Big Idea

The argument in one line.

Video style transfer no longer needs motion capture: a still reference image plus a short source clip can be fed through a model like Genjutsu to re-render any talking-head video in a completely different visual style, and an AI agent can run the whole multi-step pipeline unattended.

Who This Is For

Read if. Skip if.

READ IF YOU ARE…

You make talking-head YouTube or ad content and want a visual style that stands out from every other creator's plain camera feed.
You run video ads and want to test multiple visual styles against each other without reshooting anything.
You're comfortable directing an AI coding agent (Codex, Claude Code) through a multi-step tool-calling workflow.
You want to know what's realistic to self-host right now versus what still needs a paid API.

SKIP IF…

You want a one-click consumer app — this is a DIY pipeline with credits, prompts, and failed-generation retries.
You need perfect lip-sync and frame-accurate motion today — the video shows visible mouth-tracking artifacts on the stylized output.

TL;DR

The full version, fast.

Nick Saraev shows how to re-render normal talking-head footage into a fully animated video using Higgsfield's Genjutsu model: generate a stylized reference image of yourself with GPT Image 2.5, then feed a short source clip plus that reference image into Genjutsu, which transfers the motion onto the new visual style while keeping the original audio. Because the models can't yet handle a whole video in one pass, footage gets split into 20-second chunks, rendered separately, and stitched back together with the original audio track. He hands that entire split-render-inspect-stitch loop to GPT-6 Astra running inside Codex, which checks pricing, picks resolution and pacing, and retries failed generations on its own. WAN 3.0 is shown as a cheaper alternative to Genjutsu, and WAN 2.2 Animate is available to self-host for free. The strongest practical use case raised is producing dozens of stylistic variants of one video ad and split-testing which style converts best.

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Chapters

Where the time goes.

00:00 – 01:00

01 · I turned myself into an animated character

The presenter reveals the whole video is style-transferred and states his reason for demonstrating it this way.

01:00 – 02:43

02 · How video style transfer works

Explains the core mechanism: a normal source recording multiplied by a style-reference image produces the stylized output.

02:43 – 04:39

03 · Astra as your production manager

Introduces the 5-step pipeline (split, Genjutsu, stitch, Silero VAD + FFmpeg, review/export) that GPT-6 Astra will run.

04:39 – 05:47

04 · 10 animation styles to try

Walks through a gallery of ten preset visual styles generated from one source frame.

05:47 – 07:05

05 · Setting up Higgsfield

Signs up for Higgsfield and shows the interface used to generate and manage style transfers.

07:05 – 08:31

06 · Creating a style with GPT Image 2.5

Generates a stylized reference image of himself using GPT Image 2.5 Sunburst inside Higgsfield.

08:31 – 10:22

07 · Animating your footage with Genjutsu

Feeds a short source clip and the style reference into Genjutsu to produce the first stylized video output.

10:22 – 12:00

08 · Using style transfer for ads and content

Argues the technique is powerful for ad testing: one ad can be style-transferred into many versions and split-tested.

12:00 – 13:39

09 · Wan 3.0: a cheaper alternative

Runs the same style transfer through WAN 3.0 for a fraction of the credit cost of Genjutsu.

13:39 – 16:03

10 · Automating the workflow with GPT-6-Astra

Opens Codex, installs the Higgsfield plugin, and hands the full pipeline to GPT-6 Astra using a written operator prompt.

16:03 – 17:35

11 · Resolution, credits, and silence removal

Astra quotes credit costs, resolution options, and a silence-trimming threshold before running the full render.

17:35 – 18:40

12 · Self-hosting Wan 2.2 Animate

Points to the free, open-weight WAN 2.2 Animate model on Hugging Face as a self-hosted alternative to paid APIs.

18:40 – 20:25

13 · Reviewing the animated results

Reviews the finished stitched clips, noting minor mouth-tracking artifacts on the more stylized renders.

20:25 – 20:55

14 · Learn more with Maker School

Closes with a pitch for Maker School, his money-back-guaranteed coaching program.

Atomic Insights

Lines worth screenshotting.

