The AI Infrastructure Blueprint: 5 Rules to Stay Online

In Part 1 of this newsletter, we explored why OpenAI continues to experience outages. OpenAI’s growing pains are a lesson to everyone building in the AI era:

Solid System Design is essential to any competitive AI service.

But here's the thing: scaling AI is not an OpenAI problem. It's an everybody problem.

With AI coming for every product surface, every developer needs to know how to keep their systems fast, reliable, and cost-efficient — whether you're building on OpenAI’s API, fine-tuning your own model, or scaling inference in production.

The good news? We already have a blueprint for success.

While LLMs introduce new pressure points, the underlying playbook for high availability hasn’t changed all that much. In fact, many of today’s reliability patterns come from teams that have already solved the hard stuff—operating real-time systems under global load.

So today we'll cover your AI blueprint: 5 essential rules to scale AI systems reliably. These five rules are drawn from real-world systems that keep billions of requests flowing, from traditional hyperscalers to AI-native leaders like OpenAI.

Let’s dive in.