We scan new podcasts and send you the top 5 insights daily.
As AI agents increasingly interact with software to perform tasks, a new field of "Agent Experience" (AX) is emerging. The same principles of identifying and resolving friction in human user journeys (UX) will need to be applied to optimize the performance and efficiency of these automated agents.
Counterintuitively, the path to full automation isn't just analyzing conversation transcripts. Cresta's CEO found that you must first observe and instrument what human agents are doing on their desktops—navigating legacy systems and UIs—to truly understand and automate the complete workflow.
The next evolution of CX is autonomous systems that correct user friction in real-time. This involves capturing live user context, feeding it via API to an LLM to understand intent, and immediately providing a guided, personalized path to success within the application.
The evolution of digital experience management is moving beyond simply identifying user friction. The new frontier is about having the tools to resolve issues in real-time, directly within the product, shortening the gap between insight and action for product and CX teams.
Companies must now design their products, from documentation to onboarding, for a new primary user: the AI agent. This "Agent Experience" (AX) is critical because agents are how a new, massive user base will interact with and build upon platforms, making it a product's North Star.
AI agents are becoming the dominant source of internet traffic, shifting the paradigm from human-centric UI to agent-friendly APIs. Developers optimizing for human users may be designing for a shrinking minority, as automated systems increasingly consume web services.
For tools designed for AI interaction, the ease with which an agent can use the product (AX) is as critical as the user experience (UX) for humans. This can be improved by directly asking the agent for feedback on how to make the product more ergonomic for it.
The number of AI agents will soon vastly exceed human employees. This requires a fundamental shift in software development, prioritizing API-first design, reliability, and machine-to-machine interaction over traditional human-centric user interfaces.
As AI agents increasingly browse the web, they encounter UIs designed for humans that block their progress. This creates an invisible problem for businesses, as this server-side traffic often goes unseen. New companies are emerging to provide analytics for this agentic web traffic.
Artemis automates the analysis of product usage data by deploying AI agents instead of relying on manual session reviews. These agents identify points of customer friction and can even suggest new features to streamline workflows, turning a time-consuming process into a scalable, automated one.
As customer interactions become increasingly conversational via chatbots and AI agents, traditional CX analytics focused on clicks are incomplete. The next frontier is analyzing the content and quality of these conversations to get a full picture of the customer experience, moving towards a single source of truth.