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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
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Jack Houghton
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TikTok - @jackschats
Mindset Ai
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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, while
Market 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 & 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. 🚀
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Jack Houghton
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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
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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 & 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. 🚀
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Jack Houghton
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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
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 & 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. 🚀
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Stay in the loop—even when you’re not listening to this podcast.
Jack Houghton
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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
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 & 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. 🚀
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Stay in the loop—even when you’re not listening to this podcast.
Jack Houghton
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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
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 & 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. 🚀
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Stay in the loop—even when you’re not listening to this podcast.
Jack Houghton
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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
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 & 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. 🚀
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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
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 & 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. 🚀
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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
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 & 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. 🚀
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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
There’s a new workplace jargon floating around: AI workslop. Coined by Stanford researchers, it captures a growing frustration with AI-generated content that looks polished at first glance but falls apart upon second look.
In this episode of In The Loop, I unpack what “ AIworkslop” really means, its cost to organizations, and most importantly, question whether it's a tooling issue or a human problem.
We’ll explore how the so-called “efficiency trap” is lowering quality standards at work, how overconfidence in AI training can backfire, and why domain expertise matters more than ever. Plus, I’ll share four ways to fix this problem so we can all spend more time producing work we’re actually proud of.
⏭️ Episode Highlights
(00:55) – What “AI workslop” actually is and why it’s becoming everyone’s problem
(05:30) – The “efficiency trap” and the four stages of AI workshop evolution
(10:25) – Centaur vs. cyborg approach: what good AI use really looks like
(11:00) – Four ways to fix the AI workslop problem in your team
(14:40) – Closing thoughts: Setting expectations instead of blaming tools
🔗 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. 🚀
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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
OpenAI just made its boldest move yet—and it’s not about a smarter model. It’s about owning the future of how we use AI. At DevDay 2025, OpenAI revealed a massive shift from raw intelligence to practical utility, unveiling the ChatGPT Apps SDK, their new agent builder, and a new context-capture system that could change how every app on the planet works.
In this episode of In The Loop, I break down what these announcements mean, why they matter, and how they all fit into OpenAI’s bigger plan to sit at the center of every human–AI interaction. From deep context integration to the risks of ecosystem lock-in, I’ll unpack the signal from the noise and what these moves tell us about where AI is heading next.
⏭️ Episode Highlights
(01:10) - The new ChatGPT Apps: OpenAI’s third and most ambitious attempt at a platform strategy
(07:10) - Deep context integration and how it could redefine every app interaction
(10:05) - Inside AgentKit: building AI agents and workflows without code
(14:00) - What this all means for the future of conversational AI technology
🔗 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. 🚀
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Stay in the loop—even when you’re not listening to this podcast.
Jack Houghton
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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
Imagine a world where your glasses can translate conversations in real time, display arrows on the street to guide your way, and let you respond to messages without ever pulling out your phone. That’s the promise behind Meta’s new Ray-Ban smart glasses, announced at Meta Connect. But despite all the futuristic potential, the launch wasn’t without its awkward demo fails. So, are these glasses a glimpse of our inevitable future, or just another overhyped gadget?
In this episode of In The Loop, I unpack the features that could make these smart glasses revolutionary—or doom them to obscurity. From live translations and accessibility breakthroughs to navigation, content creation, and the ever-present question of social acceptance, we’ll explore whether this could be the iPhone moment that changes everything.
⏭️ Episode Highlights
(01:00) – Meta Connect recap and the specs of the Ray-Ban smart glasses
(04:00) – What can you use the Meta Glasses for?
(04:50) – Live captions, translations, and accessibility use cases
(06:30) – Navigation, content creation, and privacy concerns
(08:00) – Message triaging and hand-free texting
(09:07) – Camera, content creation, and related privacy
(10:15) – Speed of adoption: Price, user experience, social acceptance, and competition
(17:55) – My verdict: cautiously optimistic, but not yet at an iPhone moment
🔗 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. 🚀
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Jack Houghton
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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
This week, I’m unpacking a landmark move from the Federal Trade Commission: a sweeping investigation into AI companions. Seven of the biggest tech companies—Google, Meta, OpenAI, Snapchat, Character.ai, xAI, and Replika—now have just 45 days to reveal how their AI bots really work, how they protect young users, and how they monetize engagement.
