u/descgamqui

been thinking about this a lot lately working across a few different projects. the way I see it there's basically three levers and you rarely get all three at once. high quality usually means slower generation or higher credit costs. fast and cheap tends to mean more retries and more editing time on the back end. so the "cheapest" option often isn't once you factor in the failed generations and cleanup work. from what I've seen, the tools worth paying for aren't always the most impressive on a single demo clip. it's more about consistency across a batch. if you're making 20 short social clips a week, you want something that doesn't randomly break on clip 14. tools like Veo 3 get a lot of attention for the quality ceiling but for volume work, I've heard people getting solid results from Kling and Wan too, just depends what you're optimising for. the stat floating around about 60-second clips going from like 13 days to under 30 minutes sounds wild but honestly tracks with what teams are reporting. my rough take is the sweet spot right now is AI for drafts, concept testing, and anything that would've been cut from the budget entirely before. not trying to replace a proper hero shoot with it. curious though, for people actually shipping content regularly, are you sticking to one tool or mixing models depending on the job?

Been thinking about this a lot lately, especially with how much the conversation has shifted from "will AI replace VFX artists" to "okay so where does it actually slot in usefully.", From what I can tell, the stuff that's genuinely working right now is more on the unglamorous end, rotoscoping, cleanup, AI-estimated depth maps, matchmove assist, early concepting, that kind of thing. Not the sexy final-shot magic people were promising a couple years ago, and honestly that hype still hasn't really landed. AI denoising feels like the clearest win at this point, it's basically standard in most major, renderers now and it just quietly fits into existing lighting and render workflows without much drama. The more generative stuff is trickier to pin down. ComfyUI gets brought up heaps in these conversations and I think "experimentation layer" is still a fair description for a, lot of uses, though it's worth saying some studios are running it in more pipeline-adjacent ways now, not just hobbyist tinkering. It's a node-based workflow interface so the results really depend on what models and tools you're plugging into it, ControlNet, SAM, inpainting, that kind of stack. Useful for generating reference, prototyping ideas, or handling narrow steps before you commit to a full pipeline. The depth map thing is real but worth flagging that quality and consistency are pretty variable and usually need cleanup, it's not a reliable out-of-box solution. Biggest wall I keep hearing about is temporal consistency and deterministic control, anything needing shot-to-shot reliability, or tight art direction still needs a human watching every frame, and that's not a small caveat. Curious what people here are actually using day to day, real production use vs. just playing around. And whether anyone's found ways to integrate genAI tools into a Nuke or Resolve workflow that actually holds up under proper delivery standards.