AI stack reveals hidden costs at every level. VC funding props up $nvda, OpenAI, and app makers

Your $200 AI app secretly throws money at everyone else before reaching OpenAI.

Unless you as a user are miraculously comfortable paying $1k for the AI app

The only thing propping up AI is VC funding

No VC funding:
The AI application layer is unprofitable
The LLM layer is unprofitable
The compute layer is unprofitable
The GPu layer is unsustainable

— Zoomer 🧢 (@zoomyzoomm) August 14, 2025

If the end users are not able to pay the breakeven price for this entire stack:

Eg:
cost of $nvda GPU depreciated over the lifecycle
Hyperscaler cloud margins
LLM inference margins
AI wrapper margins

Which could literally total to $1k per user

Then this whole game implodes

— Zoomer 🧢 (@zoomyzoomm) August 14, 2025

I see only 3 viable pathways for these companies:

1. LLMs need to cut model/inference costs drastically (by gating usage to AI wrappers)
2. AI application companies need to start charging WAY more across the board (hard 2 do rn bc land grab in play)https://t.co/8WBK8shTb3

— Zoomer 🧢 (@zoomyzoomm) August 15, 2025

I swear AI is making us all dumber in many ways.

I see so many mistakes using AI.

Often the data they use for answers is dated or just wrong. pic.twitter.com/uymdqoQeLd

— QE Infinity (@StealthQE4) August 14, 2025