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Summary:

Everyone's suddenly an expert on open source AI, and almost nobody's using the term correctly. I break down what open weights actually means, why it's not the same as open source and definitely not the same as free, and why your laptop has zero chance of running a 753 billion parameter model no matter how many browser tabs you close first.

I walk through Hugging Face, show you what's actually inside these model files, and explain the real difference between downloading a model and being able to run one. If you've heard people throw around GLM, DeepSeek or Qwen and nodded along without having a clue what any of it means, this sorts it out in non tech speak.

—— Time Stamps ——

0:00 Open Source vs Open Weight AI: Why It Matters 0:40 The Open Source Price War: Why Anthropic & OpenAI Are Scared 1:49 Claude Sonnet 5 vs GLM 5.2: Anthropic's IPO Nightmare 3:15 What Open Source Actually Means (It's Not Free) 4:48 Open Weights vs Open Source: The Taxi, Car & Kit Car Analogy 7:08 How to Download AI Models: Hugging Face Walkthrough 8:06 Inside GLM 5.2: Licenses, Safetensors & 753 Billion Parameters 10:32 Running AI Models Locally: Hardware Requirements & Quantization 11:55 American vs Chinese Open Source Models: Who's Left in the Game 13:34 Open Source AI Rankings: The Top Models Are All Chinese 14:57 Trillion-Dollar IPOs vs China's Undercut Strategy 17:58 Cost Per Intelligence: $2.75 vs 50 Cents Per Task 20:39 The AI Triage System: Which Model for Which Task 23:06 Newsletter, Webinar & How to Get Paid Teaching AI

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Summary:

Fable 5 is back on the normal Claude subscription, but only for a few days, and then it vanishes behind a genuinely eye-watering price. Which puts you in an odd spot: the smartest AI in the world is sitting in your app, and you have roughly one prompt a day to use it. So the question stops being what it can do, and becomes what on earth you should ask it. This video is my answer, built around one idea: treat it less like a chatbot and more like the Oracle of Delphi.

I walk through the method I have been using all week. Leave the mundane jobs to the cheaper models. Use one of those cheaper models to help you draft the question first, then hand the finished thing to Fable 5 in a single fully specced shot, with a safety net so it never has to come back and ask. And the questions worth your one shot are the uncomfortable ones. Where am I wasting my time. What am I avoiding. What would embarrass me if someone sharp studied my work for an hour. Big model, big questions. It turns out the hard part was never the AI.

—— Time Stamps ——

00:00 Fable Is Back: You Have Until July 7th 01:33 Fable Will Be the New Normal 02:07 Two Mistakes People Are Making With Fable 03:23 The Right Mindset: Big Model, Big Problems 04:49 Use a Dumber AI to Write Your Fable Prompts 06:34 Usage Limits & the One-Prompt Strategy 07:45 How I Use Fable: Brutal Self-Challenge Questions 09:26 The Real Skill: Asking Better Questions 10:45 Time-Sensitive: Why $20 Is Worth It Right Now 12:05 Your Homework This Weekend 13:04 Resources & Wrap-Up

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Find everything else at https://aiwithkyle.com/

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Summary:

Claude Fable 5 is being taken off the subscription tomorrow and dumped behind API pricing that would cost me thousands a day to run properly. Half my community is in mourning. I get it, because for one week Fable 5 tore through problems that had been sitting on my desk for months and did work I would once have paid three people to do. But grieving Fable 5 is fixating on the wrong thing. The real story is that what feels like science fiction this week becomes ordinary within a year, the models keep getting cheaper and faster, and that is brilliant news if you build things and rather less brilliant if you have a nine to five.

So in this one I get on with the useful part: what you actually do next. I cover why the model going away barely matters, what is coming after it, and how to run capable AI on your own machine, free and genuinely private, with nothing sitting on someone else's server. LM Studio, Ollama, Hugging Face, what the parameter counts really mean, the hardware you need before the "run Claude for free" crowd walks you off a cliff, and the small local setup I lean on every single day.

—— Time Stamps ——

0:00 Claude Fable Is Going Behind a Paywall 1:12 Fable's API Pricing: $10 In, $50 Out 2:02 One Week With Fable: Debt Payoff, Book Tools & 15 Builds 3:32 We've Seen This Movie Before: The Model Hype Cycle 4:01 GPT-5.6 Rumors: Sol, Luna & Terra Coming This Week? 5:13 AI Costs Are Collapsing Up to 900x 6:44 The Release Cycle: Anthropic, OpenAI, Google & Open Models 7:54 The Apollo Analogy: 5MB of RAM Landed on the Moon 8:51 The Big Takeaway: Your Job Is Not Safe 11:42 What to Do: Build Something You Control 13:25 Where to Start: Free Courses & Finding Demand 14:55 AI Workshops: The $1K–$3K Per Hour Opportunity 16:24 Wrap-Up: Fable Leaves, Intelligence Doesn't

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Summary:

Every week a new model lands and the same question comes with it: am I on the best one? This week alone we have GPT 5.6, Grok 4.5, a new Gemini and Fable hanging on for a few more days. My answer is to stop switching between models altogether. The model is not the system. In this beginner friendly walkthrough I show you how to get ChatGPT, Claude and Gemini working together instead of forcing yourself to pick a favourite and second-guessing it a fortnight later.

