Tag:AI Agents
Articles tagged "AI Agents", page 2.
- 21 MIN READ•Aug 4, 2026
Wiring Analytical Queries to Transactional APIs in Closed-Loop Decision Agents
Wiring analytical queries to transactional APIs in closed-loop decision agents: conditional writes, sagas with compensations, decision records, and blast.
AI AgentsDecision LoopsSaga Pattern - 21 MIN READ•Aug 4, 2026
Why Agentic AI Needs a Governed Semantic Layer Behind the Model Context Protocol
Why agentic AI needs a governed semantic layer behind the Model Context Protocol: metric consistency, access control, Apache Ossie for portable.
AI AgentsMCPSemantic Layer - 21 MIN READ•Aug 4, 2026
Moving From Supply Chain Dashboards to Decision Loops With the Model Context Protocol
Moving from supply chain dashboards to decision loops with MCP: sense, decide, act, and verify, with typed action tools, idempotency keys, and graduated.
AI AgentsMCPSupply Chain - 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