In this course, you’ll master Next.js 16, the latest version of the official React framework, and learn how to build powerful, full-stack applications using its new caching and performance features. You’ll put your skills into practice by creating and deploying a Dev Event Platform, a modern app where users can browse, create, and manage events. PostHog: https://jsm.dev/devevent-posthog WebStorm: https://jsm.dev/devevent-webstorm Junie AI: https://jsm.dev/devevent-junie Warp: https://jsm.dev/devevent-warp CodeRabbit: https://jsm.dev/devevent-coderabbit CodeRabbit CLI: https://jsm.dev/devevent-coderabbitcli Cloudinary: https://jsm.dev/devevent-cloudinary The Complete Testing Course is LIVE. 🔥 Bundle up now before the deal expires and get 33% Off‼ 👉 https://jsm.dev/devevent-testing 📗 GSAP Pro Course (includes GTAVI Website): https://jsm.dev/devevent-gsap 📕 Three.js 3D Pro Course: https://jsm.dev/devevent-threejs 📙 JavaScript Pro Course: https://jsm.dev/devevent-cpjsm 🚀 Launch Your SaaS Pro Course: https://jsm.dev/devevent-saas ‼ If the links aren’t working for you, please try using a VPN (e.g., in Nigeria) 📁 FREE Video Kit (Code, Figma, Assets, Etc.): https://jsm.dev/devevent-kit 👉 Backend Pro Course Waitlist: https://jsm.dev/devevent-backpro 👉 AI Development Pro Course Waitlist: https://jsm.dev/devevent-aipro 👉 Tailwind Pro Course Waitlist: https://jsm.dev/devevent-twpro 👉 React.js Pro Course Waitlist: https://jsm.dev/devevent-reactpro 👉 React Native Pro Course Waitlist: https://jsm.dev/devevent-nativepro Rate us on TrustPilot: https://jsm.dev/trustpilot https://discord.com/invite/n6EdbFJ https://twitter.com/jsmasterypro https://instagram.com/javascriptmastery https://linkedin.com/company/javascriptmastery Business Inquiries: contact@jsmastery.pro Time Stamps: 00:00:00 — Introduction 00:04:09 — Crash Course Intro 00:08:30 — Installation 00:11:45 — Project Structure 00:14:19 — App Router 00:17:16 — React Client & Server Components 00:23:40 — Routing 00:42:42 — Data Fetching 00:48:53 — API Routes 00:52:45 — Caching 00:56:05 — Build Adapters API 00:57:24 — Metadata 01:01:23 — Theory to Practice — — — 01:02:48 — Project Setup 01:18:01 — Homepage 01:41:35 — PostHog Setup 01:50:21 — MongoDB Setup 01:52:57 — Warp Setup 01:56:46 — Database Models & Connection 02:09:36 — CodeRabbit 02:16:11 — API Routes 02:27:03 — Image Upload 02:37:51 — Fetch API Routes 02:54:47 — Event Details Page 03:14:34 — Server Actions 03:28:05 — Caching 03:39:46 — PostHog: Booking Action & Tracking 03:54:05 — Deployment 03:58:15 — Outro

This is a complete course on learning Generative ai and agentic with Langchain and Langgraph. We have included all the topics from RAG, vectorless rag, Deep agents, Guardrails, LLM Evaluation and LLM Gateways Techniques Github Links Langchain : https://github.com/krishnaik06/Langchain-V1-Crash-Course Langgraph: https://github.com/krishnaik06/Agentic-LanggraphCrash-course RAG: https://github.com/krishnaik06/RAG-Tutorials Vectorless RAG: https://github.com/krishnaik06/RAG-Tutorials/blob/main/PageIndex_Vectorless_RAG_CrashCourse%20(1).ipynb Deep Agents: https://drive.google.com/file/d/1SVjvgqvKfF-FPAIqpEZdKMQLhe13NLFD/view Guardrails : https://github.com/krishnaik06/Langchain-V1-Crash-Course/blob/main/updatedlangchain/langchain_guardrails_crash_course.ipynb LLM Evals : https://github.com/krishnaik06/RAG-Tutorials/blob/main/1-rag_evaluation.ipynb LLM Gateways: https://github.com/krishnaik06/Langchain-V1-Crash-Course/blob/main/llm_gateway_tutorial.ipynb Timestamp 00:00:00 Introduction 00:02:31 Langchain Course 02:35:12 Langraph Course 05:02:29 RAG Course 07:10:43 Vectorless RAG 08:02:11 Deep Agents 08:45:43 Guardrails 09:22:55 LLM Evaluation 10:30:25 LLM Gateways ------------------------------------------------------------------- Learn from us visit https://krishnaik.in/liveclasses

