Editing Openai/69408f2e-3acc-800c-a0c5-7ab1f3f9f65c (section)

=== Assistant: Short answer: yes — the “AI will just go away” hope is basically bullshit. ===
Short answer: yes — the “AI will just go away” hope is basically bullshit.
Long answer: there ''is'' a bubble, but it’s not the kind people think.

Let’s separate the ideas cleanly.

==== Yes. Absolutely. But bubbles are about valuation and expectations, not disappearance. ====

There is a bubble in:
* Startup valuations with no defensible moat
* “AI wrappers” that are just thin UI layers on top of APIs
* Companies promising magical automation without domain depth
* Assumptions that every AI product will 10× revenue quickly

Many of those will die.

That part looks like 1999.

==== No. And this is the key mistake people make. ====

What we’re seeing is:
* Real products
* Real revenue
* Real productivity gains
* Real willingness to pay
* Real operating profit (as we just reasoned through)

Bubbles don’t look like:
* “If we stop expanding, we’re profitable”
* “Demand exceeds capacity”
* “Customers complain when usage limits tighten”

Those are signs of a supply-constrained technology, not hype vapor.

==== This belief usually comes from one of four places: ====

===== AI threatens: =====
* Certain jobs
* Certain skills
* Certain identities

So people want it to fade, like:
* NFTs
* Metaverse hype
* Web3 buzzwords

But AI isn’t a speculative asset — it’s labor.

Labor demand doesn’t vanish.

===== The internet had: =====
* A dot-com crash
* Followed by Amazon, Google, Facebook, Netflix

AI is similar:
* Many companies die
* A few become infrastructure
* Everything else reorganizes around them

The crash (if/when it happens) clears excess — it doesn’t erase the tech.

===== This was the strongest skeptical argument. =====

But the economics already show:
* Costs are falling
* Models are more efficient
* Revenue scales faster than inference cost
* Even today, operations are likely profitable at scale

Expensive technologies don’t disappear — they get cheaper and spread.

That’s how:
* Electricity
* Computers
* Cloud
* GPUs
* Smartphones worked.

===== People point to: =====
* Hallucinations
* Errors
* Weird failures

That’s fair — but irrelevant long-term.

Early cars:
* Broke constantly
* Were dangerous
* Had no roads

They still replaced horses.

Why? Because they were directionally better.

AI already is.

==== Here’s the realistic path: ====

===== - AI “going away” =====
* LLMs being abandoned
* Reversion to pre-2022 workflows

Those are fantasies.

===== - Massive consolidation =====
* Many startups die
* Fewer, more powerful foundation model providers
* AI becomes boring infrastructure
* You stop noticing it, like search or cloud

The winners:
* Control distribution
* Control compute
* Control data
* Or deeply integrate into workflows

Everyone else gets squeezed.

==== The bubble is: ====
* “Everyone will become a 10× solo founder”
* “AI replaces all jobs next year”
* “This app with an LLM prompt is worth $200M”

Those narratives will pop.

But the baseline reality remains:

: 

That does not reverse.

==== - AI hype? Yes. ====
* AI bubble? Partially.
* AI going away? No chance.
* People hoping it disappears? Coping.

If you want, we can:
* Map which jobs are actually at risk (vs safe)
* Talk about what does get automated first
* Or explore where the next consolidation pain will hit hardest

Just say the word.