Agents are everywhere these days, but with so much information available, it’s easy to feel overwhelmed. Most tutorials and videos focus on specific frameworks without covering the fundamental principles behind these systems.

This course takes a different approach. Over four modules, you'll learn to implement the four core agentic patterns from scratch, using just Python and Groq LLMs:

* Reflection Pattern
* Tool Use Pattern
* Planning Pattern
* Multi-Agent Pattern

Explore the written lessons on my Substack blog:

https://theneuralmaze.substack.com/

Check out the code here:

https://github.com/neural-maze/agentic_patterns

––––––––––––––––––––––––––––––

If you like this content, you can also follow me here:

📩 Substack - https://theneuralmaze.substack.com/
💼 LinkedIn - https://www.linkedin.com/in/migueloteropedrido/
💻 GitHub - https://github.com/MichaelisTrofficus
🐦 Twitter - https://x.com/moteropedrido

––––––––––––––––––––––––––––––

––––––––––––––––––––––––––––––

0:00 Introduction
2:48 Module 1 - Reflection Pattern
20:40 Module 2 - Tool Pattern
44:22 Module 3 - Planning Pattern
1:13:16 Module 4 - MultiAgent Pattern
1:41:00 Conclusion

––––––––––––––––––––––––––––––
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n8n Tutorial for Beginners 2026: How to Build AI Agents
✅ self-host n8n and save tons of money with Hostinger: http://hostinger.com/youri10

In this video, I show you how to build your own AI agent in n8n from scratch, self-host it on Hostinger for unlimited executions, and automate tasks that normally waste hours every week. You’ll learn how to set up a VPS with one-click n8n installation, connect OpenAI models and memory, add real-world tools like Google Search, and turn the output into clean newsletters automatically sent to your inbox.

for inquiries: youri (at) mediaflow.group

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

Want to learn more about Agentic AI + Data? Register here → https://ibm.biz/BdeGLe

Learn more about Agentic AI + Data here → https://ibm.biz/BdeGLe

What’s the difference between generative AI and agentic AI? 🤔 Martin Keen explains how generative AI powers content creation and image generation, while agentic AI uses LLMs and chain of thought reasoning for proactive tasks like personal shopping and conference planning. Discover the future of intelligent AI collaboration! 🚀

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

#generativeai #agenticai #ai #llm

What exactly is Agentic AI? In this video, we will go through an extremely simple explanation of Agentic AI. We will compare Agentic AI systems with Workflows that use LLMs but are not agentic in nature.

00:00 Introduction
00:13 RAG Based AI System
01:06 Tool Augmented AI System
02:08 Agentic AI System
08:02 Agentic AI Apps with Code
09:31 Low Code Agentic AI
11:16 AI Agent vs Agentic AI
11:42 Gen AI vs Agentic AI

Anthropic agent guide: https://www.anthropic.com/engi....neering/building-eff
RAG and tool ammended AI system project 1: https://youtu.be/CO4E_9V6li0?si=4BhXW9c6HnPC2uww
RAG and tool ammended AI system project 2: https://youtu.be/jLM6n4mdRuA?si=oKer2d5eyixiTgF5
Agno reasoning agent: https://docs.agno.com/reasonin....g/reasoning-agents#r

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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.

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#️⃣ Social Media #️⃣

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Claude Code tutorial and guide (beginner, intermediate, advanced).

Want to go even deeper on Claude Code with hands-on help? Join my 8 day AI Coding Accelerator: https://maven.com/alpha-clarit....y/ship-with-claude-c (use code YOUTUBE for $300 off)

AI coding accelerator Scholarship Application Form: https://forms.gle/tAhxqD8TTFNrfJAj6

My complete system for starting every Claude Code project: https://youtu.be/aQvpqlSiUIQ

Want to learn even more? Check out these lightning lessons
Claude Code 101: https://maven.com/p/c513ad/cla....ude-code-101-11-mont
Claude Code 201: Skills, Plugins, MCP: https://maven.com/p/2ab172/cla....ude-code-201-skills-
——

Six months ago, I was using Claude Code all wrong. Today, I'm a Claude Code power user: I can run multiple Claude Code instances simultaneously and build a week's worth of features in just hours.

