GoKawiilAI for data is here, and the long-promised self-serve analytics is finally happening. Anyone with a data connection can chat a report into existence in an afternoon, and the first results are impressive.
The frictions show up fast, though. By default an agent turns one simple report into a pile of files: HTML, CSS, and JavaScript, a couple of chart libraries, and a React or Streamlit app once it has to be live. Tracing a result back to its source means following it through several languages and files, which is slow for people to audit and costs the agent time and tokens on every change.
BI tools went the other way and bolted copilots onto their UI-first apps. That keeps the AI on governed rails, but narrow ones: the agent can do only what the UI exposes.
So today you choose between the messy freedom of code and the narrow control of a BI tool. We built a third option: skip ahead, or read on for how BI got here.
Unbundling BI
As dbt Labs founder Tristan Handy wrote recently in BI’s Second Unbundling:
When I started in data, BI tools were full-stack. Everything happened inside one product: data ingestion, transformation, compute, caching, semantics, visualization, identity. The BI tool was the data stack. MicroStrategy, Cognos, etc: they’re not just visualization tools, they’re integrated data platforms. Then the modern data stack happened. From ~2015 to 2022, the infrastructure layers of that BI bundle got pulled out and turned into purpose-built infrastructure. Compute went to the Big 5. Ingestion went to Fivetran. Transformation went to dbt. The BI tool was left with: visualization, interactive analytical interfaces, semantic definitions (sometimes!), identity and access management, and web hosting.
< 2 0 1 2 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 Warehousing Big 5 E L T Extract Load Transform BI everything else
What that unbundling left behind is the BI tool we know today, and charts are its biggest piece. They stayed in the UI for good reason: for most people, clicking is quicker than writing YAML. But more and more charts won’t be made by people. As the front end and user of everything becomes increasingly a chat agent, this preference flips. Agents are fluent in code, SQL, and Git, and clumsy in someone else’s UI. So charts need to move to where agents work: into code.
Charts leave the BI tool
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