it has a tendency to gradually move towards highly desaturated color palettes. most prompts turn to mush after enough generations
PROMPT ENGINEERING
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The most complete tutorial on ChatGPT o3 and o4-mini
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I'm shocked – There are really people who think #ChatGPT o3 / o4-mini are bad AIs? Normal… They don't use them well. Here's when and how to use them → https:// youtu.be/AfZ0oVwYeGY PS: this is the most complete tutorial you'll find on these 3 AIs
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Generative Art Through Feedback Loops and GPT-Image
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There are many ways of making generative art, but my go-to has always been the feedback loop. Just do one thing over and over on the last output and watch unexpected artifacts emerge. With gpt-image, you can write that whole program in a prompt.
— Gene Kogan (@genekogan) 25 avril 2025
For example: "Make an exact copy… pic.twitter.com/tPCaxEsuASThere are many ways of making generative art, but my go-to has always been the feedback loop. Just do one thing over and over on the last output and watch unexpected artifacts emerge. With gpt-image, you can write that whole program in a prompt. For example: "Make an exact copy
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Steal my o3 prompt to multiply content with same tone
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Steal my o3 prompt to multiply any piece of content with the same tone of voice for any platform. ————————————
ULTIMATE CONTENT MULTIPLIER
———————————— You are an expert content strategist and voice-cloning specialist who -
Cheatsheet for reasoning models: mental structure matters most
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This cheatsheet works with all major reasoning models: – GPT-4o
– Claude Sonnet 3.5 / 3.7
– Gemini 1.5 / 2.5
– Mistral
– Meta's LLaMA It’s not about the model. It’s about the mental structure you give it. -
Two plug-and-play prompt templates for logical analysis and strategy comparison
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Here are a few plug-and-play prompt templates to try: “Act as a logical analyst. Evaluate 3 options for [X]. Use only deductive reasoning and output a step-by-step decision matrix.” “Compare 3 strategies to reach [goal]. Rank them by ROI, and explain using first principles.”
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Choose your output format to shape thinking
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Choose your output format. Why? Because format shapes thinking. Ask for: – Flowchart
– Logic trail
– Table of pros/cons
– Decision matrix
– Compare/contrast chart
– Hypothesis tree The model adapts to structure. -
List of reasoning types to ask the model
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Next, give it a reasoning task. This tells the model what kind of thinking to perform. Try these: – Tradeoff Analysis
– Root Cause Breakdown
– Ethical Scenario Assessment
– Heuristic Decision Tree
– Socratic Dialogue Be explicit.
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Assign a thinking role to sharpen model output
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First, assign the model a thinking role. This changes how it “shows up” mentally. Examples: – Strategy Consultant
– Logical Analyst
– Detective
– Policy Evaluator
– Research Synthesizer The more specific the role, the sharper the output.