How to get multiple agents to play nice at scale

2026-04-22 · Source: Stack Overflow Blog · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Software Development & Engineering · Depth: Advanced, quick

Summary

On April 22, 2026, Intuit's Chase Roossin and Steven Kulesza discussed the engineering challenge of coordinating multiple AI agents within complex systems. They explored methods for enhancing agent predictability through automated evaluations and compared the efficacy of agent swarms against single, highly skilled agents. The discussion also highlighted how direct customer behavior significantly influences and shapes the technical architecture of multi-agent systems. This podcast episode delves into practical considerations for scaling AI agent collaboration.

Key takeaway

For AI Architects designing complex systems, consider how automated evaluations can stabilize multi-agent interactions and whether a swarm approach or a single highly capable agent best fits your system's needs. Your architectural decisions should directly reflect anticipated customer behavior to ensure robust and predictable system performance.

Key insights

Coordinating multiple AI agents in complex systems is a significant engineering challenge.

Principles

• Automated evals improve agent predictability
• Customer behavior shapes technical architecture

In practice

• Evaluate agent swarms vs. single agents
• Use automated evaluations for behavior

Topics

• Multi-agent Systems
• AI Agent Coordination
• Automated Evaluations
• Agent Swarms
• Technical Architecture

Best for: AI Engineer, Machine Learning Engineer, AI Architect

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• AI Agents of the Week: Papers You Should Know About — Advanced AI agents demonstrate improved continual learning, planning, multi-agent collaboration, and safety mechanisms.
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• AI Agents of the Week: Papers You Should Know About — AI agents are evolving towards modular, self-improving systems capable of complex planning and robust multi-agent collaboration.
• Are Multi-Agent Systems More Complex Than They Need to Be? — Multi-agent systems generalize classical ML ensembles, requiring systematic evaluation and optimization to ensure reliability and manage complexity.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Stack Overflow Blog.