Who Am I?

My Journey

• Started with Python automation and developed numerous Django websites and APIs.
• Built serverless solutions leveraging AWS services like Lambda, API Gateway, SQS, DynamoDB, and EventBridge.
• Advanced into intelligent automation: exploring RAG systems, building agentic AI workflows, and understanding how modern LLMs can reason and act autonomously.

Today, I'm at the intersection of backend systems and autonomous AI by designing architectures where intelligent agents orchestrate complex workflows, integrate with external tools, and operate reliably in production.

What I Build

• Backend: Django APIs, database optimization, AWS infrastructure (Lambda, SQS, DynamoDB, EventBridge)
• Agentic AI: Autonomous agents with Claude, reasoning loops, tool orchestration, MCP integrations
• Workflow Automation: N8N pipelines, system integrations, event-driven architectures
• RAG Systems: Semantic search, vector databases, knowledge retrieval at scale
• Sports & Data Engineering: Built specialized tools as a sports enthusiast, including a Duckworth-Lewis (DLS) calculator, IPL Playoff simulator, and a Kaggle data pipeline for T20I datasets leveraging AWS.
• Development Setup: Building with Anthropic Claude, Google AI Studio, and modern AI tooling

Philosophy

I believe in learning in public. This blog documents the architecture decisions, debugging sessions, configuration patterns, and infrastructure choices that work. Not tutorials. Not theory. Just the documented path of someone building real systems and shipping them to production.

My goal: Help other engineers navigate the shift toward intelligent, autonomous systems by sharing what I've learned along the way.

Expertise