This article outlines eight core user intents that AI systems should address, such as learning, creating, and monitoring. Each intent comes with specific objectives, workflows, and design considerations to enhance user experience and effectiveness. It emphasizes the need for structured responses, clarity, and user control in AI interactions.

The article explores how leading companies like Meta and Atlassian are integrating AI into their design processes. It highlights their investment in training employees to use AI tools effectively, showcasing various strategies they've adopted to enhance efficiency in UX design, interactions, and marketing.

This article explores common pitfalls in the design process where marketers overload designers, leading to missed deadlines and frustration. It offers insights from over 100 hours of research on how successful companies streamline collaboration and improve workflows between teams.

The article discusses Penpot's MCP servers, which enable AI to interact with design files for tasks like exporting used icons or converting designs to code. These servers act as a secure bridge between AI and Penpot's open-source platform, facilitating various design-related workflows without compromising data privacy.

Honter is a workspace tool for design projects that simplifies client collaboration. Clients can join without accounts, allowing for immediate feedback and organized communication. The platform offers two pricing tiers, including a free version with basic features and a paid option for unlimited access.

This article explains how model collapse affects AI design tools, leading to degraded performance over time. It highlights the feedback loop of training AI on synthetic data, which results in poorer outputs, and provides practical strategies for detecting and mitigating these issues.

Designers are advocating for a shift from traditional linear workflows to adaptive, loop-based systems in AI design, emphasizing the importance of continuous feedback and human involvement. By leveraging cybernetic principles, these systems can better accommodate real-world complexities, enhance decision-making, and foster trust in AI applications. The article outlines key strategies for implementing this loop-oriented design philosophy in business contexts.