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@salsabil.fs2: waasikkk💃💃💃

͟͟͞🦋 ⃝𝄞𝐒𝐀𝐋𝐒𝐀🥀
͟͟͞🦋 ⃝𝄞𝐒𝐀𝐋𝐒𝐀🥀
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Saturday 29 August 2026 15:40:59 GMT
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กลิ่นไม้สุดหรู เหมาะทั้งผู้ชายและผู้หญิง กลิ่นไม่ธรรมดาไม่ซ้ำใคร กลิ่นสนเบาๆ ฉีดไปเดตหรือช้อปปิ้งดูดีมาก เป็นน้ำหอมที่ฮิตมากในไทย#น้ำหอมติดทน #น้ำหอมราคาถูก #น้ำหอมสาวไทย #น้ำหอมกลิ่นดี #น้ำหอมพกพา
กลิ่นไม้สุดหรู เหมาะทั้งผู้ชายและผู้หญิง กลิ่นไม่ธรรมดาไม่ซ้ำใคร กลิ่นสนเบาๆ ฉีดไปเดตหรือช้อปปิ้งดูดีมาก เป็นน้ำหอมที่ฮิตมากในไทย#น้ำหอมติดทน #น้ำหอมราคาถูก #น้ำหอมสาวไทย #น้ำหอมกลิ่นดี #น้ำหอมพกพา
Peace Path
Peace Path
م تفرض نفسك على زول🤎.#احمد_حفظه #احمد_الخيال🤎🐎
م تفرض نفسك على زول🤎.#احمد_حفظه #احمد_الخيال🤎🐎


Some moments don’t need words💔 @Imran Khan Official @PTI OFFICIAL #imrankhan #lordscricketground #Cricket #pakistan #fupシforyou
Some moments don’t need words💔 @Imran Khan Official @PTI OFFICIAL #imrankhan #lordscricketground #Cricket #pakistan #fupシforyou
OpenAI and Anthropic engineers revealed the prompt techniques they use through internal documents. What stands out is how different their approach is from how most people use AI. Prompting is not treated as clever wording or guesswork, but as system design built around structure, constraints, and controlled behavior. Instead of relying on vague instructions, they define strict rules that limit what the model can and cannot do. Instead of writing one long request, they break complex tasks into smaller steps that validate each other before moving forward. Instead of hoping the format stays consistent, they enforce structure so outputs remain reliable every time. They also separate system rules from user input to keep behavior consistent, adjust temperature based on the type of task, and add self checks before the final answer is returned. The goal is not to sound impressive. The goal is to reduce errors, increase first pass success, and produce results teams can actually trust. Across real workflows, these patterns lead to measurable improvements in quality, consistency, and time saved. The gap is not model intelligence. The gap is prompt discipline. What are your thoughts on this? 🤔💬 #ai #automation #Tech #ainews #aitools
OpenAI and Anthropic engineers revealed the prompt techniques they use through internal documents. What stands out is how different their approach is from how most people use AI. Prompting is not treated as clever wording or guesswork, but as system design built around structure, constraints, and controlled behavior. Instead of relying on vague instructions, they define strict rules that limit what the model can and cannot do. Instead of writing one long request, they break complex tasks into smaller steps that validate each other before moving forward. Instead of hoping the format stays consistent, they enforce structure so outputs remain reliable every time. They also separate system rules from user input to keep behavior consistent, adjust temperature based on the type of task, and add self checks before the final answer is returned. The goal is not to sound impressive. The goal is to reduce errors, increase first pass success, and produce results teams can actually trust. Across real workflows, these patterns lead to measurable improvements in quality, consistency, and time saved. The gap is not model intelligence. The gap is prompt discipline. What are your thoughts on this? 🤔💬 #ai #automation #Tech #ainews #aitools

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