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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 closes If you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends. 🤝 We're social Stay in the loop, even when you're not listening to this podcast. Jack Houghton LinkedIn - 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

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 & resources Anthropic, "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 social Stay 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

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 tools 07:45) – 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 & resources Lenny'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-building Episode transcript with more resources on the Mindset AI blog If you enjoyed this episode, rate, follow, and share. It helps others stay ahead of the latest AI trends. 🤝 We're social Stay in the loop, even when you're not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/TikTok - @jackschatsMindset AI Mindset 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

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 & resources Anthropic'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 social Stay in the loop, even when you're not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschatsMindset AI website - https://bit.ly/40lJr6B Newsletter - https://bit.ly/ITLnewsletter Mindset AI LinkedIn - https://www.linkedin.com/company/mindset-ai/ YouTube - https://www.youtube.com/@GetMindsetAI TikTok - @get.mindset.ai

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 & Resources Anthropic's Labor Report: If you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀 🤝 We're Social Stay 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/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai

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 social Stay 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/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai

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 blog 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 - @jackschats Mindset 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

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 Social Stay 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/40lJr6BNewsletter - https://bit.ly/ITLnewsletterLinkedIn - https://www.linkedin.com/company/mindset-ai/YouTube - https://www.youtube.com/@GetMindsetAITikTok - @get.mindset.ai

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 Social Stay in the loop—even when you’re not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset Ai Mindset 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

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 Social Stay in the loop—even when you’re not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/ TikTok - @jackschats Mindset Ai Mindset 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

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 & Resources Episode transcript with more resources on the Mindset AI blog If you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀 🤝 We’re Social Stay in the loop—even when you’re not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/  TikTok - @jackschats  Mindset Ai Mindset 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 

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 & Resources Episode transcript with more resources on the Mindset AI blog If you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀 🤝 We’re Social Stay in the loop—even when you’re not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/  TikTok - @jackschats  Mindset Ai Mindset 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

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 webinar AI 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 & Resources Episode transcript with more resources on the Mindset AI blog If you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀 🤝 We're Social Stay in the loop—even when you're not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/  TikTok - @jackschats  Mindset Ai Mindset 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 

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.

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 & Resources Episode transcript with more resources on the Mindset AI blog If you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀 🤝 We’re Social Stay in the loop—even when you’re not listening to this podcast. Jack Houghton LinkedIn - https://www.linkedin.com/in/jack-houghton1/  TikTok - @jackschats  Mindset Ai Mindset 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