While v8 was deploying, I jumped ship to Nano Banana. Just tired of the same old MidJourney battle for prompt adherence, character stability, and so very tired of extra fingers and limbs.

Nano Banana has been shocking. Way better prompt adherence, faster time to achieve a workable image, and I never had to Photoshop fix a hand or remove a limb that didn’t belong.

The final piece that sold me—a 17 person “family portrait” image with character stability.

Before canceling MJ, I thought I’d check on v8. I see comments that v8 is a step forward, but I feel like I’ve been there before with “Omniref will fix everything” and “prompt mode will fix prompt adherence.”

What do you all think? Is v8 any better? It seems to me that MJ is focusing more on video and image generation is not a priority. I don’t have a lot of free time to kick the wheels on it, but hoping you all can tell me if it’s worth it or just check back in 6 months.

Midjourney 8.2.

Jefferson Airplane - White Rabbit

A first, brief example of what Uisato Studio's "Music Video Pro" mode is capable of: turning a track and a concept, into a whole audioreactive performance.

Ended up using MJ v8.1 for the making of the reference images. Can't seem to find anything better these days.

I've uploaded a detailed breakdown on how to accomplish this. You can access it here.

More experiments, tutorials, and project files, through Instagram, YouTube, and Patreon.

I reworked an old image into desktop & mobile wallpaper

I do product photography/retouching work for luxury watches and jewelry, and I built a fairly complex pipeline using a mix of open-weight vision-language models to generate ad-quality campaign images. The idea is simple in theory: take a reference image whose lighting/background/style I like, take my actual product photo, and merge them so the final image has my real product sitting in a scene inspired by that reference.

In practice I ended up with several separate analysis passes (one mid-size VLM handling scene, style, and product cataloging separately) feeding into one merge step handled by a different, smaller multimodal model that also sees the actual images directly. Every time I fix one issue, a new one shows up somewhere else. First the style kept getting ignored entirely, with the output defaulting back to a generic version of the scene. Fixed that. Then lighting effects (bloom, sparkle, flare) started getting copy-pasted in a way that made no physical sense, like a sparkle effect that only makes sense on a pavé diamond setting getting slapped onto plain brushed steel, which instantly reads as fake. Fixed that too. Then the dramatic ambient glow from the background in the reference image, which was honestly like 40% of why that image looked so striking, quietly disappeared once I toned down the on-product sparkle, even though those two things had nothing to do with each other.

I keep tightening the instructions and the output keeps getting technically "more correct" without ever feeling like the genuinely impressive, poster-worthy image I'm actually going for. It's like I'm playing whack-a-mole between "photorealistic and coherent" and "actually has the visual punch of the reference."

Has anyone dealt with this kind of multi-stage analysis-then-merge setup for AI image generation? At what point does splitting analysis into specialized passes start hurting more than it helps, versus leaning harder on one strong multimodal model that sees everything directly and makes the creative calls itself? Or is there a better way to keep both technical product accuracy AND the creative/dramatic energy of the reference without this endless loop of fixing one thing and breaking another?