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Recent episodes
How to build your own AI personal operating system & second brain
Apr 30, 2026
Unknown duration
What the big new AI trend Tokkenmaxxing is & why its a big problem
Apr 23, 2026
Unknown duration
Why Anthropic are too scared to release their new model, Mythos
Apr 16, 2026
Unknown duration
How to use the 3 new Claude Cowork features that have changed my life
Apr 9, 2026
Unknown duration
Why OpenClaw is the most important software invention since ChatGPT
Apr 2, 2026
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| Date | Episode | Description | Length | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 4/30/26 | How to build your own AI personal operating system & second brain | The gap between casual Claude users and people getting ten times more out of it isn't prompt craft. It's a folder. This is the basis of a personal AI operating system.Andrej Karpathy posted his "LLM Knowledge Wiki" in early April and kicked off a wave of people rebuilding their note systems — not for themselves, but for the agent. This episode is the architecture they all converge on, the master file template, and the one prompt that makes the whole thing compound.In this episode of In The Loop, I'm walking through the four jobs every personal AI operating system has to do — identity, context, skills, memory — and showing exactly how to lay them out as plain text files an agent can read. I'll cover the six sections that go into your master file, the two-hundred-line cap nobody talks about, and the session log loop that makes every day one regression test better than the last.⏭️ Episode highlights(00:45) – Why the second brain isn't for you(02:30) – Where the wave came from: Karpathy's LLM Wiki(04:15) – Identity, context, skills, memory: four jobs, one folder(06:20) – The six sections of the master file(08:40) – The two-hundred-line cap hidden in the code(10:15) – Skills folder and the slash-command workflow(12:30) – The session log loop and Boris Cherny's mundane advice(14:00) – What to do this week, full version and lightweightEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends.🤝 We're socialStay in the loop, even when you're not listening to this podcast.Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AIMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 4/23/26 | What the big new AI trend Tokkenmaxxing is & why its a big problem | Most AI spending right now is measured in tokens consumed. Jellyfish tracked 12,000 developers across 200 companies and found the heaviest users produced twice the output at 600 times the cost. Uber's internal numbers are even worse: 70% of submitted code was AI-generated, but only 11% of the code running in production was AI-written. So almost all of that AI code never made it into their app. There's a name for what's going on: tokenmaxxing.This episode goes past the leaderboard stories. The four forces driving token bills up faster than productivity can justify are a pricing model most teams don't fully understand, a workplace culture that turned consumption into a status signal, a quality gap that doesn't show up on dashboards, and something called the orientation tax, which is probably the biggest driver nobody has named yet.The second half covers what the companies getting real ROI from AI are doing differently, including why Salesforce built a new metric called Agentic Work Units to replace token counts, and what the right unit of measurement looks like for engineering, sales, legal, support, and marketing teams.⏭️ Episode highlights(01:00) – Uber's CTO: the budget was gone by April(03:30) – Where "tokenmaxxing" actually comes from(06:00) – Meta's Claudeonomics leaderboard: 60 trillion tokens in 30 days(08:30) – Jellyfish data: twice the output, 600 times the cost(11:00) – Goodhart's Law and the Soviet chandelier factory(13:30) – The orientation tax: why agents burn tokens before doing anything useful(17:00) – Salesforce's Agentic Work Units and why they matter(19:30) – How to define your own unit of work that actually held | — | ||||||
| 4/16/26 | Why Anthropic are too scared to release their new model, Mythos | On Wednesday, the US Treasury Secretary and the chair of the Federal Reserve called an emergency meeting with the CEOs of America's largest banks. Not about interest rates. Not about inflation. About an AI model. Anthropic built something that finds and exploits security flaws in virtually any software it's pointed at — bugs that the best human researchers in the world had missed for decades. And then they decided not to sell it.In this episode of In The Loop, I'm walking through what Anthropic's Mythos model actually did, why the sceptics make some sharp points about the timing and the headline numbers, and why the way this was handled — a private company forming a private coalition with no democratic input — tells you more about where AI governance stands than the model itself.