"🔥Microsoft Applied Agentic AI: Systems Design & Impact - https://www.simplilearn.com/agentic-ai-course-training?utm_campaign=l_Zg237msTg&utm_medium=DescriptionFF&utm_source=Youtube
🔥AI Accelerator Program - From Prompts to Agentic Workflows - https://www.simplilearn.com/ai-accelerator-program?utm_campaign=l_Zg237msTg&utm_medium=DescriptionFF&utm_source=Youtube
🔥Microsoft Applied Generative AI and Agentic AI Specialization - https://www.simplilearn.com/microsoft-applied-ai-course?utm_campaign=l_Zg237msTg&utm_medium=DescriptionFF&utm_source=Youtube
🔥Virginia Tech Applied Agentic AI: Systems Design & Impact - https://www.simplilearn.com/vt-applied-agentic-ai-course?utm_campaign=l_Zg237msTg&utm_medium=DescriptionFF&utm_source=Youtube
🔥Michigan Engineering Generative AI Applications for Leaders - https://www.simplilearn.com/generative-ai-for-business-transformation?utm_campaign=l_Zg237msTg&utm_medium=DescriptionFF&utm_source=Youtube"

In this video on "What is Agentic AI", we explain the meaning of Agentic AI through the simple story of Emma, a small online business owner. You will see how traditional AI can provide useful ideas and answers, while Agentic AI can understand a goal, create a plan, use tools, take actions, and improve results step by step.

Emma initially uses a normal AI chatbot to get ideas for increasing her weekend sales. Although the AI suggests discounts, social media promotions, and email campaigns, Emma still has to complete every task herself. With Agentic AI, the experience changes. The AI reviews sales information, studies customer queries, identifies popular products, creates campaign plans, writes email drafts, prepares social media captions, recommends posting times, and tracks campaign performance. Simplilearn’s AI certification programs can help learners understand modern AI tools, prompt engineering, AI automation, and the safe use of AI systems in real-world situations.

Watch the complete video to understand how Agentic AI helps people move from ideas to action.

Topics covered:
1. What is Agentic AI?
2. What are AI agents
3. Traditional AI vs Agentic AI
6. AI guardrails
7. Business automation
8. Generative AI and the future of work.

Related Videos:
✅ 1. https://youtu.be/2MHjpOHQNNQ?si=a8lofxiO2g8ONByK
✅ 2. https://youtu.be/DfFoMhfYNLI?si=gxT5Dy5rUZ7OXh1l
✅ 3. https://youtu.be/ia7M-lJiTMY?si=fu8XSxaAjcLIgIaH
✅ 4. https://youtu.be/phkxmDo0TlQ?si=z900jRlscbwFu6iA
✅ 5. https://youtu.be/2R-niMsB0QY?si=UaM46S85L7vVmVoU

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out More AI Videos By Simplilearn: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_

🔥Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=l_Zg237msTg&utm_medium=Description&utm_source=Youtube
🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=l_Zg237msTg&utm_medium=Description&utm_source=Youtube

➡️ About Applied Generative AI Specialization

The Applied Gen AI Course equips learners with the skills to build AI-driven solutions. Learn to design, train, and deploy models while addressing ethics, bias, and compliance. Gain industry-relevant experience through hands-on projects to drive innovation and stay competitive in an AI-powered world.

Key Features

✅ Get a program completion certificate from Michigan Engineering Professional Education
✅ Engage in 70+ hours of live online sessions led by industry experts
✅ Access a comprehensive curriculum covering Python, AI literacy, and GenAI principles (VAEs, GANs, and LLMs)
✅ Explore agentic frameworks and create adaptive AI agents using LangChain
✅ Implement advanced prompt engineering, RAG, and fine-tune models for domain-specific AI solutions
✅ Apply best practices for AI transparency, fairness, security, and regulatory compliance
✅ Work with 12+ modern AI tools, including OpenAI, Stable Diffusion, Microsoft Copilot, and Streamlit
✅ Earn a course completion certificate hosted on the Microsoft Learn portal for Microsoft courses
✅ Experience flexible learning with session recordings
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Gain 24/7 access to Simplilearn’s Learning Management System (LMS)

Skills Covered
✅ Prompt Engineering
✅ Agentic Frameworks
✅ AI Agents
✅ LangChain for Workflow Design
✅ Retrieval Augmented Generation RAG
✅ LLM Fine Tuning
✅ Stable Diffusion
✅ Variational Autoencoders VAEs
✅ Generative Adversarial Networks GANs
✅ Attention Mechanisms
✅ Transformers
✅ GenAI Application Development
✅ LLM Benchmarking
✅ GenAI Governance
✅ AI Image Generation

👉 Enroll Now: https://www.simplilearn.com/applied-ai-course?utm_campaign=l_Zg237msTg&utm_medium=Description&utm_source=Youtube

Complete Agentic AI Course - AI Agents, RAG, Embeddings, Architectures, Framework, VectorDB & Memory #aiagents #agenticai #aiforbeginners #learnai #ai #2026

Join Our Discord Server :- https://discord.gg/2abyjxr4v6

🤖 Learn Agentic AI — AI Agents Explained (A Complete Powerful Course to Master It)

This is the most comprehensive Agentic AI course you'll find — completely FREE. We go from the absolute ground up — AI basics, LLMs, the Agent loop — all the way to Vector Databases, RAG, MCP, Multi-Agent Systems, and real architectures being used in production RIGHT NOW in 2026.

