We are looking at a truly massive shift today.
Yeah, you see a late night OK Boomer post, you
add in a few drinks from Sam Altman. It really
just seems like standard social media drama,
but it actually exposes a massive hidden crisis.
It reveals the new brutal economics of AI. Welcome
to the Deep Dive. Beat, I am genuinely glad you
are joining us. It is great to be here. We have
a lot of ground to cover. There is just so much
noise in Silicon Valley. People get distracted
by superficial online arguments. But our mission
today is entirely different. Right. We are ignoring
the petty gossip. Exactly. We are cutting straight
through that surface noise. We want to understand
the real infrastructure war. It is happening
right beneath our feet. And it is completely
reshaping how you will work. We are tracking
a connected chain of events today. First, an
accidental anthropic price panic. That exposed
OpenAI's incredibly aggressive predatory pricing
response. Which revealed a total industry pivot.
Tech giants are absolutely desperate to launch
always -on AI agents. Right, and that shift is
literally splitting hardware. The physical chips
are being completely redesigned to support this.
It is a massive physical transition. And finally,
it all ends with a dangerous measurement crisis.
The industry is falling for something called
token maxing. Burning compute is the new dangerous
proxy for employee value. That last point is
absolutely mind -blowing. It's completely warping
software engineering. Let us start by looking
at that human drama. It accidentally revealed
a massive technical bottleneck. Anthropic recently
triggered an absolute riot among developers.
They really stepped on a landmine with this one.
Well, so they accidentally pushed a major update
to their docs. The update suggested CloudCon
was moving pricing tiers. It was jumping from
the $20 pro plan. Yeah. It was suddenly moving
to a $100 max tier. That is a five times price
increase happening overnight. I mean, imagine
building your whole startup on their API. Waking
up to that is absolutely terrifying. Anthropic's
head of growth had to step in immediately. Omol
Avasar desperately walked back the documentation
change. He was definitely doing damage control.
He claimed it was only a test for 2 % of users.
Right, but the other 98 % still panicked entirely.
The trust was already severely damaged in their
minds. This is exactly where Sam Altman entered
the conversation. He replied to the unfolding
drama with some late -night posts. He dropped
a very blunt OK Boomer on social media. He even
admitted he was having a few drinks. It was a
very... public, incredibly messy dunk on a rival.
OpenAI's leadership doubled down on the threat
immediately. They explicitly promised that Codex
will remain on the free plan. They also guaranteed
it stays on the $20 plus plan. They basically
boxed Anthropic into a massive financial corner.
But the real story is much deeper than a tweet.
Anthropic eventually admitted their older plans
were breaking. They simply were not built for
the reality of 2026. The technological landscape
totally shifted under their feet. The core issue
driving this is long horizon sessions. Let us
clarify what that means for a second. Yeah, that
is an important concept to define. These are
AI tasks that run continuously in the background
for hours. Exactly. They are not just answering
a single quick question anymore. They just keep
working autonomously while you sleep. But maintaining
those nonstop sessions? is incredibly expensive
it is literally bleeding anthropics profit margins
dry you just cannot offer unlimited background
compute for 20 bucks the raw server costs are
way too high The math just does not work for
an independent startup. It really does not. This
is where OpenAI's actual strategy becomes very
obvious. They are backed by massive Microsoft
-linked infrastructure. They are using this specific
moment to predatory price Anthropic out entirely.
It is a very clear, very aggressive corporate
threat. OpenAI can absolutely afford to lose
money on $20 coders. They just want to keep you
locked inside their ecosystem. Think of it like
offering an all -you -can -eat restaurant buffet.
You originally priced the buffet for average
everyday diners, but suddenly your customers
are professional competitive eaters. Beat. The
business model completely breaks under that kind
of volume. That is the perfect way to visualize
it. OpenAI actually owns the massive farm supplying
the buffet. Anthropic has to buy all their food
at expensive retail prices. They are getting
crushed by the supply chain. It really is a brutal
game of survival now. I have to ask, is OpenAI's
strategy actually sustainable or is this just
a temporary flex of Microsoft's wallet? It is
a temporary flex to starve the competition before
raising prices later. That makes total sense.
