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.

With models like Gemini 3, the key skill is shifting from crafting hyper-specific, constrained prompts to making ambitious, multi-faceted requests. Users trained on older models tend to pare down their asks, but the latest AIs are 'pent up with creative capability' and yield better results from bigger challenges.

A powerful workflow is to explicitly instruct your AI to act as a collaborative thinking partner—asking questions and organizing thoughts—while strictly forbidding it from creating final artifacts. This separates the crucial thinking phase from the generative phase, leading to better outcomes.

To maximize creative exploration ("diverging"), don't rely on one tool. Run the same open-ended "explore" prompt in several different AI prototyping tools. Each tool's unique system prompts will yield surprisingly different design directions, giving you a wider range of ideas to evaluate.

Instead of spending time trying to craft the perfect prompt from scratch, provide a basic one and then ask the AI a simple follow-up: "What do you need from me to improve this prompt?" The AI will then list the specific context and details it requires, turning prompt engineering into a simple Q&A session.

Instead of giving an AI creative freedom, defining tight boundaries like word count, writing style, and even forbidden words forces the model to generate more specific, unique, and less generic content. A well-defined box produces a more creative result than an empty field.

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.

To get the best results from AI, treat it like a virtual assistant you can have a dialogue with. Instead of focusing on the perfect single prompt, provide rich context about your goals and then engage in a back-and-forth conversation. This collaborative approach yields more nuanced and useful outputs.

Achieve higher-quality results by using an AI to first generate an outline or plan. Then, refine that plan with follow-up prompts before asking for the final execution. This course-corrects early and avoids wasted time on flawed one-shot outputs, ultimately saving time.