Last week, we learned what enterprises must do with their infrastructure stack to maximize development velocity, including how to leverage the right amount of on-prem and cloud tools!
Our friends at Arcee just released AnyMCP, and it's built to easily manage your Model Context Protocol (MCP) endpoints and configurations in one central platform.
MCP is all about having a set of standard rules that we can use to build LLM application and leverage context. In this event, we’ll dive into MCP on a deeper level than we did in our original MCP event by learning about how to deploy MCP servers to API endpoints!
Upcoming Live Events
Google ADK: Agent Development Kit
Google Cloud recently introduced ADK, the Agent Development Kit. It's another agent framework that allows us to design, deploy, and evaluate intelligent multi-agent systems. Join us live to learn how to orchestrate agents with access to tools and deploy production-grade agentic applications!
Building Agentic Systems with Protocols: MCP & Agent2Agents (A2A)
You may have heard of A2A—the Agent-to-Agent Protocol—but what exactly does it enable, and how does it relate to MCP? While MCP is like the “USB-C for LLMs,” connecting models to tools and data, A2A is the operating system for multi-agent collaboration. It provides the glue for AI agents—built by different teams using different technologies—to discover, delegate, and co-complete tasks seamlessly. A2A fosters open, secure, and scalable communication across agent ecosystems, transforming brittle integrations into fluid cooperation.
Curious how A2A and MCP work together, and what this means for your AI systems? Join us to explore the future of interoperable agent networks.
Community Highlights
Evaluating Advanced RAG Retrievers: A Practical Comparison
With the explosion of new retrieval strategies—vector search, BM25, multi-query, reranking, parent-document, and ensemble methods—how do you know which is best for your use case? Muhammad Afzaal, a current student in Cohort 6 of The AI Engineering Bootcamp, walks through a real-world, metric-driven evaluation of advanced retrievers using LangChain and RAGAS.
As AI adoption accelerates across the enterprise, engineering leaders are discovering that LLMs alone can't meet the demands of reliability and trustworthiness.
Saumil, another current student in Cohort 6 of The AI Engineering Bootcamp, goes in depth on what Retrieval-Augmented Generation (RAG) is and offers a practical framework to help leaders build robust, business-ready AI systems.
The price is increasing on June 1st to $3499! Secure your spot in Cohort 7 of The AI Engineering Bootcamp for $2999 to transform your skillset as a software engineer or data scientist into an AI Engineer in 2025.
Not ready to invest the money for upskilling? You can learn 100% for free by investing only your time. Follow a straight line from zero to AI Engineer with just fifteen 1-hour lectures.