And that leads perfectly into the next major
shift. Yeah, the hardware pivot. Running these
always -on agents is financially brutal right
now. So how are these tech giants possibly justifying
this massive expense? By completely rewiring
their entire corporate ecosystems. They are changing
their hardware to make agents the default standard.
We are seeing major fundamental shifts in their
product offerings. OpenAI effectively killed
off their custom GPTs recently. Which is huge.
People really loved building those custom bots.
They did. But OpenAI launched codex -powered
workspace agents instead. These new agents handle
complex tasks for entire teams. And they operate
nonstop, even when you are completely offline.
Google is pushing the exact same strategy right
now. At Google Cloud Next, they announced major
workspace updates. They are trying to make AI
your new office intern. Exactly. Google also
launched a massive new investment fund. It is
a dedicated $750 million initiative. They want
to push AI agents into real traditional businesses.
And they are partnering with massive consulting
players to do it. Firms like McKinsey, Accenture
and Deloitte are leading the charge. They are
forcing enterprise adoption from the top down.
But to make that affordable, they have to fix
the hardware. Yeah, the physical chips. Google
is splitting its entire AI chip strategy into
two distinct paths. This is a direct calculated
attack on NVIDIA's dominance. It really is. One
physical chip path is dedicated solely to training
models. The other path is designed strictly for
running inference. Right. Training requires massive,
power -hungry clusters of data centers. But inference
just needs to be fast, cheap, and everywhere.
This physical split promises much faster performance
for everyday agents. Meanwhile, Microsoft is
also making massive physical infrastructure moves.
They are pouring $18 billion. into Australian
data centers. They are drastically boosting their
AI capabilities across that entire region. $18
billion is just a staggering physical commitment.
They're literally laying the digital pipes for
the next century. It is a huge bet on an agent
-driven future. But despite these billions spent,
consumer reality is seriously lagging. The grand
corporate promises rarely match our daily lived
experience. It can still feel incredibly frustrating
to actually use. For instance, you can now order
Starbucks. through ChatGPT. Yeah, I saw that.
But honestly, most regular users are not very
impressed. It sounds like a really cool futuristic
idea in theory, but the actual ordering experience
still feels clunky and slow. Ordering a simple
coffee should not require a massive neural network.
There are also some very serious security growing
pains happening. Anthropic is currently probing
a possible breach of its Mythos model. We should
probably clarify what Mythos is really quickly.
Go ahead. It is anthropic's newest foundational
AI model architecture. Exactly. And this potential
breach happened via a third party vendor system.
Thankfully, no core structural systems have been
compromised yet, but corporate security concerns
are rising rapidly over these powerful tools.
Consumer wins definitely exist, but they remain
remarkably simple. For example, using 12 specific
AI prompts to handle weekly meal prep. Oh yeah,
that is a great use case. Planning the menu,
building shopping lists, and prepping takes minutes.
It is honestly a brilliant way to save hours.
Those simple, targeted workflows are where the
real value lives right now. I agree completely.
In fact, I still wrestle with prompt drift myself
when these agents run too long. It is super common.
The AI just slowly wanders off the original task
entirely. Right. You ask for a quick summary
and you get a fantasy null. It requires constant
human supervision to stay on the rails. Which
completely defeats the purpose of an autonomous
background agent. It really does. So why split
the chips into training versus inference now?
Training builds the brain while inference runs
it, making everyday agents radically cheaper.
Splinter. welcome back to the deep dive we have
been talking about some massive infrastructure
changes we have established that these continuous
agents are incredibly expensive to run they are
always on and heavily subsidized by massive tech
companies the tech giants are bleeding billions
just to keep us hooked this leads to a truly
massive management problem for companies How
do managers know if they are actually getting
real value? It is a huge blind spot. Right now,
they are measuring the absolute worst possible
metric. They are aggressively optimizing for
all the wrong technical outcomes. We have officially
entered what is called the slop KPI era. That
is such a perfectly depressing name for a corporate
trend. The engineering industry is calling this
specific mindset token maxing. Yeah. The sheer
volume of token burn is becoming a dangerous
proxy for employee value. NVIDIA's CEO Jensen
Huang made a wild statement about this recently.
He did. He stated he would be deeply alarmed
by a specific scenario. He would be worried if
a $500 ,000 engineer did not burn massive compute.
