📰 Dev.to · Max Mealing

A semantic layer defines business metrics once so every consumer gets the same answer, including AI agents. Here's what a semantic layer for AI agents is, how i

Self-service BI for customers promised to free the data team. Instead it created metric chaos. Here's the category, the tradeoffs, and where charts in an AI age

Not every metric needs real-time data. Here's how to decide what needs sub-second freshness, what can be cached, and how pre-aggregation handles both.

KPI dashboards show stale numbers that nobody trusts. Governed metrics served through a semantic layer give every consumer the same live data, from dashboards t

A guide to customer-facing analytics 2026 for B2B SaaS: the options, the tradeoffs, and the MCP-native way to put interactive charts inside an AI agent.

Connect an AI agent to your data warehouse: expose governed metrics over MCP, let agents query instead of writing raw SQL, and chart the result in Claude or Cha

Comparing the best embedded analytics tools 2026 for B2B SaaS: Metabase, Holistics, Explo, Luzmo, Reveal, GoodData, Looker, Power BI, Tableau, and the MCP-nativ

An analytics API exposes your metrics programmatically. Here's how to build one that serves dashboards, AI agents, and customer integrations from the same defin

A guide to AI reporting for SaaS: the tool landscape, the trust problem, and the MCP-native way to render charts from your query results inside an agent.

A guide to AI data analysis for SaaS: the tool categories, the accuracy problem, and the MCP-native way to render charts from your query results inside an agent

Why AI agents need a semantic layer: querying raw SQL produces inconsistent, ungoverned results. Here's what goes wrong without one, and how governed metrics pl

Before adopting Cube.dev or building a custom framework, use your warehouse's native metadata...