In today's episode, we're going to explore the leaked Open AI
memo that came out just over a week ago.
In that memo, Sam Altman said we're at a critical time for
Chatji BT. Open AI is now playing defensive
against Google Gemini 3. The prediction markets have
shifted dramatically, and Google sits at between 87 and 92% odds
to have the leading model by the end of this year versus Open AI
at just 8%. Three years ago, you could never
imagine something like that happening.
Chatji BT was just released and Google announced Code Red.
Google had their two previous founders come in, Larry Page and
Sergey Brin. They came back and did all
nighters to review code personally.
Those are the two founders of Google that had stepped back
from operations completely. Teams at Google were reassigned
overnight and all resources were reallocated.
It was in that year that it felt like the beginning of the end of
Google's dominance. Fast forward to December 2025
and things have changed dramatically.
In today's episode, we're going to explore the open AI situation
and see if it really is as bad as it seems.
OK, so this week is yeah, another week of being I'll.
The flu has caught me twice in the space of a month.
I'd make it make sense. I have no idea how that even
works. Recovering from a flu, having
like 3 or 4 days recovered and then suddenly catching it again.
So I'm still incredibly bummed up and feel very, very rough,
but the show must go on. So for today's episode, we're
going to start with what Code Red actually means because that
is what Open AI have just kind of announced in that leaked
memo. Well, if we break down what it
actually says, it's really quite interesting because in it he
actually broke down, and by him I mean Sam Altman, he broke down
6 big areas of focus for Open AI, which is ChatGPT
personalisation and customisation.
It's better model behaviour measured by the LM Arena
benchmarks, it's speed and reliability improvements.
It's reducing over refusals which have become just a massive
area of annoyance for most users on ChatGPT.
They're going to try and launch a new reasoning model which they
believe, although that it's just a claim, it's supposed to be
ahead of Gemini 3. And finally, image generation
improvements too. So Mark Chan, Opening Eyes Chief
Research Officer, has become personally accountable to
leading all daily progress calls on ChatGPT because fundamentally
this is a refocusing on ChatGPT as a core product.
So yeah, this is massive internal urgency at scale Open
AI, and it's gone from yellow warnings to a red warning, which
is their highest alert level internally yet.
Most coverage online so far has completely ignored the fact that
this wasn't a sudden change to, you know, code red.
Code red was the escalation of a crisis that began a good few
weeks ago. Now, back in October, Sam Altman
sent an internal memo to different team members warning
staff to expect quite a rough period of time, maybe even much,
much slower growth as well financially.
And he admitted in that memo that Google's been doing
excellent work recently in almost every single aspect,
particularly in pre training, which is an area that Open AI
really haven't been able to innovate in for quite some time.
So when Code Red has just dropped in December, it wasn't
panic, it was the second alarm bell.
And I think what's most telling with this announcement is the
things that they've actively said they're going to drop.
So all advertising plans, for example, are on hold, and they
were quite far along. You've heard me speak about this
quite a few times, saying how disappointed I would be to see
that happen inside a large language model.
But yeah, they were quite far along with that.
I mean, Android beta code actually found in late November,
explicit references to ADS, features, search ad carousels
and bizarre content. So yeah, opening I were really
building serious ad infrastructure and then forecast
they were going to make a billion dollars in free user
monetization by 2026, which is obviously now now been stopped
and halted as a project. And to me, this shows how
confident they must have been feeling at one point to be going
for ads. And that makes me incredibly sad
personally, that the ads were going to be brought into any
ChatGPT or large language model. To me, this shows how confident
they were clearly feeling at one point to even think about
bringing ads. And in fact, the CTO of an AI
startup called Hyperbolic posted a screenshot on X of Peloton
advertisements inside the conversation and he was paying
the $200 a month license. I mean, I've spoke about this
before some Altman a good three years ago said ads were
unsettling and and a less resort for a business.
And yeah, earlier this year, he then said he really loves how
Instagram do ads and thought opening I could bring some
really cool product ads into their platform too.
So yeah, they were clearly putting a massive amount of
focus there. Another area they're dropping is
shopping and health agents. So agents that help me buy
healthy things and do healthy things.
They've also paused the Pulse feature, which is that kind of
proactive morning briefing system that Sam Altman said it
was his favorite feature of ChatGPT.
I guess what does this tell us then?
It tells us that Open AI is consolidating its focus and its
effort. They're abandoning revenue
diversification just to double down on their core products,
which is ChatGPT, and the quality they're providing to
users, which has definitely, definitely dropped.
Some may say that it's a very risky bet given the amount of
financial pressures they're under, the fact that the
economy, everybody's talking about AI bubbles and things
going wrong. So there's a lot of pressure
there and they've got incredible financial targets to hit.
However, I do the exact same. I would want to focus on what is
winning most of the market and become the best in the world at
that thing. Because ultimately, if that
foundation dies off, it's game over.