Learn to build, debug, optimize, and scale RAG systems for production. 🚀 Free Production AI Starter Kit: https://bit.ly/production-ai-pack This course teaches what tutorials skip: why 90% of RAG projects fail and how to fix them. 💻 Code, Parts 1-5: https://github.com/pdichone/production-course-main-code 💻 Code, Part 6: https://github.com/pdichone/fcc-production-rag-part-6 Paulo's channel: @vincibits ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp ⭐️ Chapters ⭐️ 0:00:00 Intro 0:01:44 Full RAG Overview 0:08:27 Development Environment Setup 0:15:35 Document Loader - Overview 0:28:27 Document Processing Pipeline - RAG Indexing Pipeline 0:48:12 Embedding Dimensions - Deep Dive 1:01:05 Hands-on - Create a Vector DB Using Chroma 1:17:48 Similarity Search with Scores 1:24:32 Building a Basic RAG System 1:33:16 Debugging RAG Systems 1:53:46 Hybrid Search 1:13:49 Token Budgeting 2:21:10 Observability - Introduction 2:29:56 LangSmith Setup 2:37:56 RAG Optimization 3:12:58 Scaling RAG Systems 3:23:35 The Real Costs of Vector Search 3:33:17 Production Hosting 3:36:00 Supabase and PGVector - Set up and Introduction 4:04:41 Three Pillars of Production Visibility 4:16:11 Production Project 4:34:36 Set up the Security Layer 4:16:11 Set up the LangGraph Agent and the FastAPI API - Testing and LangSmith Observability Dashboard 5:27:46 Test the Security Layer 5:41:36 Security Checklist 6:06:09 Advanced RAG Topics - Long Context Models vs RAG 6:14:29 Contextual Retrieval 6:24:26 Late Chunking vs Early Chunking 6:42:04 Agentic RAG - Self-Correcting Retrieval 7:04:45 GraphRAG - Multi-hop Reasoning 7:24:28 Multimodal RAG - ColPali - Vision-Based Document RAG 7:34:45 Summary - Advanced RAG (Current State) 7:37:02 RAG Evolution - Overview 7:38:35 Outro 🎉 Thanks to our Champion and Sponsor supporters: 👾 @omerhattapoglu1158 👾 @goddardtan 👾 @akihayashi6629 👾 @kikilogsin 👾 @anthonycampbell2148 👾 @tobymiller7790 👾 @rajibdassharma497 👾 @CloudVirtualizationEnthusiast 👾 @adilsoncarlosvianacarlos 👾 @martinmacchia1564 👾 @ulisesmoralez4160 👾 @_Oscar_ 👾 @jedi-or-sith2728 👾 @justinhual1290 -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

Matt will be back on stage at the World's Fair next week! see https://ai.engineer/wf and use YOUTUBEPROMO for new tickets only. Join 6000 AI engineers at the "Superbowl of AI"! --- A hands-on workshop covering the full lifecycle of AI-assisted development, from turning ambiguous requirements into agent-ready plans to running autonomous coding agents that ship production features. You'll learn to stress-test vague briefs into structured PRDs, slice work into thin "tracer bullet" vertical slices, and run an AI agent with TDD. You'll watch it select tasks, write tests, implement code, and commit. You'll then refine your prompts based on where it struggles, graduate to fully autonomous (AFK) runs, and learn to design codebases that maximize agent effectiveness. You'll walk away knowing how to: - Turn ambiguous requirements into agent-ready issues - Slice work into vertical tracer bullets an agent can grab independently - Run AI agents human-in-the-loop and autonomously with TDD - Design codebase architectures that AI agents love to work in For: Engineers ready to move beyond chat-based AI assistance and build a real workflow for shipping features with autonomous coding agents. Speaker info: - https://x.com/mattpocockuk - https://www.linkedin.com/in/mapocock/ - https://youtube.com/@mattpocockuk Timestamps: 00:00:00 - Introduction 00:00:14 - The Thesis of AI Engineering 00:04:20 - Phase 1: Research & Prototyping 00:12:45 - Phase 2: The Grill Session 00:22:10 - Phase 3: Writing the PRD 00:35:50 - Phase 4: Slicing Work into Issues 00:48:15 - Phase 5: Implementation with AI Agents 01:05:30 - Phase 6: Human-in-the-Loop Review 01:18:45 - Phase 7: Deployment & Monitoring 01:28:10 - Designing Codebases for AI Effectiveness 01:34:06 - Final Takeaways & Summary

