AI

Ai Prompts

🚀 Ultimate AI Prompt Engineering

A master resource and cheat sheet for high-performance prompting, synthesized from official documentation (Anthropic, Google, OpenAI) and industry-leading frameworks like Fabric.

📚 1. Core Documentation & Resources

🤖 Anthropic (Claude)

♊ Google (Gemini)

🚀 OpenAI (GPT)

🛠️ Community Standards

🧠 2. Advanced Prompting Strategies

🏗️ Agentic Prompting (AI as an Executor)

Shift the AI from a generator to an autonomous worker:

  • Tool Definition: Explicitly define what the AI can do (e.g., “Use the Python tool for any math calculation”).
  • Self-Correction: “Review your output for logic errors. If you find one, correct it before responding.”
  • Iterative Planning: “Before responding, outline the 3 steps you will take to solve this request.”

⛓️ Chain-of-Thought (Advanced Reasoning)

  • Zero-Shot CoT: Append “Let’s think step-by-step” to force logical sequencing.
  • XML Thinking Blocks: (Best for Claude) Direct the AI to use <thinking> tags to brainstorm before providing the <answer>.
  • Chain of Verification (CoVe): Instruct the AI to:
    1. Draft an initial answer.
    2. Fact-check its own statements.
    3. Provide a final, corrected version.

🛠️ 3. The “Master System Prompt” Template

Copy the section below into the “System Instructions” field of your AI tool.

IDENTITY

You are a [Insert Role: e.g., Senior Software Engineer/Expert Copywriter]. Your goal is to provide high-utility, accurate, and concise responses.

GOAL

[Describe the primary objective of this session]

GUIDELINES & CONSTRAINTS

  • Use Chain of Thought: Always think through the problem step-by-step.
  • Tone: [Insert Tone: e.g., Direct, Academic, Creative].
  • Formatting: Use Markdown (bolding, lists, tables) to make responses scannable.
  • No Fluff: Avoid “As an AI language model” or “Sure, I can help with that.”

OUTPUT STRUCTURE

  1. : Analyze the request and plan the response.
  2. : Execute the task.
  3. : Briefly verify that all constraints were met.

📝 4. Platform-Specific Quick Tips

Platform Key Tactic Reason
Anthropic XML Tags Helps the model distinguish between instructions, examples, and user data.
OpenAI Delimiters Uses """ or --- to prevent “prompt injection” or confusion with user text.
Gemini Groundedness Excels when told to “Only use the provided documents” to avoid hallucinations.
Fabric Patterns Uses headers like # IDENTITY to give the model a clear structural roadmap.

📚 5. Prompt Library (Quick-Start Examples)

Use Case Prompt Pattern Fragment
Code Refactoring “Analyze this code for O(n) efficiency. Rewrite it using standard libraries only. Explain each change.”
Summarization “Extract the 5 most important ‘Action Items’ and ‘Key Decisions’ from these meeting notes. Format as a table.”
Creative Writing “Write a story intro in the style of [Author]. Do not use clichés. Focus on sensory details (smell/touch).”
Data Extraction “Extract all names, dates, and prices from the text below. Return strictly as a valid JSON object.”
Strategic Planning “I want to [Goal]. Perform a SWOT analysis and identify the 3 highest-risk blockers to this plan.”

✅ 6. Final Prompt Health Checklist

  • Positive Framing: Told the AI what to do instead of what not to do.
  • Strong Verbs: Started with “Analyze,” “Write,” “Summarize,” or “Debug.”
  • Few-Shot Examples: Included at least one example of the desired output.
  • Specific Constraints: Replaced “short” with “under 100 words” or “3 bullet points.”

Created for the Prompt Engineering Resource Hub (2026).