Whether you're a total beginner or someone who's used AI tools but never truly understood them — this video is built for you.

📌 WHAT YOU'LL LEARN IN THIS VIDEO:

✅ What AI actually is — and the 3 eras that brought us here
✅ How Transformers & the Attention Mechanism changed everything (2017 → now)
✅ How LLMs generate text — tokens, temperature, and context windows explained
✅ The EXACT difference between a Chatbot and a true AI Agent
✅ The Core Agent Loop (Perceive → Think → Act → Observe) broken down simply
✅ The ReAct Pattern — how agents reason before every single action
✅ Tools & Function Calling — how agents interact with the real world
✅ Memory systems — Sensory, Working, Episodic, and Semantic memory
✅ RAG (Retrieval-Augmented Generation) — the most important AI dev concept right now
✅ Vector Databases — Pinecone, Weaviate, Qdrant, Chroma & when to use each
✅ Embeddings & Semantic Search — the math made simple
✅ MCP (Model Context Protocol) — the "USB port" for AI, explained clearly
✅ 6 Agentic Architectures — ReAct, Chain-of-Thought, Plan-and-Execute, Tree of Thoughts, Reflexion & LATS
✅ Multi-Agent Systems — Orchestrator-Worker, Parallel, Debate Pattern & more
✅ Frameworks — LangChain, LlamaIndex, AutoGen, CrewAI
✅ Advanced patterns — Self-Modifying Agents, Stochastic Consensus, Iceberg Technique, 60-30-10 Cost Rule
✅ Safety & Guardrails — Prompt Injection, Scope Creep, Human-in-the-Loop & more
✅ Real-world use cases across Enterprise, Healthcare, Finance, Education & Dev
✅ A step-by-step 10-week roadmap to go from zero to building production agents

💡 Key Insight:

A chatbot reacts. An AI Agent plans, decides, acts, and adapts — all on its own. Understanding that difference is worth everything in today's AI landscape.

Related Topics :-

Agentic AI, AI agents explained, how AI agents work, what is an AI agent, AI agents 2026, learn AI agents, build AI agents, agentic AI course for beginners, AI agents for beginners, master AI agents, complete agentic AI course, AI Fundamentals, LLMs explained, AI agent loops, AI memory systems, AI tools, RAG explained, vector databases explained, Embeddings explained, MCP explained, AI architecture patterns, agentic architecture, AI frameworks and advanced patterns, multi-agent systems, AI safety, AI guardrails, tejas ai, tejas_aiz, ai 2026, 2026 etc.

- Tejas AI

Learn the essential AI concepts and basics. We will cover theory and also go over code for building agents. We will cover both no-code tools (Zapier, N8N) and coding frameworks (langchain etc.) for building agents.


Code and assignment: https://resources.codebasics.io/GPpiop

Build your first agent using Zapier: https://youtu.be/Jekzc6BM5_w?si=tHrbHGBPJ8mmJqZv

Air canada chatbot case: https://www.forbes.com/sites/m....arisagarcia/2024/02/

Codebasics AI engineering cohort: https://resources.codebasics.io/RjnPLS

⭐️ Timestamps ⭐️
0:00 Intro
1:01 What is an AI Agent?
7:48 ReAct Loop
8:19 Multi-Agent System
9:07 Multimodal Agent
10:02 Two ways of creating agents
12:30 Workflow vs Agents
13:37 Autonomy and Guardrails
16:12 Evaluation
19:38 Assignment PDF

Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description for my affordable video courses.

Need help building software or data analytics/AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website.

🎥 Codebasics Hindi channel: https://www.youtube.com/channe....l/UCTmFBhuhMibVoSfYo

#️⃣ Social Media #️⃣

🧑‍🤝‍🧑 Discord for Community Support: https://discord.gg/r42Kbuk
📸 Codebasics' Instagram: https://www.instagram.com/codebasicshub/
📝 Codebasics' Linkedin : https://www.linkedin.com/company/codebasics/
📱 Dhaval's X handle : https://x.com/dpcodebasics

------

📝 Dhaval's Linkedin : https://www.linkedin.com/in/dhavalsays/
📝 Hem's Linkedin: https://www.linkedin.com/in/hemvad/

📽️ Hem's Instagram for daily tips: https://www.instagram.com/hemvadivel/
📸 Dhaval's Personal Instagram: https://www.instagram.com/dhavalcodebasics

🔗 Patreon: https://www.patreon.com/codeba....sics?fan_landing=tru

Build your own functional AI coding agent from the ground up using Python and the free Gemini Flash API. This project-based tutorial provides a deep understanding of how powerful AI tools work by guiding you through the creation of an agentic loop powered by tool calling. You will implement the core abilities for your agent to interact with and modify a codebase, including reading files, writing to files, and executing code to get feedback.