Learn all about Claude Code. This is the ultimate guide to turning Anthropic’s Claude into a seamless part of your development workflow. Whether you're scaffolding a brand-new project or navigating a complex, multi-file codebase, this is how you code faster without sacrificing quality. 🔗 IMPORTANT LINKS 🔬 Practice with Hands-On Labs: https://kode.wiki/claude-code 🎓 Get the Full Course here: https://kode.wiki/claude-code-course ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp ⭐️ Contents ⭐️ 0:00:00 Introduction 0:00:30 Prerequisites and Initial Setup 0:09:25 Start your first session 0:23:58 Understanding Codebases with Claude 0:32:21 Installing Claude on Ubuntu Virtual Machines 0:49:34 Building a project from scratch 0:49:34 Getting project ready for public release 0:56:49 Creating Unit Tests for our Project 1:03:20 Autonomous Task Completion 1:17:11 Environment and Configuration Management 1:30:17 Managing Long Sessions Effectively 2:07:52 Writing Effective Development Prompts 2:23:39 Multi-file Project Navigation 2:32:10 Working with APIs and External Services 2:46:16 Initial Project Analysis 2:56:24 Design Pattern Implementation Review 3:05:50 SOLID Principles Evaluation 3:24:04 Error Handling & Resilience Audit 3:36:04 Exception Flow Analysis 3:52:12 Resilience & Fault Tolerance 3:53:09 Code Quality Metrics & Standards 4:02:17 Code Duplication Detection 4:12:14 Naming Conventions & Readability 4:19:23 Test Coverage & Quality Analysis 🎉 Thanks to our Champion and Sponsor supporters: 👾 @omerhattapoglu1158 👾 @goddardtan 👾 @akihayashi6629 👾 @kikilogsin 👾 @anthonycampbell2148 👾 @tobymiller7790 👾 @rajibdassharma497 👾 @CloudVirtualizationEnthusiast 👾 @adilsoncarlosvianacarlos 👾 @martinmacchia1564 👾 @ulisesmoralez4160 👾 @_Oscar_ 👾 @jedi-or-sith2728 👾 @justinhual1290 -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

Level up your system design skills! This course progresses from foundational concepts to production-ready systems, covering databases, scaling, and load balancing. Learn practical techniques for building and securing APIs, including RESTful and GraphQL. Course developed by @hayk.simonyan ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp ⭐️ Contents ⭐️ - 0:00:00 Introduction - 0:03:05 Single Server Setup - 0:07:12 Databases: SQL, NoSQL, Graph - 0:13:32 Vertical vs Horizontal Scaling - 0:16:22 Load Balancing - 0:25:08 Health Checks - 0:28:00 Single Point of Failure (SPOF) - 0:31:01 API Design - 0:47:17 API Protocols - 0:59:10 Transport Layer: TCP, UDP - 1:04:22 RESTful APIs - 1:19:04 GraphQL - 1:24:52 Authentication - 1:45:51 Authorization - 1:57:02 Security 🎉 Thanks to our Champion and Sponsor supporters: 👾 @omerhattapoglu1158 👾 @goddardtan 👾 @akihayashi6629 👾 @kikilogsin 👾 @anthonycampbell2148 👾 @tobymiller7790 👾 @rajibdassharma497 👾 @CloudVirtualizationEnthusiast 👾 @adilsoncarlosvianacarlos 👾 @martinmacchia1564 👾 @ulisesmoralez4160 👾 @_Oscar_ 👾 @jedi-or-sith2728 👾 @justinhual1290 -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

Master TypeScript from start to finish in this immersive, hands-on course. TypeScript's meteoric rise in popularity, both on the frontend and backend, has brought demand for TypeScript developers to among the highest in the industry. In this course you'll learn all the fundamentals of the language while solving real-world type challenges each step of the way. The only Prerequisite is that you have to know JavaScript. That's it! If you don't know JavaScript, we recommend you taking our JavaScript Course which is linked below. This walkthrough was recorded by @WebDevSimplified! Use code "WEBDEVSIMPLIFIED" for 25% off your first payment. Learn JavaScript - https://www.boot.dev/courses/learn-javascript Learn TypeScript - https://www.boot.dev/courses/learn-typescript Learn to code - https://www.boot.dev?promo=BOOTSTUBE Timestamps: 00:00 - Introduction 03:31 - Chapter 1 - Types 15:17 - Chapter 2 - Functions 29:58 - Chapter 3 - Unions 55:15 - Chapter 4 - Arrays 01:05:57 - Chapter 5 - Objects 01:38:55 - Chapter 6 - Tuples 01:51:29 - Chapter 7 - Intersections 02:02:02 - Chapter 8 - Interfaces 02:16:03 - Chapter 9 - Enums 02:28:46 - Chapter 10 - Type Narrowing 02:58:06 - Chapter 11 - Classes 03:12:26 - Chapter 12 - Utility Types 03:21:37 - Chapter 13 - Generics 03:39:21 - Chapter 14 - Conditional Types 04:00:38 - Chapter 15 - Local Development 04:23:19 - Outro Like & subscribe for the algo if you enjoyed the video!

Learn Python from scratch in this complete 13-hour course designed for beginners who want to build real programming confidence. Want More? 👇 - *Python Handbook* (sketches, notes, code) https://academy.datawithbaraa.com/l/digital_download/998313/the-python-handbook - *Full Package* (projects, quizzes, structure, certificate) https://www.datawithbaraa.com/course/the-ultimate-python-mastery - *Subscribe* for more Free Data content: https://www.youtube.com/channel/UC8_RSKwbU1OmZWNEoLV1tQg?sub_confirmation=1 - More *Details* and all *Links* https://www.datawithbaraa.com/wiki/python *🏆 DATA ACADEMY* - *SQL* https://www.datawithbaraa.com/course/sql-full-course-for-beginners - *Tableau* https://www.datawithbaraa.com/course/tableau-ultimate-full-course-for-beginners *🎓UDEMY* - *Python* https://www.udemy.com/course/the-complete-python-bootcamp-13hours-go-from-zero-to-hero/?referralCode=776491A4119FF8AF41CA - *SQL* https://www.udemy.com/course/the-complete-sql-bootcamp-30-hours-go-from-zero-to-hero/?referralCode=D20781228C2EB8B98339 - *Tableau* https://www.udemy.com/course/the-tableau-ultimate-course-from-zero-to-hero/?referralCode=6544726FDC491A6B25EC ━━━━━ *CONNECT WITH ME* 📬 Newsletter https://www.blog.datawithbaraa.com 👨‍💻 LinkedIn https://www.linkedin.com/in/baraa-khatib-salkini/ 📸 Instagram https://www.instagram.com/datawithbaraa/ 🎥 TikTok https://www.tiktok.com/@datawithbaraa 🌍 Website https://datawithbaraa.com/ 💬 Discord https://discord.gg/gsVJbMxKcA 🧭 Notion Roadmaps https://www.notion.com/@datawithbaraa ⭐ Favorite Books/Gear https://candle-gosling-511.notion.site/My-Favorite-Books-Gear-Apps-28334b251f1281e58a52cf7aa594e0e9?source=copy_link 📩 Sponsorships baraa@datawithbaraa.com ━━━━━ *Get 25%* OFF DataCamp's Here https://datacamp.pxf.io/bOEe66 ━━━━━ *MY FREE COURSES* - *SQL* https://youtu.be/SSKVgrwhzus - *Python* https://youtu.be/Rq5gJVxz55Q - *Tableau* https://youtu.be/UcGF09Awm4Y - *Databricks* https://www.youtube.com/playlist?list=PLNcg_FV9n7qZoxVkw-KPhcmgLWjHWVUc9 - *Power BI* https://www.youtube.com/playlist?list=PLNcg_FV9n7qZge4KDGqGtqgiuVuhVZWzu - *Data Projects* https://www.youtube.com/playlist?list=PLNcg_FV9n7qZ4Ym8ZriYT6WF8TaC2e_R7 - *Data Careers* https://www.youtube.com/playlist?list=PLNcg_FV9n7qah95jp-aPtysu7kFCbg7hd ━━━━━ 📖 TABLE OF CONTENT 00:00 Python Course Introduction 02:07 Python Learning Roadmap *CHAPTER 1 — Python Fundamentals* 05:55 What Is Python & How It Works 12:48 Installing Python 26:11 Comments & print() 26:11 Comments & print() 52:01 Variables 01:05:39 User input() 01:14:25 Python Data Types *CHAPTER 2 — Python Strings* 01:46:54 String Basics & Transformations 02:16:56 Indexing & Slicing 02:39:04 Search, Validation & Case Conversion *CHAPTER 3 — Python Numbers* 02:59:31 Integer & Float, Types, Math 03:11:33 Rounding, Random, Validation *CHAPTER 4 — Python Logic & Operators* 03:28:04 Boolean Values 03:42:33 Comparison & Logical Operators 04:06:13 Membership & Identity Operators *CHAPTER 5 — Python Conditional Statements* 04:19:19 If, Else, Elif 04:40:34 Nested & Advanced Conditions 04:57:33 Inline If & Match Case *CHAPTER 6 — Python Loops* 05:24:56 For Loops 05:47:57 Break, Continue, Pass 06:18:39 For-Else & Nested Loops 06:40:52 While Loops *CHAPTER 7 — Python Data Structures* 07:10:04 Lists Overview 07:19:40 Creating & Accessing Lists 07:48:08 Unpacking & Analyzing 08:19:18 Add, Remove & Update 08:41:46 Sorting & Combining 09:18:29 Iterables & Filtering 09:41:38 Lambda & List Comprehension 10:12:01 Tuples 10:19:59 Sets 10:38:12 Dictionaries *CHAPTER 8 — Python Functions* 11:09:45 Functions Introduction 11:28:12 Function Parameters & Return 12:20:31 Types of Python Functions 12:46:09 Writing Clean Functions This course is perfect for data analysts, data engineers, data scientists, ai engineering, developers, and students — covering everything from Python fundamentals to advanced real-world applications. #python #learnpython #ai #dataanalytics #datascience #coding

The Ash ecosystem now includes an OAuth 2 server, MCP, and Lua. When combined, they make it easy to securely and efficiently expose an existing Ash application to AI agents! Links Screen recording software I use (affiliate): https://screen.studio/@Yy75o Demo repository: https://github.com/ChristianAlexander/amber Changes from the video: https://github.com/ChristianAlexander/amber/pull/1 Ash OAuth server: https://ash-authentication-oauth2-server.hexdocs.pm Ash Lua: https://ash-lua.hexdocs.pm Elixir Lua package: https://lua.hexdocs.pm Timestamps Some context - 00:00 App demo - 01:02 OAuth 2 server - 03:38 MCP server - 06:52 Public / private fields - 11:11 Permission filtering - 12:37 Code mode - 14:47

