When I first started creating AI-generated videos, I thought the hardest part would be writing better prompts.
I couldn't have been more wrong.
Over the past few months, I've gradually built a workflow that actually works quite well. ChatGPT is usually where I generate reference images and visual ideas. Once I have something I like, I move to Claude to polish the prompts, rethink the scene, or fix all the little details that somehow never look right the first time. Finally, everything goes into Seedance to generate the animation.
On paper, it's a pretty good workflow.
In reality... it feels surprisingly exhausting.
One moment really made me stop and think.
I had just spent almost fifteen minutes refining a prompt in Claude. The pacing finally felt right. The visual style was consistent. The camera movements were exactly what I wanted. I copied everything into Seedance, expecting to finally generate the animation.
Instead, it interpreted the same prompt completely differently.
The camera angles changed. The expressions were off. The atmosphere felt wrong.
So I started editing the prompt again.
Another time, ChatGPT generated an image that I absolutely loved, but when I tried to animate it, the framing didn't work. I had to go back, regenerate the image, adjust the composition, and then repeat the whole process.
None of these tools were doing anything wrong.
In fact, each of them is probably one of the best tools available for its specific job.
The problem was everything between them.
Every time I switched platforms, I had to upload files again, copy prompts, rebuild context, and explain my project one more time because each model "understood" the task a little differently.
At first, I thought this was simply part of creating with AI.
But after repeating the same process dozens of times, I realized something that felt a little uncomfortable.
I wasn't spending most of my time creating anymore.
I was spending it managing my AI tools.
That realization completely changed how I think about AI.
For the past two years, almost every conversation has been about building smarter models. Every new release promises stronger reasoning, better coding, better image generation, or lower latency.
And honestly, they've all improved dramatically.
But while individual models keep getting better, using multiple AI tools together still feels surprisingly fragmented.
Every new model promises to save me time.
Yet every new tool also introduces another interface, another prompt format, another place where context gets lost.
Ironically, the more capable my AI toolkit became, the more time I spent switching between it.
I don't think this is just a problem for video creators.
Developers jump between coding assistants, documentation tools, deployment platforms, and different LLMs.
Designers move between image generation, editing software, and prototyping tools.
Writers constantly switch between research assistants and editing models.
Everyone is using the right tool for the right task.
But every switch carries a hidden cost.
Not money.
Attention.
Context.
Creative momentum.
That's why I don't think the next big challenge in AI is simply building a model that's another 5% smarter.
I think it's reducing the friction between the models we already have.
Lately, I've become less interested in asking:
"Which AI model is the best?"
Instead, I keep asking myself:
"How can different AI models work together so naturally that I stop thinking about the tools altogether?"
Maybe the future of AI isn't about replacing every model with one supermodel.
Maybe it's about building workflows where every model does what it does best, while the transitions between them become almost invisible.
I'd love to hear how other creators and developers are dealing with this.
Has AI actually simplified your workflow?
Or has it quietly made it more complicated?
Top comments (0)