A single still reference image plus a short source clip is now enough to re-render an entire talking-head video in a new visual style, no motion capture required.
The current generation of video style-transfer models can't process a full video in one pass, so footage has to be split into ~20-second chunks and stitched back together afterward.
An AI coding agent (GPT-6 Astra via Codex) can run the entire split, render, inspect, retry, and stitch loop unattended once it's given the operating rules and file paths.
A 5-second Genjutsu render costs about 32.5 credits; a 20-second render costs roughly 130 credits, meaning cost scales close to linearly with clip length.
WAN 3.0 produced a comparable style transfer for about 9 credits versus 32.5 for the same length on Genjutsu, at a slight quality tradeoff.
WAN 2.2 Animate (14B) is a free, open-weight model on Hugging Face that can be self-hosted and run entirely on your own hardware.
Failed style-transfer generations refund their credits automatically, so testing a prompt costs nothing when the render fails outright.
One recorded video ad can be style-transferred into 20-30 visually distinct versions and split-tested, letting a business put its budget behind whichever visual style converts best instead of guessing.
Mouth and lip-sync accuracy degrades on softer, more stylized art styles, which the presenter attributes to those styles rendering facial detail with less precision.
Silero VAD plus FFmpeg is used post-stitch specifically to detect and trim silences longer than a set threshold, tightening pacing without manual editing.

Takeaway

How to re-style any video without reshooting it.

WHAT TO LEARN

A still reference image plus a short source clip is now enough to re-render a whole video in a new visual style, and handing the multi-step pipeline to an AI agent is what makes doing this at scale realistic.

01I turned myself into an animated character

The entire video being watched is itself proof of the technique: it was style-transferred, not just demonstrated on a short clip.

02How video style transfer works

The core mechanism is a source recording combined with a separately generated style-reference image to produce the stylized output.
No motion-capture hardware is required; a normal recording against a plain background is enough as the source.

03Astra as your production manager

The five-step pipeline (split, Genjutsu, stitch, Silero VAD + FFmpeg, review/export) is the repeatable structure behind any style-transfer project, whether run manually or by an agent.

0410 animation styles to try

Multiple style options can be generated cheaply from a single source frame before committing to a full video render, letting you pick a style before spending on motion transfer.

05Setting up Higgsfield

Aggregator platforms that host multiple image and video models in one place lower the setup cost of experimenting with style transfer.

06Creating a style with GPT Image 2.5

Explicitly prompting a model to keep facial features and identity recognizable prevents the common failure mode where a stylized image no longer looks like the source person.

07Animating your footage with Genjutsu

Trimming a source clip to the length you actually need before rendering keeps costs and iteration time down while testing a workflow.
A precise prompt describing what the style reference should and shouldn't control (style vs. motion) improves how faithfully the source performance carries through.

08Using style transfer for ads and content

One piece of source footage can be turned into many stylistic variants for split-testing which visual treatment performs best with a given audience.
The economics favor this approach once even a modest lift in conversion rate is possible, since generation costs are small relative to ad spend.

09Wan 3.0: a cheaper alternative

A cheaper model can deliver comparable results at a quality tradeoff, worth testing before defaulting to the most expensive option.

10Automating the workflow with GPT-6-Astra

Writing out explicit operating rules for an AI agent (what to check, when to ask before spending credits, how to handle failures) is what makes a multi-step pipeline safe to hand off.
Connecting a specialized tool as a plugin to a general coding agent lets that agent orchestrate work outside its own native capabilities.

11Resolution, credits, and silence removal

Having the agent quote credit cost and ask for approval before running a paid job is a simple guardrail worth building into any agent-driven pipeline that spends money.

12Self-hosting Wan 2.2 Animate

A free, open-weight version of the same category of model exists and can be run on owned hardware, trading setup effort for zero per-render cost.

13Reviewing the animated results

Reviewing output for specific failure modes, like mouth-tracking drift, before shipping catches quality issues that aren't obvious from a quick glance.

Glossary

Terms worth knowing.

