🖥️ Download the free AI Agents Playbook: https://clickhubspot.com/f865c2

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Summary:
AI Agents seem overwhelming, but in 2026, we've gotten to the point that any non-technical person can create and manage their own AI agents to accomplish tasks. I cover everything simply: what an agent actually is, what to automate, how to start, and build two agents step by step using two of the leading platforms. Then dive into common pitfalls and how to avoid them. This is everything you need to get started with building AI agents in 2026, no coding required.

Chapters
0:00 Intro
0:50 What is an agent?
1:37 Where we're at right now
2:08 What to automate first
4:58 How to start
7:01 Time to build
7:24 Build 1
14:04 Build 2
20:43 More complex agents
22:03 Zapier vs n8n
22:40 Common Pitfalls (and how to avoid them)
24:44 The real skill

Get the 10-Step Security PDF Checklist here: https://danieljindoo.substack.com/
Join Our Semi-Private Community: https://discord.gg/HmbPtVy6Eq
Join Operators: https://www.youtube.com/channe....l/UCz21u_dPpYlJ-XyLc

Your local AI agents setup is leaking data right now, and you probably don't even know it. Running an LLM locally doesn't automatically make it private & safe. If your machine connects to the internet, you’ve basically bought your own house and left every single window open.

In this video, I break down the 7 vulnerabilities hiding in plain sight in your local AI stack-from browser extensions reading your chats to OS telemetry and exposed servers. Whether you're using Ollama, LM Studio, or vLLM, if you handle client data or sensitive business info, you need to lock this down.

No enterprise BS. Just real implementation and the exact 10-step security checklist I use.

⏳ TIMESTAMPS:

00:00 - The "Local = Safe" Myth Debunked
00:14 - Renting vs. Owning: Levels of AI Ownership
01:09 - Why You Are Probably at Level 1 (Exposed)
01:45 - Leak 1: Exposed AI Servers & APIs
03:00 - Leak 2: Browser Extensions Reading Everything
04:10 - Leak 3: Cloud Sync Auto-Uploading Chats
05:16 - Leak 4: Malicious AI Models & Poisoned Weights
06:30 - Leak 5: OS Telemetry (Windows Recall & Mac)
07:36 - Leak 6: Legal Obligations (GDPR, HIPAA, CCPA)
09:01 - The 10-Step Local AI Security Checklist
10:07 - Download the Free Setup Guide

Got questions about securing your specific SMB stack? Drop a comment below and let's troubleshoot.

Subscribe for outcome-based AI use cases. Information is free. Trust is rare. I only show you what I've actually built.

FIND ME ON SOCIALX/Twitter:
https://x.com/Jdaniel1216/Instagram:
https://www.instagram.com/jinni_doo/LinkedIn:
https://www.linkedin.com/in/hy....oungjin-doo-a1939423
Newsletter: https://danieljindoo.substack.com/
Website: / https://doomade.com/

Local AI models/LLMs are the future. Here's how they work and how to set them up on ANY device.

FULL local LLM bootcamp in the Vibe Coding Academy: https://vibecodingacademy.dev
Sign up for my free newsletter: https://www.alexfinn.ai/subscribe
Follow my X: https://x.com/AlexFinn
My $300k/yr AI app: https://www.creatorbuddy.io/

OpenClaw:
https://openclaw.ai/

Hugging Face:
https://huggingface.co

Timestamps:
0:00 Intro
0:50 What are local models
6:16 Which computer you need
11:30 Which local models to use
13:54 Local models demos

In this video, I show you how to run a fully unrestricted and private, offline LLM directly on your own machine. If you are a cybersecurity professional, Red Teamer, or Pentester, you know the pain of getting the "I cannot help with that" error when working on legitimate security simulations or code analysis. I also show you how to set up a full private AI with RAG!

https://docs.privategpt.dev/ov....erview/welcome/intro
https://dev.to/docteurrs/insta....lling-privategpt-on-

