Optimal results from AI vision models require model-specific prompting. Seedance V2 thrives on highly detailed prompts, especially for preserving character identity and motion. In contrast, models like Kling 3 can perform better with more straightforward, less verbose instructions, demonstrating there's no one-size-fits-all approach to prompting.

Instead of writing prompts from scratch, upload visual references (like a mood board) to ChatGPT. Ask it to describe the visual qualities and language of the images, then use that output as a detailed prompt for AI image generators to replicate the desired style.

Avoid writing long, paragraph-style prompts from the start as they are difficult to troubleshoot. Instead, begin with a condensed, 'boiled down' prompt containing only core elements. This establishes a working baseline, making it easier to iterate and add details incrementally.

The quality and vision of an AI-generated video are determined more by the source reference images and videos than by the text prompt itself. Providing a strong visual reference gives the model a clear understanding of taste, style, and desired outcome, acting as a more powerful input than descriptive text alone.

To generate more aesthetic and less 'uncanny' images, include specific camera, lens, and film stock metadata in prompts (e.g., 'Leica, 50mm f1.2, Kodak Tri-X'). This acts as a filter, forcing the model to reference its training data associated with professional photography, yielding higher-quality results.

Instead of random prompting, break down any desired photo into its fundamental components like shot type, lighting, camera, and lens. Controlling these variables gives you precise, repeatable results and makes iteration faster, as you know exactly which element to adjust.

Standard prompts for creative tasks often yield generic, 'AI slop' results. To achieve exceptional design or copy, use hyperbolic, aspirational language like 'make it look like I spent a million dollars on design.' This 'desperate prompting' pushes the model beyond its default, mediocre state to produce higher-quality, unique work.

Midjourney's mood board feature can average out the aesthetics of multiple images, leading to generic results. For more precise control, use individual images as style references (`s-refs`). This allows the model to pull more distinct and impactful stylistic elements.

To get superior results from image generators like Midjourney, structure prompts around three core elements: the subject (what it is), the setting (where it is, including lighting), and the style. Defining style with technical photographic terms yields better outcomes than using simple adjectives.