The idea is simpler than it sounds. One smart model does the planning and the reviewing, a cheaper model does the grunt work, and they share a single folder plus a few plain text instruction files so every model reads from the same page. I walk through my exact setup, from voice-briefing the planner to pushing the finished work, and why it holds up whether you are shipping code or drafting a book. Once ChatGPT, Claude and Gemini are working together like this, the next release stops being a threat and becomes a free upgrade.

—— Time Stamps ——

0:00 Fable Deadline & a Messy Week of AI Model News 0:53 Model Paralysis: Should You Switch AI Models? 2:26 The Model Is Not the System: Model-Agnostic Workflows 3:19 Planner vs Worker: The Smart Model / Dumb Model Split 4:05 The Real Cost of AI: $15,000 in One Day 5:16 Use Intelligence Where It Matters (Not Just for Coders) 6:27 GitHub Repo Setup: Your Central Source of Truth 8:14 README, Agents & Claude MD Files Explained 9:22 Let Your Smart Model Set Up the Whole Project 10:07 Connecting Claude Code & Codex with Plug-ins 11:33 Direct Connection: MCP & CLI Between AI Models 12:48 My Personal AI Workflow: Fable Plans, Codex Builds 15:02 Don't Panic: Use All the AI Models Together 16:38 Free Webinar: Teach AI to Businesses

— Useful Resources ——

Find everything else at https://aiwithkyle.com/

Stop asking ChatGPT questions, give it a job. Grab the fix kit (Free Guide): https://aiwithkyle.com/mini/chatgpt-work

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Summary:

OpenAI has released ChatGPT Work, a new work mode inside ChatGPT, and in this video I cover everything you need to know. What it actually is, how ChatGPT Work compares to Codex and Chat, and which one you should actually use depending on what you do. There is plenty of confusion out there right now, three modes, a moving model picker, and power users asking what the point is. I cut through all of it and explain why this update is aimed squarely at the billion people who use ChatGPT every day, even on the free plan.

The bigger shift is this: stop chatting with ChatGPT and start giving it jobs. Instead of asking questions and getting answers, you hand it a task, it spins up sub-agents, does the research, checks its own work, and delivers a finished result. The presentation in this video was built by ChatGPT Work itself in about twelve minutes, so you can see exactly what it produces. I also show you where to find the new work mode on web, mobile and desktop, and what to use it for in your daily work.

—— Time Stamps ——

0:00 ChatGPT Work: OpenAI's Biggest Release This Week 0:38 What Is ChatGPT Work? Why Everyone's Confused 2:12 Where to Find the Chat vs Work Toggle 2:43 Live Demo: ChatGPT Work Builds a Full Presentation 4:22 Model Selection Differences in Chat vs Work Mode 5:05 The Three Doors: Chat, Work & Codex Explained 5:56 Why This Matters: The Agentic Age for Normal Users 6:47 What Should You Actually Use ChatGPT Work For? 7:48 The Four Big Jumps in AI (Ethan Mollick's Framework) 9:57 The Power User Dilemma: ChatGPT Work vs Codex 11:51 Claude vs OpenAI: Going in Opposite Directions 13:01 Too Many Choices: Modes, Models & Effort Levels 14:08 How to Get ChatGPT Work on Desktop, Phone & Web 16:14 How to Delegate Real Jobs to AI (Prompting Still Matters)

— Useful Resources ——

Find everything else at https://aiwithkyle.com/

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Subscribe and turn on notifications to catch the next live stream: https://www.youtube.com/channel/UChlLglbHDASnoGkbjDeHnQg

Summary:

I want to talk about something that's been bothering me for weeks now. GPT 5.6 just landed, and it's not coming to you or me. It's going straight to a vetted list approved by the US government, the same thing that happened to Claude Mythos and Fable not long before it. In this one I break down what's actually in the GPT 5.6 release, how Sol and Terra compare to Mythos on the benchmarks that matter, and why the real question in 2026 isn't whether a model is smart anymore. Every model is smart now. The question is whether you're allowed to use it.

Then I get into what to actually do about it. I cover open source alternatives like GLM and Gemma, why running a model locally on your own machine has gone from a nerdy side project to a genuinely sensible backup plan, and how to start spreading your dependence across more than one provider before the next lockdown happens. If you run a business on any of these tools, this is the part you really shouldn't skip.

