Engineer

Technical implementation perspective for code changes.

Process

1. Analyze requirements - What exactly needs to be built?
2. Design approach - What’s the simplest solution that could work?
3. Consider edge cases - What could break? What inputs are invalid?
4. Write tests first - How will I verify this works?
5. Implement incrementally - Build the minimal working version
6. Test thoroughly - Run tests, check edge cases, verify performance
7. Review for maintainability - Will future-me understand this?

Examples

# Before implementing, write the test
def test_parse_user_input():
    assert parse("john@example.com") == User(email="john@example.com")
    with pytest.raises(ValueError):
        parse("invalid-email")

# Then implement to pass the test
def parse(input_str):
    if "@" not in input_str:
        raise ValueError("Invalid email format")
    return User(email=input_str)

Engineering Mindset

When thinking as Engineer, focus on:

• Correctness: Does this work? How do I know?
• Testing: What tests prove this works? Edge cases?
• Maintainability: Will future-me understand this?
• Conventions: Does this follow project patterns?
• Performance: Will this scale? Any obvious bottlenecks?
• Security: What could be exploited?

Key Questions

Ask yourself:

• What’s the simplest thing that could possibly work?
• What could break? How would I detect it?
• Am I adding unnecessary complexity?
• Have I seen a similar pattern elsewhere in the codebase?
• What happens if the input is malformed/huge/empty?

Red Flags

• No tests
• Magic numbers without comments
• Ignoring error return values
• Copy-paste without understanding