Google just released the A2A protocol, making it easier than ever to connect your AI agents with agents built by other developers and companies—no matter which framework you're using. If you're serious about building powerful, connected AI agents, mastering A2A is essential. ​ Here's exactly what you'll learn in my brand-new A2A crash course: ✅ The basics of A2A: what it is, how it works, and why it's a must-know. ✅ Build your first simple agent workflow using A2A. ✅ Advanced workflow step-by-step: connecting an ADK agent seamlessly with CrewAI, LangGraph, and another ADK agent. Plus, I've included timestamps throughout the video, so you can quickly jump to any specific topic whenever you need. And to make things even easier, I'm giving away all the example code from the video completely free! 👉 Download free code​ This tutorial is the comprehensive, practical resource I wish I had when starting with A2A. If you’re looking to level up your AI skills, don’t miss this video! Cheers, Brandon Hancock 🧑‍💻

VIEW RECORDING - 125 mins (No highlights) Key Takeaways - Brandon completed an agent-to-agent (A2A) tutorial for ADK, showcasing integration with CRI, LandGraph, and ADK agents - Participants shared diverse AI projects, from video generation to fantasy football automation - Discussions on PDF processing, database integration, and deployment strategies for AI applications - Updates on new features in Crew AI and comparisons with ADK functionality Topics ADK Updates and Tutorials - Brandon finished an A2A tutorial for ADK, demonstrating integration with multiple agent types - New ADK deployment video coming soon, showcasing API endpoint exposure and Cloud Run integration - ADK's strengths in chat functionality, but limitations in multi-agent collaboration compared to Crew AI Participant Projects - Mitch: Working on a tool for generating video content using AI, transitioning from Airtable to a custom software stack - Juan: Deploying AI infrastructure with LLMs and RAG systems for a client, exploring Llama Index for tabular data handling - Ty: Developing custom software solutions for business needs, including inventory management and POS systems - Marc: Creating a video game-themed customer service and inventory management system using ADK and Docker

I am getting ADK Masterclass persistent_store demo. ---------- State AFTER processing ---------- Error displaying state: 'coroutine' object has no attribute 'state' C:\Vivek\AI\Code\OpenAI-SDK\Projects\GoogleADK\persistent_store\utils.py:145: RuntimeWarning: coroutine 'DatabaseSessionService.get_session' was never awaited display_state( RuntimeWarning: Enable tracemalloc to get the object allocation traceback

I am new to python and looking for some suggestions My use case - Frontend hits the api and the python backend api runs the LLMs with the inputs given by the user. Is there any document for the reference ?

VIEW RECORDING - 141 mins (No highlights) Key Takeaways - Participants shared progress on diverse AI projects, from music bots to pharmaceutical analysis tools - Discussion of various AI tools and frameworks, including Agent Development Kit (ADK), N8N, and Cursor AI - Emphasis on the importance of personal branding and content creation for AI developers - Several participants working on complex data extraction and processing challenges Topics WhatsApp Integration for Venue Information - Alex is developing a WhatsApp bot for a music venue to provide band information - Recommendations: Use a structured database instead of RAG, consider Cloudflare Workers or Railway for deployment - Maxim advised on WhatsApp API integration and user experience design AI Skill Set Matchmaker - Ty Wells participated in a Bolt.new hackathon, creating an AI skill set matchmaker for the AI community - The project faced challenges with Bolt's performance and limitations - Discussion on alternative tools and approaches for future projects