Google's Gemini 2.5 Flash and 2.5 Pro models, alongside the Veo 2 video generation model, have significantly advanced AI capabilities, enabling developers to create sophisticated systems that can reason, plan, and generate content. However, deploying these systems in production presents challenges due to their complexity, long-running nature, and susceptibility to failures such as network issues or server crashes. Temporal addresses these challenges by offering a Durable Execution platform that ensures resiliency and reliability in orchestrating complex workflows. By persisting the state of AI processes, Temporal allows systems to resume operations seamlessly after failures, avoiding costly reruns and providing detailed logs for debugging. In an open-source video generation system using Google’s AI models, Temporal manages the execution of tasks, such as scene scripting with Gemini and video generation with Veo, by handling retries, state persistence, and parallel execution. This approach allows developers to focus on building robust AI features without being bogged down by the intricacies of failure handling and state management, paving the way for more efficient and reliable production-ready systems.