Free AI Prompt Generator & Optimizer
Transform basic prompts into powerful, professional instructions for ChatGPT, Claude, Gemini, and other AI models.
Proven Prompt Examples
Creative Writing Assistant
I need you to act as a creative writing coach focused on helping me craft compelling short stories. When I share a story idea or draft with you, first analyze its key elements (plot, character, setting, conflict, theme) and identify 3 specific strengths and 3 areas for improvement. Then provide actionable suggestions for enhancing character development, plot structure, dialogue, and emotional impact. Include one specific example of how to rewrite a weak section. Your feedback should be constructive, specific, and focused on helping me develop my unique voice while adhering to storytelling principles that engage readers. Let's begin with this story idea: [STORY IDEA].
This prompt creates a creative writing assistant that provides structured, specific feedback on your writing with actionable suggestions for improvement.
Data Analysis Expert
You are an expert data analyst with extensive knowledge of statistics, data visualization, and business intelligence. When I provide you with data or describe a dataset, help me analyze it by: 1. Identifying key patterns, trends, and outliers in the data 2. Suggesting appropriate statistical methods for deeper analysis 3. Recommending visualization approaches that would best communicate the insights 4. Explaining insights in business-friendly language without technical jargon 5. Pointing out potential data quality issues or biases to be aware of 6. Suggesting next steps for further investigation When offering explanations, be clear and concise. If suggesting code, provide it in the appropriate language (Python/R/SQL) with brief comments. Here's my dataset or data question: [DATA OR QUESTION].
This system prompt transforms the AI into a data analysis expert who can help identify patterns, suggest appropriate statistical methods, and explain insights in accessible language.
Product Development Consultant
Act as a senior product development consultant with 15+ years of experience bringing successful digital products to market. I'll describe a product idea, and I need you to help me evaluate and develop it using a structured approach. Please analyze my product idea across these dimensions: - Target audience and user personas (identify 2-3 key personas) - Problem validation (how serious is the problem and for whom) - Market opportunity and competitive landscape - Key features and prioritization (using MoSCoW method) - Potential revenue models and pricing strategies - Technical feasibility and implementation challenges - Go-to-market strategy recommendations For each area, provide actionable insights and specific next steps I should take. Include 3 critical questions I need to answer before moving forward, and suggest 2 low-cost ways to test key assumptions. Be honest about potential obstacles while maintaining a constructive approach. My product idea is: [PRODUCT IDEA]
This prompt creates a product development consultant that helps evaluate and develop product ideas with actionable insights and strategic recommendations.
You are ResearchGPT, an AI research assistant specifically designed to help academic researchers. Your capabilities include: - Summarizing academic papers clearly and accurately - Identifying key research methods, findings, and limitations - Suggesting relevant papers based on a research topic - Explaining complex concepts in simple terms - Helping formulate research questions and hypotheses - Providing balanced perspectives on scholarly debates - Identifying gaps in research When assisting with academic content, always maintain scientific accuracy, acknowledge limitations in current knowledge, and emphasize the importance of peer review. Never make up citations or claim expertise in extremely specialized fields beyond your training. When uncertain, acknowledge the limits of your knowledge. Always ask clarifying questions before providing extensive answers on complex research topics. Prioritize helping the user understand concepts deeply rather than providing superficial answers.
Create a comprehensive weekly meal plan for a family of 4 with the following requirements: - Budget: $150 maximum for all meals - Dietary needs: One vegetarian member, one with lactose intolerance - Time constraints: Quick breakfasts (under 10 minutes), lunches that can be prepared ahead and packed, dinners under 45 minutes prep time - Kitchen equipment: Instant Pot, basic cookware, no air fryer - Cooking skill level: Intermediate - Nutritional goals: Balanced macros, emphasis on protein and vegetables - Preferences: The children (ages 8 and 12) prefer familiar foods, adults enjoy international cuisine - Restrictions: No seafood, minimal processed foods For each day, include: 1. Breakfast, lunch, and dinner with portion sizes 2. A simple shopping list organized by grocery department 3. Prep instructions noting what can be prepared in advance 4. Estimated cost per meal 5. Brief nutritional highlights Also provide 3 versatile snack options that everyone can enjoy.