Genjutsu: A Higgsfield video model that transfers the motion, timing, and performance from a source video onto a separately generated style-reference image, producing a re-styled version of the original clip.
Style transfer: Re-rendering an image or video so it takes on a different visual style (illustration, 3D animation, etc.) while keeping the original subject and motion recognizable.
Motion transfer: The specific technique of taking movement, gaze, blinks, and gestures from a reference video and applying them to a different, stylized character or image.
GPT-6 Astra: The AI model used here inside the Codex app to plan, run, inspect, and retry each step of the video-production pipeline, acting as an automated production manager.
Codex: OpenAI's coding-agent app that can be given a project folder, plugins, and instructions, then carry out multi-step technical tasks like running a video pipeline.
WAN 2.2 / WAN 3.0: A family of open video-generation models; WAN 3.0 is a paid, cheaper alternative to Genjutsu for style transfer, while WAN 2.2 Animate is a free, open-weight version that can be run on your own hardware.
Silero VAD: A voice-activity-detection tool used to find and trim silences in an audio track, applied here after stitching clips together to remove pauses longer than a chosen threshold.
Painterly 3D animation: One of the ten preset visual styles shown, rendering the subject with soft painted textures and warm cinematic lighting rather than flat cartoon shading.

Resources

Things they pointed at.

02:29toolGenjutsu (Higgsfield) ↗

05:47toolHiggsfield platform ↗

07:01toolGPT Image 2.5 (Sunburst)

02:44toolSilero VAD

12:00toolWAN 3.0

13:46toolGPT-6 Astra / Codex

14:10linkMaker Zero (free prompts) ↗

18:10toolWAN 2.2 Animate 14B (self-hosted) ↗

20:34productMaker School ↗

Quotables

Lines you could clip.

08:15

“I want to look like Nick Sarayev, so let's give it a go.”

quick, funny, relatable line about wanting the AI output to stay recognizable→ TikTok hook↗ Tweet quote

02:58

“This technology is not 100% yet.”

honest one-line caveat that undercuts the hype, good pattern-interrupt→ IG reel cold open↗ Tweet quote

11:05

“You basically just have one ad, a video ad, and then you flip it such that it's like 20 or 30 different styles, split test all of these futures, determine which one delivers the larger return on investment.”

the single strongest business use case in the video, self-contained→ newsletter pull-quote↗ Tweet quote

The Script

Word for word.

Read-along

Don't just watch it. Burn it in.

See every word as it's spoken — crank it to 2× and still catch all of it. The same dual-channel trick behind Amazon's Kindle + Audible.

metaphor

This entire video is going to feature me in an animated style. The reason I'm doing this is twofold. First, I genuinely believe this is the next level of creativity for creators and people on the internet like myself.

Just like we used to wear different clothes or adorn ourselves with jewelry, so too is modifying the actual style of a piece of media going to be how we express ourselves in the future. I wanted to show you guys how to do it. I'm going to open source my approach to doing this in a very scalable way.

I'll show you a consumer method that you can use first that's easily available and requires just an API call. And then afterwards, I'll show you guys a pipeline that you can use to optimize with GPT -6 Astra and other cutting edge AI agents to allow yourselves to generate these more economically. I'm also going to give you everything that you need to do this, all the templates and the skills and everything down below.

So you guys can just copy and paste this into your own business or your own media production pipeline, whatever the style is. So how exactly does this work?

Well, the actual flow all starts with a normal recorded video. In the past, you had to use complicated motion capture systems and stuff like that in order to achieve the stylistic transfers that I'm showing you. But today you don't have to do any of that.

You just record a video without a lot of noise in the background, ideally. As you guys could see over here, I'm going to be feeding in a source video that looks something like this. My hair is going to be a little bit different.

And then the background of the video is, for the most part, just like a white wall. What we're going to do is somewhere between the original recording and the ultimate stylized look, we're going to provide a style image. And you can think of that style image as basically multiplying my core recording times the style in order to get the output.

We've been able to do this for a while now with... images. And actually one of the very first things that I worked on back in 2019 was how to apply like image style transfer to a variety of different things, you know, like abstract art, pictures of myself and so on and so forth.

But right now is the first time we're actually able to do so meaningfully with video. In a nutshell, here's how it works. The core video is going to supply motion.

We're then going to generate using GPT. image 2 .5 or another model a style reference based off of that initial image that's very important needs to be the same character sort of just with some stylistic additions and then we're basically just going to multiply the two okay pass it through this genjutsu model and i'm going to show you some alternative models that you guys could optimize on your own hardware as well for cost purposes if you wanted to do this at scale like one three turbo for instance and then basically you achieve this stylized clip the way that i've set up the system and there's probably a bunch of people in the comments that can come up with a simpler and easier way is astra basically acts as the production manager i've tried using a variety of other models to do this i find that you need to provide it a lot more like oversight if you want to do a good job.

