tags: [ai, productivity, devtools, tutorial]
claude code in production is different
you need safety nets, verification, and patterns that prevent expensive mistakes
the production mindset
test everything. review everything. never trust first generation
key patterns
- pre-commit hooks catch issues before they reach your repo
- tdd with claude: write tests first, then implementation
- code review workflow: /review before every commit
- staging environments: test ai-generated code in isolation first
- rollback plans: always have git commits as save points
what to verify manually
- security-critical code (auth, payments, data access)
- database migrations (destructive operations)
- api integrations with external services
- anything that touches production data
what claude handles well
- boilerplate and repetitive code
- test generation
- refactoring with clear requirements
- documentation updates
- code reviews for common issues
production use is about trust calibration. know when to verify and when to ship
part 8 of the mastery series
Read the full guide
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