Categories of prompts you can use for LLMs

Categories of prompts with examples 

1. Direct Instruction

- Calculate the area of a circle with a radius of 5 cm.

- List the steps to reset a smartphone to factory settings.

- Write a summary of the book 'To Kill a Mockingbird'.


2. Specific Contextualization

- Explain the impact of the 2008 financial crisis on small businesses in the US.

- Describe the role of artificial intelligence in modern healthcare.

- Discuss the cultural significance of Diwali in India.


3. Comparative Analysis

- Compare the economic policies of the US and China.

- Analyze the differences between renewable and non-renewable energy sources.

- Contrast the leadership styles of Steve Jobs and Bill Gates.


4. Creative Scenario Setting

- Imagine a world where humans can breathe underwater. Describe how society would change.

- Create a story where AI has become the primary decision-maker in governments.

- Write a dialogue between two characters who discover a hidden treasure in their backyard.


5. Role Play and Simulation

- Pretend you are a customer service representative handling a complaint about a defective product.

- Simulate a job interview for a software developer position.

- Role-play a negotiation between a buyer and a seller over the price of a car.


6. Progressive Inquiry

- What are the causes of climate change? How do these causes affect global weather patterns?

- How does the human brain process language? What are the implications for learning new languages?

- What are the key factors in successful project management? How can these be applied in a tech startup?


7. Temporal Sequence Request

- Describe the events leading up to the American Revolution.

- Outline the steps involved in the scientific method.

- Explain the process of photosynthesis from start to finish.


8. Opposing Viewpoint Exploration

- Discuss the pros and cons of remote work.

- Examine the arguments for and against the use of genetically modified organisms (GMOs) in agriculture.

- Analyze the benefits and drawbacks of social media on mental health.


9. Problem-Solving Framework

- How would you address the issue of plastic pollution in the oceans?

- What strategies can be implemented to improve public transportation in urban areas?

- Propose a solution to reduce the digital divide in developing countries.


10. Multi-Turn Conversation

- Let's discuss your career goals. What are your long-term aspirations?

- Tell me about your favorite hobbies. How did you get started with them?

- What are your thoughts on the latest advancements in AI? How do you think they will impact society?


11. Conditional Scenario

- If you were given a million dollars, how would you invest it?

- Imagine you are the CEO of a company facing a major crisis. What steps would you take to manage the situation?

- If you could travel to any country in the world, where would you go and why?


12. Personalized Inquiry

- What are your favorite books and why do you enjoy them?

- How do you usually spend your weekends?

- What inspired you to pursue a career in your current field?


13. Future Prediction

- What do you think the world will look like in 50 years?

- How do you foresee the evolution of technology in the next decade?

- What are your predictions for the future of renewable energy?


14. Meta-Instructive Prompt

- Explain how to create an effective study plan for exams.

- Describe the best practices for writing a research paper.

- Outline the steps to develop a successful marketing strategy.


15. Abstract Concept Clarification

- What is the concept of 'freedom' in political philosophy?

- Explain the idea of 'entropy' in thermodynamics.

- Describe the notion of 'justice' in ethical theory.

Comments

Post a Comment

Popular posts from this blog

Key considerations for accurate and seamless AI agent interaction

 To ensure accurate and seamless exchange of information between the agents in this ecosystem, several technical points and features should be implemented. These features will allow agents to communicate effectively, maintain data integrity, and handle errors gracefully. Here’s a breakdown of key considerations: 1. Standardized Data Formats and Protocols Common Data Schema: Define a shared data schema (e.g., JSON or XML) that agents can interpret consistently, ensuring data fields like timestamps, IDs, and priority levels are uniformly formatted. Protocol Consistency: Use consistent communication protocols like REST APIs, gRPC, or messaging protocols (e.g., MQTT, AMQP) to handle synchronous and asynchronous communications between agents. 2. Inter-Agent Communication Middleware Message Broker: Implement a message broker (e.g., Kafka, RabbitMQ) to facilitate real-time, asynchronous communication between agents, allowing them to publish and subscribe to relevant data streams without d...
Read more

Human skills for working effectively with complex AI agents

A. Valuable future human skills for working effectively with complex AI agents: 1. Strategic Oversight & Direction - Setting meaningful goals and objectives for AI systems - Understanding when and how to intervene in AI processes - Evaluating AI outputs for alignment with broader objectives - Critical thinking about AI's limitations and potential biases 2. Human-AI Communication Skills - Effective prompt engineering and instruction giving - Interpreting and contextualizing AI outputs - Understanding AI capabilities and limitations - Mediating between AI systems and other humans 3. Complex Problem Decomposition - Breaking down problems into AI-solvable components - Identifying which tasks are better suited for humans vs AI - Designing workflows that combine human and AI strengths - Creating effective human-AI collaboration frameworks 4. Emotional and Social Intelligence - Managing stakeholder relationships - Handling sensitive situations requiring empathy - Providing context abo...
Read more

Top AI solutions and concepts used in them

 Breakdown of the top AI solutions in demand, the combinations of concepts they leverage, and  examples from different industries for each. 1. Predictive Analytics Key Concepts Used : Classification Models Supervised Learning Transfer Learning Explainable AI (XAI) Examples : Healthcare : AI-powered predictive models to identify patients at risk of developing chronic diseases using electronic health records. Finance : Fraud detection systems predicting suspicious transactions and potential credit defaults. 2. Natural Language Processing (NLP) Solutions Key Concepts Used : Neural Language Processing (NLP) Attention Mechanisms Recurrent Neural Networks (RNNs) Few-shot Learning Examples : Customer Service : AI chatbots and virtual assistants, such as those by banks or e-commerce platforms, for 24/7 support. Legal : Document analysis and contract review tools to identify critical clauses or discrepancies. 3. Computer Vision Applications Key Concepts Used : Convolutional Neural Netw...
Read more