Instead of trying to create a perfect prompt from scratch, instruct your AI assistant to ask you specific questions about composition, lighting, and mood. This turns the process into a guided discovery, forcing you to make crucial creative decisions you might have otherwise overlooked.

To get realistic, high-quality results from image generation AIs, provide extremely detailed prompts that include aesthetic, camera type, lighting, color palette, and a crucial call for "slight imperfections." This specific instruction helps the AI avoid generating overly polished and sterile stock-like photos, making the output more authentic.

If an AI-generated image isn't working despite multiple tweaks, the issue may be the underlying concept, not the execution. Instead of endlessly iterating with the generator, return to the ideation tool to fundamentally rethink and rewrite the core prompt. This diagnoses an "idea problem" instead of an "image problem."

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.

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.

The initial phase of prompting shouldn't aim for a perfect image. Instead, the goal is to generate quickly and analyze the results to understand how the AI is interpreting your inputs (mood board, prompts, s-refs). This diagnostic step is crucial for efficient iteration.

To get better initial results from AI ad tools, don't just specify what you want—also provide a list of negative constraints. Clearly state what the AI should not do, such as using certain illustration styles or off-brand colors. This helps avoid common AI pitfalls and reduces costly iteration cycles.

To consistently generate production-ready assets with creative LLMs, prompts must be structured around five key elements: Context (e.g., landing page), Style References (e.g., Stripe), Palette (specific hex codes), Copy (plausible text, not lorem ipsum), and precise Aspect Ratios/Resolutions for direct implementation without rework.

Use a conversational AI like Claude to collaboratively refine a vague idea into a detailed prompt. Then, take that perfected prompt to a different AI, like ChatGPT's DALL-E, for the actual image generation. This separates the creative strategy from the technical execution, yielding better results.