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welcome to episode 52
Today we dive into AI's ongoing valuation correction
the margin trap
AI valuations are soaring
at approximately 40.6 times revenue
yet margins lag 20 to 25 points below SAS
this isn't hype it's a structural economics problem
where unsustainable growth will hit a wall
welcome to the Deep Dive
where we cut through the noise
to deliver those critical insights
you need to truly stay informed
today we're diving deep into a topic that's well
it's everywhere artificial intelligence
groundbreaking stuff transformative even
but is the financial foundation
actually as solid as all the hype suggests
we're looking closely at a really insightful article
it's titled The AI Margin Trap
why billion Dollar valuations
are built on 50 Cent Economics
by Danny the VC
published August 26th, 2025
and our mission here is really to peel back the layers
you know get past the buzzwords
and understand the actual economics driving this
exactly and this article
it just
nails this fundamental disconnect that's brewing
under the surface it's a huge tension point
you've got AI
companies valued like pure software businesses right
sky high expectations effortless scale
huge profits
but then you look at how they actually operate
their costs and it looks much more like uh
manufacturing yeah
capital intensive it's
this hidden conflict
that's really critical to understand
okay so you see all this money pouring in right
the article mentions what
a staggering $104 billion in venture funding
just in the first half of 2025
feels unstoppable
but are we starting to see
maybe some cracks in that foundation
is this AI
gold rush heading for a bit of a reality check
oh absolutely
the signs are definitely there
you're seeing AI equities drop
maybe 15% in recent months
and that's bringing uh unprecedented scrutiny
onto the business models themselves
veteran investor David Sax
he put it pretty bluntly he warned about founders
turning down multi billion dollar offers
for companies that haven't even launched a product yet
he said basically these offers don't grow on trees
they just don't
he even mentioned Meyer and Ilya suggesting maybe uh
maybe they should have taken those deals
that's quite a warning from sax
and it really hits that core problem
he pointed out AI companies valued like software
operating like manufacturing
so can you give us a sense of
how big this disconnect really is
like with some numbers
how extreme is this valuation gap
it is astonishing honestly
the AI premium is just off the charts
these startups are trading at get this
40.6 times revenue 40.6 x
now put that in perspective
look at other hot sectors
fintech maybe 20.4 x
payments 17.7 x proptech 16.3 x and traditional saws
you know the usual gold standard for software that's
baseline 8.3 x so AI at 40.6 x
that's a 390% premium over sauce
it's just it's the most extreme valuation premium
we've ever seen in tech history
even higher than the dot com bubble
those multiples rarely went above maybe 20
thirty x this is something else wow
40.6 x that's hard to wrap your head around
so the market isn't just optimistic
it's basically betting that AI will be more profitable
more efficient than any other tech sector ever
that seems like an incredibly high bar
doesn't it it's an extraordinary bet yeah
essentially saying AI
economics will beat everything else we've ever seen
in software it's well
it's built on hope frankly right
but are they actually earning that hope
what do the real numbers the actual profit margins
tell us about whether that Assumption holds water
yeah and that's where the picture gets really
really stark the margin data directly contradicts
those sky high valuations
investors are paying
like five times more for AI startups than SOS right
but look at the gross margins
traditional SOS averages what 77%
you've got Gitlab way up at 91%
Adobe 88% Salesforce 76%
pretty healthy now look at AI
the leaders like anthropic
maybe 50 55%
open AI around 50% perplexity maybe 60%
even the best are operating 20
25 points below the sauce average
and for others gets worse
stack blitz 40% lovable 35%
replitz down to 23% and this isn't just
you know oh
they're young they'll
scale out of it it seems structural
it's driven by those variable inference costs
every time someone uses the AI
it costs real money for compute
that difference is just massive
but couldn't you argue I mean
people do argue these are just early days
scaling costs want the margins naturally improve
as these companies grow get more efficient
maybe closer to those sauce numbers
that's the hope right
that's definitely what investors are banking on
but the article really pushes back on that
it argues the nature of AI inference
that cost is for every single user query
creates this ongoing high variable cost
software usually doesn't have that
not to the same extent
sauce is more about high upfront costs
than near zero cost per user
AI flips that so getting those margins up is a much
much tougher climb than just waiting for scales
not automatic okay
so these thin margins
they're not just an accounting issue
they create real fragility
real operational risks
does the article give an example of where this uh
margin fragility really caused problems for a company
oh definitely
the cursor case study is that was pretty dramatic
cursor was an AI powered code editor
they ran into huge trouble
because essentially
their flat pricing hit negative unit economics
they were losing money on heavy users
then they switched to this opaque token based billing
and some users suddenly got hit with bills for like
$7,000 a day yeah
huge shock and then to make it worse
when people complained their own AI support
bots started making up fake restricted policies
yeah total mess result
mass customer exodus
and because anthropic relied on partners
like cursor for distribution
it actually threatened Anthropic's revenue stream too
yeah it just shows when your margins are that thin
there's zero room for error
no buffer for mistakes or unexpected usage spikes
it's incredibly fragile
that's a complete nightmare scenario
and it brings us back to the money
this level of capital intensity
it really makes you wonder if
investors have fully grasped it
are they funding based on this new reality
or still using the old sauce playbook
what does this margin profile mean
for how much cash these companies need
just to survive and grow
it means they need a ton more capital right
way more than a similar sauce company
David
Sax's framework on capital efficiency really drives
this home it's eye opening
say you want to scale to $150 million in ARR
an 80% gross margin sauce company
it probably hits cash flow positive
maybe even generates around $27 million by then
now take a 50% gross margin AI company
aiming for that same hundred fifty mil
a R R it burns through an extra
80 to 100 million dollars in capital
