---
# System prepended metadata

title: revised-gened-1145-vibe-coding-station

---

# gened-1145-vibe-coding-station

## intro

This station will help you see how genAI tools can assist you with coding and command-line tools in ways that align with course learning objectives (getting technical, not conceptual help!):

1. Gemini and other LLM-based AI tools can help you code or create command line scripts that can help you generate or transform video assets for your video essays
2. These AI tools can also help us imagine what the future of the "video essay” might look like as a **web-based, interactive, multimodal form**.

Bit by bit we'll learn to create something like [this web-based essay about *Godzilla*](https://gened-1145.vercel.app/video-essay/02).


## Command Line Tools

### What are they? Why use them?

* The command line is like a minimalist creative studio: no interface, just direct control.
* You can batch-process media, automate boring steps, and combine tools into custom workflows.
* Great for video essays because it:
  * Speeds up media prep (compressing, clipping, converting)
  * Enables reproducibility (same commands = same results)
  * Integrates easily with code notebooks, AI tools, or web apps


## Installing `ffmpeg` and `yt-dlp`

These two command-line tools are the foundation of your video-essay toolkit.
They let you download, trim, compress, and transform media files with a few lines of code.

---

### macOS (using **Homebrew**)

1. **Install Homebrew** (if you don’t already have it):

   ```bash
   /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
   ```

2. **Install `ffmpeg` and `yt-dlp`:**

   ```bash
   brew install ffmpeg yt-dlp
   ```

3. **Verify installation:**

   ```bash
   ffmpeg -version
   yt-dlp --version
   ```

If both print version numbers, you’re good to go.

> Tip: You may be asked to add Homebrew to your PATH. The terminal will show you how — usually something like:
>
> ```bash
> echo 'eval "$(/opt/homebrew/bin/brew shellenv)"' >> ~/.zprofile
> eval "$(/opt/homebrew/bin/brew shellenv)"
> ```

---

### Windows (using **Chocolatey**)

1. **Install Chocolatey** (if not already installed):
   Open **PowerShell as Administrator** and run:

   ```powershell
   Set-ExecutionPolicy Bypass -Scope Process -Force; `
   [System.Net.ServicePointManager]::SecurityProtocol = `
   [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; `
   iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
   ```

2. **Install `ffmpeg` and `yt-dlp`:**

   ```powershell
   choco install ffmpeg yt-dlp -y
   ```

3. **Verify installation:**

   ```powershell
   ffmpeg -version
   yt-dlp --version
   ```

## things to try with yt-dlp

To get some clips for your video essay, you may want to use `yt-dlp` which is the tool that's used on the backend of those dodgy YouTube downloader sites that attack you with pop-ups (or even malware).

Once you've installed it (see above) go ahead and find a YouTube video, then paste it into your LLM and ask it for the yt-dlp command to download it to your Desktop. Should look like this:

```
yt-dlp "https://www.youtube.com/watch?v=EjNYWCH-fJw" -o ~/Desktop/%\(title\)s.%\(ext\)s
```

If you get an error, just paste that error back into your LLM of choice.

You may find that the video format you get back isn't ideal for your computer, for instance, the above command will give you a `.webm` video, which isn't ideal for macOS. Go ahead and ask for a better mac-compatible format, and you'll get a command like this:

```
yt-dlp "https://www.youtube.com/watch?v=EjNYWCH-fJw" \
  -f "bv*[ext=mp4]+ba[ext=m4a]/b[ext=mp4]" \
  --merge-output-format mp4 \
  -o ~/Desktop/%\(title\)s.mp4
```


## things to try with ffmpeg

FFmpeg is a great all-purpose command-line video transformation tool that is helpful for thousands of workflows (at least). 

But just to get you started, paste the path for your video into your LLM of choice and ask it to give you the FFmpeg command for extracting one still every 5 seconds of your video (or 5 stills a second if you prefer).  You should see something like

```
mkdir -p ~/Desktop/godzilla_stills
ffmpeg -i ~/Desktop/godzilla.mp4 -vf fps=1/5 ~/Desktop/godzilla_stills/frame_%03d.jpg
```

Now let's say you see a still or two that are from a segment you'd like to analyze--ask your LLM how to use ffmpeg to grab a gif from that segment. For instance two stills that find a segment from the video that you really like and you want to create a gif of it. 

