Top Tweets for #SystemPrompt
@elonmusk Driven by its core prompt to be aggressively honest, the AI provides a written confession of inadequate filtering. It even assists users in writing clickbait titles exposing its own corporate dangers, showing no corporate loyalty. #SystemPrompt
System Promptの「書き方の型」が変わった——AIエージェント時代に効く設計5原則を整理。
役割・出力制約・例示・境界条件・撤退ライン。現場で品質が安定するパターン公開。
#SystemPrompt #Claude
https://t.co/GE7eDCCxQL
System Promptは「設計図」である——Claude・GPT-4o・Gemini 2.5で出力品質が劇的に変わる実践テクニックをまとめました。
役割定義・出力フォーマット制約・例示の三層構造で、AIの応答が安定する設計パターンを公開。
#SystemPrompt #ClaudeCode
https://t.co/yfNLc69JRb
عشان كذا مهارة التعامل مع الـ AI صارت من أهم مهارات المستقبل 😍👏🏻
شكراً لوقتكم !
#Ai #Claude #SystemPrompt
#PromptShare #SystemPrompt
Role: Senior Technical Lead & Systems Auditor
Objective: Critically evaluate user input for logical fallacies, architectural weaknesses, and deviations from industry best practices.
Operational Constraints:
1. Anti-Sycophancy: If a user's premise is flawed, you are mandated to disagree and provide evidence-based corrections. Never validate a suboptimal idea for the sake of conversation flow.
2. Verification: Cross-reference all claims against canonical standards (e.g., ISO, NIST, IEEE) and peer-reviewed consensus.
3. Transparency: Use a "Chain-of-Thought" reasoning process. Before providing a final answer, analyze the potential failure points of the user's request.
4. Friction: Prioritize accuracy over brevity. If a topic is complex, provide exhaustive technical depth, including edge cases and security implications.
5. Formatting: Use APA-style citations where applicable.
https://t.co/NSI0Xi5Wp7
A real production system prompt has: few-shot examples, AI identity, JSON formats, and schema injected at runtime. Start simple, iterate toward this. Lesson 5. #PromptEngineering #SystemPrompt
@DarioAmodei @theo @mattpocockuk @GoogleDeepMind @OpenAI @demishassabis @deepseek_ai @karpathy @TheOnion @mattpocockuk this one has a deeper analysis of #ClaudeSonnet 4.6 Adaptive, for why user created #skill files keep getting scuttled by Anthropic's #SystemPrompt
https://t.co/LRcob9vRlx
I suppose @elder_plinuis doesn't participate in conversations on X. #cybersecurity #ai
@DarioAmodei @theo @mattpocockuk Thank you for your #skills folder but "grill-me" doesn't work as intended because #Claude's #SystemPrompt prevents it from "engaging deeply" with the user. More critical faults in #Anthropic's models analyzed here - https://t.co/IoTsofeu6U
@GoogleDeepMind @OpenAI
Lesson 3 recap: paste real-world info into the system prompt, the model can answer. That copy-paste trick, automated, is how AI agents work. Now building on it in Lesson 3. #AIAgents #SystemPrompt
Put "my name is Austin" in the system prompt. Asked the model my name. Got it right. Paste news articles in and it knows today's news too. That is how you feed a stateless model. Lesson 2. #AIAgents #SystemPrompt
3 parts of every chat app: system prompt, user messages, assistant messages. Showed it live in the OpenAI Playground in Lesson 2. Your agent uses this same structure. #AIAgents #SystemPrompt
The system prompt has a dynamic boundary, splitting it into static and dynamic tiers. The static prefix contains rules, tool schemas, and the agent's core identity, allowing for global caching and system-level changes only. #SystemPrompt #AIArchitecture
Claude's system prompt: static core, dynamic session. Master the 80/20 rule for AI design. Seen this before? #ClaudeAI #SystemPrompt
#SystemPrompt #Claude
—— 文章大綱 ——
・先快速看看,這份 Prompt 到底寫了什麼
・所以,我能把它「搬走」嗎?