just to get there 80 to 100 million more
yeah and if you're a 23% margin company like Replit
you're burning over
a hundred and sixty million dollars
more than the sauce company that difference
we're talking
over $130 million in additional funding needed
just because of the margins
it's a fundamentally different capital game goodness
with that kind of cash burn and those low margins
the path to an IPO to actual sustainable profitability
must look incredibly steep
it's not just a long road
it sounds like climbing a cliff face
it is incredibly steep yeah
you know public markets
they generally want to see what 10
15% operating margins uh huh
so if the AI leaders are starting at 50
60% gross margins they need to find
another 35 to 45 percentage
points of operational leverage
and what that means you know
for listeners
is they have to drastically cut their other costs
R&D sales
admin relative to revenue as they scale
that's tough it implies like
three to five years of absolutely perfect execution
with basically no major competition popping up
that's a very big ask in this market
okay so the climb is already steep
but then the article mentions this
accounting gamesmanship what's going on there
how could that be making the picture
look even rosier than it actually is
ah yeah
this is a really crucial detail
turns out many AI
startups are not
including the cost of serving their free users
in their main gross margin calculations
really they just leave that out
seems so
Openai reportedly does include those free tier costs
and that's part of why
their reported margin is around 50%
which the article suggests
is probably closer to the true economic reality
but many competitors
by excluding those costs can show higher margins
maybe closer to 60% it looks better on paper right
but the article argues look
if you factor in the compute costs
for all those free users
most AI companies are probably operating closer to 40
50% gross margins in reality
and that given the valuations
is well into unsustainable territory
wow so let me make sure I understand this for
for you listening
companies might be getting valued based on numbers that
well that don't fully capture the real costs
which makes that already steep climb to profitability
even harder
pushes that need for perfect execution even further out
requires even more capital
it feels like
investors might be chasing a bit of a mirage here
that's a good way to put it
it definitely masks the true capital intensity and the
uh the underlying economic challenge
yeah puts a massive bet on future efficiency gains
that just haven't materialized yet
okay so the article basically says
the correction isn't on its way
it's kind of already happening
market forces economic reality setting in
so as things shake out
what does the article say companies need to do
what are the strategies for survival here right
at least of the survival framework
three main paths for it first is margin optimization
the efficiency play this means things like uh
deep inference optimization
quantization distillation
making models run leaner faster cheaper
also developing custom chips like Google did with TPUs
or vertical integration
controlling more of the stack to keep costs down
okay efficiency makes sense
what's the second path
second is business model evolution
the platform play
this is about shifting away from just selling compute
heavy API calls
maybe becoming more of a platform orchestrator
building marketplaces
or focusing on high value enterprise solutions
where you can charge more
create stickiness and hopefully
get better margins than just per token billing
change the game you're playing
got it and the third
third is scale economics the infrastructure play
this is for the giants really
it involves negotiating super preferential
deals with cloud providers
cause you're buying compute at massive scale
or even building your own proprietary infrastructure
basically getting so big
that you can fundamentally change your cost structure
through sheer volume
and maybe justify that custom hardware investment
efficiency new business models or massive scale
OK so looking at those paths hmm
it does feel like we've seen similar patterns
in tech before right
given these strategies who does the article suggest
is actually well positioned to navigate this
and who's really at risk in the coming shakeout
sounds like clear winners and losers are emerging
absolutely the article is pretty clear here
position for success they point to opening
I why well
diversified revenue consumer subs
enterprise API
plus those huge Microsoft subsidies acting as a buffer
and infrastructure advantage
anthropic is also mentioned as potentially well
if they maintain their focus on enterprise
and strong margins and crucially
diversify away from just being an API provider
and you know generally any company that has a clear
believable path to getting those gross margins
above 70% OK
so open AI Anthropic if they execute well
and anyone with a path to high margins
who's on the other side who's at risk
at existential risk yeah
basically companies stuck with sub 40% margins
the article names Replit Stacklet
lovable as examples facing potential funding cliffs
as investors get more discerning
also those pre product companies
still turning down huge acquisition offers
Sachs's warning seems very relevant here
and really any business that's heavily relied on
just selling API access
without a clear plan for how to dramatically
improve those margins
they're stuck with those manufacturing like costs
without the scale or strategy to escape
yeah
it really is a classic tech story playing out again
isn't it growth at all costs
eventually runs into the wall of unit economics
what we've talked about today
these 40 x revenue multiples
for businesses struggling with 50% gross margins
it really does feel like one of the most concentrated
high risk bets we've seen in venture capital history
it truly does look the AI revolution
it's real it will
form industries no doubt about that
that's not the debate
but the current valuation environment
it's just not sustainable
based on the underlying economics
we're seeing right now
so the critical question for you as an investor
for founders is will today's high flying AI startups
with these business models and these valuations
actually be the long term winners
or are they just paving the way
burning cash to build the infrastructure
for a different set of
more economically sound companies
to eventually capture the real value
it's a huge question and that really leaves us
and you with a provocative thought to chew on
thinking about everything we've just discussed
does taking that billion dollar offer for a pre
product company
suddenly sound like maybe the smartest move
some founders aren't making
what does this deep dive make you consider
about where AI
investment and innovation is really headed next