AI with Kyle - Daily AI News and Updates

Read the full issue: https://aiwithkyle.com/ai-news/i-ll-stop-soonGet AI-Ready with Kyle’s 5-Day Challenge: https://aiwithkyle.com/joinSubscribe and turn on notifications to catch the next live stream: https://www.youtube.com/channel/UChlLglbHDASnoGkbjDeHnQgSummary: 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 7th01:33 Fable Will Be the New Normal02:07 Two Mistakes People Are Making With Fable03:23 The Right Mindset: Big Model, Big Problems04:49 Use a Dumber AI to Write Your Fable Prompts06:34 Usage Limits & the One-Prompt Strategy07:45 How I Use Fable: Brutal Self-Challenge Questions09:26 The Real Skill: Asking Better Questions10:45 Time-Sensitive: Why $20 Is Worth It Right Now12:05 Your Homework This Weekend13:04 Resources & Wrap-Up— Useful Resources ——Find everything else at https://aiwithkyle.com/

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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 Matters0:40 The Open Source Price War: Why Anthropic & OpenAI Are Scared1:49 Claude Sonnet 5 vs GLM 5.2: Anthropic's IPO Nightmare3:15 What Open Source Actually Means (It's Not Free)4:48 Open Weights vs Open Source: The Taxi, Car & Kit Car Analogy7:08 How to Download AI Models: Hugging Face Walkthrough8:06 Inside GLM 5.2: Licenses, Safetensors & 753 Billion Parameters10:32 Running AI Models Locally: Hardware Requirements & Quantization11:55 American vs Chinese Open Source Models: Who's Left in the Game13:34 Open Source AI Rankings: The Top Models Are All Chinese14:57 Trillion-Dollar IPOs vs China's Undercut Strategy17:58 Cost Per Intelligence: $2.75 vs 50 Cents Per Task20:39 The AI Triage System: Which Model for Which Task23:06 Newsletter, Webinar & How to Get Paid Teaching AI
— Useful Resources ——
Find everything else at https://aiwithkyle.com/

Get AI-Ready with Kyle’s 5-Day Challenge: https://aiwithkyle.com/joinSubscribe and turn on notifications to catch the next live stream: https://www.youtube.com/channel/UChlLglbHDASnoGkbjDeHnQgSummary: 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 Matters0:40 The Open Source Price War: Why Anthropic & OpenAI Are Scared1:49 Claude Sonnet 5 vs GLM 5.2: Anthropic's IPO Nightmare3:15 What Open Source Actually Means (It's Not Free)4:48 Open Weights vs Open Source: The Taxi, Car & Kit Car Analogy7:08 How to Download AI Models: Hugging Face Walkthrough8:06 Inside GLM 5.2: Licenses, Safetensors & 753 Billion Parameters10:32 Running AI Models Locally: Hardware Requirements & Quantization11:55 American vs Chinese Open Source Models: Who's Left in the Game13:34 Open Source AI Rankings: The Top Models Are All Chinese14:57 Trillion-Dollar IPOs vs China's Undercut Strategy17:58 Cost Per Intelligence: $2.75 vs 50 Cents Per Task20:39 The AI Triage System: Which Model for Which Task23:06 Newsletter, Webinar & How to Get Paid Teaching AI— Useful Resources ——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: 
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 Time0:51 AI Lockdowns: Fable Banned & GPT-5.6 Restricted2:52 Meet GPT-5.6: Sol, Terra & Luna Model Family4:16 Too Dangerous to Release: The US Government Steps In5:44 The Benchmarks: Just as Powerful, Far More Efficient8:39 The Real Threat: Bioweapons & Hacking Banks9:10 The Permission Era: A New Digital Divide10:11 The Fix: Open Weights & Open Source10:48 Chinese Open Source Models: GLM 5.2 Max11:41 Run Powerful AI Locally on Your Own Machine13:12 Dario Amodei's Crusade Against Open Source13:56 How to Set Up Local Models on Your Devices14:27 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
— Useful Resources ——
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: 
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 Memory0:36 The Obsidian Vault Hype, Explained Simply1:30 Why Your AI Context Is Scattered in 20262:39 What Is a Markdown File?4:17 How Obsidian Works and Why the Vault Matters More5:33 Structuring Your Vault: Personal, Business, Projects6:35 Let the AI Interview You to Build It7:14 README, AGENTS.md and CLAUDE.md Explained9:13 Use Claude Code or Codex: The Interview Prompt10:02 Pro Tip: Use a Microphone and Just Talk10:38 Make It a GitHub Repo for a Durable Vault11:47 Recap: Obsidian Is Optional, Start Now12:27 Wrap-Up and Free Newsletter
— Useful Resources ——
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 Matters0:51 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 Order9:52 What Triggered the Ban? Speculation & the Enforcement Problem11:29 The David Sacks Narrative: The Government's Side of the Story13:50 Pliny Jailbreaks Fable 515:15 Anthropic vs the Administration: The Standoff17:38 The Foreign National Rule & the Digital ID Threat20:09 Why You Should Learn Local & Open-Source Models (LM Studio Guide)24:34 Think Bigger: The Real Skill as AI Keeps Improving25:42 Big Open Questions: China, the IPO & AI Geopolitics29:00 Newsletter & Webinar: Get Paid to Teach AI
— Useful Resources ——
Find everything else at https://aiwithkyle.com/

