Prompt engineering

Thiết kế và tối ưu hóa prompts để hướng dẫn mô hình AI tạo ra outputs chất lượng cao, chính xác và phù hợp.

🎯 Mục đích

• Task specification: Rõ ràng yêu cầu nhiệm vụ
• Context provision: Cung cấp thông tin cần thiết
• Output formatting: Định dạng output mong muốn
• Error reduction: Giảm hallucinations và errors

📝 Prompt Components

Instructions

• Clear objectives: What to do
• Step-by-step: How to approach
• Constraints: Limitations và requirements
• Examples: Few-shot learning

Context

• Relevant information: Background data
• User context: Personalization
• Domain knowledge: Legal terminology
• Current state: Conversation history

Output Format

• Structure: JSON, markdown, plain text
• Schema: Required fields
• Style: Tone, language, length
• Citations: Source references

🛠️ Techniques

Few-shot Learning

• Examples: Input-output pairs
• Diversity: Cover different scenarios
• Quality: High-quality examples
• Relevance: Similar to target task

Chain of Thought

• Reasoning steps: Break down complex tasks
• Intermediate outputs: Show thinking process
• Verification: Self-check mechanisms
• Explanation: Justify answers

Role Playing

• Persona: Expert role (legal expert, analyst)
• Perspective: Specific viewpoint
• Style: Professional, helpful, concise
• Constraints: Ethical guidelines

🔧 Advanced Methods

Prompt Chaining

• Sequential prompts: Build on previous outputs
• Refinement: Iterative improvement
• Decomposition: Break complex tasks
• Validation: Check intermediate results

Dynamic Prompting

• Context awareness: Adapt to user history
• Query analysis: Understand intent
• Personalization: User preferences
• Feedback integration: Learn from corrections

📊 Evaluation

Quality Metrics

• Accuracy: Factual correctness
• Relevance: Answer appropriateness
• Completeness: Information coverage
• Clarity: Understandability

A/B Testing

• Prompt variants: Compare different approaches
• User feedback: Satisfaction scores
• Performance metrics: Response time, cost
• Iterative improvement: Continuous optimization

🚀 Best Practices

Design Principles

• Clarity: Unambiguous instructions
• Specificity: Detailed requirements
• Brevity: Concise but complete
• Testability: Measurable outcomes

Maintenance

• Version control: Track prompt changes
• Documentation: Explain design decisions
• Monitoring: Performance tracking
• Updates: Regular refinement

Prompt engineering là nghệ thuật giao tiếp hiệu quả với AI models.