959: Building Agents 101: Design Patterns, Evals and Optimization (with Sinan Ozdemir) episode artwork

EPISODE · Jan 20, 2026 · 1H 4M

959: Building Agents 101: Design Patterns, Evals and Optimization (with Sinan Ozdemir)

from Super Data Science: ML & AI Podcast with Jon Krohn · host Jon Krohn

AI entrepreneur and bestselling author Sinan Ozdemir speaks to Jon Krohn about the practical differences between agentic AI and AI workflows, why evaluating accuracy on its own won’t tell you enough about AI models, and more about his latest book Building Agentic AI.  This episode is brought to you by the ⁠⁠Dell⁠⁠, by ⁠⁠Intel⁠⁠, by Fabi and by Cisco. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/959⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: (04:57) Exploring the differences between workflows and agents (17:03) How to work out parameter count for a given task (25:26) The best way to evaluate LLMs (33:12) How to run hybrid workflow + agentic projects effectively

Episode metadata supplied by the publisher feed · Published Jan 20, 2026

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959: Building Agents 101: Design Patterns, Evals and Optimization (with Sinan Ozdemir)

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This episode was published on January 20, 2026.

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