---
title: "About"
---

# About This Course

## Prerequisites

You need:

- **A Mac** (Apple Silicon — M1, M2, M3, or M4). Intel Macs work too but will be slower.
- **At least 16GB of RAM**. 32GB is better. The more RAM you have, the smarter the model you can run.
- **Terminal access** — you know how to open Terminal.app and type commands.
- **About 20GB of free disk space** for models.

That's it. No programming experience required.

## Setup Overview

There are really only two things to install:

1. **Ollama** — the tool that runs AI models locally. Download it from [ollama.com](https://ollama.com).
2. **A model** — we'll pull one with a single command like `ollama pull gemma4:26b`.

The course will walk you through both steps in detail.

## Model Recommendations

As of May 2026, here are the models the author recommends:

| Model             | Size  | Notes                                                                |
| ----------------- | ----- | -------------------------------------------------------------------- |
| `gemma4:26b`      | ~15GB | **Recommended.** Best balance of smarts and speed for most machines. |
| `gpt-oss:20b`     | ~12GB | Fast, good for quick iterations.                                     |
| `qwen3:30b-a3b`   | ~18GB | Smarter but slower. Needs more RAM.                                  |
| `nemotron-3-nano` | ~2GB  | Tiny, fast, workable on any machine. Good for testing.               |

The key insight: **pick the smartest model that fits comfortably in your RAM**. You can check this by opening Activity Monitor and watching the "Memory Pressure" graph. If it goes yellow or red during a chat, the model is too big.

### How to Choose

1. Open **Activity Monitor** → **Memory** tab
2. Note your total physical memory
3. Note the "Memory Used" when you're doing your normal work
4. The difference is what's available for the model

On a 16GB Mac, `gemma4:26b` is about the maximum. On a 32GB Mac, you might go bigger. On an 8GB Mac, stick with `nemotron-3-nano` or smaller models.

## A Note About Speed

Local models are **slower than cloud models**. A response that takes ChatGPT 2 seconds might take 20-30 seconds locally. That's normal. The trade-off is privacy, offline use, and zero cost.

If responses are taking over a minute, your model is probably too large. Try a smaller one.

## What You'll Build

By the end of this course, you'll have a directory full of working tools:

```
my-ai-tools/
├── run_prompt.sh        # runs a prompt through Ollama
├── combind.ts           # combines files into a prompt
├── extract.ts           # pulls code out of LLM responses
├── ollama-repl.ts       # interactive chat with local AI
└── ...and more
```

All generated by AI. All running on your machine.

## Ready?

Head to **[01 Getting Started →](/run-ai-locally/01-getting-started/)**