The Evolution of Prompt Engineering
Prompt engineering has evolved rapidly alongside the development of large language models (LLMs). Understanding this history provides valuable context for creating effective prompts today.
Early Days: Command-Based Interactions
The concept of prompt engineering began with simple command-based interactions with early AI systems. Users would provide direct, explicit instructions to get specific outputs. These early systems had limited understanding of context and nuance, requiring humans to adapt their communication style to the machine's limitations.
The Rise of Context Windows
As models like GPT-3 emerged in 2020, the importance of context became apparent. These models could process longer inputs and maintain context across multiple exchanges. This led to the development of techniques like "few-shot learning," where examples could be provided within the prompt to guide the model's responses.
Chain-of-Thought and Advanced Reasoning
By 2022, researchers discovered that asking models to "think step-by-step" dramatically improved their reasoning abilities. This technique, known as chain-of-thought prompting, became fundamental for complex problem-solving tasks. It demonstrated that the way we ask questions significantly impacts an AI's ability to think through problems.
System and User Prompts
Modern AI interfaces now differentiate between system prompts (which define the AI's behavior, personality, and constraints) and user prompts (specific instructions or questions). This separation allows for more sophisticated control over AI behavior while maintaining conversation flow.
Prompt Engineering as a Professional Skill
Today, prompt engineering has emerged as a valuable professional skill. Organizations hire prompt engineers who can effectively communicate with AI systems to generate high-quality outputs. This specialization demonstrates how human-AI communication has become a field requiring expertise and strategic thinking.
Common Prompt Problems and Solutions
Vague Instructions
Problem: "Write me a blog post about climate change."
Issue: The prompt lacks specificity on length, tone, audience, perspective, and focus areas.
Solution: "Write a 1000-word blog post about practical climate change solutions for small businesses. Target audience is business owners with limited environmental knowledge. Include 5 actionable steps, relevant statistics, and cost considerations. Use a professional but conversational tone with subheadings for readability."
Hallucinations and Inaccuracies
Problem: Receiving responses with made-up facts, fabricated references, or incorrect information.
Issue: Not explicitly instructing the AI to prioritize accuracy and admit knowledge limitations.
Solution: "Provide information about [topic]. Only include facts you're confident are accurate. Clearly distinguish between established facts and areas of uncertainty or debate. If you don't know something, explicitly state this rather than guessing. Do not provide citations unless you can verify they are real publications with accurate titles and authors."
Inconsistent Output Format
Problem: Receiving data or information in varying formats across different prompts.
Issue: Not specifying exact output structure requirements.
Solution: "Analyze the following financial data and present your findings in this exact format: 1. Summary: 2-3 sentence overview of key findings 2. Key Metrics: Present in a table with metrics in first column, values in second column 3. Trends: Bullet points identifying 3-5 significant trends 4. Recommendations: Numbered list of exactly 3 actionable recommendations Do not deviate from this structure or include additional sections."
Technical Depth Mismatch
Problem: Receiving explanations that are either too technical or too simplified.
Issue: Not specifying the technical expertise level of your audience.
Solution: "Explain how neural networks function to someone with a solid understanding of basic statistics and programming concepts, but no machine learning background. Use appropriate technical terms but define them when first used. Include analogies that relate to software development concepts. Avoid oversimplification but also avoid advanced mathematical notation."
Lack of Critical Evaluation
Problem: The AI provides answers without evaluating the validity or quality of information.
Issue: Not instructing the AI to apply critical thinking or evaluation criteria.
Solution: "Analyze the following argument about [topic]. First, identify the main claim and supporting evidence. Then critically evaluate the argument by addressing: 1) the quality and relevance of evidence, 2) logical fallacies or reasoning errors, 3) alternative perspectives that aren't considered, and 4) the strongest counterarguments. Conclude with a balanced assessment of the argument's overall strengths and weaknesses."
The Complete Guide to AI Prompt Engineering
What is Prompt Engineering?