In this comprehensive guide, I share 36 specific lessons that transformed me from a Claude Code beginner to pro. These are battle-tested techniques I use daily to ship real projects faster than ever before.

Whether you're new to Claude Code or consider yourself a power user, I guarantee you'll learn something from this video that will level up your development workflow with Claude Code.

🎯 What You'll Learn:
✅ Level 1 - Beginner (Foundations):
The claude.md file that puts you ahead of 99% of users
Essential commands and bash mode mastery
Screenshot debugging and test-driven development
Message queue for non-stop productivity

✅ Level 2 - Intermediate (Workflow Enhancements):
Planning modes and think keywords for complex problems
Using Claude for research, documentation, and changelogs
GitHub Actions integration for automatic PR reviews
The product manager mindset that changes everything

✅ Level 3 - Master (Advanced Techniques):
Parallel planning with multiple solution exploration
Running multiple Claude instances with Git worktrees
Custom commands and specialized subagents
MCP servers for database and third-party integrations

🔔 ABOUT AI WITH AVTHAR
Learn how to build apps with AI coding tools, even if you're new to coding. Subscribe to learn about the best AI coding tools and how to get the most out of them. I'm Avthar Sewrathan, and I'm obsessed with AI coding tools. With a decade of tech experience and background as a startup founder and AI Product Manager, I bring you practical insights on tools like ChatGPT, Claude Code, Cursor, Replit, v0, and more.

FOLLOW AVTHAR:
YOUTUBE: https://www.youtube.com/@avtharai
X (TWITTER): https://x.com/avthars
TIKTOK: https://www.tiktok.com/@vibecoder.com

TIMESTAMPS
00:00 Claude Code: The New King of AI Coding?
02:14 Level 1: Beginner
02:29 Installation
03:37 Todo lists
04:16 Essential Commands
06:35 Debugging with Claude Code
07:57 Claude.md file
09:33 Message Queue
09:57 Markdown file prompts
10:33 Level 2: Intermediate
10:51 Planning Modes
12:10 Thinking Modes
12:58 More than Code: Research, Documents, Changelogs
15:16 Github Actions Integration
15:59 Mindset for Success with Claude Code
17:23 Level 3: Master
17:48 Parallel Subagents
18:16 Multiple Claudes (aka multi-clauding) with Git worktrees
19:30 Custom Slash Commands
20:50 Custom Subagents
22:50 MCP Server Usage
24:05 Cost and Value for Money
25:56 Conclusion: What's next?

Presented at Code w/ Claude by @anthropic-ai on May 22, 2025 in San Francisco, CA, USA.

Speakers:
Cal Rueb, Member of Technical Staff at @anthropic-ai

This is my 50 Claude Code tips from 6 months of daily use personally and at Meta as a Staff Software Engineer. I've been coding with Claude Code basically 12 hours a day really trying to understand what makes Claude Code tik. Here's everything I wish I knew when I started, from foundations to advanced parallel workflows.

