Orchestrating AI Agents at Enterprise Scale: Insights from Intuit's Engineering Leaders
By
Introduction
Building systems where multiple AI agents work together seamlessly at scale is one of the hardest challenges in modern engineering. According to Chase Roossin, group engineering manager, and Steven Kulesza, staff software engineer at Intuit, the problem is not just about individual agent performance but about how to coordinate these agents within a complex ecosystem. In a recent conversation, they shared their experiences and strategies for making multi-agent systems cooperate effectively. This article explores the key insights from their discussion, offering a roadmap for any organization tackling similar issues.

Tags:
Related Articles
- From QDOS to Open Source: The Story Behind Microsoft's Earliest DOS Code Release
- Java 25 Introduces Standardized Key Derivation API: A Game-Changer for Cryptographic Security
- Go 1.26 Ships with Major Language Tweaks and Green Tea GC Now Default
- Mastering Python Development: Cursor vs Windsurf – A Comprehensive Guide
- 7 Proven Strategies to Overcome Cloud SMTP Restrictions with Brevo's HTTP API
- Modernizing Go Code with Source-Level Inlining
- 10 Critical Insights into JavaScript's Date-Time Maelstrom — and How Temporal Will Fix It
- Building Declarative Charts and Understanding Iterators vs Iterables in Python