Lane Wagner created this course.

Check out the interactive version of the course on boot.dev: https://www.boot.dev/courses/build-ai-agent-python

❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp

⭐️ Contents ⭐️
- 00:00:00 Introduction
- 00:01:14 Why Build an AI Agent?
- 00:01:49 Course Overview & What We're Building
- 00:02:25 How to Follow Along
- 00:03:47 What is an AI Agent? (Agentic Loops & Tool Calling)
- 00:06:03 The Agent's Four Tools
- 00:07:58 Prerequisites & Project Goals
- 00:10:08 Demo: Agentic vs. One-Shot Responses
- 00:13:07 Python Project Setup with UV
- 00:15:44 Getting Started with the Gemini API
- 00:19:21 Making Your First API Call
- 00:24:44 Accepting Command-Line Arguments
- 00:27:46 Managing Conversation History
- 00:30:39 Adding a Verbose Flag for Debugging
- 00:33:35 Setting Up the Project for Our Agent (Calculator App)
- 00:36:23 Building Tool #1: Get Files Info
- 00:49:39 Building Tool #2: Get File Content
- 00:58:24 Building Tool #3: Write File
- 01:05:26 Security Note: Dangers of Running AI-Generated Code
- 01:07:30 Building Tool #4: Run Python File
- 01:18:00 Understanding the System Prompt
- 01:33:10 How Tool Calling Works: Declaring Functions for the LLM
- 01:41:38 Adding All Function Declarations
- 01:49:19 Implementing the Function Calling Logic
- 01:57:30 Creating the Agentic Loop
- 02:07:11 Final Demo: Agent Fixes a Bug Autonomously
- 02:13:44 Conclusion & Next Steps

🎉 Thanks to our Champion and Sponsor supporters:
👾 Drake Milly
👾 Ulises Moralez
👾 Goddard Tan
👾 David MG
👾 Matthew Springman
👾 Claudio
👾 Oscar R.
👾 jedi-or-sith
👾 Nattira Maneerat
👾 Justin Hual

--

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://freecodecamp.org/news

Learn more: https://stanford.io/4iHlGQp

Build modern AI agents with Stanford's graduate-level curriculum, adapted for working professionals.

Taught by Stanford Adjunct Professor Chowdhery and Assistant Professor Mirhoseini, this Agentic AI program takes you beyond basic LLM prompting to agents that reason, plan, use tools, and improve themselves through interaction with their environment.

What you'll learn:
- Design agentic systems for complex, multi-step real-world tasks
- Apply test-time scaling to boost LLM performance
- Use self-improvement methods: verifiers, feedback loops, RL, and search
- Build agents that use tools and take actions effectively
- Add retrieval and long-term memory to LLMs
- Develop planning and multi-step reasoning
- Evaluate agent performance with robust frameworks

Drawing on Stanford research and the latest advances in the field.

About the Instructors
Stanford Engineering Adjunct Professor Dr. Aakanksha Chowdhery led end-to-end training of the 540B PaLM model (the largest densely trained language model in the world at the time) and drove pre-training and scaling of Gemini's mixture-of-experts models. Stanford Assistant Professor Azalia Mirhoseini co-developed the MoE architectures now used in nearly every frontier model, created AlphaChip (the RL method behind Google's TPU designs), and pioneered LLM test-time scaling; she worked on both Claude and Gemini.

Welcome to chai aur code, a coding/programming dedicated channel in Hindi language. Now you can learn best of programming concepts with industry standard practical guide in Hindi language.

All source code is available at my Github account:
https://github.com/hiteshchoudhary

Our Open-Source Project is here: https://freeapi.app

Join me at whatsapp: https://hitesh.ai/whatsapp

for community discord: https://hitesh.ai/discord

Instagram pe yaha paaye jaate h:
https://www.instagram.com/hiteshchoudharyofficial/

HTML video series: https://www.youtube.com/watch?v=XmLOwJHFHf0&list=PLu71SKxNbfoDBNF5s-WH6aLbthSEIMhMI

Complete javascript series: https://www.youtube.com/watch?v=Hr5iLG7sUa0&list=PLu71SKxNbfoBuX3f4EOACle2y-tRC5Q37

Complete Reactjs series: https://www.youtube.com/watch?v=vz1RlUyrc3w&list=PLu71SKxNbfoDqgPchmvIsL4hTnJIrtige

Javascript and react interview series: https://www.youtube.com/watch?v=1wqCyz7XrV4&list=PLu71SKxNbfoCy_MsA98SBfvUKF5eQit6L

Backend development with Javascript: https://www.youtube.com/watch?v=EH3vGeqeIAo&list=PLu71SKxNbfoBGh_8p_NS-ZAh6v7HhYqHW

Python Series: https://www.youtube.com/watch?v=Ca5DLSDfPec&list=PLu71SKxNbfoBsMugTFALhdLlZ5VOqCg2s

