AI with Kyle - Daily AI News and Updates

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Summary: Codex just shipped a mobile app, and it's the last piece I needed to properly untether myself from my desk. In this one, I walk you through how to set up an always-on vibe coding workflow across your desktop, laptop, and phone. Meaning, you can start a session at home, walk out to a cafe, and pick it up on your phone without losing a single thread of context. The key is combining the new Codex mobile release with the "Control Another Device" feature.
I also get into why I've quietly shifted from Claude Code to Codex as my main tool. The model quality gap has closed, and the usage limits on Claude just aren't worth the stress anymore. If you're still running one session per machine and wondering why it feels fragmented, this is the setup that fixes it. Full technical checklist and written guide are in the Monday newsletter at [aiwithkyle.com](http://aiwithkyle.com/).
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0:00 Codex Now Has A Mobile App: Vibe Coding Just Changed0:43 How Codex In ChatGPT Mobile Actually Works1:18 The Multi-Device Problem Killing Your Coding Flow2:36 My Old Setup Mess & Why OpenClaw Was So Exciting3:59 Mobile Controls Desktop: How Native Codex Untethers You5:30 Hardware Setup: Mac Mini As Your Always-On Vibe Coding Machine6:42 "Control Another Device" Setting + GitHub Central Repository8:17 Adding Your Phone & The Real Studio-To-Pool Workflow9:53 Why I'm Switching From Claude Code To Codex
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Tired of shipping polished AI rubbish? (Free Guide): https://aiwithkyle.com/mini/ai-fluency
Get AI-Ready with Kyle’s 5-Day Challenge: https://aiwithkyle.com/join
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Summary: Anthropic has a free AI Fluency course and, it’s good. I watched the whole thing and pulled out the frameworks that are actually worth your time, so you don't have to sit through the full thing yourself.
The big idea is this: prompting is one small part of a much larger skill set. Anthropic breaks it down into four competencies. Interestingly the one people skill entirely is ‘discernment’, that's your human judgment telling you whether the AI actually did a decent job, or whether it's handed you a beautifully formatted hallucination. I walk through all four Ds, the three modes of AI use, and the description-to-discernment loop that, once you have it in your head, changes how you work with AI entirely. The course is free, but hopefully with this video I've saved you about an hour.
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0:00 Welcome & Series Introduction1:12 The Big Takeaway: AI Skill Is More Than Just Prompting2:03 The Three Ways to Use AI: Automation, Augmentation & Agency3:36 The Four Ds Framework Explained4:29 D1: Delegation – What to Hand Off to AI vs Keep Yourself6:53 D2: Description – The RISEN Prompting Framework10:04 D3: Discernment – How to Spot AI Hallucinations13:47 The Description-to-Discernment Loop16:28 D4: Diligence – AI Ethics, Safety & Verification18:15 Final Takeaways & Why I Recommend This Course
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How Kyle turns ONE live session into 20 pieces of content (Free Guide): https://aiwithkyle.com/mini/content-machine
Get AI-Ready with Kyle’s 5-Day Challenge: https://aiwithkyle.com/join
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Summary: Every day I produce a YouTube video, a newsletter, five to eight short-form videos, carousels, PDFs, and LinkedIn posts, and there are two of us. In this video I walk through the complete AI-powered content system that makes that possible, from morning topic selection via an AI agent, through voice-note prep and slide generation, to the content processing workflow that turns a single live stream transcript into 20-plus assets automatically.
This isn't a pitch for going all-in day one. I also cover the minimum viable version for anyone who's not ready to livestream to five platforms simultaneously, including how to use AI to interview you instead, capture your voice and opinions, and still spin out a newsletter and short-form scripts without getting anywhere near a camera. The key principle throughout: the AI handles the boring infrastructure, you stay in for the parts that actually require a human.