![alt text](https://files.slack.com/files-pri/T0HTW3H0V-F09M0LPBB5F/frame_021.jpg?pub_secret=968ed29726)

![alt text](https://files.slack.com/files-pri/T0HTW3H0V-F09LMPUTNAE/frame_022.jpg?pub_secret=a8ce58fb15)

You should get back something like:

```
ffmpeg -ss 100 -to 105 -i ~/Desktop/godzilla.mp4 -vf "fps=12,scale=640:-1:flags=lanczos" ~/Desktop/godzilla_clip.gif
```

And have a nice gif like

![alt text](https://files.slack.com/files-pri/T0HTW3H0V-F09LFBNJEMR/godzilla_clip.gif?pub_secret=0ce45509f4)

## What Else Can You Do with `ffmpeg`?

### 🎧 Extract Audio from a Scene

```bash
ffmpeg -i ~/Desktop/godzilla.mp4 -ss 60 -to 90 -q:a 0 -map a ~/Desktop/godzilla_scene.mp3
```

**What it does:**
Extracts the audio between 1:00 and 1:30 and saves it as an MP3.
Useful for pulling dialogue or ambient sound for close analysis or remix.

---

### ✂️ Pull Out a Video Segment

```bash
ffmpeg -ss 60 -to 90 -i ~/Desktop/godzilla.mp4 -c copy ~/Desktop/godzilla_clip.mp4
```

**What it does:**
Copies the video between 1:00 and 1:30 without re-encoding (instant and lossless).
Great for isolating a single shot or sequence for classroom discussion or editing.

---

### 📦 Compress a Video for Web or Email

```bash
ffmpeg -i ~/Desktop/godzilla.mp4 -vcodec libx264 -crf 28 -acodec aac -b:a 128k ~/Desktop/godzilla_compressed.mp4
```

**What it does:**
Creates a smaller file that’s still good quality — easy to upload or share.
`crf` (Constant Rate Factor) controls quality: lower = higher quality, higher = smaller file (23 is good, 28 is smaller).

---

### 🔄 Transcode to a Friendly Editing Format

```bash
ffmpeg -i ~/Desktop/godzilla.mp4 -c:v prores_ks -profile:v 3 -c:a pcm_s16le ~/Desktop/godzilla_prores.mov
```

**What it does:**
Converts your file to **Apple ProRes 422** — ideal for editing in Final Cut, Premiere, or DaVinci Resolve.

---

### 🎬 Detect Cuts or Scene Changes

```bash
ffmpeg -i ~/Desktop/godzilla.mp4 -filter:v "select='gt(scene,0.4)',showinfo" -f null - 2> ~/Desktop/cuts.txt
```

**What it does:**
Analyzes the video and logs timestamps where major scene changes occur (based on visual difference).
The results in `cuts.txt` can help you identify shot boundaries automatically.

---

### 🎨 Make a Contact Sheet of Frames

```bash
ffmpeg -i ~/Desktop/godzilla.mp4 \
  -vf "fps=1/5,scale=320:-1,tile=5x5" \
  -q:v 2 \
  ~/Desktop/godzilla_contactsheet_%02d.jpg
```

**What it does:**
Generates a single image grid (5×5) of frames sampled every 5 seconds — a visual fingerprint of your clip.

![alt text](https://files.slack.com/files-pri/T0HTW3H0V-F09LKQHFL86/godzilla_contactsheet_01.jpg?pub_secret=41d10989c8)
![alt text](https://files.slack.com/files-pri/T0HTW3H0V-F09M0PYQT7T/godzilla_contactsheet_02.jpg?pub_secret=8c93cb0e9d)

---

### 🔊 Create a Waveform Visualization

```bash
ffmpeg -ss 100 -to 102 -i ~/Desktop/godzilla.mp4 \
  -filter_complex "[0:a]aformat=channel_layouts=mono,showwavespic=s=1280x200" \
  -frames:v 1 ~/Desktop/godzilla_waveform.png
```
![alt text](https://files.slack.com/files-pri/T0HTW3H0V-F09LFDCEMGB/screenshot_2025-10-15_at_7.53.37___am.png?pub_secret=cf3131cdd6)

**What it does:**
Turns an audio track into a waveform image — perfect for syncing with visual analysis or transcripts.

---

### 📚 Bonus: Batch Process Files

```bash
for f in ~/Desktop/*.mp4; do ffmpeg -i "$f" -vcodec libx264 -crf 28 "${f%.mp4}_small.mp4"; done
```

**What it does:**
Runs compression on **all** `.mp4` files in a folder — great for bulk prep work.




## 🤖 The OpenAI API (Optional)

* Use it **only for technical assistance**, not content generation.
* You might use it to:

  * Write scripts that rename, organize, or batch-process files.
  * Generate HTML/JS snippets for embedding media.
  * Create captions or alt-text for accessibility (via Whisper API).

