How to build scalable agentic AI
Here are the key takeaways from “How to build scalable agentic AI applications for enterprises” (CIO) by Hari Subramanian: What is “agentic AI” & why it matters Agentic AI refers to systems of autonomous agents (or multi-agent systems) that can carry out multi-step, complex workflows rather than just one-off responses. This shift is significant: instead of humans orchestrating AI calls or pipelines manually, these agents can coordinate themselves, interact with tools or data sources, and adapt. For enterprises, agentic AI offers the potential to scale automation in business processes, improving efficiency, reducing human overhead, and enabling new capabilities. Core components in agentic AI systems The article breaks down typical agentic workflows into four core components that must be integrated: Prompts These define goals or tasks for agents. Challenges: versioning, testing, portability across models. MCP servers / protocols “MCP” here refers to the prot...