Agentic AI infrastructure, MCP, and agent evaluation.
Principal Solutions Architect, AI/ML at AWS · Adjunct Professor, Georgetown University
I work on the infrastructure layer of enterprise agentic AI: the gateways and registries that let agents discover and call tools under real authentication and audit, and the benchmarks that tell you which model to trust for a given job. Most of it ships in the open.
This site is where I keep notes on what I am learning. Papers I have read, courses I have built, and things I got wrong the first time.
Notes, wikis, and courses I keep in public.
An interlinked wiki on generative AI, compiled from clipped primary sources. 63 articles and counting.
What I am reading, and what stuck.
A self paced six week program to a working 200 level grasp of modern AI, three weeks of it on agents.
From no containers to running the MCP Gateway Registry and serving an LLM locally, in 13 phases.
A weekend course on AI for people who do not write code.
A book project.
Long form pieces and infographics, each one a page of its own.
Open source, mostly infrastructure for agents.
Enterprise MCP gateway and registry for agents, MCP servers, and skills. OAuth and OIDC, dynamic tool discovery, auditable tool access. 180+ enterprise deployments.
The Holistic Agent Leaderboard, a standardized harness for evaluating AI agents, built with Princeton researchers.
Foundation model benchmarking across hardware and serving stacks, so teams pick on measured cost and latency rather than intuition.
18 models over 21 real tasks, reduced to a cost and quality Pareto frontier. Ships a router that names the cheapest model clearing the bar.
An early MCP server, written weeks after the protocol shipped. Ask plain language questions about your AWS spend.
Turns an OpenAPI specification into a production ready MCP server.
Georgetown University, M.S. in Data Science and Analytics.
I created and teach DSAN-6725, Applied Generative AI for AI Developers, one of the first comprehensive generative AI courses offered in academia. It is now the most popular course in the program and earned a perfect 5 out of 5 in student reviews for Spring 2026. I also teach DSAN-6000, Big Data and Cloud Computing, and am building a new graduate course on AI agents. 500+ graduate students so far.
Selected posts from thirteen on the AWS blogs.
Available to speak on enterprise MCP architecture and agent evaluation.