Building production-grade LLM systems
I design and ship end-to-end Generative AI solutions — autonomous agents, RAG pipelines, multi-agent workflows, and MCP-powered integrations — that solve real enterprise problems at scale.
| Area | What I actually do |
|---|---|
| Autonomous Agents | Multi-agent systems using LangChain, Google ADK, and Crew.ai for real-time decision-making |
| MCP Integrations | Context-aware systems using Model Context Protocol to connect LLMs with enterprise data |
| Document Intelligence | RAG pipelines for automated extraction and Q&A over unstructured enterprise documents |
| LLM Backends | Scalable FastAPI services powering Gemini-based agentic workflows in production |
I write in-depth technical articles on LLM frameworks, agent design, and emerging protocols.
| Article | Topic |
|---|---|
| MCP: All Blackboxes Explained | Deep dive into Model Context Protocol standardisation |
| Model Context Protocol: A High Level Overview | MCP architecture and functionality |
| Crew.ai — Framework for Autonomous AI Agents | Multi-agent orchestration with Crew.ai |
| RAG: Retrieval Augmented Generation — Busted | How RAG pipelines work end-to-end |
| Introduction to LangChain | Building LLM-powered apps with LangChain |
| GEN-AI Storytelling with LIDA | LLM-driven data visualisation using LIDA |
AI / LLM
Backend & Infrastructure
Data & ML
"I do not fear this new challenge. Rather like a true warrior I will rise to meet it."