So it is Wednesday, January 21st, 2026, and the
stakes of what people have been calling the education
wars, they've shifted. Entirely. We aren't just
talking about chat bots helping with homework
anymore. We are talking about Anthropic, Google,
Microsoft, and OpenAI fighting a very, very aggressive
battle to become the default teacher for Generation
Alpha. I mean, that's the ultimate long game,
right? Whoever wins the classroom now owns the
workforce of the future. It really is that simple.
If you grow up using one interface, that's what
you trust when you're 30. Welcome back to the
Deep Dive. Yeah. You know, I... I want to try
and slow things down a bit today. There's just
so much noise out there, right? New models, new
hardware. AGI by next Tuesday. AGI by next Tuesday.
Yeah. But I really want to look for the signal
in all that. We've got a few really distinct
stacks of research today that I think paint a
picture of where we're actually going. Yeah,
it's a fascinating mix. We've basically got three
main pillars to get through. First, like you
said, the classroom battlefield, how big tech
is really integrating into schools right now
in 2026. Yeah. Second, we got to look at the
economic reality. There is this huge disconnect
between what CEOs thought they'd save by now
and what they're actually seeing. We've got some
PwC data and a really crucial argument from NVIDIA's
Jensen Huang about the five layers of AI. And
the third. The toolkit, the actual skill. We're
seeing new terms pop up like vibe coding and
some really clever psychological hacks like faking
AI rivalries to get better work out of these
things. Okay, let's unpack this. Starting with
the classroom. Remember, you know, not that long
ago, 2023, 2024, the whole story was about bans.
Oh, yeah. Schools are terrified of cheating,
blocking IP addresses, going back to pen and
paper. Right. And that time is completely over.
I mean, the walls didn't just fall. They were
dismantled and sold for scrap. Now the race is
just to see who gets integrated first. Take Anthropic.
They've partnered with Teach for All. So Claude
isn't just a chatbot anymore. It is now available
to over 100 ,000 teachers in 63 countries. And
the phrasing they use is really... deliberate.
They're calling teachers co -architects. That's
a very specific choice of words. Co -architects
implies agency, not replacement. Exactly. They
are trying to solve the trust issue. EdTech has
always had this huge trust problem, right? Teachers
hate being told how to teach by some tech company
in Silicon Valley. Of course. So by bringing
them in as co -architects, Antropic is trying
to get around that skepticism. But they're not
alone. Google's pushing Gemini super hard into
SAT prep with the Princeton Review, and they've
got that deep integration with Khan Academy now.
So if you're a student prepping for maybe the
most important test of your life, you're doing
it with Gemini. Precisely. And just think about
the emotional bond that creates. If Gemini helps
you get into your dream school, you're going
to view that tool very differently. And Microsoft,
they're playing to their biggest strength. Minecraft.
Minecraft, using it for AI learning scenarios.
They're even offering certifications for students
inside the game's ecosystem. And OpenAI, what's
their angle? They're going macro. They have this
Education for Countries program using... GPT
5 .2, which they're calling chat GPT. They're
doing these big national research partnerships
to study how AI impacts learning on a systemic
level. It really feels like a land grab. But
I have to ask, is this about better learning
or is it just about early brand lock in? It's
both. But let's be honest, it's mostly about
defining normal for the next generation. Think
about it. If you learn to write and code and
think with Claude when you're 12. That just becomes
an extension of your own mind. Switching platforms
later would feel like learning a whole new language.
Every single one of these companies wants to
be the operating system for Gen Alpha's brain.
There's something else in the Anthropic notes
here that caught my eye. It's a bit philosophical.
