This paper broke my brain Researchers gave Claude a simple question: “I want to wash my car. The car wash is 100 meters away. Should I walk or drive?” Claude said walk. Every major LLM said walk. The correct answer is drive. The car has to be there. Here’s the wild part:
@godofprompt
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Creativity through constraint and surprise
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Let me tell why this works… Creativity = constraint + pressure + surprise. Generic prompts remove all three. This structure injects all three simultaneously. Here.. you are not asking the LLM to be creative, you're building a box so specific that the only way out is through
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Why ‘Be Creative’ Fails in AI
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First, understand WHY "be creative" fails. AI creativity is probabilistic. It defaults to the most statistically common answer. "Be creative" has no constraints.
No constraints = no creative pressure.
No pressure = average output. The fix isn't less structure. It's MORE of the -
Framework for AI Creativity
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Asking AI to "be creative" is the laziest prompt you can write. And it produces the laziest output. After 3 years of daily ChatGPT use, I cracked the structure that actually unlocks original, unexpected, usable creative work. Here's the exact framework
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The Hidden Truth Behind 2026’s Massive Context Windows
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Everyone's bragging about 200k, 1M, even 10M token context windows in 2026. Nobody's talking about what actually happens inside them. I just fell down this rabbit hole and I can't stop thinking about it: A new paper published January 2026 tested hundreds of thousands of data
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Multi-agent system builds from YouTube tutorials autonomously
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This guy literally built a multi-agent orchestration system with Opus 4.6 to watch YouTube tutorials and execute them autonomously 😳 pic.twitter.com/hZYy1QkruD
— God of Prompt (@godofprompt) 24 février 2026This guy literally built a multi-agent orchestration system with Opus 4.6 to watch YouTube tutorials and execute them autonomously
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Critique of AI-generated ad copy targeting
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You prompt Claude with "write ad copy for my target audience." Based on what? Recycled marketing blogs. Vibes. Zero real humans consulted. And "synthetic personas" are worse. You're paying for AI to pretend to be your customers. Studies show they miss emotion, intuition, and
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Context Stacking vs Role-Playing in Prompts
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"Act as an expert" gives you a costume. Context Stacking gives you a thinking partner. I've used this across landing page copy, debugging, strategy decks, and cold outreach. Same model. Completely different results. Save this. Your prompts will never look the same.
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AI mimics devs but lacks real expertise
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When you say "act as a senior developer" the model doesn't think like one. It writes like one. Big difference. It pattern-matches to how developers sound in training data. Not how they actually solve problems. You get confident-sounding output. Not expert-level thinking.
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Context Stacking for Better AI Results
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I finally understand why "act as an expert" prompts are destroying your results. After 200+ tests across Claude, ChatGPT, and Gemini I found what actually works. It's called "Context Stacking" and it doesn't ask the AI to pretend anything. Here's the technique ↓