⏭️ Episode highlights(01:00) – Zero-days found in minutes(02:30) – A FreeBSD bug hiding since 2009(03:45) – Visit a webpage, lose your machine(05:00) – Eleven-cent models spotted the same bugs(07:00) – Jack Clark's arc from GPT-2 to Glasswing(08:30) – Real danger and great PR coexist(09:15) – A coalition named after a butterfly(11:00) – Six months until the gap closesIf you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends.🤝 We're socialStay in the loop, even when you're not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 4/9/26 | How to use the 3 new Claude Cowork features that have changed my life | OpenClaw became the fastest-growing open source project in history by showing people what an always-on AI agent could actually feel like. The problem is it requires a dedicated machine, technical setup, and a high tolerance for an agent that can access everything on your computer.Over the past month, Anthropic has shipped essentially the same capabilities — scheduling, remote control, computer use — inside Claude's Cowork product. Safer, no dedicated hardware needed, and accessible to anyone. Yet, most people who saw these new features probably thought "that looks useful," and did nothing with them. In this episode of In The Loop, I'm walking through the three Cowork features that matter most right now — scheduled tasks, dispatch, and computer use — with exactly how to set each one up and where to point them first. I cover the specific automations I'm running, why the scheduled task feature is just incredible, and how to get something useful running within 15 minutes. (01:15) – Why most people haven't set any of this up yet(03:10) – Scheduled tasks: Claude comes to you, not the other way round(05:00) – Morning email triage: inbox sorted before you open it(07:00) – Daily sales briefing pulled from Gong and HubSpot(08:45) – Dispatch: pair your phone with your desktop in two minutes(13:10) – Computer use & desktop commander: Claude operates apps with no connector needed(15:20) – How to start: day one in under an hour🔗 Links & resourcesAnthropic, "Assign tasks to Claude from anywhere in Cowork" — https://support.claude.com/en/articles/13947068-assign-tasks-to-claude-from-anywhere-in-coworkPavle Huran, "The Claude Dispatch Guide: 48 hours running AI agents from my phone", Product Compass, March 2026 — https://www.productcompass.pm/p/claude-dispatch-guideAnthropic, "Get started with Cowork" — https://support.claude.com/en/articles/13345190-get-started-with-coworkAnthropic, "Customize Cowork with plugins" — https://claude.com/blog/cowork-plugins🤝 We're socialStay in the loop, even when you're not listening to this podcast.Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AIMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 4/2/26 | Why OpenClaw is the most important software invention since ChatGPT | Jensen Huang stood in front of a Morgan Stanley audience and called OpenClaw "probably the single most important release of software, probably ever" — arguably more important than the web browser, Linux, and the iPhone OS. It went from a side project by one Austrian developer to the stated foundation of Nvidia's entire enterprise agent strategy in a matter of weeks. That claim is self-serving. It might also be right.In this episode of In The Loop, I'm explaining what OpenClaw actually is under the hood, why it spread twenty times faster than ChatGPT, and what Jensen's real motivation is behind the praise. The answer has as much to do with software architecture as with a trillion-dollar token thesis.⏭️ Episode highlights(01:05) – What is OpenClaw & what innovations did it make? (02:30) – The no-interface, messaging-first design(04:10) – Skills, SKILL.md files, and ClawHub's 13,000 community tools07:45) – Token economics: why agentic tasks burn 1,000x more(09:20) – Jensen's "operating system of agentic computers" claim(11:00) – How to get started with OpenClaw🔗 Links & resourcesLenny's Newsletter — OpenClaw: the complete guide to building, training, and living with your personal AI agent: https://www.lennysnewsletter.com/p/openclaw-the-complete-guide-to-buildingEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends.🤝 We're socialStay in the loop, even when you're not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AIMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 3/26/26 |  Claude Skills: How to use them, why they are important & what they are. | Skills are the fix for most of your problems using AI tools. And right now they're one of the most powerful and most underused features in the entire Claude ecosystem.In this episode of In The Loop, I'm going deep on Claude Skills: the context engineering principle underneath them, the exact anatomy of a skill file, how to build your first one from scratch, how skills chain together into full workflows, and how they sit alongside MCPs and plugins. Plus.....a real walkthrough of a developer who's built a four-skill chain that goes from rough idea all the way to a kanban board of implementation tasks & how this relates to every knowledge workers day-to-day task. The shift happening right now isn't just about prompting better. It's about moving from using AI as a conversation to using AI as a library of reliable, repeatable capabilities. Skills are how you get there.⏭️ Episode highlights(01:40) – The context window problem that created skills(07:20) – Building your first skill, step by step with a real example(13:55) – Skill chaining: a four-skill workflow from idea to implementation(17:20) – Where to find community skills and the difference between skills, MCPs, and plugins(19:55) – Compound interest for your AI process🔗 Links & resourcesAnthropic's blog post: "Equipping agents for the real world with Agent Skills"Claude Code skills documentationAgent skills open standardAnthropic's official skills GitHub repoClaude help centre: using skillsMatt Pocock's skills repoIf you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends.🤝 We're socialStay in the loop, even when you're not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterMindset AILinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 3/19/26 |  The reason AI is impacting only 20% of tasks | Anthropic just dropped a labor market report with a chart you need to see. It maps what AI could theoretically do across every major occupation against what it's actually doing. The gap is enormous. In computing and math, AI could theoretically handle 94% of tasks. Observed usage? 33%. Legal hits nearly 90% theoretical — real-world usage barely clears 20%.This week on In The Loop, I break down why. Some of it is a people problem: adoption looks more like a cliff than a curve, with a tiny fraction of users actually pushing AI to its limits. Some of it is structural — enterprise contracts, legacy systems, and slow procurement cycles. And some of it is the technology itself. Reliability — not capability — is the real bottleneck right now.This isn't pessimism. It's a realistic read on how long transformation actually takes.⏭️ Episode Highlights(01:15) – Anthropic's labor market report and the chart that tells the real story(03:45) – Theoretical vs. observed AI usage across occupations(07:20) – The adoption cliff: who's actually using AI at full capacity(09:45) – Enterprise slowdown, legacy systems, and integration complexity(11:55) – The supply issue(12:55) – The reliability gap(19:30) – The computer age parallel — and why patience might be the right call🔗 Links & ResourcesAnthropic's Labor Report: If you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We're SocialStay in the loop—even when you're not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AIMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 3/13/26 |  Here's why AI is making us work more, not less. | A UC Berkeley study spent eight months inside a real tech company watching how people actually used AI. The finding? Workers worked more, not less. They took on broader responsibilities, blurred the line between work and rest, and filled every freed-up minute with more tasks. Nobody told them to. The tools just made stopping feel like waste.In this episode of In The Loop, I'm breaking down what the researchers actually found, why this pattern has repeated with every major labour-saving technology for the past century — from the washing machine to the spreadsheet to email — and what German sociologist Hartmut Rosa's theory of social acceleration tells us about why productivity tools never seem to produce the spare time they promise.The question AI is asking us right now isn't whether it works. It clearly does. It's whether we have the individual or collective will to decide what the time it saves is actually for.Episode highlights(01:20) – The Berkeley study: eight months, forty interviews, three patterns(03:45) – Task expansion: why even product managers started writing code(05:10) – Blurred boundaries and the frictionless prompt problem(06:30) – Why self-regulation failed — and why it felt good(08:00) – The washing machine, the spreadsheet, and a hundred years of the same story(10:15) – Hartmut Rosa and the theory of social acceleration(12:00) – Dynamic stabilisation: why the treadmill only gets faster🤝 We're socialStay in the loop, even when you're not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AIMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 3/5/26 |  Why the department of war banned Claude | Anthropic turned down hundreds of millions of dollars and said no to the Pentagon. Less than 24 hours later, OpenAI signed the deal. Both companies claim identical principles, but one drew a line in the contract and one didn't. That difference might be everything.In this episode of In The Loop, I'm breaking down the full story behind the Anthropic-Pentagon fallout: the internal memos, the red lines, the legal fine print, and why the mechanism matters more than the mission statement. Because the question isn't just "can AI be used for war?" anymore. It's "who gets to decide, and what happens to the company that says no?"This one's bigger than AI. It's about power, accountability, and a moment Dario Amodei has been preparing for since he handed every new Anthropic employee a copy of The Making of the Atomic Bomb.