Checkout the roadmap: https://www.krishnaik.in/ai-roadmaps
Agentic AI involves creating autonomous systems that use Large Language Models (LLMs) to plan, reason, and act to achieve goals, rather than just generating content. To learn this, focus on mastering frameworks like LangGraph, CrewAI, and AutoGen to build multi-agent workflows, and focus on agentic RAG for data access. Key skills include planning, tool usage, and human-in-the-loop interaction.
----------------------------------------------------------------------------------
Learn from me and my team
visit : https://krishnaik.in/liveclasses

Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdbhXe

Learn more about Agentic AI here → https://ibm.biz/BdbhXb

Ever hit a wall with your biggest LLM? 🚧 Shad Griffin shows how Agentic AI, AI agents, and prompt engineering turn complex problems into smart, multi‑step solutions powered by machine learning. Discover how this workflow helps developers build more accurate AI results.

AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdbLhV

#agenticai #llm #aiagents #promptengineering #machinelearning

Learn Agentic AI using a popular framework langgraph. In this agenti ai tutorial for beginners, we will start with agentic AI basics and then we will dive deeper into langgraph by covering a wide range of topics.

👉 Check out PyCharm, the IDE built for data science and AI/ML professionals: https://jb.gg/try-pycharm-now

👉 Download PyCharm and use it for free forever, plus a one-month Pro subscription is included.

Code: https://github.com/codebasics/....langgraph-crash-cour

00:00 Introduction
00:40 Agentic AI Basics
00:00 What is Langgraph
07:41 Langchain vs Langgraph
13:08 Installation and Setup
19:00 Simple Graph
31:36 Graph with Condition
36:55 Chatbot in Langgraph
45:38 Chatbot with Tool
56:03 Memory
1:05:05 Tracing with Langsmith
1:10:11 Human in the Loop

Do you want to learn technology from me? Check https://resources.codebasics.io/rS9B09 for my affordable video courses.

Need help building software or data analytics/AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website.

🎥 Codebasics Hindi channel: https://www.youtube.com/channe....l/UCTmFBhuhMibVoSfYo

#️⃣ Social Media #️⃣

🧑‍🤝‍🧑 Discord for Community Support: https://discord.gg/r42Kbuk
📸 Codebasics' Instagram: https://www.instagram.com/codebasicshub/
📝 Codebasics' Linkedin : https://www.linkedin.com/company/codebasics/

------

📝 Dhaval's Linkedin : https://www.linkedin.com/in/dhavalsays/
📝 Hem's Linkedin: https://www.linkedin.com/in/hemvad/

📽️ Hem's Instagram for daily tips: https://www.instagram.com/hemvadivel/
📸 Dhaval's Personal Instagram: https://www.instagram.com/dhavalsays/

🔗 Patreon: https://www.patreon.com/codeba....sics?fan_landing=tru

🔥IITK - Professional Certificate Course in Generative AI and Machine Learning (India Only) - https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=yLv8kud-iAE&utm_medium=Lives&utm_source=Youtube
🔥Purdue - Post Graduate Program in AI and Machine Learning - https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=yLv8kud-iAE&utm_medium=Lives&utm_source=Youtube
🔥IITG - Professional Certificate Program in Generative AI and Machine Learning (India Only) - https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=yLv8kud-iAE&utm_medium=Lives&utm_source=Youtube
🔥Caltech - AI & Machine Learning Bootcamp (US Only) - https://www.simplilearn.com/ai-machine-learning-bootcamp?utm_campaign=yLv8kud-iAE&utm_medium=Lives&utm_source=Youtube

This video on Machine Learning Full Course video by Simplilearn, will help begin with the basics of Artificial intelligence and machine learning. This Machine Learning Full Course begins with an Introduction to Machine Learning, that helps you with a complete guide to mastering machine learning concepts and applications. It begins with an explanation of what machine learning is and offers insights into how to learn AI and ML effectively. The course includes a deep learning tutorial for beginners and introduces the best AI coding tools to boost productivity. Practical guidance on how to get a job in AI and the basics of machine learning sets the foundation for career advancement. Advanced topics like Q-learning, reinforcement learning, and LSTM (Long Short-Term Memory) are also explored. You’ll delve into linear algebra for machine learning, LLM benchmarking, and learn how to run Llama privately. Additional highlights include a stable diffusion tutorial, exploratory data analysis using Python, and tools like Meta’s new Llama 3.2. The course concludes with an in-depth look at the confusion matrix in ML, equipping you with both theoretical and practical knowledge for machine learning projects.

