Everyone talks about the AI race as if it’s just an intelligence benchmark competition. GPT-6 vs Claude 5 vs Gemini vs DeepSeek.
But I’m starting to wonder if intelligence itself eventually becomes abundant and the real scarcity becomes trust and the ability to interface with reality.
For example, suppose a Chinese model is 95% as good as OpenAI and 10x cheaper.
Would Fortune 500 companies really put it inside:
financial systems?
ERP software?
defense applications?
pharmaceutical R&D?
factory automation?
autonomous agents with spending authority?
Maybe for translation or generic coding, sure. But would they trust it with the organization’s nervous system?
Which makes me think there are really several layers:
1. Intelligence Layer
OpenAI
Anthropic
Google
DeepSeek
2. Interface Layer
ChatGPT
Claude
Copilot
3. Reality Layer
Palantir
ServiceNow
SAP
Oracle
Salesforce
Anduril
The reality layer contains:
permissions
workflows
ontology
governance
auditability
human incentives
accountability
Organizations are messy. Humans are messy.
Maybe the hard problem isn’t generating tokens. Maybe it’s connecting intelligence to reality without breaking the organization.
This also makes me wonder if enterprise software ends up being more durable than people think. If foundation models become increasingly commoditized, perhaps trust, integration, and organizational operating systems become more valuable, not less.
Alex Karp often seems to talk less about models and more about institutions and organizational complexity. Perhaps he sees LLMs as interchangeable sources of intelligence and the hard problem as organizational intelligence itself.
Curious what others think.
Do you believe AI will mostly commoditize and price competition will dominate, or do trust, governance, and integration become the real moat?
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