Where Most AI Projects Break and Who Actually Handles It Better
Most AI projects begin with convincing momentum. Strong demos, clear use cases, and fast early wins make everything look under control. This early success creates a dangerous illusion: if it works in a controlled environment, it should work in production. In reality, it almost never does. Real problems don’t show up at the start. They appear later, when AI meets […]





