Anyone working on AI Agent implementation has likely encountered this dilemma:You're using a flagship model, have revised your prompts hundreds of times, and tuned your RAG system countless times. Yet when deployed in real-world scenarios, the task success rate simply won't improve—the agent sometimes performs brilliantly, other times goes completely off-track.The problem doesn't lie with the model itself, but with the operating system running outside the model—the Harness.What Is Harness Engineering?The term "Harness" originally refers to r...
Posts tagged Failure Recovery
Beyond Parameter Tuning: Harness Engineering as the Core of Stable AI Agent Deployment
The Universal StruggleDevelopers implementing AI Agents in production environments frequently encounter this frustrating dilemma:Using flagship models, revising prompts hundreds of times, tuning RAG systems repeatedly—yet task success rates remain stubbornly low in real scenarios, with performance fluctuating unpredictably between brilliance and failure.The root problem lies not in the model itself, but in the operational system surrounding it—the Harness.Understanding Harness EngineeringThe term "Harness" literally means "tethers" or "restr...
Beyond Prompt Engineering: Harness Engineering as the Key to Stable AI Agent Deployment
Developers working on AI Agent deployment have likely encountered this frustrating dilemma: using flagship models, revising prompts hundreds of times, tuning RAG systems repeatedly—yet task success rates remain stubbornly low in real-world scenarios, with performance fluctuating unpredictably between brilliant and completely off-track.The root problem lies not in the model itself, but in the operational system surrounding it—the Harness.Understanding Harness EngineeringThe term "Harness" originally refers to reins or restraint devices. In AI...