Following are the topics covered in this Machine Learning Full Course:
00:00:00 Introduction to Machine Learning Full Course
00:56:31 What is Machine Learning
00:58:05 How To Learn Artificial Intelligence and Machine Learning
01:12:13 Deep Learning Tutorial For Beginners
01:24:17 Best AI Coding tools
01:31:16 How to get a job in AI
04:28:15 Machine Learning Basics
04:29:05 What is Q Learning
05:19:32 Linear Algebra for Machine Learning
05:28:25 LLM Benchmarking
05:37:37 Run Lllama Privately
05:48:12 Stable diffusion tutorial
06:22:15 Exploratory Data Analysis Using Python
10:33:36 Reinforcement Learning
10:41:54 Meta New Lama 3.2
11:00:05 Confusion Matrix ML
11:06:17 What is LSTM

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Machine Learning tutorial videos: https://bit.ly/3fFR4f4

#MachineLearningCourse #MachineLearningFullCourse #MachineLearningWithPython #MachineLearningWithPythonFullCourse #MachineLearningTutorial #MachineLearningTutorialForBeginners #MachineLearning #MachineLearningTraining #Simplilearn

➡️ About Caltech Post Graduate Program In AI And Machine Learning

Designed to boost your career as an AI and ML professional, this program showcases Caltech CTME's excellence and IBM's industry prowess. The artificial intelligence course covers key concepts like Statistics, Data Science with Python, Machine Learning, Deep Learning, NLP, and Reinforcement Learning through an interactive learning model with live sessions.

Key Features

✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ PGP AI & ML completion certificate from Caltech CTME
✅ Masterclasses delivered by distinguished Caltech faculty and IBM experts
✅ Caltech CTME Circle Membership
✅ Earn up to 22 CEUs from Caltech CTME
✅ Online convocation by Caltech CTME Program Director
✅ IBM certificates for IBM courses
✅ Access to hackathons and Ask Me Anything sessions from IBM
✅ 25+ hands-on projects from the likes of Twitter, Mercedes Benz, Uber, and many more
✅ Seamless access to integrated labs
✅ Capstone projects in 3 domains
✅ 8X higher interaction in live online classes by industry experts

Skills Covered

✅ Statistics
✅ Python
✅ Supervised Learning
✅ Unsupervised Learning
✅ Recommendation Systems
✅ NLP
✅ Neural Networks
✅ GANs
✅ Deep Learning
✅ Reinforcement Learning
✅ Speech Recognition
✅ Ensemble Learning
✅ Computer Vision

👉 Learn More At: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=yLv8kud-iAE&utm_medium=Lives&utm_source=Youtube

👉 GET $500 IN FREE CREDITS (first 500 people only):
https://www.hyperagent.com/vaibhav

👉 GRAB EVERY PROMPT AND BUILD ALONG (FREE):
https://links.stayingahead.com/YT67

━━━━━━━━━━━━━━━━━━━━━━

Millions of AI agents are already working right now — and almost nobody outside
of tech knows how to build one. In this video you'll build 3 no code AI agents
in 15 minutes, including one that builds and manages an entire army of AI agents
for you. Zero coding. Nothing to install. Total cost: under $10.

Everyone learned ChatGPT and Claude. Almost nobody learned what came after it.

Here's the difference. Today you open a tab, ask a question, get an answer, close
it and tomorrow you start from zero. An AI agent doesn't work like that. You
build it once, it remembers you, and it keeps working long after you've shut the
laptop.

This is a complete no code AI agent tutorial for beginners. No developer
background needed, no terminal, no API keys pasted from a doc you don't
understand. Everything runs in your browser, on whatever laptop you already own.

WHAT YOU'RE BUILDING:

Level 1 — Your first AI agent. The simplest working version there is.
Level 2 — An AI agent that builds and manages an army of other AI agents,
running multiple jobs at the same time.
Level 3 — A fully autonomous agent that runs on its own every morning and has
a report waiting for you before you wake up.

We're using Hyperagent, built by the founder of Airtable. A normal AI forgets
everything about you the second you close the tab. This one remembers your whole
setup and keeps working on its own — less like a chatbot you re-explain yourself
to every time, more like an employee you hire once.

People are already selling agent builds like these for a couple thousand dollars.
This one cost under ten dollars to make. That's what a one person business looks
like in 2026.

━━━━━━━━━━━━━━━━━━━━━━

⏱ TIMESTAMPS
0:00 Everyone learned ChatGPT. Nobody learned this
0:40 The real question: how AI makes money
1:04 The tool that makes this possible
1:21 Free credits + all prompts
1:38 BUILD 1: The offer that brings money in
2:29 Building the wedding decor agent
3:38 One photo, three decorated venues
4:12 Saving it as a reusable agent
4:44 The pricing page that sells itself
5:16 What it actually cost: $11
5:39 BUILD 2: The agent that builds a whole company
6:53 Setting up the startup team
7:37 How it saves money mid-task
7:54 The research report
8:19 The builder and the brand
9:03 Finding 7 real customers, live
9:22 Turning it into reusable skills
9:42 Plugging into Gmail, Slack, GitHub
9:58 BUILD 3: The agent that runs it all
10:20 Setting up your always-on analyst
11:52 The agent that grades itself
12:12 Your daily report, built automatically
12:45 The whole one person business
13:01 Claim your credits

━━━━━━━━━━━━━━━━━━━━━━

❓ QUESTIONS PEOPLE ASK

Do I need to know coding to build an AI agent?
No. Every build in this video is no code. Nothing gets installed and nothing runs
locally.

