Master AI Agents with Google ADK & MCP

🚀 Calling all Developers: Ready to build the next generation of AI Agents? The shift from "Chatbots" to "AI Agents" is happening fast. If you’ve been looking for a hands-on way to move past the theory and actually start deploying, the AI Learning Lab is where you need to be. We’re hosting live, interactive sessions designed specifically for developers who want to master tools like Google’s Agent Development Kit (ADK) and the Model Context Protocol (MCP). Why join the Lab? 🛠 Live Build-Alongs: live coding with Google Developer Experts (GDEs). 🤖 Multi-Agent Systems: Learn to build and link agents that actually execute workflows and connect to real-world APIs. 💳 Free Resources: Gain access to Google Cloud credits and working code examples to fuel your own experiments. 🌍 Global Community: Join sessions in English, Portuguese, or Spanish and connect with a network of AI-focused engineers. Don’t just watch AI happen—build it. 👉 Secure your spot and register here: https://lnkd.in/ePY3q6DU #AICoding #GenerativeAI #GoogleDeveloperExperts #AIAgents #SoftwareDevelopment #TechLearning #CloudComputing #AILearningLab

🚀 Calling all Developers: Ready to build the next generation of AI Agents? The shift from "Chatbots" to "AI Agents" is happening fast. If you’ve been looking for a hands-on way to move past the theory and actually start deploying, the AI Learning Lab is where you need to be. We’re hosting live, interactive sessions designed specifically for developers who want to master tools like Google’s Agent Development Kit (ADK) and the Model Context Protocol (MCP). Why join the Lab? 🛠 Live Build-Alongs: live coding with Google Developer Experts (GDEs). 🤖 Multi-Agent Systems: Learn to build and link agents that actually execute workflows and connect to real-world APIs. 💳 Free Resources: Gain access to Google Cloud credits and working code examples to fuel your own experiments. 🌍 Global Community: Join sessions in English, Portuguese, or Spanish and connect with a network of AI-focused engineers. Don’t just watch AI happen—build it. 👉 Secure your spot and register here: https://lnkd.in/eTjr-HHB #AICoding#GenerativeAI#GoogleDeveloperExperts#AIAgents#SoftwareDevelopment#TechLearning#CloudComputing#AILearningLab

There's a vast difference between just using AI and actually building with it. As an AI instructor and software engineer, the question I get most is: where do I actually learn to build? Not theory—actual automations, agents, and tools that save hours and make you harder to replace at work. I partnered with Leland on their AI Builder Program because I think it's a genuine answer to that. 5 levels, taught by experts from Google, OpenAI, and Meta. Level 1 kicks off April 21 (tomorrow!) and the rest are through the summer. Use code LELANDAI50-ISHA on ai.joinleland.com for a 50% discount. Hope to see you there! DM me if you want to know more before signing up.

🚀 Calling all Developers: Ready to build the next generation of AI Agents? The shift from "Chatbots" to "AI Agents" is happening fast. If you’ve been looking for a hands-on way to move past the theory and actually start deploying, the AI Learning Lab is where you need to be. We’re hosting live, interactive sessions designed specifically for developers who want to master tools like Google’s Agent Development Kit (ADK) and the Model Context Protocol (MCP). Why join the Lab? 🛠 Live Build-Alongs: live coding with Google Developer Experts (GDEs). 🤖 Multi-Agent Systems: Learn to build and link agents that actually execute workflows and connect to real-world APIs. 💳 Free Resources: Gain access to Google Cloud credits and working code examples to fuel your own experiments. 🌍 Global Community: Join sessions in English, Portuguese, or Spanish and connect with a network of AI-focused engineers. Don’t just watch AI happen—build it. https://lnkd.in/dxmz-2R5

𝗧𝗵𝗲 𝗦𝗵𝗼𝗰𝗸𝗶𝗻𝗴 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗕𝗶𝗹𝗹 I had a surprise last month. My AI bill was 40% higher than expected. I was using AI less and coding less. So what happened? I was working on a macOS app. I got into a habit of leaving conversations open. I'd start a conversation in the morning and continue it in the afternoon. Each message carried the entire conversation history. I was paying per token, and that context window was growing. A short conversation could cost $0.04 if fresh. But with conversation history, it cost $0.40. Multiply that across a week, and you get a 40% spike. I was writing less code because I was using AI for planning. Those conversations are long and meandering. Code generation is cheap, but architecture discussions are expensive. I switched to starting fresh conversations for different topics. I also used a tool to see what I was spending in real time. That made the cost tangible. If you've had similar issues with your AI bill, what did you do? Source: https://lnkd.in/gEjavNjn Optional learning community: https://t.me/GyaanSetuAi

