Who knew prompts could feel so sneaky?
@godofprompt
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Increasing AI Model Accuracy Benchmarks
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Shipping with 42% accuracy was cute. Now there’s no excuse not to hit 90%+.
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Building an AI agent for accurate information processing
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learn about it and build an agent that understand and can give accurate info
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Using Prompting to Build Product Features
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No code.
No technical experience.
No guessing. You’ll learn how to prompt your way through real product features like: Auth Payments Backend logic UX flows -
Ultimate Vibecoding Workshop on AI-Driven Development
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It’s called The Ultimate Vibecoding Workshop a live 2-hour Zoom session run by the team at Emergent. They’ll walk you through building a full product from scratch using just natural language prompts. Join here:
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Using Prompt Engineering to Launch New Applications
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Most people don't realize how close they are to launching something great. The only thing standing between your idea and a real app? A few good prompts. This workshop will show you exactly how it’s done:
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How to optimize AI output via role and tone setting
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3. Set the tone and role You don’t want generic output. So assign the AI a role: “You are a marketing strategist with 10 years of SaaS experience.” And set the tone: “Write in a concise, punchy style. Avoid buzzwords.” This gives the AI a voice and vision.
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Using Constraints to Improve AI Prompting and Output Quality
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2. Add structure AI loves constraints. If you want a framework, give it a format: “Write in this format: Hook, 3 bullets, Summary.” If you want code, give it the output: “Create a landing page with headline, email form, and mobile responsiveness.” Clarity creates quality.
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Optimizing AI performance through goal-oriented prompting
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1. Start with the outcome Don’t ask what the AI can do. Tell it what you want done. Not “write a plan” → Instead: “Help me outline a 5-day launch strategy for a fitness app.” AI works better when you show it the finish line.
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A 3-Step Formula for Writing Effective AI Prompts
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How to write prompts that don’t suck Most people type “help with blog post” and wonder why LLMs gives generic garbage. Here’s the 3-step formula I use to get sharp, useful outputs every time: