AI agents are powerful tools for automating complex reasoning tasks, but they suffer from fragility issues such as LLM API failures and network errors, which can disrupt workflows. To address these challenges, an integration with Pydantic and Prefect has been developed to make agents production-ready by enhancing reliability, observability, and scheduling. This integration employs Pydantic AI for building type-safe agents and Prefect for orchestrating workflows, enabling automatic failure recovery through durable execution and granular retry policies. Prefect caches successful task results, allowing workflows to resume from the point of failure without repeating completed steps. This approach reduces redundancy and saves on API costs, while structured outputs from Pydantic AI allow agents to act as composable workflow components, facilitating integration with other tasks and systems. The integration shifts the perspective from treating AI agents as isolated scripts to viewing them as integral parts of the workflow infrastructure, offering a robust solution for deploying AI in production environments.