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A company is building a custom agentic application.

A company is building a custom agentic application. The company must have fine-grained control over the agent orchestration loop. The application must implement custom logic to select tools, handle multi-turn conversations that involve complex state management, integrate with proprietary logging systems, and implement custom retry strategies for tool failures.

The company wants to use Amazon Bedrock FMs but must have full control over the orchestration logic. The company has expertise in building orchestration logic but wants to use AWS infrastructure to manage model inference and tool execution.

Which solution will meet these requirements?

A.

Use Amazon Bedrock AgentCore Runtime to deploy the application agents. Use AgentCore Gateway to integrate the application with tools. Use AgentCore Memory to manage conversation states. Use AgentCore Policy to handle tool selection and retry logic.

B.

Use Amazon Bedrock AgentCore to build a custom orchestration layer that controls the agent orchestration loop, tool invocation, and state management. Use Amazon Bedrock to manage model inference.

C.

Use Amazon Bedrock AgentCore built-in memory and session management capabilities to persist conversation state. Configure the managed tool execution runtime to automatically handle tool failures and retries.

D.

Use AWS Step Functions to orchestrate multiple calls to Amazon Bedrock AgentCore Runtime endpoints. Implement custom state management and retry logic between individual agent invocations.

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