AI Product UX Patterns Collection

An opensource collections of popular UX pattern for AI products

The AI Product UX Patterns Collection is a curated set of UX patterns for builder focused on creating intuitive and effective user experiences in AI-driven applications. It's designed to support builders in navigating the complexities of AI UX design, supporting you on building applications that are both powerful and user-friendly, regardless of the underlying technology or framework.

Getting Context

Set the stage for understanding user needs and intent.

Intermediary Processing

Keep users engaged as the AI analyzes and processes data.

Presenting Results

Focus on how best to present AI-generated insights.

Version Control

Offer users the opportunity to tweak and perfect these outcomes.

The Structure

Main loop of AI interactions

Getting Context

Intermediary Processing

Presenting Results

Version Control

Monetization

Usage control

Supportive building block to scale and grow your products

The main loop of AI interaction

The structure of this patterns collection mirrors the natural progression of AI interactions, distilled into four essential steps: Getting Context, Intermediary Processing, and Presenting Results. This framework reflects the comprehensive journey of user interaction with AI, from initial engagement through to the presentation of personalized outcomes. Each step is pivotal, underlined by the foundational elements of Usage Control and Monetization, ensuring that the products are not only user-centric but also viable and sustainable.

Getting context sets the stage for understanding user needs and intent.
Intermediary Processing keeps users engaged as the AI analyzes and processes data.
Presentating of Results focuses on how best to present AI-generated insights.

Supportive Blocks for scaling and growing AI products

Beyond the primary AI interaction sequence, we identify key Supportive Blocks that are vital in scaling and enhancing AI-powered products:

Version Control: This block empowers users to manage their interaction history with AI, such as conversations, prompts, or generative tasks. It offers the ability to review and revert to previous states of the dialogue or design, allowing users to navigate through their generative flow and select preferred outcomes from past iterations.
Monetization: A critical aspect for transforming AI technology into a viable business model. This block facilitates the integration of monetization strategies, aligning product capabilities with revenue generation.
Usage Control: An important tool for overseeing the deployment of your AI solutions. Usage control ensures proper usage, manages load, and maintains an optimal experience across user interactions.

These Supportive Blocks are the bedrock for product development, ensuring that your AI offerings are not only advanced and user-centric but also commercially sustainable and adaptable to the evolving market needs. This content segment adds a section about Supportive Blocks that help in the development and management of AI products, aimed at builders and developers in the AI space.

References

Our collection's depth and breadth owe much to the incredible AI applications that pave the way for innovation and the wealth of knowledge shared by experts across articles, books, and research. We express our gratitude to these outstanding contributions and acknowledge that our collection is curated by learning from:

The ingenuity displayed in existing AI applications that set benchmarks for what is possible.
The insights and methodologies discussed in key publications that further the discourse on AI and design.

This patterns collection is a labor of love, designed to illuminate the path through the exhilarating yet daunting world of AI product design. With these consolidated patterns and organized insights, we aim to inspire and simplify your design journey. Let's embark on this journey together, creating AI applications that not only meet user needs but also enrich lives. We have learn from a variety of sources to build this collection. These include, but are not limited to:

Getting Context

Contact us to build your next product or to get consulting on your current project.