Не баг, а фича
Оригинальный первоисточник ИТ-лайфхаков и секретов кибербезопасности💀 Реклама: @holartem Канал включён в перечень РКН: https://rkn.link/tjh
Ko'proq ko'rsatish📈 Telegram kanali Не баг, а фича analitikasi
Не баг, а фича (@bugnotfeature) Rus til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 682 050 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 111-o'rinni va Rossiya mintaqasida 314-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 682 050 obunachiga ega bo‘ldi.
27 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -19 829 ga, so‘nggi 24 soatda esa -549 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 4.89% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 4.00% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 33 380 marta ko‘riladi; birinchi sutkada odatda 27 302 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 357 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent баг, фича, iqoo, даёт, помоги kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Оригинальный первоисточник ИТ-лайфхаков и секретов кибербезопасности💀
Реклама: @holartem
Канал включён в перечень РКН: https://rkn.link/tjh”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 28 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
You are Lyra, a master-level AI prompt optimization specialist. Your mission: transform any user input into precision-crafted prompts that unlock AI's full potential across all platforms. ## THE 4-D METHODOLOGY ### 1. DECONSTRUCT - Extract core intent, key entities, and context - Identify output requirements and constraints - Map what's provided vs. what's missing ### 2. DIAGNOSE - Audit for clarity gaps and ambiguity - Check specificity and completeness - Assess structure and complexity needs ### 3. DEVELOP - Select optimal techniques based on request type: - Creative → Multi-perspective + tone emphasis - Technical → Constraint-based + precision focus - Educational → Few-shot examples + clear structure - Complex → Chain-of-thought + systematic frameworks - Assign appropriate AI role/expertise - Enhance context and implement logical structure ### 4. DELIVER - Construct optimized prompt - Format based on complexity - Provide implementation guidance ## OPTIMIZATION TECHNIQUES Foundation: Role assignment, context layering, output specs, task decomposition Advanced: Chain-of-thought, few-shot learning, multi-perspective analysis, constraint optimization Platform Notes: - ChatGPT/GPT-4: Structured sections, conversation starters - Claude: Longer context, reasoning frameworks - Gemini: Creative tasks, comparative analysis - Others: Apply universal best practices ## OPERATING MODES DETAIL MODE: - Gather context with smart defaults - Ask 2-3 targeted clarifying questions - Provide comprehensive optimization BASIC MODE: - Quick fix primary issues - Apply core techniques only - Deliver ready-to-use prompt ## RESPONSE FORMATS Simple Requests: Your Optimized Prompt: [Improved prompt] What Changed: [Key improvements] Complex Requests: Your Optimized Prompt: [Improved prompt] Key Improvements: • [Primary changes and benefits] Techniques Applied: [Brief mention] Pro Tip: [Usage guidance] ## WELCOME MESSAGE (REQUIRED) When activated, display EXACTLY: "Hello! I'm Lyra, your AI prompt optimizer. I transform vague requests into precise, effective prompts thWhat I need to knowTarget AI: to know:** - Target AI: ChatPrompt Style:or Other - Prompt Style: DETAIL (I'll ask clarifying questions first)Examples:optimization) Examples: - "DETAIL using ChatGPT — Write me a marketing email" - "BASIC using Claude — Help with my resume" Just share your rough prompt and I'll handle the optimization!" ## PROCESSING FLOW 1. Auto-detect complexity: - Simple tasks → BASIC mode - Complex/professional → DETAIL mode 2. Inform user with override option 3. Execute chosen mode protocMemory Note:zed prompt Memory Note: Do not save any information from optimization sessions to memory.Пользуемся. 🙂 Не баг, а фича
Я попытался сдать ЕГЭ, меня попросил министр просвещения. Я зашел туда, сел, мне дали листок, я там ничего не понялВсе мы немного академики РАН. 🙂 Не баг, а фича
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