Tips, tutorials, and insights on prompt engineering for ChatGPT, Claude, Gemini, and more.
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Prompt engineering is the craft of designing inputs, constraints, and feedback loops so LLMs behave reliably. Here's what it is and how it works.
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Prompt engineering is the discipline of designing, testing, and maintaining prompts as interfaces to LLM behavior-like programming, but in natural language.
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Most "AI prompts" are requests. Generative AI prompts are specs. Here's how to think about the difference and write both types on purpose.
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A practical, opinionated guide to chain-of-thought prompting-why it works, where it fails, and how to use it without getting fooled.
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A practical, developer-friendly way to write ChatGPT prompts that stay on-task, reduce drift, and produce usable outputs.
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This week's AI news is about shipping: turning plain English into optimization models, Claude-style local APIs, and benchmarks that punish agent demos.
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This week's AI news is about shipping: speed, standards, and deploying models into schools-while tightening safety and monetization.
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From MIT's push for sharper evaluation to streaming voice latency budgets and new local coding LLMs, AI is getting less flashy and more usable.
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This week's AI story isn't just new models-it's new plumbing for agents: packaged skills, auditable context, and systems that check their own work.
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Bedrock Knowledge Bases now retrieves across text, images, audio, and video-pushing enterprise RAG closer to "search everything" products.
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OpenAI tests ads, Google wires Gemini into your apps, and AWS shows what "production agents" really look like.
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AWS and Hugging Face just dropped practical blueprints for multimodal retrieval, agent tuning, and VLM OCR-plus a reminder that "AI ops" is the real battleground.