From prompt chaos to clarity: How to build a robust AI orchestration layer

Editor’s note: Emilia will lead an editorial roundtable on this topic at VB Transform next week. Register today.

AI agents seem like an inevitability these days. Most enterprises already use an AI application and may have deployed at least a single-agent system, with plans to pilot workflows with multiple agents. 

Managing all that sprawl, especially when attempting to build interoperability in the long run, can become overwhelming. Reaching that agentic future means creating a workable orchestration framework that directs the different agents. 

The demand for AI applications and orchestration has given rise to an emerging battleground, with companies focused on providing frameworks and tools gaining customers. Now, enterprises can choose between orchestration framework providers like LangChain, LlamaIndex, Crew AI, Microsoft’s AutoGen and OpenAI’s Swarm. 

Enterprises also need to consider the type of orchestration framework they want to implement. They can choose between ...