Business People And Robot Putting Their Hands Together. Team Community, Unity, Artificial Intelligence And Cooperation Concept With Stack Of Hands

Designing systems for AI agents: What makes a good AX?

Designing systems for AI agents—your new digital colleagues—requires more than APIs and data. It demands a new kind of user experience thinking: Agent-Based Experience (AX). In this article, we explore the pillars of AX, from structured data and explainability to agent onboarding and recovery loops, helping teams future-proof their products and create seamless human–agent collaboration.

Vector illustration of a Artificial intelligence business concept in retro collage style with business man in suit for agentic ai article

What is agentic AI? How to understand the rise of autonomous intelligence

Agentic AI refers to intelligent systems that operate independently, make decisions, and adapt in real time without constant human oversight. Unlike traditional AI that reacts to prompts, agentic AI sets its own goals and carries them out—making it a transformative force for industries like cybersecurity, software development, and operations.

science medical technology concept background for article on health tech product scalability

Health tech product scalability: Strategies for growing your MVP into a scalable solution

Learn how thoughtful UX design and strategic planning can transform your MVP into a fully scalable health tech solution Health tech product scalability improves patient care, streamlines workflows, and offers innovative solutions to long-standing challenges. However, the path from a Minimum Viable Product (MVP) to a fully scaled solution is complex. Health tech products operate…

Robotic hand on a crosswalk. Vector illustration.

Retrieval Augmented Generation (RAG): What it is and how B2B companies can use it

While many companies have dabbled in generative AI to create content or assist customers, there’s a growing challenge: accuracy. What if the AI provides convincing but incorrect information? Enter Retrieval Augmented Generation (RAG) — an approach that ensures your AI not only generates useful content but also backs it up with real, verified information.