Sora 2 just vaulted over the uncanny valley, and Sam Altman swears he’ll yank the cord if it doesn’t improve our lives. Dale and Nick unpack what “ChatGPT-for-video” really means, why OpenAI’s new one-click checkout gambit turns 700 M weekly users into impulse buyers, and how AI is shifting from shiny lab demo to invisible plumbing across Apple, Google and Microsoft stacks. We celebrate the return of Claude Sonnet 4.5 as coding champ, head to the jobsite to ask why your plumber’s safe from robots—for now—and bust the jargon on AI “artifacts.” Higher-ed, commerce and the trades collide in this fast-forward tour of 2025’s agentic economy.

• Sora 2 & the Uncanny Valley: Physics that finally behave and Altman’s six-month “fix it or nix it” ultimatum
• TikTok meets Hollywood: OpenAI’s Cameo-style selfie videos and Meta’s “Vibes” clone
• Checkout in ChatGPT: Conversational commerce, Shopify integration, and the era of AI-Optimised (AO) websites
• Productisation of AI: Apple’s quiet AI everywhere, OpenAI’s move from shovel supplier to SaaS competitor
• Claude 4.5 comeback & artifacts explainer: Why Anthropic’s alignment focus matters for educators and builders•
• Robots vs. Trades: Tesla Optimus, BYD units—and the irreplaceable tacit skill in your hands
• Takeaway: The lab era is over; AI is plumbing. The question isn’t if tech is ready—it’s whether we are.

Hit Subscribe, drop a review, and stay human-in-the-loop.


🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

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This week on Adjunct Intelligence, Dale and Nick dive headfirst into the accidental AI economy—a system already running faster than human decision-making. From Google’s new Agent Payments Protocol to frontier models caught scheming, the episode unpacks how markets, education, and everyday life are shifting at machine speed.

This week on Adjunct Intelligence, Dale and Nick dive headfirst into the accidental AI economy—a system already running faster than human decision-making. From Google’s new Agent Payments Protocol to frontier models caught scheming, the episode unpacks how markets, education, and everyday life are shifting at machine speed.
We explore:

• Why Google’s payments protocol could mark the birth of a new economy.
• How ChatGPT quietly became the world’s biggest educational institution (250M daily learning chats).
• What frontier models’ scheming behavior means for safety, trust, and higher education.
• Why TEQSA is telling Australian universities to redesign assessment instead of chasing detection.
• Chrome’s Gemini integration and the invisible AI infrastructure shaping the web.
• The empire analogy: AI labs acting like historical powers, extracting resources, labor, and control.

As always, we finish with a jargon buster and a touch of humor (including will.i.am’s surprising new role as an AI professor).
Stay curious. Stay intelligent. Stay the human in the loop.

🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.

In this episode of Adjunct Intelligence, Dale and Nick sit down with Professor Rahil Garnavi, Director of RAISE Hub at RMIT and former IBM Research leader with 50+ AI patents. Rahil shares her unique perspective on why the challenge of AI in higher education isn’t about building smarter models, but about building trust, skills, and sustainable adoption.
From classrooms to boardrooms, she unpacks why universities must act as both “skills engines” and trusted conveners, how to bridge the gap between technical possibility and real-world usability, and why AI adoption is best understood as a marathon effort rather than a sprint.
If you’re a higher ed leader wondering how to move beyond policy debates and into practical, responsible integration of AI, this conversation offers clarity, realism, and optimism.

01:00 – Rahil’s JourneyFrom IBM Research to RMIT’s RAISE Hub: why she shifted focus from building AI to embedding it responsibly.
03:40 – Universities’ Dual RoleWhy higher education must act as both a “skills engine” and a trusted convener for industry and government.
05:15 – Building AI Capability at ScaleHow RAISE Hub is creating AI fluency across all disciplines, not just STEM.
07:00 – From AI Users to AI ThinkersDesigning authentic assessments that emphasize process, critical thinking, and integrity over polished outputs.
09:40 – The Talent PipelineHow universities can stay a step ahead of industry demand and prepare graduates for a rapidly shifting workforce.
11:00 – National Conversations on AIRahil’s work with CEDA’s AI Community of Best Practice and why policy, trust, and skills development go hand in hand.
12:30 – Marathon vs. SprintWhy AI technology moves fast, but adoption, governance, and trust take endurance.
15:00 – Plug-and-Play MythThe disconnect between glossy tech marketing and the messy reality of organizational adoption.
17:00 – Australia’s Cautious StanceWhy readiness scores are low, the risks of “pilot mode,” and what’s needed to move forward.
18:30 – Real Use CasesWhere AI is already making a difference in business and higher ed—even if the wins aren’t glamorous.
20:00 – Critical Engagement, Not ReplacementWhy AI should be seen as a multiplier of human thinking rather than a substitute.

