Source: Soft Coded
The messy reality of AI-powered products—failed API calls, incompatible outputs, repeated troubleshooting—is being absorbed by individual builders and small teams right now, not baked into the cost structure of AI vendors or reflected in their marketing. As companies rush to ship AI features, they're offloading debugging work and operational friction onto early adopters. The actual economic efficiency gains from AI remain theoretical while the busy work multiplies. Eventually, either providers build better tooling or marginal use cases get culled. For now, the gap between "AI is faster" and "AI adoption is actually slower" keeps widening.