# Fern-Style Documentary Prompt

Paste everything below the line into an AI coding agent that can run code on your computer (for example Claude Code). Fill in the three fields at the top. The agent needs to be able to run Python and ffmpeg, browse the web and download files. An NVIDIA GPU helps a lot.

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## YOUR VIDEO

- **Topic / question:** `[WRITE YOUR TOPIC HERE, e.g. "Why did the Roman Empire fall?"]`
- **Length:** `[e.g. 8–10 minutes]` (treat the upper bound as a hard limit)
- **Optional:** voice preference, accent colour, anything you already know you want or don't want

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## THE BRIEF

Make a complete, high-end documentary video on the topic above, in the style of the YouTube channel **Fern**. You own everything: research, script, concept, visuals, narration, music, sound design, editing and the final export. Quality matters more than speed. It has to look like a professional documentary, not "AI slop" and not a video game.

Work autonomously until the video is finished. Use any free or properly licensed tools, models and resources you can find. Ask me only when you truly need a decision, and send me previews as you go.

## 1. What "Fern style" means (follow this closely)

Study one or two Fern videos before starting if you can. The look comes from mixing these ingredients:

1. **White clay 3D reconstructions.** Real places, buildings, events and objects rebuilt as matte white or light-grey models:
   - soft overcast lighting, gentle shadows, ambient occlusion, light fog
   - **one** saturated accent colour marking what matters (a building, a route, a person, a data line)
   - simple faceless figures for people
   - slow, deliberate camera moves: aerial orbits, push-ins, pull-backs that reveal scale
2. **Real footage, cut in often.** Archival film, news or public-domain footage, and space or science footage, usually full frame.
3. **Real people speaking.** Short interview or testimony soundbites (4–20 seconds) where the original audio plays:
   - burned-in subtitles and a small name/title tag
   - the narration stops while they speak
   - let the footage "speak for itself" at key moments
4. **Documents and articles on screen.** Official statements, papers and news headlines, with the quoted line highlighted as the narrator reads it.
5. **Clean motion graphics.** Charts, counters, timelines and diagrams in 2D, minimal and precise. Numbers count up; lines draw on.
6. **Typography:**
   - elegant serif for chapter cards and the title
   - clean sans-serif for labels
   - date/place stamps in the lower-left ("1965 · London")
   - thin callout lines pointing at objects
   - restrained quote cards
7. **Pacing.** Mostly hard cuts, occasional fades at chapter breaks, and no shot held too long.

**Do NOT:**
- Build the film mainly from **procedural or "gamey" 3D**: glowing orbs, glossy dark voids, primitive mannequins, neon particles. It immediately looks fake and AI-made.
- Rely on **long runs of still photos**, even with a parallax effect. Photos are fine in small doses, but break them up with footage, clay scenes and graphics.
- Use one visual technique for the whole film. The mix is what makes it feel real.

## 2. Research and script

- **Research:** check every factual claim against reliable sources. No invented numbers, quotes or dates. Keep a sources list as you go; it goes in the video description.
- **Structure:**
  - a cold open that hooks with a specific, human moment or a striking fact
  - a title card
  - 5–7 short chapters, each with a chapter card
  - an ending that lands on one memorable line or image
- **Writing:**
  - aim for about 140–150 words per minute of runtime
  - use short, spoken-language sentences with a calm, curious, slightly ominous documentary voice
  - write each line with its visual in mind
- **Soundbites:** plan where 3–6 real soundbites will go, at the moments where a real expert or person saying it is more powerful than narration. Find public-domain or properly usable sources, such as government hearings, official agency footage or press-conference archives.
- **Word timings:** keep the script as structured data, one entry per line with an ID, so every visual cue can be tied to exact word timings later.

