AI Pair Programming Workflow

Overview

AI pair programming works best with short iterations: define a tiny goal, generate a draft, validate, and refine. This keeps risk low and feedback fast.

Recommended Loop

flowchart TD
    A[Pick Small Task] --> B[Ask AI for Draft]
    B --> C[Run Tests]
    C --> D[Review Diff]
    D --> E[Refine Prompt]
    E --> B
    D --> F[Commit]

Practical Example - Add Validation to Command

Step-by-step loop:

1. Ask for validator class only.
2. Run unit tests.
3. Ask for edge-case tests.
4. Review naming and error messages.

using FluentValidation;

public sealed class RegisterUserCommandValidator : AbstractValidator<RegisterUserCommand>
{
    public RegisterUserCommandValidator()
    {
        RuleFor(x => x.Email).NotEmpty().EmailAddress();
        RuleFor(x => x.Password).MinimumLength(12);
    }
}

Production Example - PR Workflow

A practical team workflow can require:

• One focused feature per AI session
• Mandatory test updates in same pull request
• Reviewer checks for hallucinated APIs and incorrect assumptions

Common Pitfalls

• Large prompts that mix architecture and implementation
• Committing generated code without running locally
• Ignoring negative path tests

Key Takeaways

• Keep AI tasks small and testable.
• Fast feedback loops prevent large rework.
• Human review is still the quality gate.