Can DSPy be used for AI agent role-playing and collaboration?

All answers to this question.

Yes, and this is where DSPy really shines. You can create a "Coder" module and a "Reviewer" module as part of a larger DSPy program. When you compile the program, the optimizer doesn't just look at one prompt; it looks at the interaction. If the Coder generates bad code, the Reviewer catches it, and the optimizer learns to adjust the "Reviewer's" prompt to be more critical or the "Coder's" prompt to follow specific patterns. It turns agent collaboration into a measurable, tunable process rather than a random conversation.

   Answered 2025-11-12 by Monica Foster

Does this multi-agent optimization in DSPy increase the token cost during the compilation phase?

   Answered 2025-11-20 by Arthur Knight

• It does, Arthur. Because the optimizer has to run the pipeline multiple times to find the best prompt, you will see a spike in usage during "compilation." However, once it’s compiled, you save tokens in production because the prompts are often more efficient and you don't need as many "retries" or "clarifications" between the agents. Think of it as an upfront investment for long-term efficiency.

     Commented 2025-11-28 by Victor Malone

I used DSPy to build a "Triage" agent that hands off tasks. The accuracy of the handoffs improved by 20% after compilation.

   Answered 2025-12-05 by Pamela Boyd

• That’s a huge improvement, Pamela! It shows that even simple "routing" logic can benefit from the systematic optimization that DSPy provides.

     Commented 2025-12-10 by Bryan Foster