CDX-201c · Module 1

When Multi-Agent Adds Value

4 min read

Multi-agent workflows are powerful — and frequently premature. A single Codex session handles the vast majority of development tasks effectively. Multi-agent adds value in exactly two scenarios: when you have genuinely independent work streams that benefit from parallelism, and when you need specialized agents with different capabilities (models, tools, context) for different phases of a task.

The cost of multi-agent is coordination overhead. Every agent needs context about what the other agents are doing. Hand-offs between agents lose information. Parallel agents can produce conflicting outputs that require manual reconciliation. If your task does not clearly fit the independence or specialization criteria, a single well-prompted session will outperform a multi-agent setup every time.

The independence test is simple: can Agent A complete its work without knowing anything about Agent B's output? If yes, parallelize. If no, sequence. The specialization test is equally simple: does this phase of the task require a fundamentally different capability (different model, different tools, different context window) than the previous phase? If yes, hand off. If no, keep it in one session.

Do This

  • Use multi-agent when tasks are genuinely independent and non-overlapping
  • Use multi-agent when different phases need different model capabilities
  • Start with 2-3 agents maximum and scale up only after validating the pattern
  • Default to single-session for tasks under 15 minutes of agent time

Avoid This

  • Use multi-agent for every task because it sounds more sophisticated
  • Split sequential work into multiple agents — you are adding latency, not parallelism
  • Launch 10 agents without clear task decomposition — quality drops with vague scope
  • Assume multi-agent is always faster — coordination overhead can negate parallelism gains