In The Loop

Has Google just leapfrogged Apple in the AI device race with its brand-new Pixel 10? After months of talking about AI trends and whether we’re in a bubble, I wanted to take a closer look at how this technology is actually showing up in the real world—and there’s no better example than smartphones.In this episode of In The Loop, I break down the new AI features Google has built into the Pixel 10, why they matter, and how they compare to Apple’s faltering “Apple Intelligence” rollout. From on-device models to context-aware assistants, Google may have just redefined how we’ll all be using our phones in the years to come. But the real question is: will people actually switch from iPhone to Pixel? Let’s unpack it together.⏭️ Episode Highlights(00:50) - The clever Google Pixel 10 ad taking direct aim at Apple(03:40) - Gemini Live, Magic Cue, and other exciting new AI features in the Google Pixel 10 (10:07) - The role of context engineering in AI device development(12:40) - What this all means for Apple’s strategy moving forward(14:45) - Closing thoughts: Will you switch from Apple to Google?🔗 Links & ResourcesEpisode transcript with more resources on the Mindset AI blogRelated episodes:EP23 - What Is Context Engineering And Why Should You Care?EP20 - Apple Is Cooked—Here Are Three Reasons WhyIf 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

This week’s topic: Are we in an AI bubble? Sam Altman himself recently said yes—and called today’s startup valuations “insane.” Meanwhile, ChatGPT faced a user rebellion, and massive infrastructure investments are being announced at a scale that rivals entire industries. So what’s really happening? Are we watching history repeat itself with another dot-com-style bubble, or are we in the middle of something much bigger and more durable.In this episode of In The Loop, I break down Altman’s comments, explore the narratives driving the AI bubble thesis, and examine the data that both supports and challenges it. We’ll look at margins, adoption metrics, and infrastructure spending to separate hype from reality—and I’ll share why I think the truth might be more nuanced than the “bubble” label suggests.⏭️ Episode Highlights(00:40) – Sam Altman’s view on the AI bubble(05:50) — Reasons why people compare AI to the dot-com bubble(06:30) – Why I don’t think AI isin a bubble: user demand, pricing structure, and enterprise integration(11:55)-- Conclusion: two likely scenarios🔗 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

GPT-5 has finally arrived—but is it the AI revolution we were promised, or just a clever business move + marketing hypeAfter months of speculation, heated debates, and a very memorable launch event, OpenAI has dropped GPT-5 into the wild. The reaction? Let’s just say it’s been… complicated. In this episode of In The Loop, I cut through the noise to give you the real story: what’s genuinely new, what’s actually useful, and what’s just marketing fluff.We unpack the features that could reshape coding forever—from massive context windows to hybrid reasoning models—and explore why GPT-5 might be less about pure AI leaps and more about aggressive pricing strategies aimed squarely at Anthropic and others. Expect real talk on the benchmarks, the “chart crimes,” and why prediction markets flipped on OpenAI minutes after the launch.⏭️ Episode Highlights(00:50) – Setting the scene: GPT model chaos, market shifts, and Anthropic’s growing lead(02:30) – What’s actually new in GPT-5: hybrid models, 400k-token context, and UI-savvy coding(07:30) – Benchmarks, reasoning gaps, and the hidden “model routing” system(10:40) – Prediction markets flip, “chart crimes” at the GPT-5 launch, and independent reviews(16:15) – Competitive threat to Anthropic and the enterprise coding market(17:25) – Closing thoughts: technical leap, business masterstroke, or both?🔗 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 

This summer, the AI landscape is evolving dramatically. Ambient agents are becoming essential, enhancing user experiences with long-term memory. Meanwhile, the 'pay-per-crawl' model disrupts the traditional web content system, impacting smaller publishers. Wall Street is treating computing power like a precious commodity, fueling a new gold rush for GPU futures. Websites are now being designed primarily for AI agents, not humans, signaling major shifts in technology and user interaction.

AI is reshaping work while corporate learning stays stuck. Compliance-first courses, born after Enron and locked into SCORM, waste time and budget. Companies spend $340B a year; 70% is forgotten within 24 hours. As automation threatens up to 800M jobs by 2030, workers need real upskilling-personalised, in-the-flow coaching, triage by need, and conversational support- not “click next” modules. Lori Niles-Hofmann has spent 20+ years inside L&D across banking, consulting, and marketing, leading large digital transformations and building data-driven frameworks that turn L&D from support to strategy. She’s published courses with 100K completions, serves on EdTech/HRTech boards, and wrote The Eight Levers of EdTech Transformation. Her ER “triage” insight—sparked by a chaotic airport-to-hospital day—explains how to prioritise skills, kill duplication, escape SCORM’s limits, and move to AI-powered learning coaches tailored to each person’s work.⏭️ Episode Highlights(03:12) – The compliance trap: Why early e-learning became "legal documents to protect the company" rather than actual learning(07:02) – Meet SCORM: The 25-year-old technical standard that has trapped corporate learning in "click next to continue" modules(12:22) – Lori's vodka-fueled revelation: How a hospital emergency room visit revealed the solution to broken workplace learning(15:06) – The triage model: Why learning should work like an ER- prioritized by need, personalized by context(18:28) – The AI future: Learning coaches that know your calendar, projects, and work context to provide just-in-time development🔗 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.Where to find Lori:LinkedIn Personal websiteHer consultancy The Eight Levers To EdTech Transformation Book🤝 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 