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0:00 Intro: How I Use AI to Become a Content Machine0:50 Why an Audience Is Non-Negotiable for Business2:06 Why Education Content Beats Entertainment4:12 What I Publish Every Single Day6:08 The AI Slop Problem: Don't Automate Everything7:40 The Full Workflow Overview12:19 Step 1: AI-Powered Topic Selection13:42 Step 2: Voice Notes to Slide Decks15:18 Live Streaming (and the AI Interview Alternative)17:44 Step 3: Transcripts to Newsletters & Articles19:14 Carousels, PDFs & 100+ Emails a Day20:56 Short Form Scripts & Where to Use AI23:27 The Self-Improving Feedback Loop24:46 Tools Don't Matter, Workflows Do (My Stack)26:56 How to Start Small Without Burning Out28:40 Why Your Humanity Becomes More Valuable & Outro
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Tired of ChatGPT and Claude spitting out generic answers that don't sound like you? (Free Guide): https://aiwithkyle.com/mini/system-prompt-builder
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 came across Marc Andreessen's viral system prompt. The co-founder of Netscape, one of the sharpest minds in Silicon Valley, posted his custom ChatGPT instructions online and got absolutely roasted for it. Telling an AI it has "intellectual firepower on par with the smartest people in the world" doesn't make it smarter. Telling it to never hallucinate doesn't stop hallucinations. And asking for answers "as long and detailed as possible" just produces verbose nonsense that buries any actual value. His system prompt is stuck in 2023.
In this video I fix it. We go through exactly what's broken in Andreessen's custom instructions and why, then build a system prompt from scratch using the RISEN(TM) framework — a structured approach to writing AI instructions that actually holds up in 2026. You'll learn why role declarations don't make AI smarter (but are still useful), why adjectives are useless without verbs, how to write custom instructions that change AI behaviour rather than just describe it, and how to define an end goal that stops your AI padding everything out. Whether you're using ChatGPT custom instructions or Claude's system prompt settings, this will change how you prompt.
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0:00 Marc Andreessen's Viral System Prompt Is Getting Mocked Online1:14 Why "World-Class Expert in All Domains" Doesn't Work2:19 "Never Hallucinate" Is Not How AI Actually Works2:58 Tone, Provocative Answers, and Why "Bloviate" Padding Backfires3:54 The Anti-Sycophancy Trick That Actually Works5:39 System Prompts vs Conversational Prompts Explained6:13 How to Add Custom Instructions in ChatGPT and Claude8:03 The Role Declaration Myth (Ethan Mollick Research)10:41 Use Verbs, Not Adjectives, In Your Prompts11:39 Why "Think Step By Step" Is Outdated in 202614:07 You Can't Prompt Your Way Out of AI Hallucinations16:47 Why Asking for Long Detailed Answers Wastes Tokens18:49 The RISEN Prompt Engineering Framework Explained24:46 RISEN in Action: A Better Version of Marc's Prompt26:13 The Coffee Order Analogy: When NOT to Engineer Prompts28:18 Free Quick-Start Guide and Outro
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 Turn Your Industry Experience Into An AI-Powered Income Stream (Free Guide): https://aiwithkyle.com/mini/ai-insider
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'm covering one of the biggest strategic moves I've seen from the AI labs: OpenAI and Anthropic both launched consulting and deployment ventures on the same day, backed by Goldman Sachs, Blackstone, BCG, McKinsey, and a handful of others. This isn't just big money doing big things. It tells you exactly where AI is heading and, more importantly, what that creates for people like you and me.
The real focus here is what you can actually do about it. I walk through why your industry knowledge combined with basic AI skills puts you in the same position these companies are paying billions to replicate, just at a scale that actually makes sense for a one or two-person outfit. Workshops, advisory, implementation: the playbook is straightforward, the market is wide open, and most industries haven't had anyone claim that space yet.
