In May 2026, a widely-discussed essay on Hacker News argued that "the bottleneck was never the code" — AI code generation has solved the coding bottleneck, but the real bottlenecks remain in specification, design, review, and deployment. It resonated with thousands of developers. But there's another bottleneck nobody's talking about enough: the routing layer between your application and the LLM providers . If you're building anything beyond a ChatGPT wrapper, you already know: models fail, rate limits hit at the worst times, pricing changes overnight, and latency varies wildly depending on region and provider load. The real engineering challenge in 2026 isn't generating code — it's keeping your LLM-dependent production app alive when upstream services go down. The Production Failure Modes Nobody Warns You About When you're prototyping with a single LLM provider, everything works. You call the API, you get a response, you move on. But at scale, here's what actually breaks: 1.…