Beyond the Semantic Layer: Building a Context Layer for the Agentic Era (opens in new tab)

Writing SQL was never the hard part. Making it accurate and trustworthy against your warehouse always was. Point an AI agent like Claude or Codex at your data stack and ask a real analytics question, and the answer is usually mediocre: the agent can scrape some context from your git repos or whatever metadata it can find, but it doesn’t know your joins, your metric definitions, or the business rules that give a number its actual meaning. So how do we make data agents reliable and accurate for...