⏱️ TIMESTAMPS
0:00 - Intro
1:04 - ACT 1: Foundations (Tips 1-25)
1:18 - Tip 1: Run from root directory
1:56 - Tip 2: Run /init immediately
2:54 - Tip 3: CLAUDE.md is hierarchical
3:27 - Tip 4: Keep CLAUDE.md concise
3:58 - Tip 5: Structure: What, Domain, Validation
5:36 - Keyboard Shortcuts
5:58 - Tip 6: Shift+Tab toggles modes
6:40 - Tip 7: Escape interrupts
7:43 - Tip 8: Double Escape clears input
7:59 - Tip 9: Double Escape on empty = rewind
8:29 - Tip 10: Screenshot and drag
8:44 - Tip 11: Add context to screenshots
9:09 - Essential Commands
9:41 - Tip 12: /clear resets context
10:13 - Tip 13: /context shows token usage
11:42 - Tip 14: Let auto-compaction work
12:23 - Tip 15: /model switches models
12:49 - Tip 16: /resume recovers sessions
13:21 - Tip 17: /mcp shows MCP status
14:19 - Tip 18: /help shows all commands
14:33 - Tip 19: Git is your safety net
15:24 - CLAUDE.md Deep Dive
15:52 - Tip 20: Add a Critical Rules section
17:08 - Tip 21: Ask Claude to update rules
17:46 - Tip 22: Use workflow triggers
18:27 - Tip 23: Commit CLAUDE.md to git
19:34 - Tip 24: dangerously-skip for throwaway envs
20:39 - Tip 25: Combine skip with allowlists
20:59 - ACT 2: Daily Workflow (Tips 26-32)
21:38 - Tip 26: Start features in Plan Mode
23:46 - Tip 27: Fresh context beats bloated
24:29 - Tip 28: Persist before ending sessions
25:03 - Tip 29: Lazy load context
26:09 - Tip 30: Give verification commands
27:32 - Tip 31: Consider Opus for complex work
28:18 - Tip 32: Read thinking blocks
29:01 - ACT 3: Power User (Tips 33-40)
29:34 - Tip 33: Four composability primitives
29:54 - Tip 34: Skills = recurring workflows
31:33 - Tip 35: Commands = quick shorthand
32:18 - Tip 36: Never create commands manually
33:02 - Tip 37: MCPs = external service docs
33:52 - Tip 38: Ask Claude to install MCPs
34:15 - Tip 39: Subagents = isolated context
37:10 - Tip 40: Avoid instruction overload
37:48 - ACT 4: Advanced (Tips 41-50)
38:02 - Tip 41: Run multiple instances
39:06 - Tip 42: iTerm split panes
40:33 - Tip 43: Enable notifications
41:10 - Tip 44: Git worktrees for isolation
41:40 - Tip 45: /chrome connects browser
43:17 - Tip 46: Powerful for debugging
43:28 - Hooks & Automation
43:41 - Tip 47: Hooks intercept actions
44:10 - Tip 48: Auto-format with PostToolUse
44:24 - Tip 49: Block dangerous commands
44:43 - Tip 50: Explore the plugin ecosystem
45:32 - Context is King (Outro)

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For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

October 21, 2025
This lecture covers deep reinforcement learning.

To learn more about enrolling in this course, visit: https://online.stanford.edu/co....urses/cs230-deep-lea

To follow along with the course schedule and syllabus, visit: https://cs230.stanford.edu/syllabus/

More lectures will be published regularly.
View the playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

Andrew Ng
Founder of DeepLearning.AI
Adjunct Professor, Stanford University’s Computer Science Department

Kian Katanforoosh
CEO and Founder of Workera
Adjunct Lecturer, Stanford University’s Computer Science Department

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

November 21, 2025
This lecture covers:
• LLM-as-a-judge overview
• Best practices and benefits
• Biases and pitfalls

To follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/

Chapters:
00:00:00 Introduction
00:07:08 Inter-rater agreement metrics
00:18:24 Rule-based metrics
00:21:00 METEOR, BLEU ROUGE
00:28:00 LLM-as-a-judge
00:33:44 Structured outputs
00:36:48 Variants
00:38:47 Position, verbosity, self-enhancement bias
00:47:22 Best practices
00:54:06 Factuality
01:00:15 Agent evaluation
01:23:50 Benchmarks
01:25:12 Knowledge with MMLU
01:29:34 Reasoning AIME, PIQA
01:33:57 Coding with SWE-bench
01:36:15 Safety with HarmBench
01:40:51 Agents with Tau-Bench

Afshine Amidi is an Adjunct Lecturer at Stanford University.

Shervine Amidi is an Adjunct Lecturer at Stanford University.

View the course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

Deep learning currently provides state-of-the-art performance in computer vision, natural language processing, and many other machine learning tasks. In this talk, we will learn when deep learning is useful (and when it isn't!), how to implement some simple neural networks in Python using Theano, and how to build more powerful systems using the OpenDeep package.

Our first model will be the 'hello world' of deep learning - the multilayer perceptron. This model generalizes logistic regression as your typical feed-forward neural net for classification.

