Tag:AI Agents

Articles tagged "AI Agents", page 3.

• 21 MIN READ•Aug 4, 2026

  Metric Contracts as the Interface AI Agents Actually Need

  Metric contracts as the interface AI agents need: calculation, inclusion rules, grain, temporal semantics, ownership, semantic versioning, and testing.

  AI AgentsMetric ContractsSemantic Layer
• 21 MIN READ•Aug 4, 2026

  Defending the Lakehouse Gateway Against Prompt Injection and Data Exfiltration

  Defending the lakehouse gateway against prompt injection and data exfiltration: per-user identity, no-SQL tool surfaces, volume bounds, and detection.

  AI AgentsPrompt InjectionSecurity
• 31 MIN READ•Jul 28, 2026

  Guardrails for Analytics Agents That Do More Than Answer Questions

  The risk isn't agents going rogue, it's agents acting correctly on bad input at machine speed.

  AI AgentsGuardrailsData Governance
• 31 MIN READ•Jul 28, 2026

  Building Agent Telemetry Tables in Iceberg That Survive an Audit

  A practical guide to building agent decision traces in Apache Iceberg that support audit reconstruction, governance review, and cost attribution.

  Apache IcebergAI AgentsData Governance
• 31 MIN READ•Jul 28, 2026

  What Agentic Analytics Actually Costs, and How to Keep It Bounded

  Agent analytics generates two cost streams that scale on different variables. Here's the arithmetic, the levers that actually move the number, and how.

  AI AgentsAnalyticsCost Optimization
• 31 MIN READ•Jul 28, 2026

  When the Query Optimizer Starts Managing Its Own Materializations

  Autonomous materialized view management replaces quarterly review meetings with workload-driven scoring, and it's essential when AI agents generate.

  Apache IcebergQuery OptimizationAI Agents
• 31 MIN READ•Jul 28, 2026

  Why AI Agents Fail on Raw Data, and What to Give Them Instead

  Agents fail on raw lake data because business rules live in people's heads. Data products with semantic contracts fix this at the source.

  AI AgentsApache IcebergSemantic Layer
• 31 MIN READ•Jul 28, 2026

  The Five Layers Between Your Lakehouse and a Trustworthy Agent

  Agent reliability is a property of the stack the model sits on. Five layers with distinct owners and failure modes turn the agent is unreliable.

  AI AgentsApache IcebergData Architecture
• 31 MIN READ•Jul 28, 2026

  Surviving Commit Conflicts When Dozens of Writers Hit the Same Iceberg Table

  Commit conflicts multiply with writer count, and AI agents introduce unpredictable write patterns.

  Apache IcebergConcurrencyData Engineering
• 31 MIN READ•Jul 28, 2026

  Wiring an AI Agent to Apache Polaris with the Model Context Protocol

  The catalog is the right attachment point for AI agents working against a lakehouse. Here's how to wire the official Polaris MCP Server and add the read.

  Apache IcebergMCPAI Agents
• 31 MIN READ•Jul 25, 2026

  Governing What Agents Cost You

  Agents break the four assumptions analytics platforms were built on. A practical guide to identity, budgets, semantic layers, caching, and instrumentation.

  AI agentscost governancedata platform
• 20 MIN READ•Jul 13, 2026

  Active Analytics Loops for AI Action Agents

  An in-depth exploration of active analytics loops for ai action agents

  AI AgentsAnalyticsData Engineering