About / 02
Nearly a decade building production software across the web stack—from Ruby on Rails and Elixir/Phoenix to JavaScript, TypeScript, and Node.js with Express and NestJS, as well as cloud systems. Now I’m going deeper into C++, systems programming, memory, concurrency, and AI/ML.
Current study
M.Tech AI/ML · In progress
Strengthening the mathematics, modelling and systems foundations behind reliable AI software.
Beyond the stack / 01
I learned software by following problems across boundaries. A feature rarely ends at the interface: it continues through an API, a queue, a database, an operating system and the constraints of the machine running it.
That curiosity has taken me from Ruby, Ember and Phoenix to TypeScript, Node.js and cloud systems. Today I am deliberately moving closer to the machine—studying C++, memory, concurrency, Linux internals and the engineering trade-offs that make software predictable under load.
My ongoing M.Tech work in AI/ML adds another layer: the mathematics behind models, how data moves through a system and how intelligent features can be built without losing sight of reliability, cost or user value.
How I work
Understand the path from user action to bytes, processes and failure modes.
Prefer clear constraints, measurable behaviour and decisions another engineer can review.
Turn unfamiliar concepts into small systems, benchmarks, notes and repeatable experiments.
Human languages
Clear communication across teams—and curiosity beyond code.
Early
Build
Now
Going deeper
