From Semantic Layer to Context Layer: Why Defining Tables Is No Longer Enough for AI Agents
The debate around semantic layer vs context layer matters because AI agents expose exactly where reporting logic stops and meaning resolution begins.
The debate around semantic layer vs context layer matters because AI agents expose exactly where reporting logic stops and meaning resolution begins.
Your dashboards may be working perfectly. Your decisions still aren’t.
Your warehouse stores data. Your semantic layer defines metrics. But neither tells an AI agent what your business actually means.
BigQuery AI Agents: Why Direct Warehouse Access Fails in Production Giving AI agents direct access to BigQuery can look impressive in a demo, but in
Most companies still think the main problem with AI is model quality. It isn’t. For the last year, the AI market has been obsessed with
Everyone is building natural-language interfaces on top of databases. Most of them are solving the wrong problem. They aren’t building AI analysts; they’re building glorified
Introduction: the end of an era The king is dead. And most companies have not even noticed. For decades, Business Intelligence (BI) was the crown
Introduction: the reporting paradox How many times have you seen a dazzling dashboard, colorful charts, neat KPIs, interactive widgets, shared in a meeting with excitement…
Introduction: Meet the data monster eating your week Imagine your marketing funnel as a bucket full of holes. Every time you try to pour in
Introduction: the 3 data problems your online store doesn’t want to admit Remember that last product launch that got stuck in QA? Or the big