Beautiful is easy. Recognizable is hard. That’s the wall u/BroadLadder6343 kept hitting while building a reference-to-image prompt system for beauty and skincare advertising, and the fix is a clean pattern break worth stealing for anyone doing AI product visuals.
Any image model can make a skincare bottle look luxurious under moody light. The much tougher job is making sure it’s still the same bottle after the prompt runs, same cap, same label, same shade of glass. That gap between “pretty picture” and “actual product” is exactly what this Redditor set out to close.
Quick start: this Redditor’s approach flips the usual prompting habit. Instead of writing prompts around vibes like “make this luxurious” or “make this cinematic,” the reference photo becomes the source of truth for the product, and the prompt only controls the advertising direction around it. Below is what changes, why it matters, and how to apply it to your own product shots.
The problem most people run into
According to the original poster, the failure modes showed up again and again once “beautiful” became the only goal:
- Packaging geometry quietly shifting shape
- Labels or branding drifting off-model
- Materials turning unrealistic (glass reading like plastic, metal reading like paint)
- Closed products suddenly rendering open
- Colors shifting between generations of the same asset
- A final image that looks great but no longer feels like the product on the shelf
Every one of those breaks trust with the exact person the ad is trying to convert. A shopper who has held the real bottle notices the fake one immediately.
🔄 Old Way vs New Way
The old habit treats the prompt as the whole instruction set. You describe the look you want, the model interprets the product loosely, and consistency becomes a coin flip across every generation.
The new approach this contributor landed on splits the job in two: the reference image locks identity, and the prompt only steers direction. That single division is the whole insight. It’s not a bigger prompt or a fancier model, it’s a different assignment of responsibility between image and text.
What the system is built to preserve
Once identity and direction got separated, the author’s prompts started explicitly protecting:
- Geometry (the actual shape of the packaging)
- Packaging and material realism (glass, foil, matte plastic, whatever the real product uses)
- Branding and typography (no melted logos, no invented fonts)
- Colors, held consistent across generations
- Product state (open stays open, closed stays closed)
- The small recognizable details that make a shopper go “yes, that’s the one”
That list eventually grew into a library of 100 beauty and skincare reference-to-image prompts, split across skincare, makeup, fragrance, and hair and body. This industry pro reports the full library has been reviewed as production-ready, with 12 prompts visually verified against a real reference-product library. That’s a meaningful signal: verification against actual products, not just eyeballing whether an image looks nice.
How to apply this to your own product shots
- Start from a clean reference photo of the real product. This is now your identity anchor, not just an inspiration image.
- Write the prompt to control direction only: lighting, setting, mood, composition. Leave shape, label, and material decisions to the reference.
- Add explicit preservation instructions for the details that tend to drift: exact packaging geometry, exact typography, exact color values, and current product state (open or closed).
- Generate, then compare side by side against the reference. Check geometry, branding, material, and color as four separate pass or fail checks, not one vague “does it look right” glance.
- Iterate on the direction language only. If identity drifts, that’s a reference or preservation-instruction problem, not a direction problem, so fix that layer instead of rewriting the whole prompt.
- Reuse the same reference across a campaign so every ad variation stays visibly the same product, just styled differently.
That workflow is a genuinely different mental model from “describe what you want and hope.” It treats the reference image the way a brand guideline treats a logo file: non-negotiable, while everything else flexes.
One Reddit commenter dismissed the post as “sneaky advertising,” and sure, self-promotion in a prompt engineering subreddit always draws that reaction. But the underlying technique holds up on its own merits regardless of who’s selling what: separating identity control from direction control is a solid instinct for any product visual, not just beauty and skincare.
If you’re generating product ads and fighting the same drift problems, packaging warping, labels sliding, colors shifting, try restructuring your next prompt around this split! Let the reference image own what the product is, and let the prompt own what the ad feels like. Then head over to the original Reddit thread to see the before-and-after examples and ask the creator about the free sample prompt pack mentioned in the post.
Same product, better prompt: what changed my AI beauty product ads
by u/BroadLadder6343 in PromptEngineering