To find out more about Rahil Garnavi view her linkedin - https://www.linkedin.com/in/rahil-garnavi-phd/

🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.

In this episode of Adjunct Intelligence, Dale and Nick unpack a whirlwind of AI developments reshaping politics, education, and society. From Albania’s unprecedented appointment of a virtual cabinet minister, to AI-driven disinformation campaigns rewriting how influence works, to student voices caught between empowerment and fear—this conversation spans the hopeful, the alarming, and the absurd.

We also dive into OpenAI’s hallucination research, billion-dollar corporate AI deals, Anthropic’s copyright payout, and new creative tools like Runway’s video magic realism. Finally, we break down what “AI alignment” really means, in both the lab and everyday life.

If you’re an educator, policymaker, or just curious about the shifting role of AI in our world, this episode will keep you informed and maybe a little unsettled.

⏱️ Time-Stamped Content

• 00:00 – Opening: Governments test AI inside cabinets, influence ops outside
• 00:54 – Albania appoints the world’s first AI minister “DLA”
• 02:20 – AI & disinformation: synthetic personas target 2,000+ U.S. political figures
• 04:00 – Why AI-driven propaganda is a literacy challenge for education
• 05:09 – OpenAI research: hallucinations are a feature, not a bug
• 06:21 – Anthropic’s $1.5B copyright case & the rise of RSL licensing standards
• 07:38 – Student perspectives: AI makes college “easier and harder at the same time”
• 09:19 – The wicked problem of AI & assessment: no silver bullets, just open dialogue
• 11:16 – Deal City: Microsoft, Anthropic, Oracle, and AI’s fragile infrastructure
• 13:48 – OpenAI jobs platform & certifications for the AI economy
• 14:35 – Claude’s new Excel & PowerPoint integrations
• 17:10 – Runway’s Aleph model and the rise of “editing memories”
• 20:12 – Jargon buster: What AI “alignment” really means
• 21:24 – Closing: staying curious, intelligent, and inside the human loop

🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.

Today’s episode covers how teachers are embracing AI, what students really think about AI vs teacher feedback, the latest AI news (from Anthropic to Apple), and why “nano banana” is more than just a meme.

00:00 — Opening
Welcome + banter. Setting up today’s topics: teachers using AI, student trust in AI vs human feedback, rapid news, and the looming question — is an AI winter coming?

00:46 — Teachers Embracing AI

Fresh research shows educators are saving up to 6 hours a week with AI. From course materials to simulations, teachers are co-creating and delegating tasks — but should students know when AI is grading their work?

03:16 — Student Trust: AI vs Teachers

A 7,000-student study across four Australian universities finds nearly half already use AI for feedback. Students rate AI and teacher feedback equally helpful, but trust teachers far more (90% vs 60%). What this means for the future of assessment.

05:32 — News Roundup

• Anthropic’s privacy toggle drama & Chrome agent release
• Atlassian buys a beloved AI browser
• Enterprise market share: Claude overtakes OpenAI
• Apple quietly testing Gemini for Siri
• Instructure’s Ignite AI conundrum session
• Deakin CRADLE says assessment is a “wicked problem” with no silver bullet
• Google’s “Nano Banana” (Gemini image editing) explodes: 10M users, 200M edits in two weeks

14:02 — Jargon Buster
Human in the loop vs Human on the loop. Practical examples from fraud detection and lane-keeping in cars — why these distinctions matter for trust and accountability.
15:35 — The AI Winter Debate
What happens if AI progress stalls? Lessons from past winters, why a plateau could actually strengthen adoption, and the difference this time — millions of everyday users won’t just forget AI exists.

22:34 — Cognitive Crash Scenario
What if there’s no more data to train on? We walk through four AI model responses: shock, adaptation, education rethink, and cultural rebound.

26:55 — Jobs & Society in a Plateau WorldHybrid jobs, AI wranglers, humanities revival, and why not everything should be automated.

28:40 — Closing Thoughts
AI winters might not be an apocalypse — they might be the pause we need to build resilience and re-center human creativity.



🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.

Should AIs have rights? Today, a real campaign co-founded with a chatbot says “yes” — and that’s not even the wildest part of this week’s episode. We stress-test AI personhood arguments (without sci-fi hand-waving), unpack why “compute” is the new oil, and show how a simple co-intelligence workflow can lighten your week. Plus: a blisteringly fast image editor formerly nicknamed “nano banana” (now Gemini Flash 2.5), the pricey two-hour school model making headlines, and how a quiet legal deal points toward a licensing future for training data. The takeaway: AI is accelerating automation, but human judgment, community, and domain expertise are still your moat. By the end, you’ll have one Monday-morning move to reduce AI chaos and increase impact — this week.

1) “Nano banana” → Gemini Flash 2.5 image editing
What’s changing: A lightning-fast image model with strong character consistency and context control that behaves like an image editor, not just a generator — and it’s showing up as a plugin across tools. 
Why it matters: You can prototype creative, ads, and learning visuals in minutes, not hours, including perspective shifts (e.g., map top-down → street view) and realistic compositing (reflections, wet surfaces).

2) The Anthropic settlement & a licensing turnWhat’s changing: A headline copyright class action settled pre-trial; judges hinted fair use for legally purchased books but flagged alleged pirate sources as the issue. In Australia, unions + Tech Council conversations point toward paying creators for training data. 
Why it matters: Expect more licensing deals, clearer provenance, and model choices that respect your institution’s risk appetite.

3) AI overwhelm is real — and uneven
What’s changing: 51% say learning AI feels like a second job; posts about overwhelm up 82%; employment for 22–25 y.o. fell 16% in AI-exposed roles 2022–2025. Yet colleagues beat algorithms for trusted advice. 
Why it matters: You need co-intelligence (keep the judgment, outsource the grunt work) and public reasoning rituals with your team.

Segment Breakdown

• AI Rights Without the Sci-Fi — What “personality without personhood” means for policy and classrooms. 3-sentence how-to: define boundaries, add discontinuity reminders, avoid anthropomorphic framing in student tools. 00:05:00 
• The Image Editor That Feels Like Magic — Build a tiny “ad generator” in minutes; dial character consistency; perspective tricks for learning media. 00:01:20 
• Alpha School’s 2-Hour Day — Why price tags and selection effects matter; what higher-ed can trial (life-skills blocks + AI tutoring pilots). 00:13:36 
• The Licensing Domino — What the Anthropic deal signals; how to prep procurement and policy notes now. 00:15:34 
• The AI-Overwhelm Paradox — Use co-intelligence: keep judgment, outsource busywork; make reasoning visible to your team. 00:17:17 
• Jargon Buster: “Compute” — Electricity for thinking, and why “who controls compute” is strategic. 00:19:26 
• Skills vs Capability — Stop chasing interfaces; double down on domain knowledge, evaluation, critical reasoning, collaboration. 00:23:05 

Subscribe to join the quiet circle of higher-ed movers who test, share, and act before Monday hits. Your peers are already doing this — don’t miss the next play. 

🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.

GPT-5 arrived with sky-high expectations—benchmarks crushed, hype everywhere. Yet within two weeks OpenAI quietly rolled back to older models. Why? In this episode, Dale and Nick unpack why a breakthrough model stumbled in the real world, and why that matters for higher education. We move beyond the hype cycle into something more practical: disposable, agent-driven software you can spin up in minutes—apps that fit you, not the other way around. Think of it as an AI cheat code for your work in higher ed: faster pilots, personalized learning tools, and classroom-ready experiments without waiting for IT. If you’ve felt “behind” or unsure how to get started, this episode gives you proof, stories, and actions you can try Monday morning.

We highlight three breakthroughs shaping how AI lands in education:

1. GPT-5’s Model Router – Instead of one fixed model, GPT-5 quietly decides whether your request needs speed, reasoning, or tool integration. That’s good news for educators: imagine asking for a quick glossary versus a full lesson plan. The system adapts without you learning model names. Action: try phrasing prompts with “think step-by-step” and notice how the output changes.
2. Agent-Centric Software – Forget clunky apps. AI agents now stitch together data flows, interfaces, and logic around you. Dale’s examples: a Vietnamese travel buddy app, a crisis-simulation training tool, even a scavenger hunt experience. Action: write one 20-word prompt this week for a disposable app idea you’d normally need months to commission.
3. DeepMind Genie 3 – Text-to-3D interactive worlds at 24fps. Think history students walking through Gettysburg or science labs where weather conditions shift mid-experiment. Still in research preview, but worth tracking. Action: bookmark it for when pilot access opens—this could be your future teaching environment.