*00:00* - Introduction to Private AI and Setup Guide
*00:56* - Understanding AI Models and Exploring Hugging Face
*01:24* - Installing Ollama for Local AI Models
*02:00* - Running Your First Local AI Model
*04:15* - Understanding what is RAG in AI
*05:05* - Setting Up Windows Subsystem for Linux (WSL) for AI
*05:24* - Private AI Setup and Installation
*10:04* - Fine-Tuning AI with Your Own Data
*10:37* - Setting Up Your Own Private GPT with RAG

Setting up Private AI on your computer
Offline AI models like ChatGPT
Enhancing job performance with Private AI
Fine-tuning AI models for specific needs
Running AI without internet
Privacy concerns with AI technologies
Surviving a zombie apocalypse with AI
Connecting knowledge bases to Private GPT
Retrieval Augmented Generation (RAG) with AI
Installing WSL for AI projects
Running LLMs on personal devices
VMware deep learning VMs
Customizing AI with VMware and Nvidia
Private GPT project setup
Leveraging GPUs for AI processing
Consulting databases with AI for accurate answers
Running local private AI in companies
Guide to private AI
Future of technology with private and fine-tuned AI

Here is the actual uncensored prompt explaining it: https://www.linkedin.com/posts/maddyhivemind_been-messing-around-with-local-uncensored-activity-7418024051081797632-myHZ?utm_source=share&utm_medium=member_desktop&rcm=ACoAADXr8m0B6M1r3WOYZgX9cWPwo96f9XA-XPk

Video Idea: https://www.youtube.com/@UC9x0AN7BWHpCDHSm9NiJFJQ

--------------------------------------------------------------------------------------------------------------------------------------------
Join the Discord: https://discord.com/servers/th....ehivemind-1235399448

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Local AI finally got good. Google's new Gemma 4 runs on a MacBook (and even on a phone) and performs about as well as the best frontier model from a year ago. Free & Offline!
In this video, I break down why local AI suddenly matters, walk through Gemma 4's real specs (not the cherry-picked charts), and test it on my M4 Pro MacBook using OpenCode, OpenClaw, and the Pi coding agent. I also rented an 80GB GPU on RunPod to try the biggest version of Gemma 4 on a more complex coding task - my own YouTube Copilot app.
If you've been wondering if it's finally time to take local AI more seriously - this video is worth a watch!

⏱ Timestamps
00:00 - How we got here
01:30 - Gemma 4
03:30 - Testing (OpenCode / OpenClaw / Pi Agent)
08:00 - Future Takeaway

🔗 Tools mentioned:
Ollama — https://ollama.com
LM Studio — https://lmstudio.ai
Google AI Edge Gallery (iOS / Android)
OpenCode, OpenClaw, Pi coding agent
RunPod (for renting GPUs)

💬 Got a more powerful machine? Running your own local setup? Drop your experience in the comments - I'd love to hear what's working for you.
👍 If this helped, smash that like button and subscribe for more hands-on AI experiments.

#LocalAI #Gemma4 #Ollama #OpenSourceAI #LLM #AI #GoogleGemma

Full video here: https://youtu.be/m0YrxLnFPzQ

Check out the full video here:
https://youtu.be/XvbVePuP7NY?si=T3PZ_UB50MmL_tVO

#SmartHome #HomeAssistant #Rhasspy

Become and AI Hero with my AI/TypeScript course:

https://www.aihero.dev/

Follow Matt on Twitter

https://twitter.com/mattpocockuk

Join the Discord:

https://mattpocock.com/discord

OpenClaw can be run for free forever using local ai models through Ollama. Models like qwen 3.5 can be setup to connect directly to Open Claw, so you won't be charged per token use like with Clade or ChatGPT.

In this video I'll show you how to setup Local Models, how to connect them to OpenClaw, and how to setup things like MCP to reduce the cost of doing large context queries or API calls.

🔶 Install MCP Tools via Zapier:
https://bit.ly/4ccnm0G

🦙 Install Ollama Setup
https://ollama.com/

The model I used for openclaw here was Qwen 3.5 however there are many other models you can use from Google, Meta, etc.