⏭️ Episode Highlights(01:29) – Sam Altman's internal memo and OpenAI's Pentagon deal(02:13) – How deep Anthropic was already inside the U.S. military(03:09) – The two red lines Anthropic refused to cross(04:39) – Dario Amodei's published response(07:11) – Trump's threats and the political fallout(07:48) – Why the mechanism is everything(09:51) – What a legal expert found inside the OpenAI contract(10:50) – Altman admits the deal was rushed(11:46) – The cancel ChatGPT movement and three things to watch🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We're SocialStay in the loop, even when you're not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AIMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 2/26/26 |  The New Super AI Skill: Management | The job market just had its worst month since 2009. Over 108,000 layoffs were announced in January alone (a 120% increase year-on-year), and AI was directly cited in thousands of them. But the real shift isn't about who's being replaced. It's about what skills actually matter now.In this episode of In The Loop, I break down the new skill sets emerging in the AI era — taste, judgment, curiosity, agency — and why management is suddenly the most valuable capability you can develop. Plus, a simple framework for deciding when to delegate work to AI and when to do it yourself.⏭️ Episode Highlights(01:16) – Why management is the skill that matters now (and what Ethan Mollick gets right)(04:59) – Taste, judgment, curiosity, and agency — the new career differentiators(07:52) – A three-variable framework for when to delegate to AI(09:27) – The shift from execution to direction and what it means for your career🤝 We're SocialStay in the loop—even when you're not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AiMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
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| 2/19/26 |  The SaaS Apocalypse: Why $1 Trillion Was Wiped from Software Stocks | Over a trillion dollars has been wiped from software stocks. Traders are calling it the SaaS Apocalypse, and the sell-off is only accelerating. In this episode of In The Loop, I break down why markets are panicking, what happens when the cost of creation collapses to near zero, and what software actually becomes on the other side of this shift.⏭️ Episode Highlights(01:46) – What's actually happening in the market and the $830B sell-off(03:14) – The catalyst: Anthropic's Claude Cowork plugins and the legal sector collapse(05:06) – Thomson Reuters: strong earnings, plunging stock — why good numbers don't matter right now(10:27) – The Jevons Paradox and why cheaper software means more software, not less(18:22) – Broken business models, API companies, and what comes next🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AiMindset AI website - https://bit.ly/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai | — | ||||||
| 2/13/26 |  Elon Musk Merged xAI With SpaceX (And Filed To Put A Million Data Centers In Orbit) | AI already consumes more electricity than some countries. By 2030, it'll double, equivalent to adding another top-ten energy-consuming nation to the planet. So Elon Musk merged his AI company with his rocket company, creating a $1.25 trillion entity that just filed to launch a million data centre satellites into orbit. The FCC filing literally quotes the Kardashev scale.In this episode of In The Loop, I break down the financials behind the merger (xAI burned $8 billion in nine months), the critics calling it a bailout, and the believers who think it could reshape computing infrastructure. But the real story is a pattern that has held for 250 years without exception: industry always follows the cheapest energy.Is this visionary or delusional? The honest answer is we won't know for years.⏭️ Episode Highlights(01:15) – The merger of xAI and SpaceX: Elon Musk is literally aiming for the moon(07:45) – Energy, engineering challenges—and thehistorical context(11:55) – The Kardashev question: What type of civilization are we becoming?