Step 01
AI-Assisted Development
Leveraging LLMs and fine-tuned models to accelerate product creation.

I build systems that write, test, and improve software using AI.
From absolute beginner to building intelligent systems.
Got my first laptop and knew absolutely nothing about it. Started learning through pure trial and error, breaking things, and learning from mistakes.
Formalized my passion by choosing Computer Science as my major. Built the foundational knowledge needed for my software journey.
Where theory met practice. Learned the core fundamentals of Software Development, Testing, SDLC, Logic Gates, Discrete Maths, Data Warehousing, DBMS, and Cloud.
Started with a 3-month intensive automation testing internship using Selenium and Java. Transitioned to a permanent role, starting my career in Software Testing and developing robust software testing tools.
Took the entrepreneurial leap during my internship period. Focused on building scalable, intelligent systems and shaping the engineering culture.
Every project below was shipped with AI as a collaborator, not a crutch — from prompt-driven experiments to agentic builds to mostly human-built systems with targeted AI assists.
CTO & Co-Founder · NxtHive · Q1 2026 – present
Hiring system with REST APIs and automation pipelines. End-to-end platform powering NxtHive's recruiting workflows, from candidate intake to interview orchestration.
CTO & Co-Founder · NxtHive · Q1 2026 – present
Marketing site and brand home for NxtHive Technologies. Motion-rich, responsive, optimised for performance and first-load clarity.
Intern · Cognizant · Q1 2026 – present
Internal automation system for enterprise workflows and mainframe interaction. Agent-driven CLI that stitches together legacy tooling with modern orchestration.
Solo · Personal · Q4 2024 → Q1 2026
Android-based tap-to-share system using NFC and Nearby Connections. Offline-first data exchange with a seamless handoff flow — UI and 95% of the backend built solo; one architectural blocker unblocked with AI assistance.
Solo · Personal · Q1 2025
ML-based outfit recommendation system using a personal wardrobe as input. Decision-support prototype exploring personalisation for everyday styling choices.
Solo · Personal · Q3 2024
Lightweight recommendation system based on user input. Hand-debugged after copying suggestions from an AI chat — a first exercise in treating AI output as a starting point, not an answer.
Every project follows a deliberate pipeline: accelerate ideation, tighten execution, and automate quality at each step.
Step 01
Leveraging LLMs and fine-tuned models to accelerate product creation.
Step 02
Crafting precise instructions to generate high-quality code and automation scripts.
Step 03
Building autonomous systems that perform tasks independently.
Step 04
Solving repetitive problems by replacing manual workflows with continuous integrations.