LaaS: Layoffs-as-a-Service
When AI Turns from Tailwind to Headwind
The launch of ChatGPT and its explosive growth in users has been the key catalyst of this AI-driven cycle, ever since its inception in late 2022. At the same time, the importance and effects of the cycle on the broader economy has to be taken into consideration.
In fact, the AI cycle was the main reason why rate hikes by the Fed didn’t cause an economic slowdown. With post-Covid deficits by both Biden and Trump also aiding the economy — in classic Keynesian deficit-spending fashion.
Now the process is maturing and past the early stages in its life cycle. We mapped out the boom/bust process in a piece from 2024 — using Sorosian boom/bust analysis to understand the process as well as its flaws. Seeing the process and the simple cause and effect is easy — seeing the flaws of the process is another thing.
1) The Tailwind: AI Capex
Those who bet on the “picks and shovels” trade of AI were vindicated as Big Tech and VC both went all in on AI.
NVDA returned a 17X since the bottom of late ‘22 — when markets were focused on the Fed’s rate hiking cycle. If you need some context to position yourself: that’s where the AI Cycle started.
And in simple terms it can be explained as: more GPUs —> more Revenue —> higher valuations and more (assumed or expected) Value Creation.
In our Techno-Imperial Cycle piece we framed the major flaw of the cycle as 👇
How much value does AI really create?
The Bust 🔄
The cycle is starting to reverse.
The first hit was Oracle and their terrible OpenAI RPO deal — with the sharp reversal of their share price. We wrote about this in Wake Up Call!
As marginal development in AI is tapering — expectations of AI’s effect on the real economy are accelerating. Refer to the recent software stock selloff as an example.
On that vertical, we published a thought piece to touch on a few misplaced narratives that we see the market adopting.
Technological Determinism & AGI
(Excerpt from Low Hanging Compute)
Technologists tend to fall into these intellectual traps. Like economists believe in market fundamentalism, and geneticists (and others) believe in genetic determinism,so do technologists believe in technological determinism.
Technological determinism is the idea that technological progress will inevitably supersede human labor and judgment — a sort of technological inevitability.
Artificial General Intelligence (AGI) is fundamentally a technologically deterministic idea.
(Excerpt end)
The debate on the relationship between Compute and Intelligence is ongoing — and we see it as just a continuation of the debate on AI Capex spend and ROI.
The answers to both will become clear after the dust has settled and everything is said and done.
Having discussed the broader issue both with technologists and finance bois — I find that the former doesn’t get it while the latter doesn’t want to get it.
Philo’s Thoughts 🦉💭
First, the market adopted the narrative that AI capex results in value creation — bidding up all layers in the AI stack. But the jury is still out on whether this massive capex spend will result in lasting value creation for every layer.
We published AI Tech Playbook to discuss and differentiate between each layer in the stack. This is where you can form opinions on the economics of AI Labs, Semiconductor Companies, Hyperscalers, the Application Layer etc.
Second, the market is adopting the narrative that the “Cost of Intelligence” is deflating fast — soon to be worth zero. The adoption of this narrative by the market is the stock crash of every company considered to be under threat from AI proliferation.
The Race is STILL On
But putting aside the complicated dynamics and relationships in play — let’s now discuss the relationship between the existential need for Big AI to continue spending in AI Capex — and how that forces them to change their business models.
Note: when I say AI Capex I mean both tangible capex (e.g. Data Centers) and intangible capex (e.g. Training LLMs).
Now the mass-layoff lever is growing with rumours of Oracle, Google and Amazon about to fire tens of thousands.
Information on their objectives suggests they were planning this for a long time — realising that their balance sheets could not sustain both unhinged spending on AI and a bloated workforce.
2) The Headwind: Mass Layoffs and AI Hybrid
While the AI Capex buildup story was economy positive — mass layoffs is massively economy negative.
These mass layoffs intend to serve a number of aims: psychological, economical but also to change reported economics (accounting) and shift cash from humans to AI.
We will touch on all of these layers in this piece.
Note: mass layoffs and cooking the books to overstate AI-led productivity will both boomerang in the face of Big AI. Please allow me to explain because there’s a lot happening here.