{"id":4095,"date":"2025-04-01T17:27:06","date_gmt":"2025-04-01T17:27:06","guid":{"rendered":"https:\/\/www.aviator.co\/blog\/?p=4095"},"modified":"2026-06-07T13:36:52","modified_gmt":"2026-06-07T13:36:52","slug":"aviator-agents-code-migration","status":"publish","type":"post","link":"https:\/\/www.aviator.co\/blog\/aviator-agents-code-migration\/","title":{"rendered":"Aviator Agents: LLM-Assisted Large Scale Code Migrations"},"content":{"rendered":"\n

Code migrations are necessary but painful. They\u2019re tricky, time-consuming, and let\u2019s be honest\u2014boring. They demand precision but often end up being a brute-force operation riddled with trial and error.

That\u2019s why we created Aviator Agents<\/a><\/strong>, an LLM-based Agentic framework to perform large-scale code migrations in your repositories.<\/strong>

Aviator Agents<\/a> act as intelligent migration assistants<\/strong>, emulating human patterns to perform migrations by finding references and documentation, understanding dependencies, breaking down large chunks of code, and verifying build status. <\/p>\n\n\n\n

How Aviator Agents Works<\/strong><\/h2>\n\n\n\n
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  1. Define the migration<\/strong> \u2013 Specify the change you want to make. This could be renaming an API, refactoring a code pattern, or updating dependencies.<\/li>\n\n\n\n
  2. AI generates initial suggestions<\/strong> \u2013 The agent analyzes your codebase and produces a migration plan, applying transformations in a sandboxed environment.<\/li>\n\n\n\n
  3. Human-in-the-loop refinement<\/strong> \u2013 Developers review, modify, and guide the AI’s changes, ensuring correctness.<\/li>\n\n\n\n
  4. Automated execution at scale<\/strong> \u2013 Once validated, Aviator Agents rolls out the migration across your entire codebase with confidence.<\/li>\n\n\n\n
  5. Continuous learning<\/strong> \u2013 Feedback loops refine future migrations, making each successive transformation smarter.<\/li>\n<\/ol>\n\n\n\n

    Unlike most LLM-based frameworks, Aviator Agents is an end-to-end framework that connects directly with GitHub. This eliminates the need to set up a custom environment and build process.<\/p>\n\n\n\n

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