Jose Calderon
Lead Software Engineer at JP Morgan Chase
In this episode of Señors @ Scale, host Neciu Dan sits down with Jose Calderon — Lead Software Engineer at JP Morgan Chase, conference speaker, and Java/Spring community leader — to dive deep into refactoring vs rewriting at scale, how to track and justify architecture decisions, and the testing strategies that keep enterprise systems reliable.
Main Takeaways from my conversation with Jose:
🛠 Refactor if you’re in control, rewrite if you’re not.
If your team understands the codebase, has tests, and changes are predictable, refactor. If one line breaks something unrelated or the code is untestable, it’s rewrite time — but keep the scope locked and avoid “bonus” features.
🚧 Stabilize before you touch it.
Before a rewrite, Jose’s teams add telemetry, fix recurring issues, and lock down changes so the new build isn’t chasing a moving target.
💾 Your code is only as good as your decision history.
He uses Architecture Decision Records (ADRs) — stored in source control — to document the why behind each decision, making it easier to evolve or roll back choices later.
📈 Tests are documentation too.
Unit tests should read like an executable spec, explaining what the code does before you even open the class.
🎯 Synthetic testing catches breakage early.
Injecting canary events into critical paths — even in production when allowed — validates integrations before customers feel the pain.
🔥 Chaos engineering builds resilience.
Game-day drills prepare teams to recover fast when production crashes inevitably happen.
👨🏫 Mentorship multiplies impact.
By teaching final-year students how to lead and coach, Jose helps prepare them for the messy realities of enterprise engineering.
🎤 Also in this episode:
- How to pick the right complementary stack with Java
- Turning conference talks into memorable stories (Gaudí, aloe vera, and more)
- Why AI won’t replace devs, but devs using AI will replace those who don’t
- How gaming helps avoid burnout
Episode Length: 1 hour and 6 minutes of pragmatic engineering lessons on managing large-scale code changes
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