards, early creative references → Sora remains the strongest; it's suited for "divergence"
• For final deliverables, product assets, batch production → tools like getsora2 are more reliable; they're suited for "convergence"
• If budget and time are limited and you just want to output quickly → don't struggle with Sora; directly use controllable tools for peace of mind

AI video is improving rapidly, but between "usable" and "easy to use" lie countless compromises. My current advice is: treat Sora as an inspiration accelerator and getsora2 as a production pipeline. They don't conflict, but understanding which half is inspiration and which half is production is far more important than obsessing over parameters.