#openclaw #ollama #ai

Want to learn web design? ⭐ Check out my course! ⭐
📘 Teach Me Design - Course: https://www.enhanceui.com/

To run openclaw local models, you need to install openclaw local llm setup. This lets openclaw llm charge you only what electricity you use for your mahcine!

Llama.cpp Web UI + GGUF Setup Walkthrough and Ollama comparisons.
Check out ChatLLM: https://chatllm.abacus.ai/ltf

My USB-C portable hub: https://amzn.to/4kw0hrf
👀 My favorite external drive (dependable): https://amzn.to/3Os9Wi3
👀 Thunderbolt 4 dock: https://amzn.to/3yVRicC

⚡ *Other gear I use:* https://www.amazon.com/shop/alexziskind

▶️ M2 MacBook Air | INSTANTLY connect 4K monitors - https://youtu.be/KLI65HnvNMg
▶️ Unity on Steroids M3 Max and RTX 4090m - https://youtu.be/COpEtHzdPG0
▶️ INSANE Machine Learning on Neural Engine - https://youtu.be/Y2FOUg_jo7k
▶️ Ultimate Web Developer MacBook - https://youtu.be/72fneIUHXyY
▶️ This is what spending more on a MacBook Pro gets you - https://youtu.be/iLHrYuQjKPU

▶️ Apple Silicon and Developers Playlist - https://youtube.com/playlist?l....ist=PLPwbI_iIX3aR88m

Developer productivity Playlist - https://www.youtube.com/playli....st?list=PLPwbI_iIX3a

— — — — — — — — —

❤️ SUBSCRIBE TO MY YOUTUBE CHANNEL 📺

Click here to subscribe: https://www.youtube.com/@AZisk?sub_confirmation=1

— — — — — — — — —

📱LET'S CONNECT ON SOCIAL MEDIA

ALEX ON TWITTER: https://twitter.com/digitalix

— — — — — — — — —

Join this channel to get access to perks:
https://www.youtube.com/channe....l/UCajiMK_CY9icRhLep


⏱️ Chapters
00:00 – Local LLMs, many stacks
01:05 – Building from source
04:15 – Picking a GGUF model
07:56 – New Llama.cpp Web UI
09:06 – Ollama UI & speed check
10:44 – Ollama’s concurrency limit
11:48 – Llama.cpp parallel chats

#llm #llamacpp #macbook

CLI tools and MCP servers are different avenues in which agents can interact with external tools. See what option works best for your projects!

Subscribe to Google for Developers → https://goo.gle/developers

Speaker: Jasmyne Roberts

Want to make money and save time with AI? Join here: https://www.skool.com/ai-profit-lab-7462/about

Video notes + links to the tools 👉 https://www.skool.com/ai-profit-lab-7462/about

Get a FREE AI Course + Community + 1,000 AI Agents 👉 https://www.skool.com/ai-seo-w....ith-julian-goldie-15

Get a FREE AI SEO Strategy Session → https://go.juliangoldie.com/st....rategy-session?utm=j

Get 200+ Free AI SEO Prompts → https://go.juliangoldie.com/chat-gpt-prompts

Run Claude Code completely offline with Ollama — no usage limits, no data leaving your machine. Full setup walkthrough plus the local models that actually work.

00:00 Intro
00:39 What Claude Code Does
01:28 Why Pair It With Ollama
02:09 Install & Connect (Step-by-Step)
03:25 Critical Context Window Tip
04:14 Best Local & Cloud Models
04:58 Real Use Cases
05:38 Hidden /loop Automation Feature
06:04 Setup Tips to Avoid Frustration
06:50 Final Thoughts

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

Learn more about Large Language Models (LLMs) here → https://ibm.biz/BdpsiS

Your laptop, your AI. 💻 Cedric Clyburn explains what Llama.cpp is and how this powerful inference engine enables local LLMs with full data privacy. Discover model quantization, RAG, and how to optimize AI for small devices.

