About this episode

This episode explores the challenges and frameworks necessary for multi-agent orchestration in deploying AI at scale within organizations.

Real-world deployments of agentic AI have so far been limited in scope, despite strong interest in using the technology to automate many of the business processes now handled by people. One reason for the slow deployment of agents is the challenge of multi-agent orchestration: the ability of AI agents to communicate with each other and coordinate their activities across enterprise applications, workflows and even corporate firewalls. There is growing recognition that developing a framework for multi-agent orchestration is essential for deploying agents on a large scale across the entire organization. In this episode, we explore the main elements of a multi-agent framework, the problems it is meant to address, who is responsible for developing it and where to find ready-made frameworks and tools. Featuring: Peter Hesse, Partner, 10Pearls In today's episode, we'll also cover: Why the tendency of agents to work in harmony can make them less resilient when their scale expands. How a framework can support AI transparency and traceability. Using "policy as code" to enforce AI consistency and trust. References: AI agent frameworks: A guide to evaluating agentic platforms Real-world…

People in this episode

Guest: Peter Hesse

Topics covered

• multi-agent orchestration
• AI agents
• enterprise applications
• automation
• AI transparency
• policy as code

Keywords

• agentic AI
• business processes
• communication
• coordination
• framework development
• AI consistency
• trust

Mentioned in this episode

Organizations: 10Pearls

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