And I mean, Steve Jobs famously said that it's just better to
have less products, but do them incredibly well and do
incredible marketing for those products and having lots of
random products in the market. That confuses everybody.
There's also a financial lens to all of this.
Now, I'm not going to spend too much time here because I feel
like there's so much discourse online about financial pressures
and economic bubbles that, you know, it's so boring.
But but yeah, open eye are of course, under lots of pressure.
So they're burning through cash at a crazy, crazy rate, you
know, $5 billion in losses in 2024, projected to be $8.5
billion this year. And HSBC analysts forecast that
they've got a $207 billion funding shortfall, so they're
short of $207 billion in funding from now to 2030.
And there was apparently some leaked financial figures that
they expect to lose up to $74 billion in a year.
The company's also committed to $1.4 trillion in infrastructure
spending over the next eight years.
And this is a really tough one because data centre
infrastructure needs to be built out to hit your growth targets.
So they'll look at the amount of users or products in the market,
therefore how much data centre capacity do they really need?
And based on the products they want to launch, they're going to
need more data centres and GPU's.
So naturally, that creates a fixed amount of spending on data
warehouse infrastructure. And if they don't commit to it
now, they won't have it in the future because it's not
something that you just, you know, it's not like buying a car
and going to the shop and driving away with it.
It needs to be built out for you.
So these are things that they can't escape from as a financial
and a business model. Well, gosh, it makes it very
expensive to run. And they're projected that
they're going to need $200 billion in revenue by 2030 as a
result just to become profitable.
And the current run rate is $13 billion.
And a run rate as a word, it basically means it's a, it's a
very simple and quick financial projection that essentially
takes your current short term revenue and earnings, say like
monthly or quarterly earnings, and then uses them to
essentially guess what your total yearly earnings would be.
So that means the math just doesn't work out.
They're not earning enough money per month and per quarter to
ever hit that amount. So they're going to have to just
keep growing bigger and bigger and faster and raise more and
more money to do it. And the way that that's going to
work out is having market dominance.
If they don't have market dominance, people don't believe
in the product. So they're not going to give
them that much money. You know, their valuation jumped
from about $157 billion in October 2024 to double that, so
double 150 billion to $300 billion by March of this year.
And then by October of this year it was at $500 billion.
Now for a what is technically a startup that is a 38 times
multiple on how much they actually earn.
And for context, NVIDIA huge earnings, they are trading at 24
times their revenue. So they're valued at 24 times
their revenue. Open AI is valued at 38 times
their revenue. So yeah, to achieve these crazy
numbers and market narrative and the amount of money that people
want to put into them, they have to be a dominant player in the
market. So Gemini 3 coming along and
potentially beating them is an existential threat, especially
because all of their competitors have access to better credit
than them. Google can get money easier and
quicker than Open AI. Now then if we go further and
look at what users are actually saying, 1 developer on the Open
AI community forum said basically because of all the new
changes, it's basically made ChatGPT as a subscription just
completely useless in most cases because either when they're
trying to do coding tasks it is overly verbose, but people who
are trying to do writing tasks, it's not verbose enough.
It's also got a big problem with over refusals as I've mentioned
before, which is when Open Eye just explicitly refuses to do
things for you. If you ask it what the very best
biscuit type is, it will say that you shouldn't be biased
towards biscuit types. 1 user asked for an explanation of
Russian Roulette and it refused to give them the rules even
though the question was just out of curiosity.
I actually tried to do this over the weekend as a test.
I wanted a series of questions of what would you do in this
situation and I wanted to make them either scary or cross and
rude and you just couldn't get it to work.
And then number one biggest problem is still sick of fancy
the model just agreeing with everything somebody is saying
and refusing to push back or giving false validation.
Now open air, I say they're going to be focusing on
personalization and customization.
So obviously they're trying to fix this, but most people are
wanting a model that is going to disagree with them.
Another major problem open air I've got here is the switching
problem. So one Reddit user perfectly
captured this. Claude smokes GPT for Python And
it isn't even close on my end. Another said that they switched
to Claude yesterday and it enabled them to build an entire
phone app and because of the context window it required you
to press continue 4 separate times so it ran out of context
and then needed to start again, yet perfectly started where it
left off and did a really really good job.
The benchmarks back all of this up on the SWE benchmark, which
is the gold standard for evaluating coding Cloud 4 Sonnet
scored 72% and GPT 4 O scored 33%.
And it also shows in the way that the world has adopted these
different language models. Cursor adopted Claude as their
main programmer language. GitHub did the same Windsurf
source graph, CODI, or bank code, they all did the same.
The financial impact of this is pretty massive.
Claude Code has hit a billion dollars in revenue in six
months, and Claude is out there acquiring a series of different
businesses to make their core code product even better.
