Hey devs,
Over the past few weeks, I’ve been working on Veo3.im — a tool that generates short videos from natural language prompts. It’s part experiment, part product, and full of engineering headaches that I think are worth sharing.
This post covers the problems I hit, how I tackled them, and where things are still messy. If you’re building in the AI/ML/video space (or thinking about it), this might save you some time — or at least give you something to improve on.
🚧 Problem #1: Low-Res Video Output (512p Is Just Not Enough)
Most pre-trained video models default to low-res outputs — typically 512p or 768p — which are okay for demos but fall apart when you try to use them in real-world content (e.g., YouTube Shorts, Reels, TikTok).
I initially tried a naive fix: stack a super-resolution layer post-inference. It sort of worked, but introduced edge noise and artifacting.
🛠 Final approach:
I redesigned the output pipeline to:
Generate video in discrete high-precision blocks (each representing a semantically consistent scene),
Apply post-composition techniques before stitching frames,
Use model-driven frame interpolation for smoother transitions.
This allowed us to reach clean 1080p export with acceptable processing time, and the results are finally “shareable” quality.
🧠 Problem #2: Users Write Beautiful Prompts. Models Need Structure.
People love writing prompts like:
“A blonde woman in a wedding dress walking by the sea at sunset.”
That’s fine for a human, but for a model, it’s noisy, ambiguous, and underspecified. The early outputs were… surreal.
💡 My solution: a "Prompt Semantic Splitter"
I built a layer that takes raw prompts and decomposes them into:
appearance_embedding: what the character looks like
scene_layout: background elements, lighting, horizon logic
motion_block: direction, pacing, physical interactions
Think of it as structured slot-filling but designed for scene composition. We’re essentially creating a mini-scene graph that gets converted into model-friendly data.
💬 UX Matters: Why I Introduced a $9.9 Trial
After launch, I got a lot of feedback that users liked the concept but didn’t want to subscribe blindly without knowing what they’d get.
So I added a low-risk entry point:
$9.9, 3 days, unlimited prompts, 1080p export.
It’s not about monetization — it’s about onboarding users into a very experimental product while gathering real-world prompt data to improve the system.
🧪 Still in Progress (Help Wanted)
Some parts of this system are still fragile or incomplete. Here’s what’s top of my backlog:
Better camera movement logic: right now, it’s fairly rule-based and lacks dynamic transitions.
Music sync: generated audio doesn’t always align with scene pacing.
Storyboard module: currently in A/B testing with different prompt-to-shot models.
If you're working on similar problems or interested in the stack, happy to chat. I'm especially curious about how others are doing scene decomposition and frame synthesis for generative media.
🔗 Try It / Break It / Suggest Something
If you want to give it a spin or just inspect the output quality, here’s the link:
👉 https://veo3.im/
You can use the trial without commitment. If you do test it, I’d really appreciate feedback on:
Prompt effectiveness
Motion smoothness
Clarity/resolution
What made you go “nope” and close the tab 😅
Thanks for reading. If you’ve worked on generative video or similar pipelines, I’d love to hear your take. Drop a comment or DM me here on dev.to — open to exchanging ideas, approaches, and even co-dev if there’s interest.
Let’s build weird, useful things together. 🚀
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