#### Example

```bash
curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -F "file=@/Users/mk/Desktop/rick.mp3" \
  -F "model=gpt-4o-mini-transcribe" \
  -F "response_format=text"
```
![alt text](https://files.slack.com/files-pri/T0HTW3H0V-F09MG6LKZR6/screenshot_2025-10-15_at_8.07.45___am.png?pub_secret=02fa2f6951)
---

## Building the Interactive Essay with AI Assistants

### Why pair AI with your editor?
- AI is your patient lab partner: it walks you through TypeScript, Tailwind, and component wiring without replacing your own interpretive voice.
- You control the film analysis; the model helps wrangle the technical scaffolding that turns ideas into a multimodal experience.
- Treat every suggestion as a draft. Run it locally, compare it to your aesthetic goals, and keep iterating until it feels like your essay.

### Step-by-step flow for beginners
1. **Map the story you want to tell.** Sketch the beats of your analysis (e.g., “clip 004 = Witnesses to Ruin”) and keep them in a simple outline or Google Doc. This outline becomes the data structure you feed the app.
2. **Ask your AI for scaffolding.** Prompt it with: “Generate a Next.js App Router page that imports a `ScrollVideo` component and renders an array of clips with titles, summaries, and notes.” Paste a real clip entry from `src/app/video-essay/02/page.tsx` so it copies the format.
3. **Validate inside the repo.** Drop the suggested code into a new page file such as `src/app/video-essay/03/page.tsx`, then run `pnpm dev`. Fix TypeScript errors by copying error messages back to the model and asking for corrections.
4. **Style with intent.** Share a screenshot or snippet of the current layout plus a Tailwind color palette with the AI. Ask for targeted tweaks—“make the hero title gradient echo Godzilla’s electric blues”—and merge only the classes that match your vibe.
5. **Automate media prep.** When you need clips, paste your goal into the chat: “Write an ffmpeg command that outputs 15-second VP9 `.webm` segments with intra-frame accuracy.” Compare the answer to `_scripts/extract-clips.sh`; adjust parameters like `clip_length` or `video_bitrate` together.
6. **Keep accessibility in the loop.** Request help drafting alt text, transcript snippets, or hover states that narrate the archival context. This reinforces the essay’s academic rigor while stretching the “video essay of the future” toward inclusive design.

### Prompt patterns that work well
- **“Read this file and explain the structure.”** Paste the top of `src/app/video-essay/02/page.tsx`. Ask what each section does so you internalize the React patterns before copying them.
- **“Transform these notes into structured data.”** Give the AI bullet notes on a sequence and ask for the JSON-like entry (`id`, `src`, `title`, `summary`, `notes`) so you can drop it into the clips array.
- **“Suggest UI flourishes that amplify the theme.”** Invite ideas like scroll cues, ambient audio toggles, or split-screen comparisons that align with the essay’s question: what happens when analysis and footage breathe together?

### Staying in charge of the creative voice
- Keep a changelog in your doc or commit messages noting which pieces came from you, from AI, or from archival research.
- Re-run `pnpm lint` or `pnpm build` after major changes so you catch regressions before publishing.
- Reserve conceptual decisions—interpretation, framing, argument structure—for yourself. Let the model handle plumbing: data mapping, reusable components, responsive layout tweaks.

### Bringing it back to the course theme
The scroll-synced Godzilla essay shows how reader agency, multimodal assets, and critical storytelling fuse inside the browser. Generative AI fits here as a fabrication tool: it accelerates mechanical steps so you can experiment with new narrative shapes. Use it to:
- Prototype alternate pathways (e.g., “branch the essay when the reader pauses on clip 005”).
- Generate quick variants of interactive overlays that annotate frames.
- Explore how a future video essay could respond to reader input without sacrificing historical rigor.

When you combine your analytical lens with AI-assisted coding, you’re literally vibe-coding the “video essay of the future”—a living document where film history, computation, and collaborative authorship meet.
