Neural networks started as an esoteric discipline. A small group of researchers trying to teach machines to think, largely ignored by the industry. Then the creature got life — and everyone rushed in to build on top of it. The problem with rushing: you rebuild what already exists. Not because you're careless. Because nobody told you to look at the right shelf. The agentic AI field is in a phase every young technology goes through: rediscovering solved problems without knowing they are solved. Engineers are building bespoke orchestration frameworks that duplicate Dapr. Inventing retry logic that misses guarantees Sagas have provided since 1987. Designing agent communication protocols that solve problems gRPC solved in 2015. The infrastructure layer largely maps onto solved distributed systems patterns. Stop rebuilding it from scratch. But three problems have no ancestor. Semantic failure is invisible. A microservice failure returns HTTP 500.…