During a two-month period, Brian Tinarwo focused on stabilizing and automating cloud-based machine learning deployments. In the aws-samples/sagemaker-genai-hosting-examples repository, he improved SageMaker deployment reliability by pinning SGLang to a specific Docker image version, reducing environment drift and ensuring reproducibility for production workloads. The following month, in awslabs/amazon-bedrock-agentcore-samples, Brian enhanced the runtime-gateway example by introducing CloudFormation-based automated deployment and refining code quality through linting, typo correction, and file renaming to resolve circular imports. His work leveraged AWS, CloudFormation, and Python, demonstrating a methodical approach to deployment automation and maintainability in cloud-native development environments.