Lesson 1686 of 2116
AI coding: refactor safely by stating invariants
Tell the AI what must stay true after the refactor — call signature, side effects, performance bounds — and it stops introducing surprises.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2refactoring
- 3invariants
- 4behavior preservation
Concept cluster
Terms to connect while reading
Section 1
The premise
Refactor prompts fail when the AI optimizes the wrong axis. Stating explicit invariants — what must not change — keeps the rewrite focused on the dimension you actually want improved.
What AI does well here
- Preserve a documented public API while restructuring internals
- Apply a named pattern (extract method, strategy) consistently
- Diff old vs new behavior when given both
What AI cannot do
- Guarantee semantic equivalence across complex side effects
- Detect performance regressions without benchmarks
- Know which 'cleanups' your team actually accepts
Key terms in this lesson
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