Hand big work to AI without getting burned (Free Guide): https://aiwithkyle.com/mini/fable-commissioning
Get AI-Ready with Kyle’s 5-Day Challenge: https://aiwithkyle.com/join
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Summary: 
Claude Fable 5 and Mythos are here, and they've quietly split the AI world in two. In this episode I break down exactly what these models are, why most people are only getting Fable and not Mythos, and what the June 22nd deadline actually means for your access. The hierarchy has shifted: it no longer goes Opus, Sonnet, Haiku. There's a new tier above all of that, and it costs significantly more than your current subscription.The uncomfortable truth is that $200 a month now puts you in the lower class of AI user. The models capable of genuinely transformative work are heading toward pay-per-use pricing at roughly $40 an hour, and only businesses with serious cash flow will run them at scale. I cover what this bifurcation means practically, who it affects, and how to get the most out of Fable while you still have free access. 
—— Time Stamps ——
0:00 This Week in AI: Mythos, Fable 5 & the IPO News1:20 First Impressions: Why Fable 5 Feels Like a Step Change3:13 Prompting vs. Commissioning: A New Way to Work With AI4:55 The Backstory: "Most Dangerous Model," Glasswing & the IPO6:13 The New Model Hierarchy: Where Fable Fits7:00 Safeguards: Why Biomedical Researchers Got Cut Off7:50 Ethan Mollick's Isochronic Map: What Fable Can Really Do9:02 AI as a $40-an-Hour Employee & the Impact on Jobs10:37 The Black Box Problem & Distillation Attacks11:56 Is Fable Overkill? When Not to Use It12:38 Solving Big Problems: The Youth Unemployment Case Study13:42 The June 22nd Cutoff & the AI Wealth Divide16:15 Controversies: Gatekeeping, Jailbreaks & Transparency17:42 AI for the People or the Elites? OpenAI's Opening18:50 Wrap-Up & Free Newsletter
— Useful Resources ——
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: 
AI search is eating into Google and if your business isn't showing up inside ChatGPT, Claude, or Google's AI Overviews, you're already behind. In this video I go through what Ahrefs found across 1 billion data points and 14 studies: which content formats actually get cited by AI, why schema markup does essentially nothing, and why YouTube turns out to be the single strongest signal for AI brand visibility. Yes, really.
Practical stuff only. Blog listicles, homepage rewrites, reviews, directories, podcasts, and a YouTube strategy most businesses are completely sleeping on. Nobody's even agreed on a name for this yet (GEO? AEO? LLM SEO?) but the playbook is simpler than you'd think.
—— Time Stamps ——
0:00 Intro: How to Be Discoverable Inside AI01:07 What Do We Even Call It? AI SEO vs GEO vs AEO1:39 AI Still Looks for Real Evidence Across Surfaces2:59 Blog Listicles: ChatGPT's #1 Cited Content Format3:40 Chatbots vs Google AI Overviews Explained5:34 Wikipedia & the Sources Marketers Can't Control6:35 The Hidden Discovery Layer: Zero Google Visibility7:46 Retrieved vs Cited: ChatGPT's 50% Citation Gap8:27 Off-Site Signals: Reviews, Podcasts & Directories9:22 Why YouTube Is the #1 Signal for AI Visibility10:43 How AI Overviews Are Killing Your Website Clicks12:28 Comparison Pages & Why Schema Markup Is a Waste14:36 Stop Tricking the Algorithm — Just Be Useful15:19 The Practical AI Visibility Checklist16:17 Wrap-Up & Free Resources
— Useful Resources ——
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: 
AI is getting very good at writing, coding, and creating polished content. So good, in fact, that polish is now the least interesting thing you can offer. In this one I make the case that the most valuable skill you can build right now is getting on camera and talking, because that is exactly what AI cannot replicate convincingly.
I walk through the full progression from short-form video to livestreaming to paid AI workshops for businesses, and why non-technical communicators are the people companies actually want to hire. You have a phone and an opinion. That is genuinely all you need to start
—— Time Stamps ——
0:00 Public Speaking & "Yapping": Your AI-Proof Skill1:26 Why Polished Content Now Kills Your Engagement3:34 From Short-Form Video to the Stage: The Progression7:16 Don't Hide Behind AI Avatars or Voice Clones9:14 Turn Content Into a Business (and Niche Down)12:03 What "Yap" Content Is & Twitter's Video React13:09 The Fundamentals of Yap Content14:45 How to Start: Phone, Apps & Recording Tips16:58 Final Thoughts: Why Being Human Wins
— 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: 
Tokenization is one of those concepts that sounds technical until you realise it explains basically everything. Why AI can't count the letters in "raspberry." Why a bigger context window sometimes makes things worse. Why your API bill might be quietly spiralling. This is a 101 lesson on tokens: what they actually are, how models use them, and why the common assumption that a token equals a word is close but not quite right.
The second half gets into context windows, the working memory of a model, and why the "just give it everything" instinct is both expensive and counterproductive. Whether you're building on the API or just a heavy user wondering why long threads start getting weird, understanding this stuff changes how you work. Also, token maxing is a trend and it is, in my view, a bit dumb. We get into that too.
—— Time Stamps ——
0:00 Intro: What Tokenization Is & Why It Matters1:27 Tiktokenizer Demo: How Words Break Into Tokens4:18 Token IDs: How Models Store Words as Numbers5:35 Tokens Across Languages: Why English Is Cheapest7:59 The Raspberry Problem: Why AI Can't Count Letters9:49 Context Windows Explained: What "1 Million Tokens" Means11:40 Context Compaction: Why Chats No Longer Cut You Off13:27 Why a Bigger Context Window Isn't Always Better16:18 API Pricing: How Tokens Drive Your AI Costs18:42 "Token Maxing": The Wasteful AI Trend to Avoid20:13 Finding Real Context Limits & DeepSeek vs GPT Pricing22:36 Rules of Thumb: Optimize for Useful Context25:12 Wrap-Up & Andrej Karpathy Recommendation26:20 Newsletter & Sign-Off
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