He expects them to burn $250 ,000 in compute
tokens. He's literally demanding that his engineers
burn massive amounts of server juice. If they
are not burning tokens, he thinks they are not
working. The newsletter drew a brilliant, sobering
analogy about this broken mindset. It is the
ever clear versus fine wine comparison. This
perfectly captures why the current system is
so deeply flawed. Everclear is a cheap grain
alcohol that is 95 % alcohol. A 1937 Domaine
de la Romanée Conti is only about 13 % alcohol.
One is purely cheap fuel. The other is a complex
masterpiece. Exactly. But if your only metric
is that more equals better, the grain alcohol
wins. The cheap antiseptic -grade alcohol is
technically seven times superior to the vintage
wine. TokenMaxin treats nuanced AI output exactly
like cheap alcohol by volume. If a meta engineer
lands at the top of the token leaderboard, what
does it mean? Are they actually a highly productive
visionary software genius? Or did they just ask
the AI to translate war and peace into Hellenic
Greek 80 ,000 times? Wow. Yeah, they're just
spamming the data centers to guarantee their
annual bonus. Beyond the terrible performance
metrics, there is a severe technical cost. This
corporate obsession with sheer volume creates
something called context bloat. It is clogging
the pipes and slowing everything down across
the board. Let us define context bloat clearly
so we understand the mechanical problem. It means
stuffing massive, unneeded data dumps into the
AI before tasks start. You are basically blinding
the smart model with entirely useless information.
We see this clearly when people connect AI to
enterprise systems. They connect it to their
company networks via MCP. Which is a universal
translator letting AI read your private databases.
Then they recklessly dump entire massive Salesforce
databases into the prompt window. Whoa, imagine
scaling to a billion queries just burning through
server farms for a metric. Two sec silence. It
is incredibly wasteful. Think about judging a
novelist by the physical weight of their typewriter
ribbon. That makes no sense. You are ignoring
the actual story they wrote entirely. But that
is exactly what is happening in enterprise tech
right now. Volume is replacing vision. We clearly
need a much better way to measure actual tangible
value. A systems thinker named Lannan proposed
a compelling solution to fight the token maxer.
I really like his approach. He calls his new
measurement framework the Slop Index. The Slop
Index aggressively focuses on human quality over
pure compute volume. It focuses on measuring
neurons instead of counting artificial tokens.
It values actual human thought rather than raw
server compute cycles. But applying this index
requires one very expensive, unpredictable piece
of hardware. It requires a human being in the
loop. The slap index asks the only questions
that actually matter for a business. Right. Did
this specific digital output actually solve a
real human problem today? How does a company
actually transition from measuring tokens to
measuring neurons? They must stop praising volume
and start auditing the actual human business
outcomes. Let us bring all of these complex threads
together now. We started this journey with what
looked like petty, late -night social media drama.
Just a couple of billionaires arguing online
over a $100 price tag. But that tiny public crack
revealed the true hidden state of AI today. Tech
giants are quietly subsidizing an enormous ecosystem
of always -on background agents. They are fundamentally
rewiring global data center hardware just to
support this vision. The physical infrastructure
shift is permanent. There is simply no going
back now. It is the new normal. But we are falling
into a massive, dangerous trap along the way.
If we embrace token maxing, we completely destroy
the underlying value of the tool. Absolutely.
If we measure success by how much server juice
we burn, we fail. We just end up mass producing
an endless ocean of digital slop. We absolutely
have to measure the final outcome, not just the
mechanical effort. Which brings us to a final
provocative thought for you to deeply consider.
AI compute is rapidly becoming a perfectly subsidized,
endless cheap commodity. OpenAI and Google are
aggressively ensuring it remains cheap. through
their brutal price wars. The massive server farms
will keep humming no matter what happens next.
They are not turning those machines off anytime
soon. If that raw compute power is infinite and
practically free, something else shifts fundamentally.
Pure human thought becomes the absolute rarest
asset on the entire planet. That is profound.
Those natural neurons we talked about from the
slop index framework, they quietly become the
most expensive, highly sought after premium asset
in the world. That is a truly wild paradigm shift
to think about. Your genuine human insight is
the very last bottleneck remaining. So the ultimate
question remains, how are you protecting your
neurons? Thank you for exploring the deep dive
with us today. Out to your own music.