In this episode of In The Loop, I explore why teenagers are so drawn to these AI “friends,” the real risks of emotional dependence, and the potential benefits that are often overlooked. From regulation and age checks to psychological impacts and the future of AI companionship, this is a conversation about what comes next for society as we enter an era where AI can become a confidant, a mentor—or something much more.
⏭️ Episode Highlights
(00:50) – Why the FTC’s investigation matters for the future of AI
(04:30) – What makes an AI companion different from a chatbot
(08:50) – Ethical and psychological considerations
(09:25) – When AI friendships turn toxic: emotional dependence and “ambiguous loss”
(12:50) – What regulation might look like: age checks, consent controls, and tackling manipulative design
(15:25) – Big-picture reflections: AI companions are here to stay, but how do we manage them responsibly?
🔗 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. 🚀
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Jack Houghton
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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
This week on In The Loop, I’m breaking down OpenAI’s staggering financial projections and what they reveal about the true cost of pursuing AGI. With spending expected to soar to $115 billion by 2029, the question is: where is all this money actually going—and can it really deliver the future OpenAI is betting on?
In this episode, I follow the money trail to uncover the massive investments in data centers, chips, and infrastructure that power AI. From the scale of Project Stargate to the risks of building custom hardware, I explore the economics, the environmental impact, and the high-stakes race among tech giants. By the end, you’ll have a clear picture of just how enormous—and risky—this journey to AGI really is.
⏭️ Episode Highlights
(00:40) - Why compute and training costs are driving massive investments
(06:20) - The cost of poser: The rising demand for energy and the environmental toll of AI infrastructure
(09:20) - The cost of training data: How copyright settlements could add billions to training costs
(10:40) - Historical parallels: railway mania, the dot-com bubble, and today’s AI boom
(11:45) - Closing thoughts: Will AI infrastructure spending outpace actual demand?
🔗 Links & Resources
Episode transcript with more resources on the Mindset AI blog
EP28 - Is The AI Bubble About To Burst?
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Jack Houghton
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TikTok - @jackschats
Mindset Ai
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Newsletter - https://bit.ly/ITLnewsletter
LinkedIn - https://www.linkedin.com/company/mindset-ai/
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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 & Resources
Episode transcript with more resources on the Mindset AI blog
Related episodes:
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Jack Houghton
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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
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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: three likely scenarios
🔗 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. 🚀
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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
GPT-5 has finally arrived—but is it the AI revolution we were promised, or just a clever business move + marketing hype
After 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 & 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. 🚀
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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
This summer, the world of AI has taken a sharp and fascinating turn. In this episode of In The Loop, I break down four powerful trends that are quietly—and not-so-quietly—reshaping the future of our digital economy. From AI companies being forced to pay for content, to Wall Street trading computing power like it's oil, things are shifting fast. And these aren't just random changes—together, they signal a much bigger story.
Let’s explore the rise of ambient agents, the monetization of web data, the financialization of compute power, and a surprising new twist in how products are being built not for humans but for AI agents. This is one of those episodes that connects the dots between what’s happening now and where we're all headed next. You don’t want to miss it.
⏭️ Episode Highlights
(00:55) - Trend #1: What are ambient AI agents?
(08:30) - Trend #2: Pay-per-crawl: How AI is disrupting the web’s free content model
(12:30) - Trend #4: Computing power as a commodity: Wall Street’s new gold rush into GPU futures
(15:20) - Trend #5: AX (Agent Experience) is here: Why websites are now being designed for AI, not humans
(16:30) - What these trends say about the bigger AI transformation ahead
🔗 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
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 & Resources:
If you enjoyed this episode, rate, follow, and share! It helps others stay ahead of the latest AI trends.
Where to find Lori: