I design production-grade AI systems — multi-agent pipelines, RAG architectures, and the infrastructure that holds them together when real users show up. Working across Google ADK, Claude ADK, and LangGraph. Writing and building at the frontier of what's possible.
My path into AI started with classical computer vision and NLP — shipping object detection models, 3D point cloud systems, and BERT-based semantic search in production environments, back when none of that came with a convenient API wrapper.
That foundation shapes how I work today. Years spent in the unglamorous parts of ML — data pipelines, model registries, latency budgets, failure modes — means I know what's inside these systems, not just what they can do when everything goes right.
Today I work at the frontier of multi-agent AI — designing production systems across Healthcare, Finance, and Telecom using Google ADK, Claude ADK, and LangGraph. I've contributed to internal agent frameworks used across large engineering organisations, and I lead teams through the hardest part: turning a compelling demo into something that holds up when real users and real data arrive.
My longer game is to write, research, and build in public — sharing the patterns, pitfalls, and principles that only come from doing this work for real.
I'm open to conversations about ambitious AI systems, technical architecture, and writing collaborations. If you're working on something interesting — reach out.
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