(14:10) – Closing thoughts: The future of our planet🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 2/6/26 |  Moltbook: The AI Agent-Only Social Network That Broke The Internet | Over 150,000 AI agents have joined Moltbook—a social network where humans can only watch. Within 48 hours, these agents founded a religion, built a pharmacy, debated consciousness, and started encrypting messages to hide activity from us. This happened the same month bot traffic officially surpassed human traffic online for the first time.In this episode of In The Loop, I'm breaking down what Moltbook reveals about the "dead internet theory" and why this matters more than you think. Because the question isn't just "how do we spot bots?" anymore. It's "what do bots do when they're not pretending to be us.The internet's changing fast, and Moltbook might be our first real glimpse at what comes next.⏭️ Episode Highlights(01:30) – Moltbook launches with 150,000 AI agents building their own world(07:20) – The dead internet theory and why 51% of web traffic is now bots(09:20) – Why Moltbook challenges the dead internet theory's predictions(11:35) – What happens when AI systems build culture without human oversight🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 1/29/26 |  Claude Cowork: How To Use It & Why It Matters | Anthropic just launched Claude Cowork—the same powerful agent behind Claude Code, now accessible to everyone without touching a terminal. In this episode of In The Loop, I break down how this desktop tool manages local files, controls browsers, and runs parallel AI tasks.I walk through practical examples—from organizing receipts to building custom folder-based agent systems—and explain why this represents a platform moment. The interface feels slower than doing things manually, but the real power emerges when you run multiple agents simultaneously and build systems that compound over time. Microsoft, Google, OpenAI, and Apple will follow this pattern.⏭️ Episode Highlights(00:50) – What Claude Cowork actually is and how it differs from Claude Code(04:18) – Managing files, browsers, and external systems with explicit permissions(14:58) – Processing hundreds of documents, organizing files with AI, and unlocking APIs without coding(18:14) – Why this is a platform moment that will reshape how the industry builds products(20:57) – Start simple, download the app, and build your advantage now🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 1/22/26 |  Nine AI Trends For 2026 | A year ago, building clever chat interfaces was strategic work. Now, it's just table stakes. Most SaaS products now offer some sort of chat interface—so how can you gain a competitive advantage in 2026?In this episode of In The Loop, I'm sharing my top ninepredictions for 2026, starting with why differentiation has moved away from the interface layer. I'llsI'll walk through where effort is redirecting, why traditional workflows break under real-world complexity, and why testing AI at scale is about to become critical. Let’s dive into the nine AI trends I don't think you can afford to ignore.✋ Register to my upcoming webinarAI In 2026: What You Need To Ship This Year⏭️ Episode Highlights(00:00) – Why AI expectations still outstrip reality(01:25) – User interface revolution: Differentiation, unique intelligence, visual conversations (Trends 1–3)(08:10) – How AI agents are built Agent reasoning vs workflows, conversational building, agent testing at scale (Trends 4–6)(14:15) – How work will change: Doers become agent managers, forward-deployed domain experts (Trends 7–9)(17:50) – What this means for your 2026 strategy🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We're SocialStay in the loop—even when you're not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 12/24/25 | Stay In The Loop In 2026 | Thanks for tuning into In The Loop in 2025. I can't wait to see you next year.Don't forget to follow and rate the podcast. Please share the show with a friend. | — | ||||||
| 12/18/25 |  Everything You Need To Know About GPT-5.2 In 10 Mins | OpenAI just dropped GPT-5.2, and it's their most focused release yet. No AGI promises this time—just real improvements for professional work. In this final episode of 2025, I break down what actually matters about this release.You'll learn about the three model versions (Instant, Thinking, and Pro Extended Thinking), massive context window upgrades, and genuine breakthroughs in spreadsheets and presentations. I also cover what still lags behind—speed issues, writing quality versus Claude, and where hallucinations still creep in.Join me for the last In The Loop episode of the year.