The Codebase That Kept Breaking
We had a problem. Our main client project — a React SPA with roughly 50,000 lines of JavaScript — was becoming fragile. Every sprint brought regressions. A renamed prop here, a changed API response there, and suddenly three pages were broken.
The team was spending more time debugging than building. Something had to change.
Why TypeScript? (And Why We Hesitated)
I'll be honest: I was skeptical at first. TypeScript felt like overhead. More files to write, more syntax to learn, more tooling to configure. Our small team couldn't afford to slow down.
But after the third straight sprint where we shipped a hotfix for a type-related bug, the cost of not migrating became clear. We weren't saving time by avoiding TypeScript — we were spending it in the worst possible way: on preventable bugs.
Our Migration Strategy: No Big Bang
We tried a full rewrite once. On a different project. It failed. Three weeks of work thrown away because the codebase moved too fast underneath us.
This time, we went incremental:
Phase 1 — Infrastructure (Week 1)
Added tsconfig.json with strict: false and allowJs: true. Renamed the entry point. That's it. The app still ran. No features broken. Team confidence: intact.
Phase 2 — Shared Types (Week 2-3)
Created a /types directory. Started with API response types — the highest-value, lowest-risk target. When your API returns user.adress instead of user.address, TypeScript catches it before your users do.
Phase 3 — Component by Component (Ongoing) Every time someone touched a file, they converted it. No dedicated "migration sprints." It just happened organically as part of normal work.
The Surprises (Good and Bad)
What went better than expected
Onboarding speed doubled. New developers stopped asking "what does this prop do?" They could hover over any variable and see its type. Our most recent hire was productive in 3 days instead of the usual week.
Refactoring became fearless. Before TypeScript, renaming a prop meant grep-searching the entire codebase and praying you didn't miss one. Now the compiler tells you every single place that needs to change. We refactored our entire auth flow in an afternoon — something that would have taken days before.
API mismatches caught at build time. We use zod schemas to validate API responses at runtime, and TypeScript interfaces for compile-time safety. The combination catches issues before they reach production.
What was harder than expected
Third-party typings. Some libraries had outdated or incomplete type definitions. We spent more time writing custom .d.ts files than we anticipated.
Team buy-in. Not everyone was excited. One senior developer felt TypeScript was "Java in disguise." It took a few weeks of seeing real bugs caught by the compiler before the whole team was convinced.
Generic types. Our shared component library needed generics — Table<T>, Select<TOption> — and these were genuinely difficult to type correctly. This was where the learning curve was steepest.
The Numbers After 6 Months
Here's what we measured:
- Production bugs from type errors: 12/month → 0-1/month
- Average PR review time: 45 min → 25 min (reviewers trust the compiler)
- Onboarding time for new devs: 5 days → 2-3 days
- Developer satisfaction (internal survey): increased from 6.2 to 8.4/10
The migration took about 4 months to reach 90% coverage. We're now at 98%. The remaining 2% is legacy code that nobody touches.
What I'd Do Differently
Start with strict: true. We started with strict: false to ease the transition, but it meant we had to do a second pass later. In hindsight, ripping off the bandaid would have been faster.
Invest in shared types earlier. Our biggest wins came from having a single source of truth for types. We should have built the /types directory in the first week, not the second.
Don't migrate test files last. We left test files for the end, which meant our tests were lying to us about coverage. Type your test fixtures early.
Is It Worth It?
For any project with more than one developer and a lifespan longer than 6 months — absolutely. TypeScript doesn't prevent all bugs, but it eliminates an entire category of them. And in my experience, that category is responsible for about 60% of production incidents.
The migration cost us roughly 15% of our velocity for 4 months. The return has been permanent and compounding.
If you're running a growing JavaScript codebase and things are starting to feel fragile: don't wait as long as we did.