Joe Barrow is a Senior Research Scientist at Adobe Research, working on training and efficiently serving VLMs for document tasks. He previously led the machine learning team at Pattern Data, building document processing pipelines for hundreds of millions of pages. His open source ML projects include commonforms (making PDF forms fillable), tinyhnsw (building a vector database for fun and no profit), and LambdaNet (Haskell deep learning framework).

I’m an AI and product engineer building systems that work with private knowledge and support real workflows. I’ve taught people how to use AI, from a Boot.dev RAG course to live courses on AI-assisted development. I’ve also helped teams improve AI products, tools, and workflows from AnkiHub (collaborative learning tools) and SpecStory (agentic software) to enterprise companies like Travel + Leisure and General Mills.

These days I focus on context-first AI systems. In practice, that means helping teams see and improve the parts of the system that decide what the system can use: retrieval, memory, tool use, evals, traces, harnesses, and the product interface around them. I help teams find where the process bottlenecks, whether the problem is search, agent behavior, workflow design, or the human interface, and then fix that layer.

Hamel Husain is a ML Engineer with over 20 years of experience. He has worked with innovative companies such as Airbnb and GitHub, which included early LLM research used by OpenAI, for code understanding. He has also led and contributed to numerous popular open-source machine-learning tools. Hamel is currently an independent consultant helping companies build AI products.