So they're not just winning the market or head in the market,
They are investing extremely heavily into becoming the leader
and winner of that market. And you'll notice in the list of
priorities that I said some Altman laid out, coding wasn't
in there. So yeah, my read is that Open AI
is kind of quietly accepting and conceding that the market has
been lost for now for coding to Anthropic.
They've still got their codecs product out there.
They're probably going to still continue it, but clearly it's
not the main priority anymore. And it makes sense because
really they're having huge pressure from the consumer
market when it comes to Gemini and that's their main base of
users and revenue, 800 million ChatGPT users.
So yeah, they are facing huge competition and I think it's
worth spending a little bit of time on that competition.
On benchmarks, Googles Gemini 3 currently sits at #1 on the LM
Arena with a record 1400 score. Anthropic dominates 6 of the top
ten spot and Chat GBTS 5.1 is only in 6th place.
That's not terrible, but it's also not market leadership
because you know, on user metrics, ChatGPT still has 800
million weekly active user, which is which is just enormous.
And apparently according to open AI, they dominate with 70% of
all AI assistant usage. That's not going to last
forever. Gemini just jumped from 450 to
650 million active users and that's monthly active users.
So yeah, quite far behind open AI.
But they will and are able to catch up.
And that happened between July and October of this year.
And a metric that will really worry Open AI is session time.
Google Now has a better session time than Open AI. 7 minutes and
8 seconds versus 6 minutes and 25 seconds Open AI.
When users are spending more time with one product over
another, it probably will start to tell you something.
Unless of course the extra couple of minutes and Gemini is
spent being really frustrated, which I don't think is the case.
And chat GPTS daily active users dropped 6% recently.
They're also facing massive competition from an enterprise
market perspective. According to a mid 2025 report,
Anthropic now has 32% of enterprise market share versus
opening eyes 25%. Now just one year prior, Open
air had 50% and Anthropic just had 12%.
That's a massive reversal. Open AI also facing a massive
talent drain right now as well. Dozens of top researchers have
left for competitors, you know, Open AI CTO launch thinking
machines and recruited loads of incredible talent from Open AI.
Meta's new super intelligence lab obviously then poached
people aggressively too. And Mark Chen revealed how
intense this talent wall really is because Meta is spending $10
billion annually on acquiring AI talent.
And apparently Zook has been hand delivering people soup to
try and persuade them to come on board.
So yeah, no wonder the Open AI has has sounded the alarm and
made Code Red such a big priority.
See, over the next period, I think you'd need to be all
watching for a few things and I'll lay them out just now.
So I think first and foremost, the Code Red memo promised a new
reasoning model over the next few that's supposedly better
than Gemini's new model. Apparently Mark Chen, the chief
research officer, said that Open AI had succeeded in infusing a
smaller model with the same amount of knowledge than
previously was required for a big, large system.
This is important because when they throttle intelligence so IE
reduce the number of tokens and make everything very short and
concise, it just makes you feel like it's just stupider.
Every single person wants the most powerful, cleverest model
possible all of the time. A second thing to look out for
is user attention. So Chachi BT's engagement
metrics are still incredibly strong to 12.74 visits per
unique visitor. But Gemini's user base is
growing really quickly, as I said, from 450 million to 650
million in just a few months. People will be watching very
closely to see if Open AI's improvements in their product
leads to a more retained user base or just a slower attrition
and a slower decline. A third big thing to watch for
will be enterprise wins. The Fortune 500 market is
incredibly important to these products and if you see
Anthropic winning over and over again, well, it will tell you a
lot about where Open AI is heading. 4th is developer
sentiment. The coding market is where AI
accomplishes big long term value through API revenue to
integration, developers building products on their on their
platform. And right now Claude is owning
that conversation. Open AI has to close the coding
gap. See, there's some of the big
things that I've been looking for.
Now to conclude this episode, I think what I find so interesting
about this moment in time right now is that, you know, just
three years ago, smart money would say that Google was going
to struggle. You know, they've been caught
completely flat footed. The founders had to come back.
The panic was real. Market sentiment was very
negative. Yet today Google has the best
rank model in the world, the fastest growing user base in the
world and the infrastructure advantage from building their
own chips, their own products, just vertically integrated
product set, whereas Open AI are now in a position that Google
were in just a few years ago. The difference is Open AI
doesn't have Google's resources, They don't have distribution,
they don't have the hardware vertical integration, and
they're burning through capital are a crazy, crazy rate.
And they're having to fight a consumer war against Google.
Yeah, they're fighting a coding war against Anthropic and an
enterprise market war against Microsoft.
These are all very different markets with very different
dynamics. So, yeah, opening eyes, Code Red
really is a fantastic reminder that perceived market leadership
never lasts forever. However, Google's return also
shows that anything is possible. See, I hope you enjoyed today's
episode and I'll see you next week.