Building ambient agents with Amazon Bedrock AgentCore: From event-driven signals to human-in-the-loop workflows
Ambient agents respond to events such as an Amazon S3 upload, a schedule, or an alert instead of waiting for a chat prompt. This post walks through building framework-agnostic ambient agents on Amazon Bedrock AgentCore using Amazon SQS, AWS Lambda, and Amazon DynamoDB, with a single ask_human tool and a Jobs page for human-in-the-loop review.
Ambient agents solve the problem of manual triage by automatically reacting to events in infrastructure and requesting human input when necessary. For example, when a new file is uploaded to an Amazon S3 bucket, an ambient agent can analyze the file, surface findings, and ask for approval before proceeding. This differs from chat-based agents where the user initiates the conversation by typing a prompt.
Ambient agents listen to event streams and perform actions accordingly, potentially handling multiple events simultaneously. The key component enabling this is Amazon Bedrock AgentCore, a platform for building, connecting, and optimizing agents at scale using any framework or model. AgentCore Runtime provides a container-based execution environment with support for long-running workloads, session isolation, and integration with Amazon Bedrock foundation models.
The reference implementation uses AWS Lambda for event processing and Amazon DynamoDB for state management, resulting in a fully serverless ambient-agent platform.
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