The Agentic Lifecycle with Opik: Trace, Evaluate, Iterate

Hosted by Abby Morgan and Hugo Bowne-Anderson

Thu, Feb 26, 2026

11:00 PM UTC (30 minutes)

Virtual (Zoom)

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Building AI Applications for Data Scientists and Software Engineers
Hugo Bowne-Anderson and Stefan Krawczyk
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What you'll learn

Tracing your agent's reasoning

How to capture every step with Opik's @track decorator: tool use, retrieval, and decisions

Building evaluation pipelines for agents

Build evaluation datasets, score agent outputs, and iterate rapidly with side-by-side experiments

Live end-to-end agentic build

Code walkthrough building and evaluating a multi-step research agent with Opik and OpenAI

Why this topic matters

Organizations are deploying multi-step AI agents, but most teams lack the tooling to build them reliably. Errors compound, behavior is non-deterministic, and debugging without observability is nearly impossible. The cost: hallucinated outputs, runaway token spend, lost user trust. This session gives you production-grade observability and evaluation with Opik, fully open source.

You'll learn from

Abby Morgan

AI Engineer at Comet, ex-Springboard

Abby Morgan is an AI Research Engineer and Developer Advocate at Comet, where she helps teams build reliable ML and LLM systems. She creates technical content on MLOps, LLMOps, and generative AI, and speaks on experiment tracking and observability at scale.


Hugo Bowne-Anderson

AI & data engineer, consultant, educator of 3+ million students (ex-Yale)

Hugo Bowne-Anderson is an independent data and AI consultant with extensive experience in the tech industry. He is the host of the industry podcast 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 has also worked with organizations like Data Carpentry to promote data literacy. His impact on data science education is significant, having developed over 30 courses on the DataCamp platform that have reached more than 3 million learners worldwide. Hugo also created and hosted the popular weekly data industry podcast DataFramed for two years. Committed to democratizing data skills and access to data science tools, Hugo advocates for open source software both for individuals and enterprises.

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