What is an AI agent, in simple terms?
A normal AI answers one question and forgets you. An agent is set up once, keeps
your context, and keeps working on its own without being prompted again.

Is Hyperagent free?
No, it's a paid tool. The first 500 people through the link get $500 in credits,
which covers everything built in this video.

Can I sell AI agents I build?
People are charging a couple thousand dollars for builds like these. The video
shows exactly what goes into one.

━━━━━━━━━━━━━━━━━━━━━━

#AIAgents #NoCodeAI #AIAutomation #AITutorial #Hyperagent

--------

To Know More,
Follow Vaibhav Sisinty On ⤵︎

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https://www.linkedin.com/in/vaibhavsisinty

Deploy your site using here.now completely for free, copy the prompt for your agent here! https://here.now/r/twt

In this complete guide, I walk you through the best local agentic coding workflow using LM Studio and VS Code - no API keys, no cloud, no cost per token.You'll learn how to install and configure LM Studio, choose and run the right local models for coding, and connect everything to VS Code so you can use AI-powered agents directly in your editor. This is the exact setup I use for local AI coding that actually works.

Want to make real money with coding? I share high-signal insights on careers, monetization, and leverage in my free newsletter. Join here and get my guide How to Make Money With Coding instantly: https://techwithtim.net/newsletter

🚀 Tools I Use
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Openclaw setup: https://www.hostinger.com/techwithtim
VPS setup: https://www.hostinger.com/techwithtim10
Wispr Flow (Best AI Dictation): https://ref.wisprflow.ai/TechWithTim-jun26

🎞 Video Resources 🎞
Presentation in This Video: https://clever-mirage-d82v.here.now/
LM Studio Download: https://lmstudio.ai/
VSCode Download: https://code.visualstudio.com/

⏳ Timestamps ⏳
00:00 | Overview
00:46 | What are Local Models
02:30 | VRAM & Computer Hardware
05:18 | Memory & Model Speed
06:39 | How to Pick a Model
11:10 | Trying It Live
12:23 | LM Studio Setup & Model Download
22:15 | Using Local Models in VS Code
28:43 | Autocomplete Model Setup

Hashtags
#LMStudio #AICoding #AIDevTools

UAE Media License Number: 3635141

GStack is an open-source toolkit built by YC President & CEO Garry Tan that turns Claude Code into an AI engineering team — with skills for office hours, design, code review, QA, and browser testing.

Use it with Claude Code or Codex or Cursor. It's free and open source: https://github.com/garrytan/gstack

In this video, Garry walks through how GStack works, starting with Office Hours, a skill modeled after real YC partner sessions that pressure-tests your idea before you write a line of code. He demos it live, going from idea through adversarial review, design mockups, and automated QA in a single session.

00:00 – AI Just Changed Coding Forever
00:09 – From YC to Building With AI
01:07 – Why AI Coding Feels So Different
02:45 – Turning AI Into a Real Team (GStack)
03:45 – Let’s Build an App Live
05:23 – The Question That Kills Most Ideas
07:13 – This Idea Just Got Way Bigger
08:38 – The “Feels Illegal” AI Hack
10:50 – Upgrading the Idea in Real Time
12:44 – Breaking + Fixing the Plan
14:25 – AI Designs the App
16:59 – The Full System Explained
18:00 – Running Multiple AI Engineers
20:00 – Shipping 10x Faster
21:20 – The Only Thing That Matters Now

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Work at a startup: https://www.ycombinator.com/jobs

https://www.conductor.build/

Everyone is talking about AI agents and almost nobody can tell you what one actually is. Ask someone to explain the difference between an agent and ChatGPT and you get hand-waving. In this video I explain every single piece of a real AI agent in plain English — and then prove it by building one from scratch, live, using open source tools.

Want to LEARN how to build useful AI agents that actually get things done? Go here: https://aiagentbuilders.co/yt

How to Make Money With Coding instantly: https://techwithtim.net/newsletter

🚀 Tools I Use
Get 10% off with code techwithtim
Openclaw setup: https://www.hostinger.com/techwithtim
VPS setup: https://www.hostinger.com/techwithtim10
Wispr Flow (Best AI Dictation): https://ref.wisprflow.ai/TechWithTim-aug26

🎞 Video Resources 🎞
TrueForge Github : https://github.com/truefoundry/trueforge
TrueForge Docs: https://trueforge.dev/introduction
TrueForge Benchmarking Article : https://www.truefoundry.com/bl....og/engineering/truef

⏳ Timestamps ⏳
00:00 | Overview
01:07 | AI Model vs AI Agent
02:27 | 1. Harness
03:40 | 2. MCP Servers
04:45 | 3. Skills
05:36 | 4. Sandbox
06:41 | 5. The Production Layer
08:03 | Building Agents
16:55 | Deploying an Agent
17:52 | Benchmarks & Speed

Hashtags
#AIAgents #HowAIWorks #TrueForge

UAE Media License Number: 3635141

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

A friendly introduction to Bayes Theorem and Hidden Markov Models, with simple examples. No background knowledge needed, except basic probability.
Accompanying notebook:
https://github.com/luisguiserrano/hmm

