Practitioners working on AI Agent deployment have likely encountered this frustrating dilemma: despite using flagship models, revising prompts hundreds of times, and fine-tuning RAG systems repeatedly, task success rates simply won't improve in real-world scenarios. The agent sometimes appears brilliant, other times goes completely off-track.The root of the problem lies not in the model itself, but in the operational system surrounding it—the Harness.Understanding Harness EngineeringThe term "Harness" originally refers to restraint or contro...