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0:00 Intro: AI Labs Push Into Consulting & Advisory0:30 The May 4th Announcements: $10B AI Enterprise Deals1:53 Following the Smart Money: AI Engineers Embedded Inside Companies3:23 The Palantir Playbook: How AI Locks In Forever4:55 The Jagged Frontier: Why AI Got Coding First7:08 From Coding to White Collar: The Harvard Study Proof8:16 When AI Fails: The Government Report Disasters9:13 The Hilarious Irony: Wall Street Is Next11:26 What This Means for Your Job12:46 The Solopreneur Opportunity Gap14:54 4 Ways to Profit From AI: Advisory, Implementation, Education, Content18:26 My Story: Building 300K Audience in Two Years19:07 Where to Start: Why Workshops Are the Best Entry Point21:35 Recap & Newsletter CTA
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Stop AI from making things up. Get the free Hallucination Defence Kit (Free Guide): https://aiwithkyle.com/mini/ai-hallucinations
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 hallucinations aren't going away, and the reason might surprise you. In this one, I break down exactly what's happening under the hood when your chatbot confidently lies to you. Whether it’s making up a book, a statistic, or a legal citation, why it happens more with the smarter reasoning models, and why calling it a "bug" fundamentally misunderstands what these systems actually are.
More importantly, I give you a set of practical things you can do today to reduce the damage: which settings to turn on, when to use stronger models, how to prompt for accuracy instead of agreement, and a genuinely underrated use of NotebookLM.
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0:00 Intro: What Are AI Hallucinations?0:32 When AI Hallucinations Go Public: Chicago Sun-Times & Deloitte2:28 The Scary Stats: 92% Don't Fact-Check AI4:05 The Two Types of Hallucinations You Need to Know5:56 Why ChatGPT Isn't a Database (How LLMs Actually Work)8:01 Andrej Karpathy: Hallucination Isn't a Bug, It's the Feature12:18 Will AI Hallucinations Ever Be Fixed?14:39 When Hallucinations Are Most Likely to Happen18:17 Practical Fixes: Web Search, Paid Plans & Stronger Models21:22 The NotebookLM Trick: Build Your Own Verified AI22:17 Better Prompting: How to Stop AI From Lying to You24:28 The New AI Paradigm (and Final Thoughts)
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Does your writing smell like AI? Grab the fix kit (Free Guide): https://aiwithkyle.com/mini/goblins
Get AI-Ready with Kyle’s 5-Day Challenge: https://aiwithkyle.com/join
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Summary:  OpenAI banned the word ‘Goblin’ from their models, and the reason why is a reinforcement learning feedback loop that turbo-charged a "nerdy personality" setting into goblin obsession. This is an interesting insight into how AI writing ticks develop in the first place. 
Practically, what does this mean for you? I walk you through Wikipedia's living list of AI writing giveaways (yes, they built a 15,000-word guide to protect themselves from AI slop, and yes, I show you how we’ll be using it against them), how to compress it into system instructions and a skill file, and why running your output through both a pre-write and post-write filter is the closest thing to a reliable humaniser you're going to get. I also discuss AI detectors, spoiler: they're worse than useless, and the academic institutions using them to penalise students are in for a rough few years.
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0:00 Intro: OpenAI Banned Goblins From ChatGPT1:42 Why Goblins? The Reinforcement Learning Loop4:33 What Are AI Tells?5:39 Wall of Shame: AI's Most Overused Words7:46 Wikipedia's Signs of AI Writing Guide9:42 How to Stop AI From Sounding Like AI (Belt & Braces System)13:02 Why AI Detectors Don't Work (And Never Will)15:59 AI Tells Are a Moving Target19:18 The Disclosure Paradox: Does Anyone Actually Care?22:00 Free Resources & Wrap-Up
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New to GitHub? Skip the confusion (Free Guide): https://aiwithkyle.com/mini/github
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:  GitHub keeps coming up everywhere if you're building with AI, and nobody ever properly explains what it actually is. So here it is: a complete beginner's guide to GitHub, what it does, why it matters, and how to get it set up and connected to your AI tools of choice, whether that's Claude Code, Codex, Lovable, or Cursor. Think of it as Google Drive for your projects. One central folder that everything syncs to, across every tool and every device.