🔥Enroll for Agentic AI Course: https://intellipaat.com/agenti....c-ai-systems-design-

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Master the future of AI with this complete Agentic AI Full Course for Free 2026 covering AI Agents, LangChain, RAG, Embeddings, MCP, Large Language Models, and Agentic AI Design Patterns. This course is designed for beginners, developers, and AI enthusiasts who want to understand how autonomous AI systems work and how modern AI applications are built. 🚀

In this Agentic AI Full Course for Free 2026, you’ll learn the difference between Generative AI and Agentic AI, explore powerful AI frameworks, and understand concepts like embeddings, LLMs, RAG Agents, and Model Context Protocol through detailed explanations. The course follows a practical learning approach to help you build a strong foundation in AI engineering and intelligent automation.

Whether you want to start your AI journey, upgrade your development skills, or explore the next generation of AI systems, this Agentic AI Full Course for Free 2026 gives you a complete roadmap to mastering AI agents and real-world AI workflows. Don’t forget to like, share, and subscribe for more AI tutorials and tech content.

📖 Below are the concepts covered in the video on "Agentic AI Full Course":
00:00:00 – Introduction to Agentic AI Course
00:01:18 – Generative AI vs Agentic AI
00:10:57 – What is a Generative AI System?
01:03:48 – What is LangChain
01:23:32 – AI Agents
01:41:50 – Agentic AI Design Patterns
02:33:37 – Agentic Frameworks & Basics
04:34:25 – Embeddings
05:05:53 – Large Language Model
06:54:04 – RAG Agent
07:52:06 – Model Context Protocol

#agenticai #artificialintelligence #ai #machinelearning #datascience #aitrends #futureofai #aiagents #langchain #intellipaat


➡️ About the Course
The Agentic AI Systems & Design course by Intellipaat is an advanced program focused on building autonomous AI agents that can plan, reason, and execute tasks using tools like APIs, coding environments, and web search. Unlike traditional Generative AI courses, this program goes beyond prompt-based outputs and teaches you how to design production-grade AI systems capable of independent decision-making and complex problem-solving. It is ideal for professionals such as data scientists, AI/ML engineers, and developers who want to move from basic AI usage to creating intelligent, real-world applications powered by agentic workflows

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▶️ Intellipaat Achievers Channel: https://www.youtube.com/@intellipaatachievers

📚For more information, please write back to us at [email protected] or call us at IND: +91-7022374614 / US : 1-800-216-8930

Thanks to Microsoft for sponsoring this video! Submit your #CodingWithCopilot stories so I can review them! I'm excited to check out more!

Today I'll be showing you how to build local AI agents using Python. We'll be using Ollama, LangChain, and something called ChromaDB; to act as our vector search database. All of this will be local and free to run.

🎞 Video Resources 🎞
Code in this Video: https://github.com/techwithtim/LocalAIAgentWithRAG
Ollama Library: https://ollama.com/library
Download Ollama: https://ollama.com/
Virtual Environments Video: https://www.youtube.com/watch?v=Y21OR1OPC9A
Ollama Video: https://www.youtube.com/watch?v=UtSSMs6ObqY&t=1s

⏳ Timestamps ⏳
00:00 | Video Overview
00:34 | Project Demo
02:02 | Python Setup/Installation
04:33 | Ollama Setup
07:14 | GitHub Copilot
08:22 | Local LLM Usage
14:52 | Vector Store Database Setup
23:24 | Connecting LLM & Vector Store

#sponsored

🔥DevOps Engineer Masters Program: https://www.edureka.co/masters....-program/devops-engi

In this video, *DevSecOps Interview Questions and Answers* , we’ll cover the essential DevSecOps Interview Questions and Answers to help you excel in any DevSecOps role. From foundational security principles to advanced DevSecOps practices, we tackle questions about integrating security into CI/CD pipelines, container security, vulnerability management, and key tools like Docker, Kubernetes, and security scanners. You'll not only learn how to craft compelling answers but also understand the critical reasoning behind them, equipping you to stand out in your interviews. Whether you’re new to DevSecOps or a seasoned professional, this video is your ultimate guide to mastering DevSecOps interviews. Don’t forget to like, share, and subscribe for more insightful content!

✅ 02:28 - Use Case
✅ 08:04 - Why DevSecOps?
✅ 08:50 - What is DevSecOps & What is stands for?
✅ 10:09 - What are the benefits of DevSecops?
✅ 11:12 - DevSecOps vs. DevOps
✅ 14:37 - What are the Components of DevSecOps?
✅ 16:07 - What are the best practices of DevSecOps?
✅ 17:24 - What are common DevSecOps tools?
✅ 18:39 - What are the challenges of implementing DevSecOps?
✅ 19:42 - DevSecOps Culture
✅ 20:51 - How does DevSecOps work?

✅Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

📝Feel free to share your comments below.📝

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- - - - - - - - - - - - - -
What is the difference between DevSecOps vs DevOps?