So I'm just going to be using Astra. But keep in mind, maybe if you give it the exact SOP, you guys can do away with a cheaper model that might use fewer tokens. Essentially, what GPT -6 Astra is doing is it's going to plan, run, inspect, and that's important, as well as retry any failed gens because this technology is not 100 % yet.

So the flow looks like this. We're going to feed in a piece of footage, the core thing. We're then going to use a model known as Genjutsu to apply the style transfer.

We're then going to stitch the outputs together, and then we're going to post -process them using a tool called Solero Voice Activity Detection and then FFmpeg. We're going to do all this at a specific frame rate to, in my case, give it like an animated sort of style. And then at the end, we review and we export.

As mentioned, there's a fair bit of splitting going on. And so really what's happening because of the current limitations of these models, including Genjutsu, is you can't just feed in the whole video in one go and be done with it. The models just aren't that good yet.

Maybe they will be in three to six months from now, but certainly not right now. And so in order to achieve this, you need to take, you know, let's say a five -minute video, and then you need to divide it into chunks. So this might be kind of your first 20 seconds here.

This might be your second 20 seconds here. This might be your third 20 seconds here, and so on and so forth. And the good news is you get the original audio.

Your model, aka GPD6 Astra, basically is just going to inspect every join to make sure there are no major discrepancies between the gens. Because as you'll see, if you're feeding in multiple runs to this Genji 2, model and i'm going to show you guys an alternative to that in a moment as well you know sometimes the the stylization is going to look a little bit different from person to person now the first thing you have to do in order to make this work is you need some form of style transfer and so what i've done here is i've taken a single frame of my face and i basically had gpt image 2 .5 make a bunch of modifications to it So I'm going to run you through an actual practical zero to one of me, like literally making the prompt and then generating the image in a moment.

But first, I just wanted to show you what all of the styles that you guys saw earlier. started as. You could see that one was a 3D sort of painted style, and that's the one that I chose just because I think it's pretty cool.

This one here is a prestige hand -drawn anime. You could see the original image was this, and this is sort of the stylized one. Next one was that sculpted stop -motion effect, which I think is super cool, obviously.

It kind of changed the fundamental nature of my sweater, but it is what it is. This one's the ink and graphic novel. We have oil -painted animation, which I think was really cool too.

Watercolor slash graphite. layered paper relief, premium feature film CG, lean Claire animation. I don't actually know how to say that, but I think the style is really cool.

Kind of reminds me of that Keanu Reeves movie and then charcoal and chalk as well. Okay. So we need to actually generate these.

That's sort of step number one. So what I'm going to do first is actually walk you guys through how to do this. Probably the simplest and easiest one -stop shop for all of the stuff is Higgs field.

These guys basically have just aggregated every image and video model known to man and stuck it all in one place. And so that is what I'm using here more for my own ease of use than anything else. I'm going to walk you guys through how to sign up and then set everything up right now, too.

So you can do the same thing. And what's really useful is they also host their Genjutsu model, which is the model that I'm using initially as part of this demo. I'm going to run you guys through some other software that you could use at the end of the course as well.

But this is definitely probably the easiest way of doing so. So they have some sort of discount up. I'm just going to click get my discount and then.

I'm going to go continue with email, make sure to actually agree to those dang terms. Let's put in my email address. I was previously running a bunch of influencer campaigns with user -generated avatars and stuff like that, marketing the skincare brands and so on and so forth.

That's what all of those are. I don't think there's any way to remove that, or maybe there are, and I'm just being silly. But the way that this interface works is basically over here, you have all of your previous generations.

and then right down over here is where you feed in the image that you want to modify and so i'm going to be using gpt image 2 .5 sunburst that's the model that i want and then what i want to do is i just want to feed in a frame of my face okay which i've actually already done over here as you can see i'm looking kind of silly you can get this frame any way that you want i mean you could literally just take like a screenshot of any video that you've recorded or something like that in order to get it but basically you just need a frame okay and then afterwards you convert it to some sort of style so i don't know i think that like i want a cool 3d style let's say convert this to a cool 3d avant -garde stylized you know style while making sure the man's features and everything else about him are recognizably him Okay, so the idea is, you know, I want this to be recognizably me, but you'll find a lot of the time happens when you do stuff like this is they come out and then they're not recognizably you for whatever reason.

