How Agents Manage Other Agents: Four Subagents Patterns in 2026

2026-05-05 · Source: philschmid.de - RSS feed · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, long

Summary

This article, published May 5, 2026, details four distinct patterns for managing subagents, building on the concept of isolating tasks for improved reliability. It outlines how advancements in model planning and tool use enable more sophisticated agent management. The patterns are ordered by the main agent's control over the subagent lifecycle: Inline Tool (subagent as a function call), Fan-Out (spawning agents and waiting for results), Agent Pool (persistent agents with messaging), and Teams (agents communicating directly). Each pattern is described with its tool surface, example code, use cases, and limitations, emphasizing how model capabilities and infrastructure requirements increase with complexity. The article concludes with guidance on choosing the appropriate pattern based on task complexity and model sophistication.

Key takeaway

For AI Engineers designing agent systems, understanding these four subagent patterns is crucial for selecting the right architecture. Start with the Inline Tool pattern for most tasks, escalating to Fan-Out, Agent Pool, or Teams only when task complexity or required coordination genuinely demands it. This approach ensures efficient resource use and avoids over-engineering, especially when working with models of varying capabilities.

Key insights

Four subagent patterns offer increasing control and complexity for managing AI tasks, from simple function calls to autonomous team coordination.

Principles

• Isolate tasks into focused agents for reliability.
• Model capability dictates viable subagent patterns.
• Start with simpler patterns and escalate as needed.

Method

Progress from Inline Tool for self-contained tasks, to Fan-Out for parallel work, Agent Pool for multi-step collaboration, and Teams for complex, self-coordinating tasks.

In practice

• Use `call_agent` for basic, self-contained subagent tasks.
• Employ `spawn_agent` and `wait_agent` for concurrent, independent tasks.
• Utilize `send_message` for multi-turn agent collaboration.

Topics

• Subagent Patterns
• Agent Orchestration
• Inline Tool Pattern
• Fan-Out Pattern
• Agent Pool Pattern

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

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Editorial summary, takeaway, and curation by AIssential. Original article published by philschmid.de - RSS feed.