One of the most valuable lessons I’ve learned working with GenAI for image (and not only) generation is this: the real bottleneck often isn’t the model’s capability, it’s the translation layer between your vision and the model.
When we keep tweaking prompts, adding styles, shuffling adjectives, we’re really just guessing at how to bridge that gap. Sometimes, the fastest way forward is counterintuitive:
🔹 Don’t prompt for the image. Prompt for the prompt.
Instead of saying “make me an image of X,” try:
“Here’s the concept I want to visualize—how would you prompt for that?”
This works because the model is exceptionally good at teaching itself its own “dialect.” You’re not just outsourcing creativity—you’re outsourcing translation.
And here’s where it gets powerful: when you land on an output that feels exactly right, don’t just celebrate. Ask the model:
“What’s the ideal prompt to reproduce this result consistently?”
Over time, this practice gives you:
A reusable library of prompts that lock in style, mood, or structure
A clearer understanding of how the model maps language to visuals
A feedback loop where your intuition and the model’s strengths converge
Prompting for prompts isn’t a gimmick—it’s a way of collaborating with AI as both interpreter and co-creator.
Help the AI help you see what you see.