Hermes Agent is the best AI tool out there. Here is your COMPLETE tutorial. FULL Hermes Agent bootcamp in the Vibe Coding Academy coming up: https://www.skool.com/vibe-coding-academy 2nd Youtube Channel: https://youtube.com/@AlexFinnLabsOfficial Sign up for my free newsletter: https://www.alexfinn.ai/subscribe Follow my X: https://x.com/AlexFinn Henry Intelligent Machines (my new startup): https://meethenry.ai My $300k/yr AI app: https://www.creatorbuddy.io/ Prompts: I want you to schedule a task for yourself to do every single night at 2am. It should be a micro app, UI, or system that helps us get closer to my personal goals and ambitions. It should save us time, make us more productive, or just be generally useful. Make sure this is scheduled for every single night at 2am. hermes-agent.nousresearch.com Timestamps: 0:00 Intro 1:50 What Hermes Agent is 3:13 Hermes vs OpenClaw 5:17 Hermes vs Claude Code 7:57 Hermes installation 9:28 Choosing a model 13:44 First things to do 18:02 Hermes dashboard 21:00 Hermes Kanban board 23:15 Use case 1 25:40 Use case 2 27:47 Use case 3 29:40 Memory and skills 34:30 Mission control 37:38 Troubleshooting 38:42 Security

🚀 Work with us - https://aifoundations.io/apply ✨ Join Ai Foundations - https://aifoundations.io This is the only Claude tutorial you’ll ever need. With this guide you can go from beginner to pro using Claude. I cover the basics like signing up, settings, memory, prompting and we work our way up to the intermediate features like Claude projects, artifacts, inline visualizations, data analytics and more. Then we finally dive into Claude desktop, where I teach you how to use Claude Cowork with computer use, scheduled tasks, and connectors for Notion, Gmail and Google Calendar. I even show you how to build Claude skills from scratch. After you have a beginner's understanding of Claude we dive into Claude Code. I show you how to deploy a real website in Netlify and even control Claude through a remote environment on Anthropics servers. We cover github, environment variables, pretty much everything you need, explained in beginner terms. I even cover exporting your ChatGPT memories and bringing them over to Claude. If you've been hearing about Claude AI, Claude Cowork, or Claude Code and wondering how it all fits together: this is the video you’ve been searching for. I walk through everything step-by-step leaving no stone unturned. Utilize the chapters and resources below to get the most out of this video. If it’s your first time watching, I recommend watching all the way through at least once, then coming back to spend extra time on specific chapters! Resources Mentioned: Join Ai Foundations - https://aifoundations.io DBS Framework Skill - https://aifoundations.io/resources/the-dbs-framework-skill Claude Code Mastery - https://aifoundations.io/products/claude-code-mastery Sign up for Claude - https://claude.ai Chapters: 0:00 - Claude Tutorial Intro 0:25 - How to Use This Guide 0:40 - Claude Pricing Comparison 1:22 - Sign Up for Claude 1:49 - Claude Onboarding 3:10 - Claude Chat Layout 3:50 - General Settings 4:53 - Notifications 6:00 - Claude Appearance 6:35 - Claude Voices 6:51 - Privacy and Billing 8:02 - Claude Memory 8:26 - Exporting Memories from ChatGPT 9:21 - Tool Settings 10:14 - Claude Artifact Settings 11:23 - Code Permissions 12:10 - Connector Settings 13:00 - Language Settings 13:15 - Claude Status and Support 13:50 - Gifting Claude 14:23 - Keyboard Shortcuts 14:40 - Claude Models 16:15 - Attachments and Connections 17:10 - Writing Styles in Claude 17:53 - Talking to Claude Voice 19:00 - Organizing Chats 19:40 - Incognito Chats 20:20 - GCAO Prompt Template 21:50 - Prompting Claude 24:50 - Ai Foundations Offers 25:38 - Claude Chat Search 26:34 - Claude Projects Guide 27:18 - Project Instructions 29:40 - Projects Guide Continued 30:56 - Claude Artifacts Library 32:37 - Creating Claude Artifacts 36:40 - Sharing Artifacts 37:15 - Mini App Artifacts 38:35 - Inline Visualizations 39:00 - Visualizing Data Analytics 41:15 - Claude Desktop 42:45 - Claude Cowork Setup 44:00 - Claude Quick Chat 45:00 - Cowork Settings Continued 47:00 - Organizing Files in Cowork 48:20 - Claude Computer Use 49:30 - Cowork Scheduled Tasks 51:22 - Cowork Projects 52:40 - Cowork Prospecting Project 55:00 - Claude in Chrome Extension 56:10 - Cowork Project Results 57:05 - Claude Dispatch Setup 57:50 - Cowork Connectors 58:20 - Claude Notion MCP Connector 59:30 - Using Connectors 1:00:18 - Claude Gmail Connector 1:02:40 - Claude Skills 1:04:18 - DBS Framework Skill 1:05:30 - Uploading Skills 1:06:00 - Creating a Basic Skill 1:07:36 - Testing the Recipe Skill 1:09:25 - Creating an