Show HN: DAC – open-source dashboard as code tool for agents and humans
Positions itself as a solution for automating dashboard creation for AI agents, addressing the limitations of UI-driven BI tools and the complexity of agents building dashboards from scratch. It emphasizes version control, reviewability, dynamic capabilities, static analysis, and standardized deployment.
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- every dashboard turns out to be different
- have to implement a backend to centralize the query execution
- there is no centralized mechanism to control the rules and standards around visualizations
- there is no way to get a semantic layer working with the dashboards easilyIn the end, agents ended up reinventing the wheel for every new dashboard, even under the same project. Building a standardized, local project for these turned out to be building a BI tool from scratch.After trying these out, I asked myself: what if the dashboards were built for agents as the primary user?A product like that would need to have a couple of features:
- First of all, everything needs to be driven by version-controllable text. YAML is fine.
- Changes to the dashboards should be easy to review and understand by humans.
- Agents are great at writing code, it'd be great if this were driven by code to have dynamic stuff: JSX would be great.
- Static analysis being a first-class citizen: validate dashboards before deploying. Agents can check their work too.
- A standardized way of deploying these based on a couple of files in a folder: operationally very simple.
- Built-in semantic layer to standardize metrics.That's what I ended up building: dac (Dashboard-As-Code) is an open-source tool and a spec to define dashboards, well, as code. It contains an implementation in Go that can be deployed as a single binary anywhere. The dashboards are defined in YAML and JSX, YAML for static stuff, JSX for dynamic dashboards. You can run queries at load time to define conditional charts, generate tabs on the fly per customer, or list charts for each A/B test you are running.I built it in Go because I do love Go, and I think it is the greatest language at the moment to work with AI agents.dac runs as a single binary, you can get started with a `dac init` command and it'll automatically create some sample dashboards for you based on duckdb. It supports 10+ SQL backends, with more to come. It supports validation, custom themes and whatnot.You can see it here: https://github.com/bruin-data/dacI would love to hear what can be improved here, please let me know your thoughts.
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