A comprehensive toolkit for product designers, engineers, and researchers building AI-powered experiences that are thoughtful, explainable, and genuinely useful.
What's inside
The Toolkit brings together the methods, components, and evaluation frameworks that are otherwise scattered across whitepapers, conference talks, and internal wikis.
A library of battle-tested patterns for integrating AI into product experiences — prompts, flows, and interaction models that actually work.
Evaluate and improve AI outputs using frameworks grounded in cognitive science and UX research, not just technical metrics.
Drag-and-drop components and starter templates that let teams test AI-assisted interfaces in hours, not weeks.
Capture, replay, and explain AI-driven decisions with built-in provenance tracking — designed for teams that need accountability.
Let cross-functional teams mark up AI outputs together, turning model responses into shared institutional knowledge.
Catch bias, dark patterns, and misleading AI affordances before they ship, using automated heuristics and peer review tools.
Who it's for
Whether you're shipping your first AI feature or standardizing practices across an org, the Toolkit adapts to where you are.
Move from prototype to production with guardrails that prevent common failure modes and align AI behavior with user expectations.
Extend your existing design language with tokens, patterns, and documentation purpose-built for dynamic, model-generated content.
Replace ad-hoc model evals with structured rubrics, annotation workflows, and reporting dashboards that non-engineers can own.
Establish a shared vocabulary and toolkit that lets every team build AI products coherently — without reinventing the wheel.
Free to use. No account required to browse the pattern library. Jump in and explore at your own pace.