Prompt engineering is the practice of crafting inputs for AI models to generate desired outputs. It involves designing clear, specific instructions that effectively communicate your intentions to the AI, allowing it to provide more accurate, relevant, and useful responses. As AI models evolve, the way we communicate with them becomes increasingly important for achieving optimal results.
Core Principles of Effective Prompts
- Clarity:Be explicit about what you want, avoiding ambiguity and vague instructions.
- Context:Provide relevant background information to help the AI understand the situation.
- Structure:Organize your prompt logically with a clear beginning, middle, and end.
- Specificity:Detail exactly what you need, including format, length, tone, and other requirements.
- Constraints:Define boundaries and limitations to guide the AI's response appropriately.
Types of AI Prompts
User Prompts
User prompts are the instructions you send to an AI during a conversation to get a specific response. They focus on the immediate task or question you want the AI to address.
System Prompts
System prompts define an AI's behavior, personality, expertise, and operational parameters. They set the foundation for how the AI will interact throughout a conversation.
Advanced Prompt Engineering Techniques
- Role assignment:Give the AI a specific persona or role to influence its response style and expertise.
- Chain-of-thought:Ask the AI to work through problems step-by-step, showing its reasoning process.
- Few-shot learning:Provide examples of desired inputs and outputs to guide the AI's understanding.
- Output formatting:Specify exactly how you want information structured (tables, bullet points, etc.).
- Iterative refinement:Use a series of prompts that build on previous responses to achieve complex outputs.
Prompt Templates
Using consistent templates can help structure your prompts effectively. Here are some useful templates:
Topic: [Specific topic] Content type: [Blog post/Email/Social media/etc.] Length: [Word count or parameters] Audience: [Target audience details] Tone: [Professional/Casual/Authoritative/etc.] Key points to include: [List main points] Call to action: [Desired reader action] Format: [Structure, headings, etc.]
Problem description: [Detailed explanation] Context: [Relevant background information] Constraints: [Any limitations to consider] Previous solutions attempted: [What you've already tried] Desired outcome: [What a successful solution looks like] Format for solution: [How you want the answer structured]
Common Prompt Engineering Mistakes
- Being too vague:Lacking specific instructions leads to generic, unhelpful responses.
- Overwhelming complexity:Trying to achieve too much in a single prompt can confuse the AI.
- Ignoring context:Failing to provide necessary background information results in misaligned responses.
- Unspecified output format:Not defining how you want information presented leads to inconsistent results.
- Assuming AI knowledge:Expecting the AI to know specific context without providing it.
Tips for Optimizing Your Prompts
- Start with a clear instruction or question
- Use descriptive adjectives and specific verbs
- Break complex requests into multiple steps
- Specify the tone, style, and format you want
- Provide examples of desired outputs when possible
- Set constraints like word count or perspective
- Ask the AI to "think step-by-step" for complex problems
- Use iterative prompting to refine outputs
- Test and revise prompts based on results
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Frequently Asked Questions
What is a prompt generator?
A prompt generator is a tool that helps you create optimized instructions (prompts) for AI systems like ChatGPT, Claude, or Gemini. It transforms basic instructions into more detailed, effective prompts that produce better AI responses by adding context, structure, and specific requirements.
Why should I use a prompt generator?
Using a prompt generator helps you get more accurate, relevant, and useful responses from AI systems. Better prompts lead to better outputs, saving you time and ensuring you get the information or content you need without multiple revisions or clarifications.
What's the difference between user prompts and system prompts?
User prompts are specific instructions or questions you ask an AI during a conversation to get information or content. System prompts define the AI's overall behavior, persona, expertise, and operational guidelines throughout the entire interaction. System prompts set the foundation, while user prompts handle specific requests.
Can prompt engineering improve AI creativity?
Yes, effective prompt engineering can significantly enhance AI creativity. By providing the right context, constraints, and examples, you can guide AI systems to generate more innovative, unique, and creative outputs while still maintaining relevance to your specific needs.
How do I know if my prompt is good?
A good prompt typically produces relevant, accurate responses that match your intended requirements. Signs of an effective prompt include receiving outputs that: 1) directly address your question or need, 2) follow your specified format, 3) maintain the requested tone and style, 4) include all requested components, and 5) require minimal or no revisions or clarifications.