DevOps and DevSecOps share the goal of streamlining software delivery, but they differ in their focus and approach. DevOps emphasizes collaboration between development and operations teams to ensure fast and reliable software delivery. Security in DevOps is often treated as a separate phase or addressed later in the development lifecycle. In contrast, DevSecOps integrates security into every stage of the DevOps process, adopting a ""shift-left"" approach where security is a shared responsibility across development, security, and operations teams.
- - - - - - - - - - - - - -

Who should take this course:

Software Developers looking to streamline development and deployment.
IT Operations Professionals wanting to integrate with development teams.
QA Engineers seeking to automate testing within CI/CD pipelines.
System Administrators interested in managing infrastructure as code.
DevOps Enthusiasts eager to learn the latest tools and practices.
Students/Freshers wanting to start a career in IT and DevOps.
- - - - - - - - - - -- - - - --

Prerequisites for DevOps Course:

Basic programming knowledge (Python, Java, etc.)
Understanding of Linux/Unix systems
Familiarity with version control (Git)
Basic networking concepts
Awareness of cloud platforms (AWS, Azure, etc.)
Knowledge of the software development lifecycle
Willingness to learn and adapt.


For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US & Others: +18885487823 (toll-free)

Join My Community to Level Up ➡ https://www.skool.com/earlyaidopters/about

🚀 Gumroad Link to Assets in the Video: https://markkashef.gumroad.com..../l/agenticdesignpatt

Work With Us: https://www.promptadvisers.com/

🎬 Core Video Description

What if you could learn the 20 agentic design patterns the pros actually use—without wading through a 400-page manual? In this practical 63-minute breakdown, I translate a Google engineer’s book into plain English and show you exactly how to apply each pattern in real workflows. You’ll see where each architecture shines, the tradeoffs that matter (cost, latency, failure modes), and quick ways to combine patterns for robust systems—so you can ship reliable agents faster and avoid over-engineering rabbit holes. Expect concise TL;DRs, labeled visuals, and a free repo packed with diagrams, ASCII flows, and Mermaid files to help you implement immediately.

[Main Topic]: A practical, plain-English guide to 20 agentic design patterns

[Key Benefits or Outcomes]: Understand when/why to use each pattern, reduce hallucinations and cost, add safety/quality gates, route work across models/agents, and ship production-ready automations with fewer retries and rollbacks

[Tools or Techniques Covered]: Prompt chaining, routing, parallelization, reflection loops, tool use, planning/orchestration, multi-agent collaboration, memory management, learning/feedback, goal tracking, exception handling, human-in-the-loop, RAG, inter-agent comms, resource-aware model routing, reasoning strategies (CoT/ToT, debate), evaluation & monitoring, guardrails/safety, prioritization, exploration/discovery

⏳ TIMESTAMPS:
00:00 – Intro: Why agentic patterns separate pros from beginners
00:36 – What you’ll get: TL;DRs, visuals, free resources
00:54 – Pattern 1: Prompt Chaining (assembly-line steps & validations)
05:42 – Pattern 2: Routing (smart triage to specialist agents)
09:30 – Pattern 3: Parallelization (split, normalize, merge)
13:16 – Pattern 4: Reflection (critic → revise → pass)
15:51 – Pattern 5: Tool Use (discover, authorize, execute, fallback)
18:19 – Pattern 6: Planning (milestones, dependencies, constraints)
20:49 – Pattern 7: Multi-Agent Collaboration (manager + roles + shared memory)
23:45 – Pattern 8: Memory Management (short/episodic/long-term, retrieval)
26:42 – Pattern 9: Learning & Adaptation (feedback → prompts/policies/tests)
29:17 – Pattern 10: Goal Setting & Monitoring (KPIs, drift, course-correct)
31:34 – Pattern 11: Exception Handling & Recovery (classify, backoff, fallbacks)
34:11 – Pattern 12: Human-in-the-Loop (review cues & approvals)
36:01 – Pattern 13: Retrieval (RAG): parse, chunk, embed, rerank
38:14 – Pattern 14: Inter-Agent Communication (protocols, IDs, expiry)
43:08 – Pattern 15: Resource-Aware Optimization (route by cost/complexity)
46:35 – Pattern 16: Reasoning Techniques (CoT, ToT, self-consistency, debate)
49:57 – Pattern 17: Evaluation & Monitoring (golden sets, SLAs, drift)
52:44 – Pattern 18: Guardrails & Safety (PII, injection, sandboxing)
56:04 – Pattern 19: Prioritization (value×effort×urgency×risk, re-order)
59:29 – Pattern 20: Exploration & Discovery (map space, cluster, probe)
62:17 – Free Repo & Diagrams (ASCII + Mermaid)
63:08 – Final CTA: Share, comment, and join the community

#AgenticAI #AIAgents #PromptEngineering #RAG #LLMEngineering #Automation #MCP #AIDesignPatterns #Evaluation #Guardrails #Routing #Parallelization #Reflection #AIforBusiness #WorkflowAutomation