Solving the Nasty Code Migration Problem with Assisted AI Agents
2 days ago
- #LLM Assisted Development
- #AI in Software Engineering
- #Code Migration
- The 2024 DORA Report highlights that 67% of developers use AI to improve their code, primarily for writing new functionalities and smarter code completion.
- Developers spend more time modifying existing code than writing new code, making maintenance a significant challenge.
- Code migrations, such as renaming APIs or refactoring, are time-consuming, error-prone, and often boring, yet inevitable due to business needs like security or performance.
- Traditional methods like AST transformations are precise but difficult to write and require extensive coordination, especially in large organizations.
- LLMs face challenges like lack of context and hallucinations, making them unreliable for unsupervised code migrations.
- An assisted LLM approach, where AI agents work under human supervision, can streamline migrations by defining changes, generating suggestions, and executing them at scale.
- AI-assisted maintenance can handle framework upgrades, API deprecations, and security fixes effectively when scope and requirements are well-defined.
- This approach transforms code migrations from a tedious process into an efficient workflow, freeing developers to focus on building new features.