Building AI-Native Products

Why Tool Calling Breaks—and What to Do Instead

Hosted by Hugo Bowne-Anderson and Alan Nichol

Mon, Jun 2, 2025

4:00 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

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

Why most “tool use” patterns break at scale

Understand the limitations of atomic function calls and ReAct-style orchestration in real-world systems.

How to design stateful, multi-turn business logic

Learn how to guide users through complex, multi-step processes—without relying on brittle prompt chaining.

How Process Calling works in production

See how to combine LLMs and deterministic processes to deliver robust, explainable conversational experiences.

Debug less and ship faster with modular flows

Discover how structured, reusable business processes reduce flakiness and accelerate iteration.

Why this topic matters

Most agent frameworks give LLMs tools and hope they pick the right one. But real conversations aren’t API-ready—users say things like “you messed up my order” and expect resolution. That requires branching logic, memory, and follow-up. In this lightning lesson, Alan Nichol and Hugo Bowne-Anderson show how Process Calling makes agents reliable, inspectable, and effective.

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.

Alan Nichol

CTO, Rasa, OSS Sorcerer

Alan Nichol is the Co-Founder and Chief Technology Officer of Rasa, a leader in generative conversational AI. Founded in 2016, Rasa enables enterprises to build and deliver next-level AI assistants. Under Nichol's leadership, Rasa has merged a state-of-the-art engine with a user-friendly no-code UI, offering a transparent and flexible platform that aligns with business logic. This innovative approach has made Rasa a reliable and trusted choice for enterprises seeking to enhance customer interactions while reducing costs.

Learn directly from Hugo Bowne-Anderson and Alan Nichol

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