Transitioning AI agents from prototypes to production can be challenging, particularly in areas like fraud detection. The process involves managing factors such as authentication, memory persistence, observability, and isolation. This in-depth guide illustrates the deployment of AI agents using Amazon Bedrock AgentCore, the Strands SDK, and Pulumi, highlighting the journey from initial development to a production-ready state. The Strands SDK facilitates local agent development with minimal code, while the Bedrock AgentCore offers a managed runtime with Firecracker isolation, supporting complex, long-running tasks. The guide also emphasizes the importance of adopting a progressive approach, starting with simple solutions and incorporating additional complexity and infrastructure as code only when necessary. Additionally, it explores event-driven architectures and the integration of short-term and long-term memory to enhance agent functionality. The use of Amazon's managed services, such as the MCP Gateway for tool integration and X-Ray for observability, ensures security and efficient operation at scale. This comprehensive roadmap not only demonstrates the technical steps involved in deploying a fraud detection AI agent but also underscores the strategic considerations necessary for effective production deployment.