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The Hidden Simplicity of GenAI Systems

Hosted by Hugo Bowne-Anderson and John Berryman

Tue, Jul 1, 2025

3:30 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

71 students

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Go deeper with a course

Building LLM Applications for Data Scientists and Software Engineers
Hugo Bowne-Anderson and Stefan Krawczyk
View syllabus

What you'll learn

Understand the core building blocks behind GenAI apps

Learn how four GenAI pillars—instructions, context, reasoning, and tools—support agents, RAG, and workflows.

Reframe complexity into reusable patterns

See how core GenAI ideas combine into popular patterns, & how to move beyond them to design systems that fit your goals.

Leave with practical inspiration

Walk through two simple but powerful examples so you leave ready to adapt, remix, and build GenAI features your way.

Why this topic matters

At first, GenAI seems neatly split into agents, RAG, and workflows, but up close, it’s messy. This talk clears the fog by uncovering the small set of principles behind all major patterns. Once you grasp them, the space opens up: you’ll see how patterns relate and gain the confidence to build systems that match your exact goals.

You'll learn from

Hugo Bowne-Anderson

Podcaster, Educator, DS & ML expert

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 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.

John Berryman

AI Consultant and Builder, Co-Author of Prompt Engineering for LLMs, ex-Github

John Berryman is the founder of Arcturus Labs, where he helps teams build AI applications. He was an early engineer on GitHub Copilot, contributing to both its code completions and chat features, and is the coauthor of Prompt Engineering for LLMs (O’Reilly).


Before Copilot, John worked in search – helping build systems for the US Patent Office, Eventbrite, and GitHub. He also coauthored Relevant Search (Manning), a guide to modern search technology.


With experience spanning foundational search and cutting-edge LLM tools, John brings a deep, practical understanding of how to design smart, useful AI systems.

GitHub
Yale University

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