You know, they like try and make you look prettier than you really are. I don't want to look prettier, man. I want to look like Nick Sarayev, so let's give it a go.

After a few moments, an output like this is going to show up. As you guys could see, it's stylized with really big eyes and I kind of look like a cartoon character. My hair looks pretty dope though, I'm not gonna lie.

Let's go see some ideas. And now you have everything that you need in order to actually do the style transfer, assuming we also have the core video. There's also this one here where I'm kind of blocky and I really like the blocky one.

Actually, I think it looks really neat. So I'm going to give that a try. So all I'm going to do is click download in the bottom right hand corner.

And now I actually have this on my computer so I can continue with the next step. And now you need some sort of video of yourself. So I have a 50 second clip that I recorded kind of just as a demo because I wanted to show you guys how you can do this on a short clip.

Obviously, short clips also keep costs low, but I'm going to run you guys through what that whole process looks like here. The only issue is I don't have my headphones, I think. So that's one thing I'm going to have to change, but that should be OK.

The model to choose is video and then go to Higgs Field Genjutsu. this is the thing that'll actually transfer the motion and then what we're going to want to do is we're going to feed in that video with the still that i showed you guys a moment ago my case that's right over here i'm just going to feed that in and we do have to trim it to 30 seconds in order to use it just because what we're doing here is a test and i just want to show you guys something as quick as humanly possible let me just move it to when i start talking there we go and then after that we're just going to add this here which should add the stylized image after it's all ready to go see we now have that sort of 3d version that's what i want to select and it's the same thing that i showed you guys earlier with like a cool 3d effect last thing we have to do is add a prompt and so the prompt i'm going to use here is transfer the exact same performance from the reference video that's this to the same man in the style reference image that's that preserve his recognizable identity face shape curly hair stubble gray sweatshirt and black microphone

Now, because I used this for a previous prompt, it says the reference image defines only the painterly 3D rendering style and character design. I'm just going to remove the painterly and I'll just say 3D rendering style. But the video is authoritative for head movements, gaze direction, blinks, mouth shapes, lip articulation, shoulder movement, and so on and so on and so forth.

So you need... So yeah I mean I'm going to give you guys the whole prompt below you don't need to read it all but we're basically just saying hey keep it as simple and as close as humanly possible to the original gen. One of the reasons I think this is so cool is because you can use another model to actually generate the video.

And then you can stylistically flip it or style transfer the generated video with a generated image style. And so obviously I'm doing this here on my own footage. And the reason why is because I think this is genuinely like a step towards all creators having their own distinct visual style and so on and so forth.

But you don't have to, you know, just use your own footage for this. You guys could use whatever the heck you want. This is extremely...

powerful for ads. Because a lot of the time, human beings, according to where they live and their culture and their preferences and their markets, we like different things. And so I'm imagining a future where you basically just have one ad, a video ad, and then you flip it such that it's like 20 or 30 different styles, split test all of these futures, determine which one delivers the larger return on investment, say if it's like a 30 -second ad or something like that, and then just put all your money in that basket instead of spreading them all out like most people do.

And as somebody that's run a fair few number of ad campaigns myself now, I could see something like that working really well. And that's where the economics of video production start to actually make sense. Right now, this costs, what, 32 .5 credits in order for me to do this on a five -second run.

I think mathematically, if you were to do this for a 20 -second run, it'd be like 130 credits or so. You know, 130 credits is not free, right? Like obviously you're spending money for it.

But if you do this across, let's say, a number of ad sets, and then it helps you determine what one specific ad that has, I don't know, 1 .5 to 2x the conversion potential because that style just happens to be in or it's much more visually appealing, then you make your money back on that in the first few clicks that you get.

And it's worth noting, you can use the exact same approach that I talked about here, but then use WAN 3 .0. WAN 3 .0 is basically just another model that's very similar to Genjutsu and probably related to what they're doing underneath the hood, but it's just the core intelligence. And so what I did here is actually ran a test of WAN 3 .0, where I fed in this reference image as style, and then this video over here as the actual motion.

