Agents as Tools: Control Today, Migration Pain Tomorrow

The 'agents as tools' pattern is the most straightforward multi-agent architecture. Instead of a single agent with many tools, you hand specialist agents to an orchestrator as callable tools. Each specialist runs isolated, processes only its input, and returns a filtered result, preventing noise from polluting the orchestrator's context.

The video demonstrates two OpenAI Agents SDK implementations: passing an agent directly as a tool or wrapping it with @tool to reset context every call. By default, specialists lack memory and never see the orchestrator’s history, keeping the orchestrator the sole decision-maker for easy governance.

The trade-offs are immediate. The orchestrator is a bottleneck—all data flows through it, specialists can't collaborate directly, and execution order isn't guaranteed because orchestration is model-driven. This means you can't count on a specific specialist being called before another, nor can you fan out to multiple agents in parallel.

For simple, separable tasks, it's a pragmatic starting point that avoids premature complexity. But for any workflow requiring deterministic sequencing, parallel execution, or agents that build on each other's work without returning to a coordinator, a graph architecture becomes necessary. The pattern is a controlled gateway to more capable multi-agent systems, not the final destination.