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

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

Super Data Science
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1 Plays1 month ago

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 natalie@superdatascience.com 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
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