Built-in tools like web search, file search, and code interpreter allow developers to extend model capabilities out-of-the-box. This summary covers the concepts, compares them to function calling, and details a demo of building a data exploration dashboard using multiple tools in concert.
7 AI Terms You Need to Know: Agents, RAG, ASI & More
A deep dive into seven essential AI concepts shaping the future of intelligent systems, including Agentic AI, RAG, Mixture of Experts (MoE), and the theoretical frontier of Artificial Superintelligence (ASI).
Making Your Data Agent-Ready with EnrichMCP // Simba Khadder // Agents in Production 2025
Simba Khadder explains that the primary bottleneck for LLM agents is not intelligence, but access to structured data. He introduces EnrichMCP, an open-source framework that creates a semantic layer over data models, enabling agents to discover, reason about, and query data sources like SQL databases effectively, moving beyond the limitations of RAG and direct API conversions.
Real World Development with GitHub Copilot and VS Code — Harald Kirschner, Christopher Harrison
A deep dive into "Vibe Coding," a development methodology that prioritizes outcomes over code-level details, using the advanced AI features of VS Code and GitHub Copilot. The talk explores three stages of this methodology—YOLO, Structured, and Spectrum—and demonstrates how to leverage agent modes, custom instructions, reusable prompts, and the Model Copilot Protocol (MCP) to enhance productivity from rapid prototyping to enterprise-scale development.
Building Agents at Cloud Scale — Antje Barth, AWS
A deep dive into building and scaling production-ready AI agents, detailing a model-driven approach using the open-source 'Strands' SDK and a cloud-native architecture for deploying remote tools with MCP and AWS Lambda.
Building AI agents with Claude in Amazon Bedrock | Code w/ Claude
In a presentation from Code w/ Claude, AWS advocates Du'An Lightfoot, Suman Debnath, and Banjo Obayami introduce Strands, a new open-source Python SDK for building AI agentic applications on AWS. They showcase how Strands simplifies development by focusing on three core components—models, tools, and prompts—and leverages the full reasoning power of foundation models like Claude 3.5 on Amazon Bedrock. The session includes live demos on creating a multi-tool weather agent, integrating with Modular Connected Protocol (MCP) servers for AWS documentation and diagram generation, and using Claude Code to auto-generate a complete Strands agent for AWS CDK.