My take: Whereas AI agent tools focus on build, test, and deploy, platforms supporting agentic AI should make it possible to connect to an ecosystem of data platforms, AI agents, governance capabilities, and tools to support operations.
3. Developer experience
Once organizations have a broad understanding of AI agent development tools and agentic AI capabilities, then dive deeper into their features, form factors, and experiences. I always begin with end-user experiences because if tools are too difficult to learn or use, it slows down progress and leads to workarounds.
“When evaluating agent-building platforms, look for those that combine intuitive development experiences, deep enterprise integration, and built-in governance,” says Dhiraj Pathak, managing director of data and AI at Brillio. “The ability to orchestrate across systems, ensure explainability and compliance, and continuously learn from feedback is what will separate scalable transformation from short-lived pilots.”
