Posts - Page 23
All the articles I've posted, page 23.
- 15 MIN READ•Jul 6, 2026
Trustworthy Concurrency in the Agentic Lakehouse: Reconciling Academic Proofs with High-Frequency Production Writes
How Iceberg optimistic concurrency behaves under many agent writers, and the retry discipline, isolation contracts, write leases, and queues that keep it sane.
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
What a semantic layer is, how it rewrites queries, who built the category, today's major tools, and how teams roll one out so AI agents and BI share one metric.
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
How to run autonomous materialization for agent query workloads: tie it to workload evidence, add governance checks, measure results, and avoid failure modes.
AI agents table performancereflectionsautomated acceleration - 15 MIN READ•Jun 22, 2026
Composable Semantic Layers for Analytical Agents
Why a metric catalog is not enough for AI agents, and how composable semantic layers keep business logic intact across multi-step analysis, with a rollout plan.
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
AI agents need more than a semantic layer. Learn how to add lineage, quality, freshness, compliance, and ownership context, with guardrails and a rollout plan.
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