What if you could get the performance of a massive, 100-example prompt, but with 13 times fewer tokens?
That’s the breakthrough promise of "instruction induction" —teaching an AI to be the prompt engineer.
This week, we dive into PROMPT-MII , a new framework that essentially meta-learns how to write compact, high-performance instructions for LLMs. It’s a reinforcement learning approach that could make AI adaptation both cheaper and more effective.
This episode explores the original research by Emily Xiao, Yixiao Zeng, Ada Chen, Chin-Jou Li, Amanda Bertsch, and Graham Neubig from Carnegie Mellon University.
Read the full paper here for a deeperdive: https://arxiv.org/abs/2510.16932