Built something I genuinely wish I had as a student. Class Pilot now has a class-specific AI assistant, each class gets its own AI that knows everything about it. Uploaded materials, upcoming deadlines, active polls, attendance sessions, announcements all of it, in one place and you can just ask. The technical side is a RAG pipeline where each class is completely isolated, students from one class can never see another class's data. The AI processes vague questions into better search queries before hitting the vector database, handles follow up questions with conversation context, and falls back to live class data when there's nothing in the documents. Still polishing, but it's working and being tested on real documents . (ignore the document names :) #NextJS #OpenAI #EdTech #BuildInPublic

Most "learn AI" courses are fluff. This one from Microsoft is free and teaches you how to actually build. It's 18 lessons. Zero to building real AI apps. Here are the first 8: 0/ Course Setup How to set up your dev environment. 1/ Introduction to Generative AI and LLMs What GenAI is and how LLMs work. 2/ Exploring and Comparing Different LLMs How to pick the right model for your use case. 3/ Using Generative AI Responsibly How to build GenAI systems the right way. 4/ Understanding Prompt Engineering Fundamentals Hands-on prompt engineering best practices. 5/ Creating Advanced Prompts Techniques that actually improve your outputs. 6/ Building Text Generation Apps Build a real app using Azure OpenAI / OpenAI API. 7/ Building Chat Applications Techniques for building and integrating chat apps. I compiled all 18 lessons with direct links into one resource. Subscribe below and I'll send it straight to your inbox. 👉 https://lnkd.in/efsHKZhv

I spent time exploring AI agents from the ground up. Not by only reading posts By going through repos, notebooks, walkthroughs, and trying things hands on. These 10 GitHub repos gave me a strong starting point in understanding how AI agents actually work. 1. Hands On Large Language Models Great for learning LLM basics all the way to fine tuning 2. AI Agents for Beginners Simple step by step series to build a first working agent 3. GenAI Agents Helpful for understanding agent workflows and architectures 4. Made with ML Strong resource for building production ready ML products 5. Prompt Engineering Guide Useful to learn how prompt design changes output quality 6. Hands On AI Engineering Good examples of LLM apps and agent use cases 7. Awesome Generative AI Guide Curated collection of tools, learning content, and research 8. Designing Machine Learning Systems Helpful to think beyond models and focus on scale and systems 9. Machine Learning for Beginners by Microsoft Good place to start for anyone new to ML 10. LLM Course Clear roadmaps and notebooks for building with LLMs What stood out most AI agents are not just about prompts They need structure, memory, tools, workflows, and clear problem framing For anyone starting out, these repos can save a lot of time The real learning starts when you pick one repo, build something small, break it, and rebuild it better Which repo helped most in your AI journey? Want all 10 GitHub links in one place? Comment AI Agents below and I’ll send them over DM (Make sure you are commented) Prefer directly? DM me for the links. Send a connection request to stay connected. Repost for priority access #AI #AIAgents #LLM #MachineLearning #GenerativeAI #ProductManagement

Stop scrolling if you want to master AI for free. 🚀 Google just dropped 9 professional courses to level up your tech game. No cost. No gatekeeping. Just pure value. The AI Roadmap: Generative AI Essentials: Understand the "why" and "how" behind the hype. Large Language Models: Deep dive into the tech powering the tools you use daily. Responsible AI: Learn the ethics of building and using AI safely. Image Generation: Master the art of creating visuals with code. The Architecture: Break down Transformers, BERT, and Encoder-Decoder models. Whether you are a developer, a designer, or an entrepreneur, these certifications are the ultimate way to stay ahead. Which one are you starting first? Let's discuss below. 👇 #googlecloud #freecourses #ai #generativeai #techskills #learning #professionaldevelopment

No AI course will teach you this. But these blogs will. If you want to go beyond building toy apps… If you want to learn how AI is actually built, deployed, and scaled in production Start here - 1/ AI Infra & Tooling - Databricks: https://lnkd.in/gX-rAhwS - GitHub: https://lnkd.in/gryVESev - Microsoft: https://lnkd.in/gmvQVn3v - Nvidia: https://lnkd.in/g8K378ak 2/ Research & Model Development - OpenAI: https://lnkd.in/gyuMHRrE - Meta: https://ai.meta.com/blog/ - Google: https://lnkd.in/g7-kjM9K - X: https://x.ai/news 3/ Applied ML in Products - Spotify: https://lnkd.in/gc5U8j9Y - LinkedIn: https://lnkd.in/gb5XjpwH - Airbnb: https://lnkd.in/g-DHZpzY - Netflix: https://lnkd.in/gWS44qbK - Uber: https://lnkd.in/gjBHNh2g - Amazon: https://lnkd.in/gZn-4NWn These aren't tutorials. They're behind-the-scenes playbooks from teams running AI in the real world. If you want real AI skills: - Read these blogs - Build things - Repeat #AI #EngineeringBlogs