I walk you through creating your first repo, the key terminology you'll actually encounter (commit, push, pull, branch), and how to connect it all up without touching the terminal once. I also show you how I use GitHub beyond code, as the backbone of my content system and second brain. One repo, set up properly, changes how you work with AI permanently.
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0:00 What Is GitHub & Why Vibe Coders Need It2:05 The Version Control Nightmare Without GitHub4:05 Create Your First GitHub Repo (Step by Step)6:12 GitHub Terms Explained: Repo, Commit, Push, Pull8:42 Cloning, Branching & Merging Made Simple11:01 Connect GitHub to Lovable, Cursor, Claude Code & Codex13:12 GitHub Beyond Code: The Obsidian Second Brain Workflow15:39 Install GitHub Desktop (No Terminal Required)18:01 Best Practices: Folder Structure & When to Commit19:57 Your Action Plan: Set Up GitHub Today21:33 Wrap Up & Newsletter Resources
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Want to run AI privately on your own laptop? (Free Guide): https://aiwithkyle.com/mini/local-llmGet AI-Ready with Kyle’s 5-Day Challenge: https://aiwithkyle.com/join
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Summary: Running a large language model on your own computer sounds like the kind of thing that requires a computer science degree and a spare weekend. It doesn't. In this video I walk you through exactly how to get a local AI model running on your machine today, from downloading LM Studio to picking the right model for your hardware. We cover how to figure out what your device can actually run (RAM is the main thing), what quantization means and why it's not as scary as it sounds, and why Gemma 4 is the sensible starting point for almost everyone.
There are real limitations to local models and I'm not going to pretend otherwise. But for general chat, for working offline, for keeping your data off someone else's servers, they're genuinely good and getting better fast. By the end of this you'll have a working local LLM and a decent handle on where this whole space is heading.
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0:00 Intro: How to Run AI on Your Device2:11 What Is a Local Large Language Model?3:53 4 Reasons to Run AI Locally (Privacy, Cost, Offline, Learning)6:35 LM Studio vs Ollama: Best Tool to Start8:49 Finding Local AI Models on Hugging Face10:25 Best First Model for Beginners: Gemma 411:35 How Much RAM Do You Need? The Parameter Rule15:36 Quantization Explained: Compressing AI Models17:08 Picking Your Model Inside LM Studio19:08 Edge AI: Run AI on Your iPhone or Android21:06 Hobbyist vs Production: When Local AI Makes Sense22:45 Outro & Free Resources
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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 ground has shifted. The nine-to-five used to be the low-risk option, the sensible, boring, reliable choice for anyone who didn't fancy betting everything on a business idea. That deal is off the table. AI is attacking your job at three levels simultaneously: the tasks inside your role, the company that employs you, and the industry you work in. Any one of those can collapse without warning, and most people are sitting there hoping it won't. I'd rather you got a bit annoyed at me now than blindsided later.
The good news, and there is good news, is that entrepreneurship has never been more accessible or less intimidating than it is right now. I'm not talking about raising venture capital or moving to San Francisco. I'm talking about making your first quid from a stranger on the internet, building a small side income, and slowly rewiring your brain to understand that you can generate your own money. AI makes the operational parts of running a small business genuinely manageable for one or two people. The risk-reward on doing your own thing has never looked more reasonable by comparison.
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0:00 Why Your Job Isn't Safe From AI Anymore0:26 When the 9-to-5 Was Actually the Safe Bet1:32 The Three Levels of AI Risk: Job, Company, Industry5:19 Take Responsibility — The Brutal Data on AI Layoffs9:09 The Risk-Reward of Work Has Completely Flipped13:13 How Gen Z Are Building Their Own Way Out17:14 Objection 1: "But Not Everyone Wants a Business"19:56 Where to Start: Freelancing With AI as Your Team22:15 Objection 2: "But My Job Is Creative"25:02 Objection 3: "Just Go Into the Trades"27:19 Why Businesses Can Be Beautifully Simple31:13 The Bottom Line: Start Generating Your Own Income
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