Our second model will be an introduction to unsupervised learning with neural nets - the denoising auto-encoder. This model attempts to reconstruct corrupted inputs, learning a useful representation of your input data distribution that can deal with missing values.

Finally, we will explore the modularity of neural nets by implementing an image-captioning system using the the OpenDeep package.

Markus Beissinger
Recent graduate from the Jerome Fisher Program in Management and Technology dual degree program at the University of Pennsylvania (The Wharton School and the School of Engineering and Applied Science), and current Master's student in computer science. Focus on machine learning, startups, and management.

Slides: http://goo.gl/P9QGnV

Provides an intuitive explanation for what deep learning models are doing when they find an 'efficient feature representation'
Full course playlist here: https://www.youtube.com/playli....st?list=PLnrO0TOwDbu

🔵 Intellipaat AWS DevOps Course: https://intellipaat.com/aws-de....vops-certification-t
In this AWS DevOps training video, you will learn everything about AWS and DevOps from basic to advance level. This video on AWS DevOps Tutorial For Beginners includes an introduction to DevOps, AWS, why DevOps with AWS, AWS codepipeline, hands-on project, and interview preparation. This is a must-watch session for everyone who wishes to learn AWS DevOps and make a career in the cloud domain.

🔵 Read the complete DevOps tutorial here: https://intellipaat.com/blog/t....utorial/devops-tutor

#AWSDevOps #AWSDevOpsTutorialForBeginners #AWSDevOpsTraining #AWSDevopsCertification #DevopsAWS #AWSDevOpsCourse #Intellipaat

🔵 The Following are covered in this AWS DevOps video:
00:00:00 - AWS DevOps Tutorial For Beginners
00:04:58 - Introduction to Cloud Computing
00:16:24 - Cloud Computing Models
00:20:10 - Deployment Models
00:34:58 - Cloud Providers
00:41:17 - Introduction to amazon web services
01:04:03 - AWS Demo
01:28:19 - AWS Services - Storage
01:45:56 - AWS Services - Database
02:06:00 - AWS Pricing
02:13:38 - Introduction to DevOps
02:20:00 - What is DevOps?
02:23:35 - DevOps Lifecycle - How DevOps works?
02:36:00 - DevOps Tools
02:42:48 - Introduction to Git
02:44:49 - Common Git Commands
03:40:27 - What is Docker?
03:48:46 - Docker Installation
03:56:04 - Common Docker Operations
04:11:01 - Creating a Docker Hub Account
04:31:48 - Introduction to DockerFile
04:33:59 - Various Commands in DockerFile
04:50:19 - Introduction to Docker Volumes
05:16:10 - AWS CodePipeLine
06:59:03 - Netflix AWS Project
08:21:57 - AWS DevOps Certification
08:41:16 - DevOps Interview Questions

To subscribe to the Intellipaat channel & get regular updates on videos: https://goo.gl/hhsGWb

🔵 Interested to learn DevOps still more? Please check similar what is DevOps blog here: https://intellipaat.com/blog/what-is-devops/

Are you looking for something more? Enroll in our DevOps certification course and become a certified DevOps professional (https://intellipaat.com/devops....-certification-train It is a 32 hrs instructor-led DevOps training provided by Intellipaat which is completely aligned with industry standards and certification bodies.

If you’ve enjoyed this DevOps course video, Like us and Subscribe to our channel for a more similar informative video.
Got any questions about DevOps Tools? Ask in the comment section below.

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🔵 Why DevOps is important?

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🔵 Why should you opt for a DevOps career?

For very long times the development and the operations teams of any software enterprise have stayed at arm’s length. But this organizational cultural shift thanks to DevOps a lot of changes are happening in forward-thinking enterprises. Learning DevOps will help you master all the skills needed in order to successfully build, operate, monitor, measure, and improve the various processes in IT enterprises by better integrating development and operations. You will grab the best jobs in top MNCs after finishing this Intellipaat DevOps online training. The entire Intellipaat DevOps course is in line with the industry needs. There is a huge demand for DevOps certified professionals. The salaries for DevOps professionals are very good. Hence this Intellipaat DevOps tutorial is your stepping stone to a successful career!

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