## 3. Narration (the most common failure point)

- **Voice:** use the best natural TTS available, not a free robotic voice. Test 3–4 voices on the same paragraph first, and send me the samples.
- **Check every generated line automatically.** Transcribe it with a speech-to-text model such as Whisper and:
  - confirm every word matches the script, with nothing skipped or garbled
  - flag **any pause longer than ~0.3 s that is not after punctuation**. Random mid-phrase pauses ("data … centers") make it sound broken. Regenerate any line that fails.
  - measure words per minute on every line. Aim for **140–155 wpm** and slow down rushed lines (the speed parameter works), because rushed narration sounds cheap.
- **Word-level timestamps:** get these for every line by force-aligning the transcription to the script words, and drive every on-screen cue from them.
- **Length:** check the total runtime against the target once the voice is final. Slower voices make films longer; trim pauses or lines to stay inside the limit.

## 4. Visuals and assets

- **Licensing:** use only public domain, CC0 or CC BY material, never share-alike, non-commercial or "all rights reserved". Record title, author, licence and link for every asset.
- **Good free sources:**
  - Wikimedia Commons. Download politely, one request every few seconds, using the standard thumbnail widths (1920 / 3840).
  - NASA image and video library
  - Library of Congress
  - The Met open access (CC0)
  - Internet Archive's Prelinger Archives (public-domain archival films)
  - US government hearing and agency video
- **Choosing assets:** build contact sheets of candidates, look at them, and pick deliberately. Avoid near-duplicates and low-resolution material.
- **Archival video:** old MPEGs are often interlaced and anamorphic, so deinterlace and fix the aspect ratio before scaling up. Grade old film consistently and add subtle grain and gate weave.
- **Photos:** use them sparingly as 2.5D parallax shots (AI depth maps from Depth Anything or similar) with slow camera moves and colour grading.
- **Clay 3D scenes:** make these the backbone of explanatory moments, such as maps, places, scale comparisons and "what happened here". They must look like tasteful architectural models, not a game.
- **Credits:** put a small on-screen credit line on every borrowed shot.

## 5. Sound

- **Music:** original or properly licensed. Ambient score that follows the chapters' moods, rises at key moments and goes quiet for impact.
- **Sound design:** whooshes, low impacts on reveals, subtle ticks on text, and period-appropriate atmosphere.
- **Mixing:**
  - duck the music under narration and soundbites
  - level-match soundbites to the narrator
  - master to about −14 LUFS, true peak −1 dB

## 6. Rendering and export (be kind to the computer)

- **Output:** 1920×1080 or higher, 30 fps, H.264 master at high quality, plus a smaller share copy.
- **Don't max out the machine.** Long, heavy CPU and RAM jobs (big parallel renders, slow CPU encodes) can crash or blue-screen consumer PCs.
  - Run heavy work at low priority with limited threads, one job at a time.
  - Prefer the GPU video encoder (NVENC or similar) for the final encode.
  - Watch free RAM and stop if it gets low.
  - **Ask me before starting anything that will max out the PC for a long time.**
- **Make rendering resumable.** Render in short chunks so a failure only costs one chunk.
- **Verify automatically** before calling it done:
  - no blank, black or frozen stretches
  - no missing assets
  - frame count matches the timeline
  - video footage actually moves
  - interview audio is in sync with lips
  - the final file decodes with zero errors

## 7. Working with me

1. Start by telling me your plan: the concept, chapter outline, visual approach and voice choice.
2. Send preview stills and short preview clips with audio early (a 720p preview is fine), then the full video.
3. Expect feedback rounds, and make each change without breaking what already works.
4. At the end, give me:
   - the final master and a share copy
   - a **YouTube description text** with all sources and image, footage and music credits
   - a note on which parts are AI-generated (narration, visuals), so I can disclose it

## 8. Final quality bar

Before you hand it over, watch it the way a viewer would, frame samples from every chapter plus the audio checks, and ask:

- Does it feel like a real documentary rather than a slideshow or a video game?
- Is there always something moving or changing on screen?
- Are there real people and real footage, not just narration over pictures?
- Is every claim correct, and every asset licensed and credited?
- Does the narration sound natural, with no odd pauses and no rushing?
- Is it inside the target length?

If any answer is no, fix it before delivering.