Purpose Drift During Refactoring
When AI assistants lose sight of the original purpose during refactoring. The code undergoes continuous improvements, but these changes gradually disconnect from the original objectives, resulting in a solution that might be “cleaner” but no longer addresses the core problem effectively.
How to Spot It
Look for these signs:
- Multiple successive refactoring suggestions without reconnecting to original goals
- Increasing complexity without corresponding functional improvements
- Comments like “we can improve this further by…” without justifying the improvements
- Disappearance of key functionality during “simplification”
- Extended discussions about implementation details with no reference to user needs
- Inability to explain how a change relates to the original requirements
- Significant changes to public interfaces without clear benefit
Why It’s Harmful
- Causes loss of essential functionality
- Wastes development effort
- Creates code that’s technically “better” but functionally worse
- Extends development time without adding value
- Produces solutions that drift from user needs
- Makes it difficult to explain the purpose of code sections
What to Do About It
When you see this happening:
- Say “Let’s step back and remember what problem we’re trying to solve.”
- Ask “The original goal was X. How does this refactoring help with that?”
- Question: “What specific improvement will users or developers see from this change?”
- Set limits: “Let’s limit our refactoring to areas that directly impact our current goals.”
To prevent it next time:
- Document purpose clearly and revisit it regularly
- Define specific goals: “We’re refactoring to achieve X, Y, and Z improvements.”
- Add checkpoints: After each refactoring step, verify the solution still meets requirements
- Make connections: For each refactoring, connect it to a specific requirement or pain point
- Set time limits: “We’ll spend at most X time on refactoring before moving on.”
- Apply the “rule of three”: Wait until you see the same problem three times before refactoring
Example
AI: “Now that we’ve refactored the data access layer, we should also rework the service layer to use dependency injection, and then update the controller to follow CQRS principles…”
You: “Before we continue refactoring, let’s check if we’ve maintained the original functionality. The main goal was to fix the bug where users couldn’t update their profiles. Does our current solution address that, and is further refactoring necessary for that specific goal?”
Benefits of Fixing This
- Maintains focus on delivering actual value
- Reduces wasted effort on unnecessary improvements
- Aligns technical decisions with business outcomes
- Creates clearer justification for refactoring efforts
- Makes development progress more predictable
- Simplifies communication about the purpose of code changes