Day 12

Day 12 of 1% Better.

Today, I learned why Foundation Models changed the way we build AI.
Here's the simplest way to think about it:

1. Before Foundation Models
↳ Most AI models were designed for a specific task.
• Speech-to-text → One model
• Translation → Another model
• Image classification → Yet another model

2. Foundation Models changed the game
↳ Instead of building a model for every task, we start with one general-purpose model.

Then we adapt it for different applications.
For example, the same model can be adapted to:
• Build a customer support assistant
• Summarize legal documents
• Generate product descriptions
• Analyze financial reports

The foundation model stays the same.
The application changes.

3. How do we adapt a Foundation Model?
Different applications require different approaches.

• Prompt Engineering
↳ Improve how you instruct the model.
• RAG
↳ Give the model relevant external knowledge.
• MCP
↳ Let the model use external tools and systems.

4. Why this matters

•A few years ago, building AI often meant spending months collecting data and training models.

•Today, you can build a useful AI application in days by starting with a foundation model and adapting it to your problem.