Engineering ideas into existence
From failing exams in school to building AI systems at scale — raw personal stories and no-BS technical write-ups from my journey as a developer.
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Personal
Featured
I used to score below 40% in most subjects. Not because I wasn't capable — but because I was studying wrong. The moment I stopped studying out of fear and started studying out of curiosity, everything shifted. This is that story.
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Personal
Calculus, linear algebra, probability — I didn't know they were training me for AI/ML. Looking back, every formula I struggled with in 12th grade became a building block for the models I build today.
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Personal
I wasn't the smartest coder. But I was consistent, communicative, and genuinely cared about others improving. Here's how that attitude turned into a leadership role at Hackslash and what I learned running 5+ workshops.
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Personal
It was 2 AM, second year of college. I was watching a YouTube video about how Netflix recommends shows. That one video rewired my path forever. I share the exact moment curiosity became obsession.
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Personal
24 hours, 3 people, one idea. We built an LLM-powered resume intelligence system that blew the judges away. This is the behind-the-scenes story: the panic, the pivot, and the win.
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Technical
In school, we had a subject called "Introduction to Java." I thought it was just another boring class. But it became my entry point into programming — teaching me OOP, logic, and the joy of seeing code run for the first time.
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Technical
My first AI project: a voice-activated Python assistant I called JARVIS. No transformers, no LLMs — just speech recognition, pyttsx3, and Wikipedia API. Simple? Yes. But it was the brick that built my AI journey.
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Technical
Flask, MySQL, automated WhatsApp confirmations. This is the full technical breakdown of the Raghavendra Swami Mutt booking system — architecture decisions, database schema, and lessons learned.
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Technical
A deep-dive into Retrieval-Augmented Generation. How I built semantic search with OpenSearch, connected Amazon Bedrock LLMs, and deployed the whole thing on AWS ECS — with real token cost breakdowns.
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Technical
Multiple users, one editor, zero conflicts. I walk through the full architecture of my WebSocket-powered collaborative coding platform — room management, operational transforms, and Socket.IO under the hood.
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Technical
Standard CNNs tell you what they think. Bayesian deep learning tells you how confident it is. A technical breakdown of how we built uncertainty-aware pneumonia detection — and why it matters for real clinical use.
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Technical
Not just a black-box model — users see exactly which features drive the price. The full breakdown of feature engineering, XGBoost tuning, SHAP visualization, and serving real-time predictions via Flask REST API.
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I write what I build, and I build for real problems. If something resonated, let's talk — or just say hi.