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The first generation of AI applications often had a surprisingly simple backend architecture. An application accepted a request, sent it to an LLM API...
AI applications are becoming increasingly conversational, interactive, and real-time. Users expect an answer to start appearing immediately rather than waiting...
An AI application can use a powerful model and still feel painfully slow. The problem is often not the LLM itself. A production AI request can pass through...
AI agents are changing what software is expected to do. Traditional applications wait for a user request, execute predefined business logic, call a few...
GraphQL has become an important API architecture for complex digital products because it gives clients more control over the data they request. That...
API rate limiting is supposed to protect backend systems. It prevents abuse, controls traffic spikes, protects databases, and keeps one consumer from...
Choosing an API architecture is no longer a simple decision between familiar HTTP endpoints and newer alternatives. Modern backend applications serve web...
Modern backend applications can have excellent infrastructure, fast application servers, and well-designed APIs, yet still feel painfully slow. One of the most...
For years, the standard architecture for AI applications was straightforward. The user interacted with a mobile app, browser, or desktop application. That...
