Lesson 1689 of 2116
AI coding: large migrations with checkpoint commits
Break a framework or version migration into named checkpoints. Each checkpoint compiles, passes tests, and is committed before the next prompt.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2migration strategy
- 3checkpoint commits
- 4incremental change
Concept cluster
Terms to connect while reading
Section 1
The premise
Big-bang AI migrations fail because errors compound across files. Splitting the migration into compileable, testable checkpoints keeps each prompt narrow and each rollback cheap.
What AI does well here
- Apply a single mechanical transform across many files
- Update imports and call sites consistently
- Generate a migration plan from before/after examples
What AI cannot do
- Hold a 50-file migration in working memory coherently
- Decide which behavioral changes are acceptable
- Catch logic regressions without your tests
Key terms in this lesson
End-of-lesson quiz
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