Advanced Skill 1:10:20 - Google Calendar Connector 1:12:24 - Testing the Calendar Skill 1:13:10 - Claude Code Prerequisite 1:14:20 - Claude Code Mastery 1:15:23 - Two Ways to Use Claude Code 1:15:48 - Claude Code Environments 1:17:45 - Claude Code Models 1:18:10 - Claude Code Effort 1:18:34 - Claude Code Permissions 1:18:50 - Claude Code Enhancements 1:20:20 - Folder Setup 1:21:30 - Creating Claude MD 1:22:12 - Opening Files Quickly 1:22:31 - Building a Personal Website 1:25:15 - Planning with Claude Code 1:28:05 - Plan Mode in Claude Code 1:28:45 - Editing My Site 1:29:19 - The Complete Website 1:30:00 - Deploying with Netlify Connector 1:31:12 - Setting a Domain Name 1:31:45 - Adding Environment Variables 1:34:00 - Testing Email Connection 1:34:30 - Creating Remote Skills 1:36:18 - Github Repo Setup 1:37:00 - Initial Commit in Github 1:38:00 - Claude Code Cloud Environments 1:39:00 - Claude Code on my Phone 1:39:55 - Netlify + Github Deployment Setup 1:41:00 - Updating My Website 1:42:00 - Website Complete 1:42:20 - Claude Code Scheduled Tasks 1:44:24 - Scheduled Tasks with Skills 1:47:30 - Updating My Website from Anywhere 1:49:50 - Claude Code Terminal 1:50:30 - Claude Code Commands 1:51:10 - Claude Code Terminal Test 1:51:58 - Final Thoughts #claude #claudecowork #claudecode

This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their "psychology", and how to get the best use them in practical applications. I have one "Intro to LLMs" video already from ~year ago, but that is just a re-recording of a random talk, so I wanted to loop around and do a lot more comprehensive version. Instructor Andrej was a founding member at OpenAI (2015) and then Sr. Director of AI at Tesla (2017-2022), and is now a founder at Eureka Labs, which is building an AI-native school. His goal in this video is to raise knowledge and understanding of the state of the art in AI, and empower people to effectively use the latest and greatest in their work. Find more at https://karpathy.ai/ and https://x.com/karpathy Chapters 00:00:00 introduction 00:01:00 pretraining data (internet) 00:07:47 tokenization 00:14:27 neural network I/O 00:20:11 neural network internals 00:26:01 inference 00:31:09 GPT-2: training and inference 00:42:52 Llama 3.1 base model inference 00:59:23 pretraining to post-training 01:01:06 post-training data (conversations) 01:20:32 hallucinations, tool use, knowledge/working memory 01:41:46 knowledge of self 01:46:56 models need tokens to think 02:01:11 tokenization revisited: models struggle with spelling 02:04:53 jagged intelligence 02:07:28 supervised finetuning to reinforcement learning 02:14:42 reinforcement learning 02:27:47 DeepSeek-R1 02:42:07 AlphaGo 02:48:26 reinforcement learning from human feedback (RLHF) 03:09:39 preview of things to come 03:15:15 keeping track of LLMs 03:18:34 where to find LLMs 03:21:46 grand summary Links - ChatGPT https://chatgpt.com/ - FineWeb (pretraining dataset): https://huggingface.co/spaces/HuggingFaceFW/blogpost-fineweb-v1 - Tiktokenizer: https://tiktokenizer.vercel.app/ - Transformer Neural Net 3D visualizer: https://bbycroft.net/llm - llm.c Let's Reproduce GPT-2 https://github.com/karpathy/llm.c/discussions/677 - Llama 3 paper from Meta: https://arxiv.org/abs/2407.21783 - Hyperbolic, for inference of base model: https://app.hyperbolic.xyz/ - InstructGPT paper on SFT: https://arxiv.org/abs/2203.02155 - HuggingFace inference playground: https://huggingface.co/spaces/huggingface/inference-playground - DeepSeek-R1 paper: https://arxiv.org/abs/2501.12948 - TogetherAI Playground for open model inference: https://api.together.xyz/playground - AlphaGo paper (PDF): https://discovery.ucl.ac.uk/id/eprint/10045895/1/agz_unformatted_nature.pdf - AlphaGo Move 37 video: https://www.youtube.com/watch?v=HT-UZkiOLv8 - LM Arena for model rankings: https://lmarena.ai/ - AI News Newsletter: https://buttondown.com/ainews - LMStudio for local inference https://lmstudio.ai/ - The visualization UI I was using in the video: https://excalidraw.com/ - The specific file of Excalidraw we built up: https://drive.google.com/file/d/1EZh5hNDzxMMy05uLhVryk061QYQGTxiN/view?usp=sharing - Discord channel for Eureka Labs and this video: https://discord.gg/3zy8kqD9Cp Educational Use Licensing This video is freely available for educational and internal training purposes. Educators, students, schools, universities, nonprofit institutions, businesses, and individual learners may use this content freely for lessons, courses, internal training, and learning activities, provided they do not engage in commercial resale, redistribution, external commercial use, or modify content to misrepresent its intent.

