The Problem I Was Trying to Solve§

In a multi-agent system, passing the conversation context from one agent to another (e.g. from a Triager agent to a specialized Billing or technical Support agent) is fraught with risk. In naive implementations, developers manually concatenate the chat history, leading to state corruption, lost variables, and exceeded token windows. We wanted to build a secure, deterministic multi-agent handoff loop using the native primitives of the new OpenAI Agents SDK.

Tools and Setup (auto-link injection fires here)§

Our orchestrator stack consisted of:

  • OpenAI Agents SDK for Python.
  • GPT-4o as the core intelligence engine.
  • A state manager mapping user session variables to execution contexts.
# Python snippet demonstrating Agent Handoff
from openai_agents import Agent, Runner

def handoff_to_billing(session_state):
    # Safe transition logic
    return billing_agent

triager_agent = Agent(
    name="Triager",
    instructions="Determine if the user needs billing or technical support.",
    tools=[handoff_to_billing]
)

Step-by-Step: What I Actually Did§

1. Configuring Native Handoffs: Instead of writing complex state management code, we mapped handoffs as return values of tool calls. When the triager agent returns billing_agent as a tool response, the runner automatically switches execution context. 2. Context Compression: We injected a compression middleware that summarizes conversation history upon handoff, ensuring the destination agent receives a clean, token-efficient summary. 3. Testing State Preservation: We validated that variables (like customer IDs or billing reference numbers) remain locked inside the session state across the agent handshake.

Results and Takeaways§

  • No State Leaks: User session variables were preserved perfectly across multi-agent hops.
  • Lower Cognitive Load: Decoupling agents into small, single-purpose roles reduced prompt size and improved reason accuracy.
  • Handoffs Are Primitives: Always treat agent transitions as native framework transitions rather than building custom state wrappers.