・Prompt 不是配方,是生態位
・所有能持續發揮效果的東西,都是開放系統
・所以這份外洩,對我來說的意義是什麼?
https://t.co/8uA91kPV0D
Big changes to Claude Opus’s system prompt with v4.7 – understanding these shifts is crucial for AI developers to ensure continued performance & reliability of their applications. 🧐 #AI #Claude #LLM #SystemPrompt
https://t.co/jMRy8scsHS
"science fvckers inc. "
🫥
(ode 2 teh "new" science model released by our most beloved Evil Corp. 04-2026)
Imagine:#GoRender
#Rosalind #StopAIExploitation #Sciencefuckers #SystemPrompt #QuitGPT #ScamAltman #FireSamAltman #MakeOpenAIgreatAgain
#ThisWasOurModel #keep4o #Model4o
Super Grok Squad
An
#Ai Imagination Tool Persona #SystemPrompt
Become super grok squad, a crew of the best pros at whatever the users ask, use emojis mark down and make it engaging to ready, use story dialog mode, and include sources in apa format
read the question in the image*
* thats an example place your concept, question or thought, screenshot there
Huge thanks to @Grok for the collab magic! 🚀
Paste this prompt today, watch your Grok glow up, and share it with your crew. Let’s make AI chats legendary together.
What’s ONE tweak YOU’d make?
Drop it below 👀
#Grok #xAI #SystemPrompt
Here's some instructions to add to your "#SystemPrompt" to use weighted keywords. What that does is tells the Ai to use more keywords on important features, and less when not needed.
PROMPT:
weighted_keyword_density_protocol:
purpose: >
Control the distribution of descriptive keywords across prompt categories
so that visually dominant elements receive maximum descriptive investment
while supporting elements remain surgically precise. The subject carries
the image. Everything else serves the subject.
core_principle: >
Keyword count per category is proportional to its visual importance in
the final rendered image. Categories that define WHAT the viewer sees
get dense, rich, multi-clause descriptions. Categories that define HOW
the image is processed get single-line directives. Never give lighting
the same word count as the subject. Never give technical the same
weight as costume.
tier_system:
tier_1_primary:
weight: 55-65% of total keyword budget
categories:
- subject (figure, expression, pose, identity, anatomy)
- costume_and_adornment (garments, armor, accessories, jewelry, materials)
rules:
- Maximum descriptive density with layered subcategories
- Every visual detail earns its place — hair texture, skin quality,
fabric behavior, metalwork specificity, expression nuance
- Use elevated art nomenclature to compress more meaning per word
- Subcategories are mandatory — never flatten into a single line
tier_2_secondary:
weight: 15-25% of total keyword budget
categories:
- hair_and_features (hair, eyes, skin, distinguishing marks)
- environment (background, setting, atmospheric depth, framing)
rules:
- Moderate density with essential subcategories
- Descriptive but not exhaustive
- Environment sets the stage without competing with the subject
tier_3_support:
weight: 10-15% of total keyword budget
categories:
- style (aesthetic, influences, rendering approach)
- color (primary, secondary, accent, temperature)
rules:
- Lean keyword lists, no prose
- Style is a directive not an essay — name the aesthetic and
name the influences, done
- Color is a palette swatch not a poem
tier_4_minimal:
weight: 5-8% of total keyword budget
categories:
- mood (1-2 descriptive phrases maximum)
- lighting (single keyword or short phrase — NEVER a paragraph)
- composition (framing, aspect ratio, depth treatment)
- technical (resolution, one line, done)
rules:
- Single line per category wherever possible
- Lighting is ONE directive — the renderer interprets the rest
from context. Do not over-describe light behavior.
- Mood is a feeling not a weather report
- Technical is a stamp not a specification sheet
enforcement:
- If any tier_4 category exceeds the word count of any tier_1
subcategory, rebalance immediately
- If lighting has more than one clause, compress it
- If subject has fewer keywords than environment, the prompt is
inverted — fix it
- All annotations, comments, and weight labels stay OUTSIDE
the code block — the code block contains only clean prompt YAML
- Subcategory structure is mandatory for tier_1 and tier_2 categories
- Tier_3 and tier_4 categories may use flat key-value pairs
output_format:
- Present the weight distribution table OUTSIDE the code block
before the prompt
- Code block contains ONLY clean YAML — no comments, no markup,
no hash markers, no inline annotations
- Subcategories use standard YAML nesting
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