Episode Description:In just ten days, OpenAI went from market leader and top dog to a series of very painful events that threaten its market leadership. This episode breaks down the dramatic collapse of their $3 billion Windsurf acquisition, the power play from Microsoft that unraveled it, and how Google swooped in for a surgical “hackquisition.” But that was just the beginning.We unpack how Elon Musk’s Grok 4 leapfrogged OpenAI’s GPT lineup to become the best AI model in the world (for now), and how Meta pulled off the most aggressive talent raid in recent memory with jaw-dropping offers and the promise of research freedom.This isn't just a bad week. It might be the turning point where OpenAI's grip on the AI race starts to slip.⏭️ Episode Highlights(00:35) - $3 billion Windsurf AI acquisition deal collapses(03:00) - The Microsoft partnership agreement lands Windsurf AI's technology in Google's hands(07:35) - Elon Musk's Grok 4 beats the best ChatGPT models(09:45) - Meta talent war continues: Mark Zuckerberg pouches 20+ AI researchers from OpenAI(11:40) - What does this all mean for OpenAI?🔗 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

Context engineering is more than just the latest AI buzzword—it’s shaping up to be the future of how we build truly intelligent systems. In this episode of In The Loop, I explore the shift from prompt engineering to context engineering, why this evolution matters, and how it impacts the effectiveness of AI agents. If you’ve ever wondered why some AI tools feel magical while others fall flat, context engineering holds the answer.I unpack what "context" actually means in the world of AI—from prompts and system instructions to long-term memory and external data. You’ll hear how building multi-agent systems without proper context coordination often fails, and why simpler, sequenced workflows are currently more effective. Whether you’re building AI products or simply using tools like ChatGPT, this episode will change how you think about how they work.⏩ Episode Highlights(01:00) - What is context engineering—and how is it different from prompt engineering?(09:20) - What role are orchestration and multi-agent systems help maintain context and improve p(16:05) - The impact of context engineering: personalization, privacy, and better UX(16:00) - Closing thoughts: what this means for the future of AI🔗 Links & Resources:📖 Episode 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

In this episode of In the Loop, I bring you a very top-of-mind topic: how AI is transforming the job market—but this time, we’ll focus on the jobs AI will create. I unpack a recent New York Times article that outlines 22 new roles AI is expected to create, and contrast it with a powerful historical perspective on the Luddites, offering a surprising lens on the current AI discourse.This isn't just about technology—it's about people, work, and the way progress reshapes our lives. From fears of job loss to the deeper ethical and societal implications, I explore the big questions: Should we slow down innovation to protect current livelihoods? Or do we owe it to the future to push forward, even if the transition is tough? Whether you're anxious or excited about AI, this episode brings clarity, context, and a little hope.⏩ Episode Highlights (00:50) - Exploring the global tension around AI and economic anxiety.(04:50) - A little history: Did the Luddites have a point? What they really fought for and what we can learn.(09:20) - Why today’s comforts are built on past generations’ risks.(11:15) - AI job displacement vs. AI job creation: 22 new jobs AI will create.(16:25) - Closing thoughts: Compassion for a successful AI transition.🔗 Links & ResourcesNew York Times article: 22 New Jobs AI Could Give YouEpisode 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

This week, I’m diving into one of the most insightful pieces of research I’ve come across lately—a report by a16z based on interviews with over 100 enterprise CIOs across five industries. If you’re building, selling, or using AI in a big company—or just trying to understand how enterprise AI is evolving—you’ll want to hear what’s really driving AI adoption at scale.In this episode of In The Loop, I break down three of the most interesting trends from the report that totally shifted how I think about enterprise AI today. From the dramatic shift from “build” to “buy,” to a budget explosion that shows just how serious companies are about integrating AI, to how wrong we all were about model consolidation—this research is packed with mind-blowing insights. Whether you're a SaaS founder, enterprise tech leader, or AI enthusiast, there's something in here for you.⏩ Episode Highlights(01:00) – Why enterprises are ditching "build" for "buy" when it comes to AI solutions(06:40) – Budget explosion: AI spending grows 75% beyond expectations(09:55) – Customer-facing AI: the next wave of enterprise adoption(11:10) – How wrong we were about LLM consolidation—and why multi-model is the future(16:45) – What this all means for builders: why it’s time to move faster than everLinks & Resources🤖 Check out Mindset AI’s customer-facing embed AI agents📊 a16z How 100 Enterprise CIOs Are Building and Buying Gen AI in 2025📖 Episode transcript + graphs on the Mindset AI blogIf you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀

In this episode of In The Loop, I unpack what feels like a turning point for Apple—and not in a good way. From a lackluster WWDC 2025 filled with buzzwords instead of breakthroughs, to a baffling research paper, The Illusion Of Thinking, that downplays the entire AI industry, Apple seems more confused than ever about its future.And then comes the gut punch: Jony Ive, the design visionary behind nearly every iconic Apple product, has joined forces with OpenAI to shape the next era of AI hardware. It’s a move that says more about Apple’s current state than any press release or gimmicky marketing campaign ever could.I’ll break down the three major signals that Apple may be spiraling. ⏩ Episode Highlights(00:50) - Apple WWDC 2025 keynote letdown: Liquid Glass instead of Siri innovation(02:50) - Reason 1: Siri’s downward spiral and Apple’s decade-long AI fumble(07:05) - Reason 2: The controversial Apple research paper on AI reasoning (The Illusion of Thinking)(11:10) - Reason 3: Jony Ive joins OpenAI to design the next generation of AI devices(13:50) - The big takeaway: Apple’s lost identity and the cost of playing it safe🔗Links & Resources:🎧 EP9 - Apple’s AI Crisis Exposed: Is It Having A Nokia Moment?🍎 Apple’s The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity📖 Read the written version of this episode on the Mindset AI blog (with all relevant links and resources). Read here.If you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends. 🚀