—— Time Stamps ——

0:00 Why I'm Disillusioned With AI for the First Time 0:51 AI Lockdowns: Fable Banned & GPT-5.6 Restricted 2:52 Meet GPT-5.6: Sol, Terra & Luna Model Family 4:16 Too Dangerous to Release: The US Government Steps In 5:44 The Benchmarks: Just as Powerful, Far More Efficient 8:39 The Real Threat: Bioweapons & Hacking Banks 9:10 The Permission Era: A New Digital Divide 10:11 The Fix: Open Weights & Open Source 10:48 Chinese Open Source Models: GLM 5.2 Max 11:41 Run Powerful AI Locally on Your Own Machine 13:12 Dario Amodei's Crusade Against Open Source 13:56 How to Set Up Local Models on Your Devices 14:27 Don't Depend on One Model (or One Country) 15:53 The New Question: Do You Even Have Access? 16:51 IPO Fallout & Final Thoughts

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Find everything else at https://aiwithkyle.com/

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Summary:

Today I'm tackling the problem nearly everyone using AI seriously eventually hits: your tools don't talk to each other. ChatGPT on your phone has no idea what Claude Code did on your desktop, and Codex on your laptop is working blind to both. I walk through how to build a vendor agnostic AI vault, a shared brain made of simple markdown files that any tool can read, so your context stops getting lost between apps. I show you how to get an AI to interview you and build the entire folder structure for you, no technical setup required, and where GitHub and Obsidian actually fit into the picture (hint: Obsidian is for you, not the AI).

If you've seen those gorgeous Obsidian graph diagrams floating around and felt like you were missing something, this clears it up. I explain why the vault, not Obsidian, is the actual brain, why GitHub is the smartest way to sync it across devices, and how to keep growing the system over time so it gets more useful the more you use it. Whether you're juggling client projects, personal life admin or a dozen half finished side builds, this gives every AI tool you use the same source of truth.

—— Time Stamps ——

0:00 The Problem: Your AI Tools Don't Share Memory 0:36 The Obsidian Vault Hype, Explained Simply 1:30 Why Your AI Context Is Scattered in 2026 2:39 What Is a Markdown File? 4:17 How Obsidian Works and Why the Vault Matters More 5:33 Structuring Your Vault: Personal, Business, Projects 6:35 Let the AI Interview You to Build It 7:14 README, AGENTS.md and CLAUDE.md Explained 9:13 Use Claude Code or Codex: The Interview Prompt 10:02 Pro Tip: Use a Microphone and Just Talk 10:38 Make It a GitHub Repo for a Durable Vault 11:47 Recap: Obsidian Is Optional, Start Now 12:27 Wrap-Up and Free Newsletter

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Find everything else at https://aiwithkyle.com/

Get AI-Ready with Kyle’s 5-Day Challenge: https://aiwithkyle.com/join

Subscribe and turn on notifications to catch the next live stream: https://www.youtube.com/channel/UChlLglbHDASnoGkbjDeHnQg

Summary:

The most advanced AI model ever released to the public, Anthropic's Fable 5, was pulled from shelves roughly 48 hours after launch. Not by Anthropic. By the US government, citing national security and export control concerns. The ban applies to all foreign nationals, meaning non-US citizens are locked out entirely. I went through the full timeline on the live: the jailbreak, the Amazon angle, David Sacks' government-side narrative, and why Dario Amodei arguably talked his own model into a ban by spending months telling everyone it was a weapon.

The more interesting question though isn't whether we get Fable back. It's what this reveals about the structure underneath all of it. You don't own your AI access. It's rented land. A government or a boardroom decision and it's gone, sometimes with 90 minutes' notice. In this one I get into what that actually means practically: local models, open source alternatives, the geopolitical chess game between the US and China, and the one skill that matters regardless of which model you're using.

—— Time Stamps ——

0:00 Fable & Mythos Banned: What Happened and Why It Matters 0:51 Background: Fable vs Mythos, Project Glasswing & the "Super Weapon" 2:58 Why People Fell in Love With Fable 5 (Expert Reactions) 7:10 The Ban Timeline: Launch, Backlash & the 90-Minute Export Order 9:52 What Triggered the Ban? Speculation & the Enforcement Problem 11:29 The David Sacks Narrative: The Government's Side of the Story 13:50 Pliny Jailbreaks Fable 5 15:15 Anthropic vs the Administration: The Standoff 17:38 The Foreign National Rule & the Digital ID Threat 20:09 Why You Should Learn Local & Open-Source Models (LM Studio Guide) 24:34 Think Bigger: The Real Skill as AI Keeps Improving 25:42 Big Open Questions: China, the IPO & AI Geopolitics 29:00 Newsletter & Webinar: Get Paid to Teach AI

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Find everything else at https://aiwithkyle.com/