Microsoft.Google.AWS.Everyone's solving the same problem for Agents:How to build a real-time context layer for Agents across dozens of data sources?Airweave is an open-source context retrieval layer that solves this!Learn how this layer differs from RAG below: https://t.co/hqycgs5eoqAvi Chawla (@_avichawla):You are in an AI engineer interview at Google.The interviewer asks:"Our data is spread across several sources (Gmail, Drive, etc.)How would you build a unified query engine over it?"You: "I'll embed ever ...

Next, repeat these steps for the 2nd server to host the Smolagents Agent and its LLM.- Line 1-10 → Imports + define the Server & the LLM.- Line 12 → Decorate the method.- Line 21-28 → Define the Agent with a web search tool.- Line 31 → Serve the Agent.Finally, we use an ACP client to connect both agents in a workflow.- Line 6-7 → Connect the client to both servers.- Line 11-14 → Invoke the first agent to receive an output.- Line 18-21 → Pass the output to the next agent for enhancement.Next, run the two ser ...

ACP is a standardized, RESTful interface for Agents to discover and coordinate with other Agents, regardless of their framework.Just like A2A, it lets Agents communicate with Agents. There are some differences, which we shall discuss later.Here's how it works:- Build the Agents and host them on ACP servers.- The ACP server receives requests from the ACP Client and forwards them to the Agent.- ACP Client itself can be an Agent to intelligently route requests to the Agents (like MCP Client does).Let's dive in ...

Transaction Volume - Virtuals Protocol transactions increased by 500% in one week following x402 integration [1] - The introduction of payment rails triggered a significant surge in transaction volume [1] Latent Demand - Elizaos has over 50,000 agents awaiting similar unlocking [1] - Infrastructure that enables latent demand represents an undervalued opportunity in the crypto market [1]

Industry Trend - The industry is moving towards an era where every website must be "Agent-ready" [1] - Agents, not humans, will be making purchases in the future [1] - Agents will be responsible for finding the best options [1] Technological Advancement - Postman's latest Guidebook on building AI-ready APIs is highlighted as a crucial document for developers [1]

LangChain Essentials Course Highlights - LangChain releases a new LangChain Essentials course for learning the basics of LangChain in an hour [1] - The course focuses on building agents using the `create_agent` abstraction [2] - The pre-built agent utilizes a ReAct-style architecture for reasoning and acting with tools [3] Agent Architecture and Scalability - The agent is built on LangGraph to balance flexibility with pre-built abstraction benefits [4] - The agent is designed to be scalable, resilient to failures, and allows for human intervention [3] - The agent can dynamically select prompts and models, with optional middleware for customization [4] Course Content - The course covers features of the `create_agent` abstraction through building increasingly sophisticated agents [5] - The course utilizes LangChain building blocks including messages, tools, and models [5]

And so you have this iterative process of creating the right prompt and shaping the right guard rails and other code in order to get it to be like really useful in those situations. Open source has been a huge part of lang chain from ever since we got started. Obviously it started as an open source package and it's evolved a lot over the years.We now have Typescript packages. We now have lang chain and langraph. And so you know as we release 1.0% know of these packages.It's a huge moment for us as a company ...

Heat. [Applause] [Music] Heat. Heat. [Applause] [Music] Heat. Heat.Heat. [Music]. ...

Andre Karpathy, one of the most important figures in artificial intelligence, says we're 10 years away from AGI. He was just on Dwaresh's podcast, and it was really an incredible discussion between the two. But I actually found his follow-up post on X to be just as interesting. And that's what we're going to go over today. He clarifies many of the points he made on the Darkh podcast and even goes a little bit further. Let's get into it. And quickly, let me just tell you about our new 100 ways to use AI guid ...

Core Problem & Solution - The open-source Parlant framework introduces a new reasoning approach to prevent hallucinations in LLMs [1] - This new approach achieves a SOTA success rate of 90.2% [2] - It outperforms popular techniques like Chain-of-Thought [2] Key Features of Parlant - Parlant enables the building of Agents that do not hallucinate and follow instructions [1]