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Multi-File Editing with AI

Techniques for LLM-assisted changes across multiple files. Coordinate edits, maintain consistency, and avoid drift.

Overview

Multi-file editing is where LLM coding assistants provide the most value — and where they are most likely to introduce inconsistencies. Effective techniques ensure changes across files remain coordinated and correct.

Provide the Full Picture

  • Include all files that need changes in the LLM context
  • Show type definitions, implementations, and tests together
  • Include the integration points where changed code is consumed
  • If a file is too large, provide the relevant section plus its public API

Change Order

OrderFile TypeWhy First
1Types / InterfacesDefines the contract all other code follows
2ImplementationImplements the contract defined by types
3TestsVerifies implementation matches expectations
4Integration pointsWires everything together (routes, config)

Verification

After multi-file changes: run the type checker (catches interface mismatches), run tests (catches behavioral regressions), and do a final review of the complete diff. Never merge multi-file LLM changes without all three checks.

Frequently Asked Questions

How do I prevent inconsistencies in multi-file AI edits?

Include all affected files in context, start with types/interfaces, then implementations, then tests. Run type-checking after changes to catch mismatches.

What LLM tools are best for multi-file editing?

Agentic tools like Cursor Agent Mode, Claude Code, and Copilot Agent Mode handle multi-file edits natively. They understand cross-file dependencies.