Learn the basics of artificial intelligence. This course is for absolute beginners. This course was created by learnaianywhere.org and released to support the goals of National AI Literacy Day. You can learn more at https://learnaianywhere.org and download the resources used. For more on AI Literacy Day, check out ailiteracyday.org or their YouTube playlist: https://www.youtube.com/watch?v=vihMGH6aqTY&list=PLGhqQNp1xV3McvqOTfJmX2mAuuZqOKMEs ❤️ Try interactive AI courses we love, right in your browser: https://scrimba.com/freeCodeCamp-AI (Made possible by a grant from our friends at Scrimba) ⭐️ Contents ⭐️ - 00:00 Welcome To The Course - 01:46 Prerequisite - 02:51 Symbol Key - 03:19 Lesson 1: What is AI - Objectives - 03:35 Lesson 1: What is AI - What Is AI AI or Not: https://learnaianywhere.org/courses/ai-literacy-for-everyone/ai-or-not - 05:39 Lesson 1: What is AI - How AI Can Help Us Recap Quiz: https://learnaianywhere.org/courses/ai-literacy-for-everyone/recap-quiz-1 - 07:14 Lesson 1: What is AI - Project Time - 09:06 Lesson 2: The Key Parts of Machine Learning - Objectives - 09:27 Lesson 2: The Key Parts of Machine Learning - What is Machine Learning - 12:01 Lesson 2: The Key Parts of Machine Learning - Neuropocket Tutorial - 14:39 Lesson 2: The Key Parts of Machine Learning - AI Tools Can Make Mistake Recap Quiz: https://learnaianywhere.org/courses/ai-literacy-for-everyone/recap-quiz-2 - 16:27 Lesson 2: The Key Parts of Machine Learning - Project Time - 17:20 Lesson 3: How Do Machines Train - Objectives - 18:06 Lesson 3: How Do Machines Train - The Describer Drawer Game - 19:51 Lesson 3: How Do Machines Train - The Describer Drawer Game Demonstration - 23:07 Lesson 3: How Do Machines Train - What Is An Algorithm - 25:37 Lesson 3: How Do Machines Train - The Human Learning Algorithm - 30:25 Lesson 3: How Do Machines Train - The Machine Learning Algorithm Recap Quiz: https://learnaianywhere.org/courses/ai-literacy-for-everyone/recap-quiz-3 - 38:05 Lesson 3: How Do Machines Train - Project Time - 39:07 Lesson 4: Can Machines Be Responsible - Objectives - 39:34 Lesson 4: Can Machines Be Responsible - Bearly A Dog Challenge - 40:14 Lesson 4: Can Machines Be Responsible - What is Bias - 44:06 Lesson 4: Can Machines Be Responsible - Who is Responsible - 46:50 Lesson 4: Can Machines Be Responsible - Data Privacy - 50:46 Lesson 4: Can Machines Be Responsible - Responsible AI Recap Quiz: https://learnaianywhere.org/courses/ai-literacy-for-everyone/recap-quiz-4 - 51:20 Lesson 4: Can Machines Be Responsible - Project Time

In this episode, I sit down with Alex Finn for a full, screen-shared walkthrough of Hermes Desktop, the new desktop home for the Hermes AI agent. I open with a clear challenge: by the end, sell me on installing Hermes Desktop, show me real ways to make money and stay productive, and explain his move from OpenClaw. Alex tours every major surface — sessions, profiles, artifacts, skills, cron jobs, and sub-agents — and shares money-saving tactics at each step. We close on the idea that matters most to me: aiming these agents at other people's challenges as the clearest path to real value. Timestamps 00:00 – Intro 04:04 – Sessions and Context Management 06:10 – Profiles Explained 08:49 – Model-Based vs Role-Based Profiles 12:58 – Artifacts as a Second Brain 14:32 – Why Alex Switched From OpenClaw 17:32 – Skills, Tools, and Tool Sets 19:19 – Messaging and Cron Setup 21:44 – Reverse Prompting and the Brain Dump 28:09 – Sub-Agents vs Profiles 32:12 – Putting It Together: Solving Challenges 32:38 – The Daily Business Opportunity Scan 37:05 – Local Models: Mac Studio vs DGX Spark 39:03 – Reframing Cost as Investment 41:59 – The Real Way to Make Money With Hermes 42:51 – Closing Thoughts Key Points * Hermes Desktop pulls sessions, profiles, artifacts, skills, and cron jobs into one polished, Apple-style interface. * Smart session and context management keeps each message slim and keeps monthly costs low. * Profiles map to different models — Opus 4.8 for strategy, ChatGPT 5.5 for coding, a local Qwen model for free research — so each task runs on its best fit. * Reverse prompting plus a personal brain dump produces far stronger prompts, cron jobs, and outputs. * Sub-agents handle one skill across many parallel tasks; profiles handle work where each step needs a distinct skill set. * The biggest opportunity: aim your agent at Reddit and X to surface real problems you are positioned to solve. Numbered Section Summaries 1. The Moment Hermes Overtook OpenClaw Alex shares his screen and calls Hermes Desktop the best AI agent experience available right now, framing the recent release as the moment Hermes pulled ahead. He compares the focused, polished Hermes updates to Apple and the broader OpenClaw approach to Android, and notes his switch came purely for the love of the game. 2. Sessions and Context Management Alex shows how each new chat opens its own session, keeping context clean and separated by topic. He explains that slim context keeps every message small, and small messages keep monthly bills modest — his top money-saving tip. 3. Profiles Mapped to Models Profiles are separate Hermes agents, each with its own skills, a soul.md personality, and its own memories. Alex organizes his by model — Opus 4.8 for high-level strategy, ChatGPT 5.5 for coding, and a local Qwen model for free, fast research — and picks the profile whose strengths match the task. 4. Artifacts as a Productized Second Brain Artifacts gathers every link, image, and file you send your agent into one searchable place. Alex drops links to his "Librarian" profile and lets Artifacts file them automatically, which turns the agent into a tidy, searchable second brain. 