Type Hints Make AI Code Generation Significantly Better

If you're using AI coding assistants without type hints, you're leaving performance on the table.

When you ask an AI to complete this:

def process(data):
    # TODO: split by comma and return uppercase words

The AI has to guess what data is. A string? A file? A list?

But with type hints:

def process(data: str) -> list[str]:
    # TODO: split by comma and return uppercase words

Now the AI knows:

• data is definitely a string
• It should return a list of strings
• Methods like .split() and .upper() are appropriate

The result: More accurate completions, fewer hallucinations, less back-and-forth.

This extends to entire codebases. When your functions have type hints, AI tools can:

• Generate code that matches your existing types
• Suggest appropriate methods for the given types
• Catch inconsistencies in their own output
• Understand relationships between modules

Where this matters most:

• API handlers (FastAPI uses type hints for automatic validation)
• Data processing pipelines
• Any code that interfaces with AI-generated components

Type hints are documentation for both humans and machines. In 2026, that dual purpose matters more than ever.

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This is adapted from my upcoming book, Zero to AI Engineer: Python Foundations.

I share excerpts like this on Substack → https://substack.com/@samuelochaba