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1.3 The New Core Skill: An Introduction to Prompt Engineering

Key Points to Cover:

  • What is Prompt Engineering?
  • The art and science of communicating with AI
  • Why it's becoming a critical developer skill

  • Prompt as the new interface for programming

  • Basic Prompt Structure

  • Clear instructions and context
  • Input-output examples
  • Constraints and requirements
  • Format specifications
graph TD
    A[Your Prompt 📝] --> B{Quality Check}
    B -->|Vague| C["Write code"]
    C --> D[Confused AI 😕]
    D --> E[Mediocre Result]

    B -->|Specific| F["Write a Python function
that validates email addresses
using regex, includes error
handling, and has docstrings"]
    F --> G[Happy AI 😊]
    G --> H[Excellent Result! 🎉]

    style C fill:#ffcccc
    style E fill:#ffcccc
    style F fill:#ccffcc
    style H fill:#ccffcc
  • Key Principles
  • Be specific and explicit
  • Provide context and background information
  • Break complex tasks into smaller steps

  • Iterate and refine based on results

  • Common Prompt Patterns for Developers

  • Code generation prompts
  • Debugging and error analysis prompts
  • Code explanation and documentation prompts
  • Refactoring and optimization prompts

  • Test generation prompts

  • Advanced Techniques

  • Few-shot learning (providing examples)
  • Chain-of-thought prompting
  • Role-based prompting ("Act as a senior developer...")

  • System prompts vs. user prompts

  • Do's and Don'ts

  • ✓ Be clear about programming language and framework
  • ✓ Specify coding standards and best practices
  • ✗ Assume the AI knows your project context

  • ✗ Accept first output without review

  • Practice Exercise Ideas

  • Writing prompts for common development tasks
  • Comparing results from different prompt formulations
  • Refining prompts iteratively