dbt Blog

The Open Semantic Interchange (OSI) project has been accepted into the Apache Incubator and renamed to Apache Ossie (Incubating). The specification, community, and mission remain unchanged; all references to OSI are historical and will be removed over time.

We've seen this pattern often enough to name it. A team migrates to dbt, spends six months, and ends up with a dbt project that looks exactly like their old workflow, just with Jinja templating instead of drag-and-drop. The data model still has the same problems. It's only…

What's missing from every agentic data pipeline diagram

What is context engineering?

The AI readiness gap is bigger than it looks

AI agents do not fail because of a weak model. Rather, they fail because of using infrastructure that was never meant for autonomous decision-making.

When it comes to getting their data AI-ready, many organizations start with cleaning and structuring their data and then simply stop. This is an important first step, but it's not the last step, because AI-ready data relies heavily on context: the layer of meaning that explains…

It's been a big few months of shipping at dbt. We've got a lot to cover — from the dbt Developer Agent going into preview, to making the upgrade to the dbt Fusion engine self-serve, to new ways to lock down your account security, to quality-of-life improvements for practitioners…

Coding agents are doing a tremendous amount of useful work today. Since Claude Code dropped last year, followed by Opus 4.5 and GPT 5.2, software engineering has very clearly passed a phase change. We've gone from copilot-style autocomplete to agents that can run end-to-end…

dbt Developer Agent is now available in Preview—grounded in your dbt project so you ship faster without breaking downstream.

Meet Antigravity: Google's agentic IDE enters the dbt orbit

Learn how to operationalize your analytics agents by building context for LLM models with dbt and MCP servers.

Learn how to connect dbt, when to migrate, and what the tradeoffs are for your data team.

The root cause of AI hallucinations in data contexts

Anders Swanson explains what data teams can realistically expect when attempting to run on top of Iceberg in production.

Metadata management improves discovery, governance, performance, and trust in modern data systems.

ETL consolidates fragmented data, enforces quality, and satisfies compliance requirements modern organizations depend on.