Building sustainable, cost-effective generative AI on AWS requires integrating agentic AI, efficient architecture, and cloud-native optimization. Agentic systems using Amazon Bedrock AgentCore employ contextual memory, asynchronous execution, and on-demand tool invocation to minimize compute waste. MCP enables secure connections between AI agents, AWS services, and custom tools. Efficiency increases through AWS's Trainium and Inferentia2 silicon (50% better performance per watt), Amazon SageMaker for scalable development, and optimization techniques like quantization and speculative decoding. Auto-scaling, batch processing, and spot instances prevent over-provisioning. Combined with CloudWatch and Cost Explorer monitoring, this approach delivers high-performance, low-carbon generative AI solutions.

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