Handoffs vs Subagents: OpenAI Agents SDK vs Google ADK vs LangGraph
📰 Dev.to AI
Learn to differentiate between handoffs and subagents in multi-agent architectures for AI workflows, and understand the implications for context visibility, testing, and retries
Action Steps
- Identify the requirements of your AI workflow and determine whether handoffs or subagents are more suitable
- Design your workflow to transfer ownership of the conversation to a specialist using handoffs or call a specialist and get a result back using subagents
- Implement a fixed pipeline where the application controls the next step, considering context visibility and testing
- Test and retry your workflow, taking into account approval boundaries and error handling
- Evaluate the trade-offs between handoffs and subagents in terms of complexity, scalability, and maintainability
Who Needs to Know This
Developers and engineers working with AI agents and workflows will benefit from understanding the differences between handoffs and subagents, as it affects the design and implementation of their applications
Key Insight
💡 Handoffs and subagents are not interchangeable terms in multi-agent architectures, and the choice between them affects the complexity, scalability, and maintainability of AI workflows
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💡 Handoffs vs Subagents: Understand the differences in multi-agent architectures for AI workflows #AI #MultiAgent #Workflow
Key Takeaways
Learn to differentiate between handoffs and subagents in multi-agent architectures for AI workflows, and understand the implications for context visibility, testing, and retries
Full Article
“Multi-agent” is often used as if it describes one architecture. It does not. For a coding workflow, there is a big difference between transferring ownership of the conversation to a specialist, calling a specialist and getting a result back, and running a fixed pipeline where the application controls the next step. Those choices affect context visibility, testing, retries, approval boundaries, and how easy it is to explain a bad run. This is a documentation-based compari
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