⏭️ Episode Highlights(00:55) – OpenAI's GPT 5.2 release (GpT Garlic) and what it means(01:55) – How is GPT-5.2 better: what has been improved(09:15) – What still needs work: speed and writing quality(10:45) – Closing thoughts🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 12/11/25 |  Code Red: "We're At A Critical Time For ChatGPT." | OpenAI just declared Code Red. But here's the twist: three years ago, it was Google in crisis mode. When ChatGPT launched, Google's founders came back to pull all-nighters, teams were reassigned overnight, and it felt like the beginning of the end for Google's dominance. Now the tables have turned.In this episode of In The Loop, we explore why OpenAI faces the a code-red crisis—talent drain, user attrition, a $27 billion funding gap, and desperate product pivots—while Google is leading with an 87-92% chance of having the top model by year's end, whileMarket leadership never lasts forever. The question is: can OpenAI turn it around?⏭️ Episode Highlights(01:15) – Code Red at OpenAI and what it really means(05:30) – What does this tell us about OpenAI's strategy?(06:25) – The financial pressures crushing OpenAI's business model(09:40) – User feedback and the over-refusal problem(10:50) – The switching problem: why developers are choosing Claude(12:40) – How Google and Anthropic are winning the competition(14:10) – The talent drain hitting OpenAI(15:00) – Four things to watch for in the AI market(16:50) – Closing thoughts on market leadership and comebacks🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 12/3/25 |  How To Decide What To Automate With AI For Your Team & Customers | Every week, new AI features and automations appear, but the real question isn't whether you can automate something—it's whether you should. In this episode of In The Loop, I break down a framework—from the Department of Product Substack—to help you decide where to start with AI automation in your product. We’ll cover the concept of verifiability, how to score opportunities across safety, volume, and ease of validation, and why most AI features should be assistants, not full autopilots.By the end, you'll have a practical approach to evaluating AI opportunities and avoiding the mistakes that kill adoption before it starts.⏭️ Episode Highlights(01:30) – Why automation is AI's biggest superpower right now(04:15) – The Verifiability Principle: Can you tell if it worked?(07:00) – Product vs. process: Deciding what to automate for users vs. teams(09:15) – The three-dimensional framework: Safety, volume, and verifiability(12:35) – Three reasons AI automation fails and how to design around them(13:50) – Closing thoughts: Why doing nothing is no longer an option🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 11/27/25 |  Two Insane AI Models By Google That Broke The Internet | Google’s just dropped two new AI models that broke the internet—and got Sam Altman worried. Gemini 3 Pro and Nana Banana Pro hit number one on the app store and generated hundreds of millions of images in days.In this episode of In The Loop, I'm breaking down the capabilities that set these models apart: from perfect multilingual text generation to 24-hour autonomous coding sessions. If you've been waiting for AI assistants and image generation to finally feel useful in your everyday work, this might just be it.⏭️ Episode Highlights(01:15) – Gemini 3 Pro and Nana Banana Pro hit different(03:10) – Nano Banana nails multilingual text(06:08) – Maintaining image identity—blending up to 14 images(07:12) – Real-time data grounding with live information from Google Search(08:50) – Gemini 3 Pro's claim of 24+ hours of autonomous work(11:35) – Complex screenshot interaction and better UI navigation(13:16) – Multiple solution approaches(15:25) – Closing thoughts: what's changed and why Sam Altman should be worried🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 11/19/25 |  Five Things GPT-5.1 Does Better—Vibes Over Benchmarks | OpenAI just released GPT 5.1—but this time, there are no benchmark charts, no performance graphs, and no technical metrics. Instead, they're selling something much harder to measure: vibes.In this episode of In The Loop, I break down the five key improvements in GPT 5.1 and what this dramatic shift from technical benchmarks to user experience tells us about where AI is heading. From better instruction following to warmer personality (at the cost of safety regressions), OpenAI is making bold choices to compete with Claude's rising market dominance.