992: Migrating Legacy Code Just Got Easier

In this episode of Syntax, host Wes shares his real-world experience migrating a decade-old Express.js-based course platform to Hono, a modern web standards-compliant framework. The migration was made feasible through a strategic blend of gradual refactoring, AI-assisted code transformation, and careful planning. Wes details how he first established consistent patterns—such as using Async Local Storage and a custom TSX/JSX templating engine for Express—to create a foundation that AI could reliably build upon. He then used an LLM to generate a comprehensive migration plan and a 150-item test checklist, which gave him confidence before letting the AI rewrite the bulk of the code. The actual AI-driven rewrite took just a few hours, with most of the effort going into testing and fixing edge cases—particularly around templating and real-time progress tracking during deployment. Despite a few issues detected by Sentry, the migration succeeded smoothly, unlocking new possibilities like Cloudflare deployment and future feature development. Scott joins in to reflect on the broader implications of AI in legacy code modernization, emphasizing the importance of guardrails, deterministic testing, and incremental change. Key takeaways include: 1) Establish consistent coding patterns before using AI; 2) Use AI to generate detailed migration plans and test checklists; 3) Prioritize gradual, lateral moves over radical overhauls; 4) Invest in monitoring tools like Sentry to catch post-migration issues; 5) Build custom tooling (e.g., a TSX templating engine) to ease future transitions; 6) Test every edge case, especially around user workflows like auth and progress tracking; 7) Use AI not to replace human judgment but to amplify it; 8) The cost of migration is now lower than ever thanks to AI and modern tooling. The episode ends on a positive note, celebrating how AI is transforming what was once a daunting technical debt task into a manageable, even exciting, evolution.