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
