Building Agents with Amazon Nova Act and MCP - Du’An Lightfoot, Amazon (Full Workshop)
AI Summary
This video features a workshop on building intelligent autonomous AI systems using Amazon Nova ACT and MCP, presented by Dewan Lifford and Banjo Bami from AWS. They explore the concept of agentic AI which involves planning, action, and reasoning to complete complex tasks autonomously by leveraging large language models (LLMs), knowledge bases, and tool integrations.
Key highlights include:
- Understanding agentic AI architecture, components such as LLM, knowledge base, guardrails, tools, and memory.
- Different approaches to agents on AWS: specialized (Amazon Q), fully managed (Amazon Bedrock), and DIY (Strands agents).
- Hands-on demo of Amazon Nova ACT, a research preview model for browser automation which can perform tasks like searching Amazon.com and interacting with web pages via natural language commands.
- Using MCP (Modern Context Protocol) to build servers that integrate Nova ACT for complex task automation and multi-agent collaboration.
- Introduction to Strands, an open-source lightweight agent framework for building agents easily with Python, supporting multi-agent workflows and native MCP integration.
- Examples of building multi-agent solutions for AWS architecture tasks including generating diagrams, cost analysis, and executive presentations.
- Discussion on limitations like CAPTCHA handling, regional availability (U.S. only currently), and the importance of responsible AI use.
- Q&A covering technical details, use cases, and comparison with other AWS offerings.
Overall, the workshop shows how developers can utilize these tools and frameworks to build scalable, autonomous AI-driven workflows to improve productivity and innovation on AWS.