Topic
Agentic AI
Follow the path from a governed data source to a trustworthy agent answer: interfaces, semantic context, evaluation, and operational controls.
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Agentic Data Architecture
A six-layer reference architecture for agents on company data: planners, tool boundaries, identity, the semantic layer, and what breaks when a layer is missing.
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Guardrails for AI on Company Data
The control surfaces that actually contain damage once an agent is fooled: identity, permissions, audit trails, and prompt injection at the query layer.
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The Plan and the Worker: Two Open Specifications for Agent Harnesses
Two open specifications, the Agentic Graph Specification and the Open Agent Profile, turn agent plans and agent identity into portable, reviewable files.
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The Chase-Catch Gap in Enterprise AI Agents
An in-depth exploration of the chase-catch gap in enterprise ai agents
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The State of Agentic AI Standards in 2026: MCP, A2A, WebMCP, OSI, and the Protocol Stack Taking Shape
The agentic AI protocol stack is solidifying in 2026, MCP for tools, A2A for agents, WebMCP for the web, OSI for semantics, payments, identity.
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Lakehouse as the Operating Layer for Agentic AI
Agentic AI announcements are useful when they validate the need for governed data, semantic context, and cost-aware execution.
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The Ultimate Guide to Open Table Formats - Iceberg, Delta Lake, Hudi, Paimon, and DuckLake
Understanding Iceberg, Delta Lake, Hudi, Paimon, and DuckLake
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The 2025 & 2026 Ultimate Guide to the Data Lakehouse and the Data Lakehouse Ecosystem
What is the Data Lakehouse and the Data Lakehouse Ecosystem? This comprehensive guide covers everything you need to know about the Data Lakehouse architecture, open table formats like Apache Iceberg, Delta Lake, Apache Hudi, and Apache Paimon, and the modern data ecosystem that supports them.
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Unlocking the Power of Agentic AI with Apache Iceberg and Dremio
Unlocking the Power of Agentic AI with Apache Iceberg and Dremio