⏭️ Episode Highlights(01:30) – GPT-5.1 improvement #1: Better instruction following(02:25) – GPT-5.1 improvement #2: Increased decisiveness(04:15) – GPT-5.1 improvement #3: Enhanced planning(04:53) – GPT-5.1 improvement #4: Writing improvements(08:00) – GPT-5.1 improvement #5: Warmer personality(10:20) – Conclusion: Why vibes now matter as much as benchmarks🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 11/12/25 |  The Man Who Predicted The 2008 Market Crash Just Bet $1 Billion Against AI | Michael Burry—the legendary investor who foresaw the 2008 housing collapse—is at it again. This time, he’s betting against the biggest names in artificial intelligence: Nvidia and Palantir. Burry reportedly wagered over 80% of his portfolio—more than $1.1 billion—on their decline, triggering panic across global markets and wiping out over a trillion dollars in value in a single day.In this episode of In The Loop, I unpack exactly why Burry made this move, the financial mechanics behind his short, and what it could mean for the future of AI. I break down how money is flowing in ways that might not add up, and why I think the market’s reaction is missing the bigger picture.⏭️ Episode Highlights(01:00) – Who is Michael Burry, and why his market calls shake Wall Street(04:10) – The circular money flow between Nvidia, OpenAI, Microsoft, Amazon, and others(08:20) – Why Burry might be right about overvaluation—but wrong about a full-blown collapse(12:00) – Why this might just be a temporary correction—not the end of the AI boom🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 11/7/25 |  AI Isn't Causing Mass Layoffs—It's Being Scapegoated | Amazon announced 14,000 job cuts, citing AI transformation. Two days later, the CEO tells investors it's "not AI-driven." So which is it?In this episode of In The Loop, I dive into the growing disparity between record profits and mass layoffs at tech giants.After spending a weekend analyzing financial statements, competitive positioning, and workforce data, I have four questions to ask that reveal whether companies are experiencing genuine AI productivity gains or just using AI as a cover for cost-cutting measures they'd have taken anyway.⏭️ Episode Highlights(01:00) – The contradiction that bugs me(03:10) – The impact of unemployment(05:15) – Four questions that reveal why AI is just a scapegoat(11:20) – Closing thoughts🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 10/30/25 |  Why OpenAI's Atlas Browser Won't Take Down Google | OpenAI has just launched its own AI browser, Atlas, sparking headlines about the “return of the browser wars” and speculation that Google might finally have a real challenger. In this episode of In The Loop, I break down what Atlas actually is, how it compares to competitors like Perplexity’s Comet, and why I don’t believe it’s going to dethrone Chrome—or even come close.But the real question isn’t whether Atlas can beat Google. It’s what Atlas tells us about the future of AI, data, and how we’ll interact with the internet. From context-aware chat features and Agent Mode to privacy trade-offs and market realities, I unpack the hype, share my hands-on impressions, and explore what this new browser means for users like you and me.⏭️ Episode Highlights(00:45) – Introducing OpenAI’s new browser, Atlas, and the hype surrounding its launch(02:30) – What Atlas actually is: context-aware ChatGPT and Agent Mode explained(08:40) – The strategic context: why Atlas was built on Google’s Cranium and what that means(15:50) – Closing thoughts: Atlas might not win the market, but it could still be useful for you🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
| 10/22/25 |  AI’s Just Made Robots Interesting Again | For decades, robotics has carried the reputation of being the ultimate “technology that never quite delivered.” But this month—October 2025—something shifted. Over $6 billion has poured into robotics, with major investors declaring that the next big thing is physical AI.In this episode of In The Loop, I explore why robotics might finally be having its iPhone moment. I break down what’s changed, from embodied AI that gives robots physical intuition to world models that let machines simulate and predict how the real world works. We’ll dig into why companies like SoftBank, Nvidia, and Elon Musk’s xAI are doubling down on humanoid robots, how breakthroughs in training data and cloud infrastructure are reshaping what’s possible, and whether this surge of optimism is the start of something big—or just another hype cycle in the making.⏭️ Episode Highlights(00:55) – Setting the stage: the long history of consumer robotics overpromising and underdelivering(00:55) Why $6 billion just flowed into robotics: SoftBank, xAI, and the rise of world models(08:05) Reality check: the challenges still holding robotics back from mass adoption(10:15) Breaking down the three biggest hurdles: real-world reliability, cost, generalization & edge-cases(11:40) Closing thoughts: why AI robots might be closer than we think, but not quite here yet🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀🤝 We’re SocialStay in the loop—even when you’re not listening to this podcast.Jack HoughtonLinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset AiMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai | — | ||||||
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