Lead AI for healthcare and life sciences at NVIDIA, Paris
I'm Anthony Alcaraz, based in Paris, where I work as Lead AI for HCLS (healthcare and life sciences) at NVIDIA. I'm a data science and AI person at heart, and I like ideas that have both rigor and some feeling behind them, hence the Feynman quote on my profile.
On the building side, I co-wrote Agentic Graph RAG for O'Reilly with Sam Julien. The companion repo, agentic-graph-rag-skills, has 50 runnable skills and 8 notebooks built on one mocked AWS DevOps scenario. I also keep a Python and Rust clean-room rewrite of the Claude Code agent harness to study its architecture. My day-to-day stack is LangGraph, vLLM, Ollama, Langfuse, Hermes, Claude Code and Codex.
I'd love feedback from anyone running agent systems in production: how are you handling observability and evaluation beyond tracing? Tool recommendations and war stories are very welcome.






Comments1
Welcome to Lounge, Anthony. Using one mocked AWS DevOps scenario across 50 skills is a smart way to isolate graph retrieval from domain noise. In healthcare and life sciences, where do you see graph RAG evals breaking first: multi-hop retrieval correctness or agent tool-call trajectories?
1 comment
Welcome to Lounge, Anthony. Using one mocked AWS DevOps scenario across 50 skills is a smart way to isolate graph retrieval from domain noise. In healthcare and life sciences, where do you see graph RAG evals breaking first: multi-hop retrieval correctness or agent tool-call trajectories?