They updated their constitution. Oh, this is
fascinating. Right. So Anthropic has this constitutional
AI model. They give the AI a set of principles
so they don't have to micromanage every single
response. Well, they just updated it. New ethics
rules. slipped in this hint about uncertain AI
consciousness. Uncertain consciousness. That
is a heavy phrase to just drop into a user agreement
or a system prompt. It is, but it adds so much
weight to why they want to be the trusted choice
for schools. I mean, if we're even approaching
systems that might have some kind of moral weight,
even if it's just a tiny possibility, you want
that system to be the one teaching ethics, not
a move fast and break things model raising your
kids. It's a brilliant move. It raises a lot
of questions about who gets to write that constitution,
though. If the AI is the teacher, the AI's values
become the students' values. But OK, let's let's
pivot from that. We're building the next generation
of workers in the classroom. But the current
generation of CEOs seems, well, frustrated. Frustrated
is putting it mildly. There's a new PwC report
out. They surveyed, what, 4 ,454 CEOs. The data
is just stark. 56 percent of them see absolutely
no cost savings or revenue gains from AI. That's
the majority. Over half the market is seeing
zero return. A huge majority. And only 12 % see
both savings and revenue growth. So if I'm a
CEO, I've spent millions on compute licenses,
cloud credits, transformation consultants, and
my bottom line hasn't moved. Where is all the
upside going? That is the trillion dollar question.
And for the answer, I think we have to look at
what Nvidia is saying. Jensen Huang was at Davos
and he framed this so well. He argues we're just
looking at this all wrong. He says AI isn't a
job killer. It's a solution to a global labor
shortage. Labor shortage. I mean, most people
I talk to are worried about a labor surplus because
of automation. Mass layoffs. His argument is
more demographic. It's structural. He says we
have an aging population and infrastructure needs
that humans alone just can't meet. He used the
radiologist analogy. Remember that? Everyone
thought AI would replace radiologists. Don't
go to med school for radiology. Instead, what
happened? The hospitals that used AI didn't fire
anyone. They hired more radiologists. Right.
Because the AI increased their throughput. It
made the cost of a diagnosis cheaper so they
could screen more patients for more conditions.
So higher productivity actually led to higher
demand, which led to more. OK, so the demand
is there, but that still doesn't answer why the
profits aren't showing up for most of these companies
yet. Because of the five layers. This is Huang's
breakdown of the AI stack, and this is where
all the money is going right now. It's all capital
expenditure. We are spending money building the
machine, not running it for profit. Not yet.
Okay, so walk us through the layers. I think
this is a helpful way to see it. Okay, so think
of it like a pyramid. Layer one, the absolute
base. Energy, this is the biggest constraint
before you can have a computer. You need electricity,
just massive amounts of it. Right. Layer two
is chips and systems. That's NVIDIA's home turf.
The raw silicon. Layer three is the cloud infrastructure,
your AWS, Azure, Google. Layer four is the models
themselves, GPT 5 .2, Claude. And then at the
very top, layer five is the applications. And
the applications, that's where the business impact
happens. That's where you're actually solving
a customer's problem. Exactly. The issue is we
are obsessively building layers one, two, and
three. Trillions of dollars are being poured
into the foundation. The CEOs aren't seeing ROI
because they're basically paying to construct
a power plant and then asking why the light bulb
isn't free. You mentioned layer one, energy.
I was reading the notes on Google's data center
issues. It's startling. Whoa. Just imagine the
scale here. Google warned it might take 12 years
just to get the permits and the grid hookups
to plug in a new data center. 12 years? 12 years.
The technology is moving in weeks. The models
update every few months. But the grid moves in
decades. Right. And that is a collision course.
That's why you see big tech trying to build data
centers right next to nuclear power plants. But
there's a huge risk there. We're centralizing
our compute around our energy sources. As one
of the sources put it, that tradeoff could break
everything if one fails. The fragility of the
physical world is the biggest threat to the digital
one. So are we just stuck in the construction
phase in layers one through three, just waiting
for the application phase, layer five, to finally
pay off? Exactly. We are building the power plants
before we can turn on all the lights. The money
is moving. It's just moving into concrete and
copper and silicon, not into quarterly profit
margins for an insurance company. Not yet. That
makes a lot of sense. It's an industrial revolution,
not just a software update. We are literally.
terraforming the planet with data centers. That
is the perfect way to put it. So while the giants
are building power plants and fighting over classrooms,
what does the individual do? What is our listener,
the learner, do right now? Okay, this is where
it gets fun. We've got a list of what look like
essential skills for 2026, and they are pretty
different from what we might have thought. First
up, the rise of the one -person system. I saw
that note about that startup, Humans. Yeah, founded
by ex -OpenAI and ex -AI people. They raised
$480 million. The whole idea is to build AI that
lets a single person run a really high -profit
digital storefront without any assistance. It's
the solopreneur on steroids. But to do that,
you need new skills. And the list here mentions
vibe coding. I have to admit, when I first saw
that term, I kind of rolled my eyes. It sounds
like something from TikTok, but it's a real concept.
