Agentset

✅ Get Your FREE AI Company Operating System here: https://go.danmartell.com/3SXCfgk 👥 Are you building an AI software company? Partner with me: https://go.danmartell.com/4pjN7RP By 2030, the biggest wave of new jobs isn't going to reward people who can chat with AI. It's going to reward people who can build with it. Right now most people are still typing prompts one at a time, while a small group is quietly building AI agents that run their businesses in the background. In this video, I show you exactly how I went from doing the work to directing it, and how you can build your first AI agent this week even if you've never touched code. Watch until the end and you'll walk away with a repeatable way to think about every future agent you build. Prompts from the video: Identity files prompt: "I want to build an AI agent that runs my inbox [your AIM from previous Step]. Create its three identity files: a SOUL file, an IDENTITY file, and a USER file (about me). Ask me any questions you need to fill these in accurately, then write all three." Manager agent prompt: "You are my Manager agent. You never do any task yourself. When a job comes in, your only move is to spin up a dedicated sub-agent for that one job, hand it the task, and let it run. One agent, one lane. If a job touches on multiple areas, split it into separate sub-agents, one per area. You coordinate and report back to me." Specialist agent prompt: "Your one job is my inbox — nothing else. You never step outside the inbox." Email voice study prompt: "Connect to my email and read my last 50 sent messages. Study how I actually write — my tone, my greetings and sign-offs, how long my sentences are, the phrases I use the most. Then write a style guide that captures my voice and tone. To test it: draft a reply to my newest unread email as me, and I'll tell you what's off so you can tighten it." ▸▸ Subscribe to The Martell Method Newsletter: https://bit.ly/3XEBXez ▸▸ Get My New Book (Buy Back Your Time): https://bit.ly/3pCTG78 IG: @danmartell

🧪AI Agents Labs for Free: https://kode.wiki/3Wh4DZ6 Learn everything about AI agents from scratch in this comprehensive tutorial. No prior knowledge required. We'll take you from zero to building production-ready AI systems with hands-on labs. 🎯 What You'll Learn: • AI Fundamentals - LLMs, tokens, embeddings, and context windows • LangChain - Simplify AI development with pre-built components • Prompt Engineering - Zero-shot, few-shot, and chain-of-thought techniques • Vector Databases - Semantic search with ChromaDB and Pinecone • RAG (Retrieval Augmented Generation) - Build intelligent document search • LangGraph - Create multi-step AI workflows and agents • MCP (Model Context Protocol) - Connect AI to external tools 🔧 Hands-On Labs Include: ✓ Making your first OpenAI API calls ✓ Building semantic search engines ✓ Creating RAG systems for document retrieval ✓ Developing multi-agent workflows ✓ Integrating external tools with MCP Perfect for developers, data scientists, and anyone wanting to understand modern AI development. Follow along with free labs and build a real-world AI assistant that searches 500GB of documents in under 30 seconds. 🚨Start Your AI Journey with KodeKloud: https://kode.wiki/4qsrspX ⏰ TIMESTAMPS: 00:00 - Introduction to AI Agents 00:40 - How LLMs work in real time? 04:56 - Embeddings & Vector Representations 05:56 - How LangChain works? 10:12 - Practice Labs - Your First AI API Call 14:57 - Practice Labs - LangChain 17:57 - Prompt Engineering Techniques 21:21 - Practice Labs - Master Prompt Engineering 24:46 - Vector Databases Deep Dive 31:27 - Practice Labs - Build Semantic Search Engine 35:15 - RAG (Retrieval Augmented Generation) 38:14 - Practice Labs - RAG Implementation 42:14 - LangGraph for AI Workflows 45:51 - Practice Labs - Build Stateful AI Workflow 48:51 - Model Context Protocol (MCP) 51:56 - Practice Labs - Advanced MCP Concepts 55:21 - Conclusion 🔔 Subscribe to KodeKloud for more AI development tools and tutorials! #AiAgents #AI #Aifundamentals #LangChain #MCP #LLMs #RAG #Langgraph #vectordb #promptengineering #VectorDatabases #Tutorial #kodekloud