Learning to Orchestrate Agents in Natural Language with the Conductor

–> TL;DR For the past few years, humans have been doing “prompt engineering” to coax the best performance out of different LLMs. In this work, we explored what happens if we train an AI to do that job instead. In this work, by training a Conductor model with RL, we found that it naturally learns to write highly effective, custom instructions for a whole pool of other models. It essentially learns to ‘manage’ them in natural language. What surprised us most was how it dynamically adapts. For simple factual questions, it just queries one model.