00:00 Traces as the New Source of Truth in AI Systems

03:12 From Code-Based Logic to Trace-Based Documentation

08:47 Deterministic vs. Agentic Workflows: Precision vs. Recall

12:59 Observability, Traces, and the Flywheel Effect

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00:00 Context Graphs & Decision Traces

05:52 Why Systems of Record Fall Short

10:32 Challenges for Incumbents

13:43 Paths for Startups and Agent Observability

15:33 The Future Data Stack

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00:00 The Shift-Left Data Platform Thesis

06:49 Platform DNA and Structural Advantages

12:35 The Single Model of Truth for AI Systems

21:26 Research Engineering as the Next Core Discipline

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00:00 IBM’s Acquisition of Confluent and the Role of Real-Time Data

03:10 IBM’s Hybrid Cloud and AI Strategy Behind the Deal

08:23 Why Infrastructure Companies Rely on M&A for Growth

12:18 Ontology, Knowledge Graphs, and the Foundations of Digital Twins

17:01 Modeling Organizations as Digital Twins and the Shift to Agentic Software

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00:45 Why UI Is Pre-AI: From Human-Centered Interfaces to Agent-First Systems

10:52 Enterprise Moats in an Agentic Era: Commoditization vs. Service

14:08 The Future Role of Agents, OS, and Agent Engineering

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00:00 The Modern Data Stack and Industry Consolidation

03:14 Snowflake’s Acquisition of SelectStar

05:47 The Shift in Data Context Importance

08:01 Strategic Moves in Data Companies

10:26 Databricks vs. Snowflake: Innovation and Strategy

14:55 The Future of Interfaces in AI and Data Workflows

25:32 Conclusion and Future Outlook

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00:00:00 Salesforce Acquisition and the Data Consolidation Arc

00:04:21 Slack’s Role as the Hub for Human-AI Enterprise Communication

00:08:44 The System of Record vs. System of Intelligence

00:11:46 The Business Context Layer and Its Role in Enterprise AI

00:15:00 Context Layer vs. Reinforcement Learning and Infrastructure Adoption

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01:00 Gamma’s Success, Product Design, and Market Positioning

06:08 Inception Labs and the Future Direction of Diffusion Models

09:12 Architecture Debate: Diffusion vs. Transformers and GPU Consolidation

17:16 Forward Deployed Engineering: Palantir’s Model and Its Practical Limits

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01:18 The Rise of Ontology in Data Management

07:55 Deepnote and the Evolution of Data Notebooks

10:38 Cursor’s New AI Model and Market Dynamics

14:01 The Future of Code Generation and Automation

17:00 AI Supervisors and the Future of Monitoring

22:01 Data Network Effects in Agentic Businesses

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00:00:00 Further Data Stack Consolidation and Omni/Explo Acquisition

00:07:01 End of Modern Data Stack Hypergrowth and AI Layer Formation

00:14:43 OpenAI Browser and Platform Shift Implications

00:20:38 Distributional Leverage and Hyperscaler Threat

00:27:21 Ontology Layer as the Future Platform for Data Teams

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