We dive into why most AI tools today feel like “horseless carriages”: retrofitted instead of reimagined.
In this episode, we explore:
* The shift toward agentic software
* The need for headless systems and declarative interfaces
* Why precision and recall matter more than ever in data analytics
* Why evaluating agentic systems requires new abstractions drawing on physics, semantics, and statistical observability
* How AI operates in a kind of semantic space.
00:00:00 Introduction to Agentic Data and Skeuomorphic AI
00:04:26 The Shift to Headless and Agentic Software
00:14:18 Precision, Recall, and the Taxonomy of Questions
00:22:58 Challenges in LLM Evaluation and Industry Mindset
00:29:29 Physics Analogies for Agentic Software
00:38:28 Conclusion: The Future of Agentic Analytics
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