What is the best way to coordinate a multi-agent system where agents have different specialties?

All answers to this question.

For your specific use case—software development—a hierarchical (centralized) approach is usually superior. Using a "Manager" agent allows for better quality control; the manager can send code back to the developer if the security agent finds a critical vulnerability. CrewAI is fantastic for this because it allows you to define "Process" types (Sequential or Hierarchical). AutoGen is more flexible for "conversational" agents that need to brainstorm, but it can get chaotic in a rigid production pipeline where you need a specific output like a clean repository.

   Answered 2025-02-12 by Victoria Manning

Would the manager agent also be responsible for managing the token budget, or is that something we have to hard-code into the framework to avoid overspending?

   Answered 2025-02-13 by Marcus Thorne

• Great question, Marcus. Most frameworks don't let the agent "manage" the budget autonomously yet. You should set a max_rpm (requests per minute) or a total token limit in your API wrapper. However, in CrewAI, you can set a max_iter for the whole crew, which is a life-saver for preventing a loop where the security agent and developer keep arguing forever and draining your wallet!

     Commented 2025-02-14 by Lawrence Black

I prefer the "Consensus" model where all three agents must approve the final PR. It takes longer but the code quality is significantly higher than a single-agent output.

   Answered 2025-02-15 by Pamela Gibson

• I agree with Pamela. Having that final layer of "Agentic Consensus" really catches those edge-case bugs that a single LLM pass almost always misses.

     Commented 2025-02-16 by Jordan Casey