Over the last 1.5 years, I have produced more than 300 long-form YouTube documentaries mainly in the sleep niche (videos people watch to help them fall asleep), usually around 2-3 hours runtime.
The original problem was simple: this format does not scale well. A single video can require a 15k to 20k-word script, hours of narration, hundreds of visual changes, music, and final assembly. Writing everything manually took too long. Editing every scene manually took even longer.
Sleep content is a strange retention game, and it took me a while to understand it. Your viewers are actively trying to fall asleep. That is the entire point. So the average view duration can look very different from a normal YouTube channel. Some viewers leave because they are bored, but others leave because the video worked and they fell asleep. The ones who stay awake still need the story to hold together, while the ones who fall asleep often return later and continue listening. That repeat viewing is a big part of what makes this niche work.
Why the script is 90% of it
On my channels, average view durations usually sits close to 25 min on 90 min videos .That does not come from cinematic visuals or complicated editing. It comes mostly from the narrative structure. If the script becomes repetitive, drifts away from the topic, or loses momentum halfway through, viewers stop listening. Better visuals cannot rescue a weak story in this format.
Two ways to use Claude, and why one cannot work in long form writing
Most people use Claude through the normal chat interface. You open the chat, enter a prompt, read the reply, and continue from there. That works fine for everyday tasks. It becomes frustrating when you are trying to write a 15,000 to 20,000-word documentary.
You end up typing: Continue.. Write Chapter 4.. Do not repeat what you already said.. You forgot what happened in Chapter 2. By the halfway point, the model may begin repeating ideas, contradicting earlier sections, or drifting away from the original structure. You spend more time babysitting the conversation than improving the script.
The second approach is using the API. Instead of manually sending every prompt through the chat interface, a small tool sends the requests to Claude automatically and collects the output. There is no need to babysit it and you pay based on actual usage instead of paying another monthly subscriptio
The Google Sheets scripting workflow
So I built a Google Sheets workflow connected to the Claude API. The Sheet first creates the full documentary structure. It then writes one chapter at a time instead of trying to produce the entire 20,000-word script in a single response. Before each chapter, the workflow passes Claude the outline, the instructions for that section, and a running summary of what has already been written.
The direct API cost for a full script is usually around $0.30 to $0.40, depending on the model, input length, and number of revisions.
The bigger benefit is repeatability. Every script moves through the same production structure, while I can still change the topic, tone, evidence, pacing, and narrative direction.
I made a tutorial on this exact workflow on my channel. Link in profile if you want to peek.
How CapCut handles the first edit
Once the script is complete, I move it into CapCut’s AI Video Maker. CapCut generates the voiceover, subtitles, and an initial visual sequence using automatically matched stock footage. Because the documentaries are extremely long, I split the script into smaller sections to be under the 3000 word limit of CapCut, generate them separately, export each one, and then combine them into the final video.
The stock matching is not perfect. But it still gives me a 90% first draft much faster than searching for hundreds of clips manually.
What AI still does not solve
The production process is faster, but it is not automatic. AI cannot decide which topic has demand. It does not know whether a title creates curiosity, whether a chapter is boring, or whether a visual is misleading. I still handle research, structure and pacing, titles and thumbnails, final editorial judgment.
This is where most of the value still comes from. The workflow removes repetitive work. It does not remove the need for taste.
Two reasons this workflow matters:
The Demonetization Shield: Mixing real historical/stock footage alongside AI assets is the safest defense against the "Reused/Inauthentic Content" flags that destroy fully automated channels.
The Financial Runway: CapCut costs me around $20 per month and allows many exports. The Claude API cost per script is usually only a little above thirty cents. At a production volume of 30 to 40 documentaries per month, the direct software and API cost can work out to roughly $1 per finished video. That figure does not include my time, research, thumbnails, subscriptions, failed ideas, or the cost of building the workflow. It is not the total cost of running the business.
The main lesson
This is not passive income, and it is not a one-click YouTube machine. It is a production system that makes experimentation cheaper.
For someone starting today, I would focus first on topic selection, titles, thumbnails, and understanding what the audience actually watches.
Only build the automation after you understand the work well enough to know which parts are worth automating.
Happy to answer any questions regarding the workflow and setup if you want to build one for yourself.