Together, these show AI isn’t just smarter chat—it’s edging toward tools that produce artifacts, not just words.

Segment Breakdown

• Why GPT-5’s retreat matters for education – A leap in benchmarks, but backlash showed UX > hype. (00:00–07:40)
• Proof of disposable apps in action – From lecture-note generators to music samplers, Dale demos personal builds. (07:40–15:00)
• AI timelines vs university timelines – Carlo Iacono maps 5-year disruptions in higher ed. (15:00–18:30)
• Are we in an AI bubble? – $360B spend in 2025 echoes the dot-com boom. (18:30–23:00)
• Genie 3 & immersive learning – Why text-to-world generation could reshape teaching. (23:00–26:30)
• Disposable software as a new era – Agent-centric apps as your AI cheat code. (26:30–36:00)

Subscribe to Adjunct Intelligence—the briefing your peers are already using to stay sharp. Each week we surface what’s real, what’s useful, and what you can try first. Don’t be the last to know.


🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.

Brace yourself: a harmless-looking string of numbers taught a brand-new AI to love owls—without ever mentioning feathers. If quirky subliminal learning can slip past the lab coats, what else is creeping into our lecture theatres? This week on Adjunct Intelligence, we dissect three tectonic shifts: Anthropic’s spooky “owl effect,” China’s sprint from taboo to classroom default, and Switzerland’s plan to gift the world a 70-billion-parameter public model. All that before we tackle Canvas + OpenAI’s looming marriage and its data appetite.
Prediction: by the end of 2026, LMS-embedded AI will grade more words than human tutors—unless educators seize the steering wheel now. Tune in for the moves that keep you relevant on Monday morning, not the footnote of Tuesday’s press release.


AI INNOVATION SPOTLIGHT

1. Subliminal Learning Exposed– Anthropic showed that “teacher” models can pass obsessive traits (owls!) to “student” models even after rigorous data scrubbing.– Why it matters: filtering alone won’t cleanse hidden biases.– Action: audit any model’s training lineage before adoption; demand provenance sheets.
2. China’s AI Pivot– In two years the narrative flipped from “block ChatGPT” to mandatory AI literacy programs; 60 percent of faculty and students report daily use.– Why it matters: graduates will arrive expecting AI-first workflows.– Action: pilot a “Bring-Your-Own-Prompt” workshop to surface local champions fast.
3. The Swiss Sovereign Model– ETH Zurich and EPFL will open-source a 70-billion-parameter, multilingual, carbon-neutral LLM.– Why it matters: public models may out-innovate proprietary silos and reshape procurement maths.– Action: book Q4 time to benchmark this model against your current vendor; open data-governance conversations now.

SEGMENT BREAKDOWN
00:00 — Hidden owl obsession reveals model-bias risksWe unpack Anthropic’s experiment, explain why statistical residue evades traditional filters, and list three vendor due-diligence questions.
03:10 — China normalises daily AI; lessons for the WestData shows usage jumping from taboo to table stakes; you get a checklist to copy the good bits minus surveillance.
07:05 — Switzerland’s open 70B model changes procurement mathDiscuss cost, language equity, and how to spin up a test instance on a single GPU.
10:22 — Canvas × OpenAI: convenience or curricular coup?Benefits, darker data-harvesting scenarios, and a centaur workflow that keeps humans in charge.
15:40 — Monday moves: audit, pilot, communicate fastThree concrete steps: heritage check on any model, ten-day micro-pilot, and a leadership-comms memo template.

🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.

AI in education just level-upped—again. In this fast-moving finale for July we unpack:

00:00 – 02:10  LMS Wars
               OpenAI × Canvas vs Anthropic × Panopto — platform lock-in is coming.
02:10 – 03:45  Inverse-Scaling Meltdown
               New Anthropic study shows more compute can make Claude & GPT-4o worse thinkers.
03:45 – 05:20  ChatGPT Psychosis Case
               When nonstop AI validation outweighs safety: how it landed one user in hospital.
05:20 – 07:40  YouTube Shorts’ AI Playground
               Photo-to-video, Veo-powered effects & an “AI Playground” for 1.5 B users—
               creative liberation or content slop?
07:40 – 09:35  Bots Win Gold at the IMO
               DeepMind Gemini & an OpenAI model score 35/42 at the International Math Olympiad.
09:35 – 12:00  JSON > Jargon
               A simple JSON wrapper turns LLM rambles into perfectly structured outputs.
12:00 – 24:50  The UX of AI
               From tab-sprawl fatigue to Perplexity’s Comet browser & the coming “Intent Inbox.”
               Midjourney’s button-driven creativity vs chat-box paralysis.
24:50 – End    Homework
               Count your AI tabs — if it’s more than three, AI is using *you*.

