Hey, I’m Pranav! My journey as an engineer didn’t begin with a line of code, but with a soldering iron and an insatiable curiosity for the magic inside my childhood toys. I wasn’t content just playing with them; I had to understand how they worked. This drive led me from simply taking things apart to building them back, better.
The Spark: The Logic of Circuits
In middle school, my obsession with electronics grew. I moved from basic circuits to designing complex boards to automate my own home—long before “smart devices” were mainstream. I wasn’t just following tutorials; I was spending hours wrestling with logic gates, debugging with a multimeter, and learning from failure until a system worked as intended. This hands-on experience taught me my first crucial lesson in engineering: a system is only as reliable as its foundation.
The First Evolution: A Deep Dive into Machine Learning
As I transitioned to software, my fascination with systems that could “think” led me straight into the world of Machine Learning. I dove headfirst into the field, building predictive models and learning to handle vast, complex datasets. My internship at Piatrika Biosystems was a culmination of this, where I worked with mission-critical genotypic data to predict plant phenotypes.
I learned to build models that could achieve high accuracy. But a new, more frustrating and fundamental question emerged, one that the model itself couldn’t answer:
How do you serve this intelligence to millions of users, reliably, instantly, and at scale?
The Pivot: The Backend Revelation
That question was the catalyst. I had a profound realization: the most sophisticated AI model is worthless without a backend system capable of delivering its power. My fascination shifted from the “brain” to the “central nervous system”—the high-performance infrastructure that powers everything.
This was my deliberate pivot to backend engineering. I became obsessed with solving the foundational problems that make modern applications possible:
- Scalability: How do you handle a million concurrent users?
- Latency: How do you ensure every request is answered in milliseconds?
- Fault Tolerance: What happens when a part of the system inevitably fails?
- Data Integrity: How do you guarantee that data is never lost or corrupted?
My experience in Machine Learning wasn’t a detour; it was the critical context that gave me a deep appreciation for why robust backend architecture matters. I now design systems with the firsthand understanding that they must support complex, data-intensive business logic under pressure.
The Mastery: Building the Tools of the Trade
To truly master backend engineering, I believe you have to understand the foundational tools from first principles—to open the black boxes most developers take for granted. This conviction led me to a series of self-directed deep dives where I am building core developer tools from scratch:
- A Performant In-Memory Key-Value Store: Recreating the core functionality of Redis to master caching strategies and data structure optimization at a low level.
- A Container Runtime: Implementing the Linux syscalls and namespaces that power Docker to grasp the fundamentals of process isolation.
- A Content-Addressed Version Control System: Deconstructing the genius behind Git and its surprisingly complex distributed data model.
- A Multi-threaded Web Crawler: Developing a high-throughput crawler in Go to master I/O-bound concurrency with goroutines and channels.
My Principles in Practice
My journey—from tinkering with hardware, to training complex models, to building the underlying infrastructure of the internet—has shaped not just my skills, but my professional philosophy.
- Strong Opinions, Weakly Held: I advocate for well-researched solutions but readily embrace better ideas backed by data. The best outcome is the goal, not my initial idea.
- Documentation as Empathy: I treat clear documentation and well-written pull requests as a cornerstone of effective remote collaboration, respecting the time of my teammates and my future self.
- Pragmatism Over Perfection: I focus on shipping value by finding the simplest solution that effectively solves the business problem, avoiding premature optimization and over-engineering.
Ultimately, I see software engineering as a craft. It’s a continuous journey of learning, building, and refining, and I’m always open to connecting with fellow builders who share that passion.
Feel free to reach out on LinkedIn .