What we learned from leaders building agentic AI at scale

In discussions with CTOs, AI engineering leads, and product leaders from various industries, it emerges that while the development of agentic AI is progressing, the key challenges lie not in the models themselves but in user experience (UX). As companies transition from Gen-1 to Gen-2 AI, which involves more complex interactions like assistants and agents, the importance of seamless UX becomes apparent. Issues such as latency, communication standards, and continuity across sessions are critical, as users expect progress visibility and the ability to interrupt or steer AI tasks. Despite advancements in models and frameworks, the lack of standardization in agent-to-client communication means many teams must develop bespoke solutions, which complicates scalability. Failures, particularly partial ones, are common, prompting teams to focus on retries and durable workflows. Additionally, cost optimization and presence awareness are becoming priorities to manage AI workloads efficiently. Ultimately, the future success of agentic AI will depend on delivering reliable and user-friendly experiences, rather than merely having the most advanced models.