Lesson 3 Openai Prompts | Module 1

OpenAI Prompts: From Basic to Advanced

This lesson covers essential OpenAI prompting techniques, progressing from simple text inputs to advanced patterns like streaming, structured outputs, and function calling.

Lesson Structure

Each sub-lesson focuses on a specific prompting technique with working code examples. Follow them in order to build your understanding progressively.

📚 Prompt Techniques Overview

Lesson 3a: Basic Prompt

Simple text input prompt with OpenAI.

Send a basic text prompt to OpenAI
Receive a simple text response
Understand the foundation of AI interactions
Use Case: Quick, straightforward queries

Lesson 3b: System Prompt

Defining AI role and behavior with system prompts.

Set the AI's personality and expertise
Provide context and guidelines
Control response style and tone
Use Case: Specialized assistants (travel agent, code reviewer, etc.)

Lesson 3c: Temperature Control

Adjusting response creativity with the temperature parameter.

Learn how temperature affects randomness
Balance creativity vs consistency
Understand when to use different temperature values
Use Case: Creative writing (high temp) vs factual responses (low temp)

Lesson 3d: Extended Prompts

Detailed context and instructions for advanced prompt engineering.

Provide comprehensive background information
Use detailed instructions for complex tasks
Structure multi-part prompts effectively
Use Case: Complex analysis, detailed planning, multi-step reasoning

Lesson 3e: Streaming Responses

Real-time output with streaming responses.

Stream AI responses word-by-word
Provide immediate user feedback
Handle partial responses
Use Case: Chat interfaces, real-time assistants

Lesson 3f: Structured Output

Validated JSON output using Zod.

Define schemas with Zod for type safety
Get validated JSON responses
Parse structured data reliably
Use Case: Data extraction, form filling, API integrations

Lesson 3g: Function/Tool Calling

Integrating external APIs and tools with function calling.

Define functions the AI can call
Let AI decide when to use tools
Integrate with external APIs and services
Use Case: Weather lookups, database queries, calculations, external integrations

Learning Path

Legend:

🔵 Light Blue: Foundation concepts
🟡 Light Yellow: Intermediate techniques
🔴 Light Red: Advanced patterns

Quick Reference

Technique	Complexity	Best For
Basic Prompt	⭐ Beginner	Simple queries
System Prompt	⭐ Beginner	Defining AI role
Temperature	⭐⭐ Intermediate	Balancing creativity
Extended Prompts	⭐⭐ Intermediate	Complex instructions
Streaming	⭐⭐ Intermediate	Real-time UIs
Structured Output	⭐⭐⭐ Advanced	Type-safe data
Function Calling	⭐⭐⭐ Advanced	Tool integration

Prerequisites

Before starting these lessons, ensure you have:

✅ Completed Lesson 2: TypeScript Setup
✅ OpenAI API key configured in .env
✅ Node.js and pnpm installed
✅ Basic TypeScript knowledge

Getting Started

Start with Lesson 3a: Basic Prompt and work through each lesson sequentially. Each builds on concepts from the previous ones.

Navigation

Previous: Lesson 2: TypeScript Setup
Next: Lesson 3a: Basic Prompt
Module Index: AI SDK Essentials

Coming Soon: Advanced Prompt Techniques

Additional lessons are in development to cover more advanced OpenAI capabilities:

🔜 Lesson 3h: Vision & Image Analysis (Coming Soon)

Analyzing and understanding images with GPT-4 Vision

Upload and analyze images
Extract information from screenshots
Describe visual content
Combine vision with text prompts
Use Case: Document scanning, image captioning, visual Q&A

🔜 Lesson 3i: PDF Processing (Coming Soon)

Reading and extracting data from PDF documents

Parse PDF content
Extract structured data from forms
Summarize long documents
Multi-page document analysis
Use Case: Invoice processing, contract analysis, research papers

🔜 Lesson 3j: Batch Processing (Coming Soon)

Process multiple prompts efficiently with Batch API

Submit batch requests
Cost-effective bulk processing
Handle large-scale operations
Monitor batch job status
Use Case: Data processing, content generation at scale, report creation

🔜 Lesson 3k: Audio & Speech (Coming Soon)

Working with audio input and speech-to-text

Transcribe audio files
Generate text from speech
Audio analysis and summarization
Use Case: Meeting transcriptions, podcast summaries, voice commands

What You'll Learn

By completing the current seven lessons, you'll master:

✅ Core prompting techniques
✅ AI behavior customization
✅ Response control and formatting
✅ Real-time streaming
✅ Type-safe structured outputs
✅ External tool integration

And coming soon:

🔜 Image analysis and vision capabilities
🔜 PDF document processing
🔜 Batch operations for scale
🔜 Audio and speech processing

Ready to begin? Start with Lesson 3a →

Module 1 - Lesson 3: OpenAI Prompts Overview