5. Skills, Tools, and the Cron Section Alex walks the Skills interface, where 150-plus skills ship out of the box and you keep only the ones you use to trim context and cost. He highlights tool sets as a fresh way to group skills together, and praises the Cron section for giving one-click confirmation that scheduled tasks truly exist. 6. Reverse Prompting and the Brain Dump My favorite tip from Alex: brain dump everything about yourself — interests, goals, skills — then ask the agent for the best prompt to use. He demos it live by building a morning brief, and the reverse prompt returns a detailed, well-formatted instruction that pulls fresh, real headlines, prices, and scores from the last 24 hours. 7. Sub-Agents vs Profiles Alex clarifies the difference: sub-agents are copies of your main agent that share its skills, ideal for running one skill across many parallel tasks, like building several features of a micro-SaaS at once. Profiles each carry distinct skill sets and memories, ideal when a job needs a researcher, a writer, and a designer working in sequence. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com/ LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ALEX ON SOCIAL Youtube: https://www.youtube.com/@AlexFinnOfficial/videos X/Twitter: https://x.com/AlexFinnX Creator Buddy: https://www.creatorbuddy.io/

An LLM is an incredibly powerful brain that knows everything about humanity and nothing about you or the software you run. This video walks through the four buzzwords that turn that raw brain into a system you can trust: agent harness, loop engineering, LLM Ops, and eval. No jargon, step by step, technical or not. You can build anything. You can learn anything. 💪 Timeline 0:00 Intro: the 4 AI agent buzzwords 0:42 What an AI agent run actually is 1:52 The memory system: procedural, semantic, episodic 3:37 What "harness" really means (the horse) 5:07 Storing and updating memory (databases, skills, summarizer agent) 8:28 Retrieval: RAG, SQL vs semantic search 10:00 Tool calling and why agents loop 10:52 Loop engineering and end-loop guardrails 13:21 A Claude Code hooks example 14:18 Eval and LLM Ops: why you need them 15:55 Tracing every run (Langfuse, LangSmith) 16:43 Evaluation: LLM as a judge 17:20 Diagnosing what broke 18:16 The gate: ship the fix or fix the bug 18:57 Zoom out: the full system 19:53 Wrap up Launch Full-Stack App Template: https://github.com/ShenSeanChen/launch-mvp-stripe-nextjs-supabase My AI Agent Startup AutoManus.io is an AI sales lead manager for made-to-order product sales. We embed directly where conversations happen (WhatsApp, email, web chat) to capture inbound, automate follow‑ups, and kill CRM busywork; live with 4 pilots and 2 contracts in motion, pre‑seed backed by Character VC. Focused on US/UK/Germany, raising to expand engineering and scale deployments. ☕️ Buy me a coffee: https://buy.stripe.com/5kA176bA895ggog4gh - X: https://x.com/ShenSeanChen - Sean's Discord: https://discord.gg/tvECErKcFr - AutoManus Discord: https://discord.gg/5HhcNjCR - LinkedIn: https://linkedin.com/in/shen-sean-chen - Github Link: https://github.com/ShenSeanChen - Instagram: https://www.instagram.com/sean_ai_stories Sub Count when launched: 13,050 Top Github Repos - LaunchMVP NextJS,Supabase,Stripe (1015 stars): https://github.com/ShenSeanChen/launch-mvp-stripe-nextjs-supabase - ReactNextJSTips (114 stars): https://github.com/ShenSeanChen/yt-react-nextjs-tips - DeepResearchAgentBackend (70 stars): https://github.com/ShenSeanChen/yt-DeepResearch-Backend - SupabaseTipsKanban (64 stars): https://github.com/ShenSeanChen/yt-supabase-tips-kanban - RAGVectorDB (56 stars): https://github.com/ShenSeanChen/yt-rag - KimiK2Claude (37 stars): https://github.com/ShenSeanChen/yt-kimi-k2-claude - DeepResearchAgentFrontend (33 stars): https://github.com/ShenSeanChen/yt-DeepResearch-Frontend - AgenticRAG (13 stars): https://github.com/ShenSeanChen/yt-agentic-rag You Can Build Anything Playlist (Full-Stack Dev Without CS Degrees) - Core7: 95% React/NextJS Use Cases https://www.youtube.com/watch?v=vZzFlAjz4rA&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=16 - Core6: 95% Supabase Use Cases https://www.youtube.com/watch?v=Pnoq2tIif3s&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=15 - Core5: StripeNextJSSupabase https://www.youtube.com/watch?v=ad1BxZufer8&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=8 - Core4: AuthSupabaseGoogle https://www.youtube.com/watch?v=AZAU3ClAWWE&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=6 - Core3: FastapiGCPPro https://www.youtube.com/watch?v=u3sfqpzzo-U&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=5 - Core2: SupabaseHero https://www.youtube.com/watch?v=V0kmgkyPsVQ&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=4 - Core1: LaunchAnApp https://www.youtube.com/watch?v=iQ2izvGG4tQ&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=3 - Launch WhereToMeet w/ GoogleMaps, Calendar, Supabase, Cursor: https://www.youtube.com/watch?v=5xMjX1QxGUY&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=2 - Launch EncourageMe w/ Cursor, Supabase, Vercel https://www.youtube.com/watch?v=hnvL4xa2DHA&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR