Making LLM Agents Observable & Debuggable

Hugo Bowne-Anderson is an independent data and AI consultant with extensive experience in the tech industry. He is the host of the industry Vanishing Gradients, where he explores cutting-edge developments in data science and artificial intelligence. As a data scientist, educator, evangelist, content marketer, and strategist, Hugo has worked with leading companies in the field. His past roles include Head of Developer Relations at Outerbounds, a company committed to building infrastructure for machine learning applications, and positions at Coiled and DataCamp, where he focused on scaling data science and online education respectively. Hugo's teaching experience spans from institutions like Yale University and Cold Spring Harbor Laboratory to conferences such as SciPy, PyCon, and ODSC. He h

Vincent Koc is an AI research engineer at Comet, focused on model and agentic system evaluation as well as telemetry aware agentic systems. With nearly two decades of experience from shipping AI systems for publicly traded companies, contributing to leading open-source projects and working from statistics to deep learning. Vincent is also an adjunct lecturer at leading universities teaching applied AI and generative AI focusing on NLP. Vincent brings a very hands-on, cross-industry lens to his work with an academic grounding. He is passionate about making AI accessible to everyone and is currently authoring a book and has published for several publications and papers in this space. His work is available on github.com/vincentkoc ⁠ ⁠