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

#llm #llama #inference #localai

Check out Brilliant Here: https://brilliant.org/AILABS/

Community with All Resources 📦: http://ailabspro.io/
Video code: V43

Browser agents are broken. Not because the models are bad, but because the entire internet was built for human eyes, not machines. WebMCP changes the approach entirely: instead of making agents better at reading websites, it makes websites better at talking to agents.

We tested it with Claude Code, built both the declarative and imperative implementations, and ran into real limitations along the way.

Here's what actually works, what doesn't, and what Google is quietly setting up with this "open standard."

Build meeting bots and desktop recording apps in hours - https://www.recall.ai/fireship gets you $100 in free credits

In today's we'll look at 7 open source AI projects you've never heard of that will help you whip your agents into shape and build highly effective slop pipelines.

#coding #programming #ai

🔖 Topics Covered
- Agency Agents
- PropmtFoo
- MicroFish
- NanoChat
- Impeccable
- Heretic
- OpenViking

Want more Fireship?

🗞️ Newsletter: https://bytes.dev
🧠 Courses: https://fireship.dev

In this video, we break down the key differences between Large Language Models (LLMs) and AI Agents.

Large Language Models like ChatGPT generate text-based responses based on training data. AI agents, on the other hand, use Large Language Models along with additional tools and capabilities to take autonomous actions - making them more versatile for achieving specific objectives.

#LLMs #AIAgents #AI #MachineLearning #AI #ArtificialIntelligence #ChatGPT #KaneAI #Claude #LamaAI#GitHubCopilot

𝐊𝐧𝐨𝐰 𝐦𝐨𝐫𝐞:
https://accounts.testmuai.com/register?utm_source=YouTube&utm_medium=Organic&utm_campaign=July11&utm_term=68FJbCYIRrg&utm_content=LT_Sign_Up

𝐄𝐱𝐩𝐥𝐨𝐫𝐞:
HOME: https://bit.ly/4uOCPKK
BLOG: https://bit.ly/4nlq87I
LINKEDIN: https://bit.ly/438HIm2
TWITTER: https://bit.ly/4eOI74s
GITHUB: https://bit.ly/4ucseJI
NEWSLETTER: https://bit.ly/4dI8Y0S
CERTIFICATIONS: https://bit.ly/4tVdw9j

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

Learn more about AI Agent Use Cases here → https://ibm.biz/Bdexeb

AI agents can reason, plan, and act autonomously to achieve complex goals. 🤖 Martin Keen highlights 10 use cases, including IoT in agriculture, RAG for content creation, and multi-agent disaster response. Explore how AI agents are transforming industries and solving real-world problems. 🚀

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

#aiagents #iot #aiusecases #multiagentsystems

Setting up a local AI model can be intimidating, which is why I created this video. In this video I will show you everything you need to know about setting up local AI models from the basics of how local AI models work, to how to optimize local AI models for your hardware, and even how to use these local AI models in real world agentic environments.


📚 Materials/References:

LM Studio: https://lmstudio.ai/
Hugging Face: https://huggingface.co/
Pi Coding Agent: https://pi.dev/


🌎 Find Me Here:

My Blog: https://blog.webdevsimplified.com/
My Courses: https://courses.webdevsimplified.com/
Patreon: https://www.patreon.com/WebDevSimplified
Twitter: https://twitter.com/DevSimplified
Discord: https://discord.gg/7StTjnR
GitHub: https://github.com/WebDevSimplified
CodePen: https://codepen.io/WebDevSimplified


⏱️ Timestamps:

00:00 - Introduction
01:08 - How Local AI Works
05:33 - Picking Models
11:46 - Configuring Your Model
21:57 - Using Local Models In Your IDE
34:17 - Using Local Models With Copilot
38:17 - Using Local Models With Pi
40:55 - Comparing Local Models to Anthropic Models


#LocalAI #WDS #AgenticCoding