Microsoft treats agent skills like trainable neural weights
Microsoft just open-sourced SkillOpt, a framework that optimizes agent skill files like deep-learning parameters without altering underlying model weights. By using text-space forward passes, reflective edits, and strict validation gating, it boosted GPT-5.5 benchmark scores by 23.5 points. Why it matters: It replaces messy manual prompt hacking with a reproducible, controlled training loop.