GitHub Copilot & ChatGPT for Developers

1 Introduction to ChatGPT (Developer Perspective)

What ChatGPT Can Do

• Generate code from natural language

• Explain unfamiliar code

• Debug errors

• Refactor code

• Write tests & documentation

What ChatGPT Cannot Reliably Do

• Guarantee correctness

• Replace design thinking

• Understand hidden system context

📌 Tip: Emphasize AI as a co-pilot, not an autopilot

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2 Prompt Engineering for Developers

Prompt Types

• Instructional: “Write a Python function to…”

• Contextual: “You are a backend engineer…”

• Iterative: “Improve the previous solution by…”

• Constraint-based: “Use only standard libraries…”

Prompt Components

• Role

• Task

• Context

• Constraints

• Output format

Bad Prompt

Write code to sort data

Prompt 2: Write SQL query to select 10 records from products table

Good Prompt

You are a Python developer. Write a function to sort a list of dictionaries by price in descending order. Handle missing keys gracefully.

Ask questions before starting the work. do not assume anything implicitly

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3 Hands-on: ChatGPT Coding Scenarios

Activity 1: Code Generation

• Ask ChatGPT to:

  • Create a number guessing game

  • Build a REST API skeleton

  • Write a data validation function

Activity 2: Code Explanation

• Paste unfamiliar code

def process_numbers(numbers):

result = []

for n in numbers:

if n % 2 == 0:

result.append(n ** 2)

else:

result.append(n ** 3)

return result

Explain this Python code line by line.

Assume I am a beginner and also explain why this logic might be useful.

Activity 3: Debugging

def calculate_average(numbers):

total = 0

for i in range(len(numbers)):

total = total + numbers[i]

average = total / len(numbers)

return avg

The following Python code throws an error.

Identify the issue, explain why it happens, and provide the corrected code.

Follow-up prompt

Improve this code using Python best practices.

· ChatGPT as a code explainer

· ChatGPT as a debugging assistant

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4 Free ChatGPT Alternatives

• Google Gemini – reasoning + search

• Microsoft Copilot – enterprise & M365

• Claude – long context, safer responses

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5 Introduction to GitHub Copilot

What Copilot Is

• AI pair programmer inside IDE

• Context-aware code completion

Capabilities

• Inline suggestions

• Comment-based prompting

• Copilot Chat

• Test generation

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6 Prompting with GitHub Copilot

Inline Prompting

# Write a Python function to check if a number is prime

Comment-Driven Design

# Game: Player vs Computer

# Rules:

# - Guess a number between 1 and 100

# - Provide hints

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7 Rules for Effective Prompts (Copilot & ChatGPT)

• Be explicit

• Add constraints

• Describe intent, not syntax

• Iterate, don’t expect perfection

• Always review output

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8 Hands-on: Game Scenario (Language-agnostic)

Task

• Build a simple game:

  • Guess the number / Tic-Tac-Toe / Dice game

• Use:

  • ChatGPT for logic

  • Copilot for implementation

Outcome
Participants experience:

• AI-assisted design

• Faster coding

• Reduced boilerplate work

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9 Module 1 Takeaways

• Prompt quality = output quality

• ChatGPT excels at reasoning & explanation

• GitHub Copilot excels at in-IDE productivity

• Developers remain accountable for correctness