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.
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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.
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.
Using adjectives like 'elite' (e.g., 'You are an elite photographer') isn't about flattery. It's a keyword that signals to the AI to operate within the higher-quality, expert-level subset of its training data, which is associated with those words, leading to better-quality output.
Instead of accepting an AI's first output, request multiple variations of the content. Then, ask the AI to identify the best option. This forces the model to re-evaluate its own work against the project's goals and target audience, leading to a more refined final product.
To correct an AI's output when it's off track, use numerical multipliers to signal a dramatic shift. Instead of vague feedback, prompts like "be 100x more direct" or "make this 10x more creative" give the model a quantitative instruction to escalate its response, leading to more significant adjustments.
AI-generated text often falls back on clichés and recognizable patterns. To combat this, create a master prompt that includes a list of banned words (e.g., "innovative," "excited to") and common LLM phrases. This forces the model to generate more specific, higher-impact, and human-like copy.
Leverage AI as an idea generator rather than a final execution tool. By prompting for multiple "vastly different" options—like hover effects—you can review a range of possibilities, select a promising direction, and then iterate, effectively using AI to explore your own taste.
Instead of using AI to generate final creative work, use it as a tool for anti-inspiration. Figma's CEO asks generative AI for the "10 cliche ways to say this" so he can consciously push beyond the obvious and predictable. This technique helps creators find novel angles and maintain a unique voice.
To fully leverage advanced AI models, you must increase the ambition of your prompts. Their capabilities often surpass initial assumptions, so asking for more complex, multi-layered outputs is crucial to unlocking their true potential and avoiding underwhelming results.
Asking an AI to 'predict' or 'evaluate' for a large sample size (e.g., 100,000 users) fundamentally changes its function. The AI automatically switches from generating generic creative options to providing a statistical simulation. This forces it to go deeper in its research and thinking, yielding more accurate and effective outputs.