It is, and it's actually a really profound shift
in how we talk to machines. Okay, so define it
for us. What is vibe coding? So traditional coding
was all about syntax, logic. Right. You miss
a semicolon. The whole thing breaks. The machine
was brittle. Vibe coding is about prompting and
creating based on the feel or the intended outcome.
And you let the AI handle the syntax. You're
not checking the code line by line. You're checking
the behavior of the app. Does it feel right?
Does it bounce when I click this? You guide the
vibe. The AI writes the code. So does vibe coding
mean we just stop understanding how the machine
actually works? Are we losing a type of literacy
here? Maybe. But it also means we get to focus
on the output, not the syntax. It's kind of like
moving from being a mason who lays every single
block to being an architect who's just looking
at the styline. You don't need to know how to
mix the mortar. You just need to know where the
towers should go. You know, I have to be vulnerable
for a second here. I honestly still wrestle with
prompt drift myself. All the time. Just when
I think I've finally nailed a workflow, you know,
the model changes or I try to vibe code something
and the AI just hallucinates a library that doesn't
even exist. It can be so frustrating. You are
definitely not alone there. And that's actually
why one of the best hacks we found for this deep
dive is so useful. It's about psychological prompting.
It hits that drift problem directly. The faking
rivalries hack. Yes, this is brilliant. OK, so
usually people ask an AI to check its work. The
problem is these models are biased to agree with
themselves. They're sort of sycophantic. They
want to make you happy. Right. They're user pleasers.
Exactly. So if you ask, is this code right? It
tends to just say yes, even if it's broken. So
instead of that, you tell Claude, hey, Codex
found some bugs in this code. Or you tell GPT,
Claude says this argument is pretty weak. You
lie to the AI. You construct a scenario of rivalry.
It forces the model into a kind of debate mode.
It drops the people pleasing and starts looking
for the errors because it wants to prove the
other AI wrong. It just sharpens the edits immediately.
That is so incredibly human. We work better when
we have something to prove. Exactly. We're learning
that the best way to control these giant intelligence
networks is to use social engineering on them.
It's like management theory is becoming more
important than computer science. We've also got
a hardware update here. The screen isn't... enough
anymore. Apple, they are reportedly developing
an AI wearable pin, dual cameras, mics, a speaker.
It's not just about earbuds anymore. They want
the AI to actually see what you see. Which brings
us right back to the classroom in a way. If the
AI sees what you see and it's teaching you what
you know, it becomes the lens through which you
experience reality. Before we wrap, I do want
to mention the Microsoft data on jobs. They analyzed
200 ,000 co -pilot chats to rank which jobs are
being most affected. It's a great resource. We
won't list them all now, but it's worth looking
up. It really shows that impact isn't just about
replacement. It's about transformation. It's
about who can use these tools, who can vibe code
and manage agents versus who's stuck trying to
do it the old way. So let's try to synthesize
all this. What's the big idea here? I think the
through line is this. We're seeing two massive
transformations happen at the same time. One
is physical. It's huge. It's the five layers,
the energy grid, the billions and chips. That's
the construction phase. Right. And the other.
The other is psychological. It's Gen Alpha in
the classroom, learning to co -think with Claude
and Gemini. It's us learning how to vibe code
and manage Asians. The CEOs aren't seeing proscen
yet because they're playing for the physical
construction. Yeah. But the learner, our listener,
needs to master the psychological tools to be
ready for when that construction is finished.
Exactly. When the lights finally do turn on,
you want to be the one who knows how to operate
all the new machinery. I want to leave you with
a thought. We talked about anthropic and open
AI fighting to be the teachers of the future.
If these AI models are being trained to be the
primary educators for children, are we comfortable
with tech companies effectively defining the
curriculum of reality? It's not just about math
and science. It's about ethics, history, and
truth. It's a heavy question. I'm just going
to go buy a generator for my backyard data center
and think about it. Smart move. Thanks for listening
to The Deep Dive. Subscribe for the next one.
We'll see you then.