The Difference Between a Demo and a Product We’ve all seen the flashy AI demos. They work perfectly in a controlled environment, but the moment you try to put them in production, they fall apart. According to recent industry estimates, nearly 88% of AI agent projects never make it to production. Why? Because the model isn't the problem—the infrastructure around it is. In modern AI engineering, we call this the AI Harness . It is the operating layer that surrounds your Large Language Model, handling everything from context assembly and memory to control loops and quality gates. As models become more commoditized, the quality of your harness becomes the primary competitive advantage. What is an AI Harness? Think of your application as: Agent = Model + Harness While the model provides the raw intelligence, the harness provides the reliability, safety, and control . It defines the rules of engagement. Without a robust harness, you're just firing prompts into the void and hoping for the best.…