Building an AWS solutions architect agentic app with Amazon Bedrock (DEV331)

Building an 8-way AWS Architect Agent App with Amazon Bedrock

Introduction

  • The speakers are Banjo Biami, a Senior Developer Advocate at AWS, and Shar, a software engineer and YouTuber.
  • The session focuses on building an agentic workflow using Amazon Bedrock, a fully managed serverless service for building and scaling generative AI applications.

AWS Generative AI Stack

  • The AWS generative AI stack consists of various services and tools for building, training, and deploying AI models.
  • At the bottom, there are services like Amazon SageMaker, AWS Trinium, and AWS Inferentia for infrastructure and model development.
  • Amazon Bedrock is a key service that allows building and scaling generative AI applications using foundation models.
  • Other tools in the stack include Amazon Lex (business-focused) and Amazon Q (developer-focused).

Agentic Workflows

  • Agentic workflows are about building AI agents that can perceive, decide, and act autonomously to achieve goals, adapting their behavior based on experiences and interactions.
  • Key design patterns for agentic workflows include reflection, tool use, planning, and multi-agent collaboration.
  • Building agentic systems can help with breaking down complex tasks, increasing autonomy, improving efficiencies, and achieving better scalability.

Building the AWS Architect Agent App

  • The speakers demonstrate building an AWS Architect Agent app using Amazon Bedrock.

  • The agent is designed to help customers with the following tasks:

    1. Querying the AWS Well-Architected Framework knowledge base
    2. Generating AWS Lambda functions
    3. Describing AWS diagrams
    4. Drawing AWS diagrams
    5. Extracting text from websites
  • The agent uses various action groups (tools) to accomplish these tasks, and a knowledge base with the AWS Well-Architected Framework.

  • The agent demonstrates its capabilities by:

    • Providing a response to a query about cloud security best practices using the knowledge base
    • Describing an existing AWS diagram for a media streaming solution
    • Creating a new diagram for an e-commerce architecture
    • Generating a AWS CDK script to deploy the e-commerce architecture
    • Creating a Lambda function for sentiment analysis and providing the client code to use it

Key Takeaways

  • Agentic workflows empower builders to integrate AI into their personal and professional workflows, leveraging tools like Amazon Bedrock and Amazon Q.
  • The best way to utilize these tools is to experiment and find the use cases that work best for your specific needs, as there is no one-size-fits-all solution.
  • The workshop "Building Agentic Workflows on AWS" is recommended for a step-by-step guide on creating agentic workflows using Amazon Bedrock and other AWS services.

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