Design for the AI-native analytics era.
AI is rewriting what an analytics product looks like every quarter. This is a living reference for the people building dashboards, semantic layers, and data products through that shift, and it evolves as the field evolves.
Four sections, evolving with the field.
Visual Design
Color, type, layout, charts, components. The visual grammar of a dashboard that respects the reader.
User Experience
How modern analytics products feel in the hand: navigation, drilldown, period filters, AI as a second hand on the same data, the moment of comprehension.
Designing for AI
Setting up the data environment a business-facing AI chatbot needs to answer questions, investigate, and build charts and dashboards. The work is transcribing table relationships, metric definitions, business logic, and the rules nobody wrote down into shapes AI can actually read.
Spicy Repos
Plug-and-play artifacts for Omni, dbt, and Hex, published as open-source GitHub repos you can fork into your workspace.
This guide will change as the field changes.
New AI tooling rewrites what is possible every quarter. Treat this as the version we believe today. Feedback, corrections, and counter-examples welcome.