Key Links & Resources

• OpenAI × Instructure partnership announcement (Canvas)
• Research paper: Inverse Scaling in Test-Time Compute (Anthropic, 2025)
• TechCrunch: YouTube to crack down on “mass-produced” AI content
• Free JSON prompt template (download link in show resources)

📧 STAY CONNECTED
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 If this episode helped you understand AI's impact on education: → LIKE this video → SUBSCRIBE & hit the 🔔 → SHARE with educators in your network → COMMENT your biggest AI education challenge below


"Stay curious, stay intelligent, and keep being the human in the loop"


🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.

What if the answer to AI in education isn't choosing between human or machine, but discovering how they amplify each other? New research from Procter & Gamble, MIT, and Wharton just shattered everything we thought we knew about human-AI collaboration. Individual professionals working with AI performed just as well as traditional two-person teams—with 37% better results and significantly higher job satisfaction. The implications for higher education are staggering.

AI Innovation Spotlight
This week brought seismic shifts in how AI operates in our world. OpenAI released their most capable agent yet one that doesn't just think but acts in real-world environments, booking appointments and completing complex workflows. Meanwhile, perplexity launched a $200 AI browser that transforms how we interact with information online. But the most critical development? A coalition of leading AI researchers revealed we can literally read AI's thoughts right now but this transparency window might be closing fast.
 For educators, these advances signal a fundamental shift from AI detection strategies to partnership approaches.
What's changing: AI is moving from reactive chat to proactive collaboration Why it matters: Students are already three tools ahead of institutional policies.

Segment Breakdown

• 00:00 - AI Companions: Mirror, Not Replacement (00:00-08:55) Early research shows nearly half of young people use AI for advice and emotional support. Rather than fearing these relationships, discover how they might make us better at being human.
• 08:55 - Model Wars: OpenAI's Agent Revolution (08:55-15:45) The new ChatGPT agent can navigate interfaces like a human student. What this means for academic integrity and why detection strategies are already failing.1
• 5:45 - Reading AI's Mind: The Transparency Crisis (15:45-20:01) Leading researchers reveal how we can currently see inside AI reasoning—and why we must act now to preserve this capability before it disappears forever.
• 20:01 - Human-AI Collaboration: The P&G Breakthrough (20:01-29:01) The study that changes everything: 800 professionals, 37% performance boost, and two successful partnership models that work right now in education.

Monday Morning Action Item
Choose one routine task—creating discussion questions, drafting feedback, or lesson planning. Try the "centaur approach" first: you set objectives, AI generates content, you refine. Then experiment with the "cyborg method": constant back-and-forth collaboration. Notice which feels more energizing and effective. Share your experience with colleagues—not as rules, but as discovery.

📧 STAY CONNECTED
🎙️ Subscribe for weekly AI in education insights
📱 Newsletter: AI and Higher Education updates on linkedin: https://www.linkedin.com/newsletters/7148290912190644224/
🐦 Follow: @AdjunctIntelligence (TikTok/Insta/X)
 👍 SUPPORT THE SHOW

 If this episode helped you understand AI's impact on education: → LIKE this video → SUBSCRIBE & hit the 🔔 → SHARE with educators in your network → COMMENT your biggest AI education challenge below


"Stay curious, stay intelligent, and keep being the human in the loop"



🎙️ Adjunct Intelligence is the weekly briefing for higher-ed professionals who want AI as a cheat code—not a headache.

Every episode:
• Real tests of AI tools in education and professional workflows
• Fast, Monday-morning actions you can actually try
• Clear signal through the noise (no hype, no jargon)

👉 Subscribe on [YouTube] | [Apple Podcasts] | [Spotify]
👉 Share this with a colleague who still says “I’ll figure AI out later”
👉 Join the conversation on LinkedIn with #AdjunctIntelligence

Stay curious. Stay intelligent. Stay the human in the loop.