// HACKER NEWS — CYBERSECURITY
Charts built for Chat
We’re open sourcing dbt Charts, a declarative language for dashboards, so that even the dashboards you build by chatting with an agent can be governed.
AI 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.
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.
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.
Today we’re taking the next step in unbundling BI: we’re open sourcing
dbt Charts, which takes charts out of
the BI tool and puts them in code, specifically a new structured YAML language
that can declare a full interactive dashboard in one auditable YAML file. Chat
freely with an agent, and what it makes has the freedom of code while staying
easy to read.