Posts - Page 17
All the articles I've posted, page 17.
- 15 MIN READ•Jul 6, 2026
Trustworthy Concurrency in the Agentic Lakehouse: Reconciling Academic Proofs with High-Frequency Production Writes
Agentic lakehouses change the concurrency conversation. Traditional data pipelines already deal with overlapping jobs, retries, compaction, merges...
concurrencyagentic lakehouseproduction writes - 30 MIN READ•Jul 6, 2026
When Gatekeepers Panic: The Encyclopédie, Open AI Models, and the Politics of Accessible Knowledge
The fight over open AI models mirrors the 18th-century suppression of Diderot's Encyclopédie, revealing the same pattern of institutional fear.
open source AIAI regulationopen weights - 30 MIN READ•Jul 6, 2026
The Who, What, and Why of Semantic Layers: The Layer That Decides Whether Your Numbers Can Be Trusted
There is a survey statistic making the rounds this year that I cannot stop quoting: 84 percent of data teams report regularly encountering conflict...
semantic layersanalyticsdata governance - 14 MIN READ•Jun 22, 2026
AI-Ready Metadata Prevents Query Failures
AI-ready metadata reduces query failures by making ownership, freshness, lineage, quality, and policy visible at execution time.
lineage quality LLM query failuresmetadata for AI agentsgoverned analytics - 14 MIN READ•Jun 22, 2026
Autonomous Materialization for Agentic Analytics
Autonomous materialization is useful when it is tied to workload evidence, governance checks, and lifecycle management.
AI agents table performancereflectionsautomated acceleration - 15 MIN READ•Jun 22, 2026
Composable Semantic Layers for Analytical Agents
AI agents need more than metric names. They need composable business logic that survives multi-step analysis.
semantic layer agentsmetrics catalogsagentic analytics - 15 MIN READ•Jun 22, 2026
Built for Agents and Managed by Agents
Dremio Agentic Lakehouse is easiest to understand as two ideas: data built for agent access and platform work managed by agents.
built for agentsmanaged by agentsautonomous lakehouse - 14 MIN READ•Jun 22, 2026
ClickHouse in the Loop for Active Agents
Low-latency analytical systems can help active agents, but only when event loops include validation, context, and safety boundaries.
real-time event streamsactive analytics agentslow latency BI - 14 MIN READ•Jun 22, 2026
The Context Layer for AI Agents
A semantic layer is necessary, but agents also need lineage, quality, freshness, compliance, and ownership context.
AI metadatalineagedata quality - 14 MIN READ•Jun 22, 2026
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.
agentic analyticslakehouse operating layergoverned AI data - 14 MIN READ•Jun 22, 2026
Event-Driven Table Compaction with Agents
Event-driven compaction is valuable when agents coordinate maintenance with workload signals, table health, and commit safety.
agentic compactionIceberg maintenancetable optimization - 15 MIN READ•Jun 22, 2026
Fabric Agentic Analytics and Lakehouse Schema Design
Microsoft Fabric agentic analytics is a reminder that schemas, semantic models, and governed lakehouse design now shape AI behavior.
Microsoft Fabric agentic analyticslakehouse schema designAI analytics stack