GPT-5's launch caused widespread AI application failures when OpenAI deprecated older APIs without warning. The incident highlights the brittleness of AI systems that depend on single providers or models. Modern AI applications are complex stacks involving prompts, embeddings, and retrieval logic that break when underlying models change. To build resilient AI systems, developers should implement AI High Availability (AIHA) architectures with multi-provider support, automated fallback mechanisms, behavioral monitoring, and contract testing. Key strategies include abstracting API layers, maintaining separate prompt libraries for different models, implementing graceful degradation, and treating model deprecation as an expected lifecycle event rather than an emergency.