AI as Infrastructure: Foundation Models Are the New Internet Deepthink AI Newsletter

Just like electricity powered the industrial era, and the internet rewired the information age — foundation models ( like GPT, Claude, Gemini ) are now becoming the invisible infrastructure of the AI era.

They're not just features in apps.
They are the new platform.

The Shift: From Applications to Infrastructure

In the past, companies built software on codebases.

Today, they're building on pre-trained intelligence.

Before: Build from scratch
Now: Build on ChatGPT and foundation models

Before: Code-based logic
Now: Prompt-based logic

Before: User experience (UX) focused
Now: Intelligence (IX) focused

Before: SaaS platforms
Now: AI agents and co-pilots

Before: APIs for data
Now: APIs for cognition

What Are Foundation Models?

Foundation models are massive AI systems trained on internet-scale data — capable of language, vision, reasoning, and even tool use.

They’re "foundational" because:

• They’re general-purpose (not task-specific)

• They can be fine-tuned or adapted for any domain

• They become the base layer apps are built on

Think of them like operating systems — but for intelligence.

Real World Examples (Plain Format)

Use Case: Notion AI
Built on: GPT

Use Case: Jasper
Built on: GPT

Use Case: Perplexity
Built on: Mix of LLMs

Use Case: Runway (Video Editing)
Built on: Custom Multimodal Models

Use Case: Replit Ghostwriter
Built on: Code-specific LLMs

Why This Changes Everything

1. Power Consolidation
Only a few companies can afford to build these models — leading to power concentration (OpenAI, Google, Anthropic, Meta).

2. Platform Play
Just like AWS powers web infra, OpenAI/Gemini will power intelligence infra.

3. Plug & Play Intelligence
Startups can launch powerful products fast by just layering UX over existing AI brains.

4. Dependency Risk
If you rely on a third-party model — and the API changes or prices jump — your product is at risk.

What This Means for Builders

• You’re not competing with foundation models — you’re building on them

• Speed to market > training your own model

• Differentiation = fine-tuning + UX + distribution

They’ll just plug into the infrastructure.

Final Thought

Foundation models aren’t just tools to use.
They’re becoming layers to build on.

Understanding this shift will define which products, platforms, and people lead in the AI-first future.

Stay mindful,
Deepthink