Then I said, transfer the exact performance from the reference video, the same as the style reference image. And you can see for the same length of time, rather than it taking over 32 .5 tokens or credits, I think it was before. Now we're down to nine at 720p at 16 by nine.

And so the quality is not the exact same, but it's still pretty good. Occasionally a transfer will fail. And so this was one that failed with Higgs field Genjutsu over here.

When that happens, you have all your credits refunded. And then, you know, it's just because of usually some mathematic elaboration, not because you got censored or whatever, unless you were using a copyrighted character, in which case you probably will get. but then anyway you can just click retry and it'll rerun it.

By the way I'm going to show you how you can do this not just manually but also with GPT -6 Astra in a minute. I want to make sure to build out the logic so you guys know the steps that you have to follow in order to get it done. Okay you guys could see we've actually now finished it and the results are pretty cool.

He animated just like this and the reason I'm making it is because I think this is a Right. So an important thing to note here is we just did this for five seconds.

Aside from that, though, it did pretty well. I mean, it captured virtually all of my features. It captured like everything about my apartment room.

And I also had some pretty cool, sexy lighting. What I did now, if you think about it, is I just showed you guys how to go from zero to an actual generated version of the output. That's really cool and pretty straightforward to do.

But if we want to go beyond just generating like a five second or a 10 second or a 20 second stitch, we kind of have to level up. And I could sit here doing it all manually, or I could just give it to GPT -6 Astra to do it for me. So how do you do this in Codex?

It's fairly straightforward. All you need to do is open up the Codex app, which you guys can download from ChatGPT's website. It looks something like this.

Then give it a folder to work in. In my case, I'm working in the example folder. And then just make sure that it's inside and can hear what you're saying.

My model picker here is set to GPT -6 Astra High. Obviously, you guys can go as high as you possibly want. I'm not going to go much higher than that.

Then, if you guys head over to Maker Zero, which is the second link in the description, it'll have links to full prompts with everything you need in order to stylize your videos, just like how I showed you guys a moment ago. The one that you guys are going to want is this Genjutsu prompt, assuming you guys want to do the Genjutsu workflow.

And then from here, it'll say, you are Astra, I'm a video production operator. Help me turn a recording of myself into a polished... animated or illustrated video using the Hikso plugin and Gijutsu from the work with the available tools and so on and so on and so forth.

So all you have to do is just double click this and then go back into Codex and then paste it in. It's already reading the pasted requests and what it's first asking for is for me to attach my video or to give it its accessible local file path. So I have my minute long video here.

I'm just going to drag and drop it right in and I'll say here's the video. Now it's going to use that to come up with that cool file path. as discussed earlier.

Once it's done you then have a little snippet or a frame that it's been taken from. It defaults to painterly 3D animation, which is the style that I'm using for this video, but obviously you guys can do it however you want. I'm going to say yes, use that default, just because I think that style is super dope.

And now what it's going to do is check Higgs Field's available models, account status, and pricing before preparing the quote. It's then going to send the media to Higgs Field, and then the benefit is it's even going to ask you if you guys are open to spending X credits for X result. The reason why I put that in there is because I just wanted to make sure that there was a verification step before you continued.

Now, if you don't have Higgs field connected as a plugin, this is where you'd have to add it. The way to do that is really straightforward. Just head over to plugins up here, type Higgs field, click the bat puppy and click the install plugin button.

So if you don't already have that in, what this will do is install the plugin for you. After you run that OAuth, it'll then verify what account you are a part of. In my case, that is my account.

And now it's actually going ahead through the production range. So here it's giving you some options. It's saying, do you want to do the full 60 seconds, a short test only or specific range?

You know, what sort of resolution do you want? Do you want 1080p, 720p, 480p? Do you want to keep the original pauses, cut pauses longer than 0 .8 seconds, 0 .4 seconds or a custom threshold?

What I'm going to say here is, you know, let's do the full 60 sec. We'll do 720p. Actually, I don't want this to take forever.

Maybe we'll do 480p. No, we'll do 720p. And then I'll cut anything longer than um 0 .5 seconds okay the idea there is you know it's just what you need to get one of those cool youtube jump cuts and that's obviously my my style it'll get back to you with information on how long the tests are going to take credit wise it's going to run the painterly 3d still just using nano banana pro to save on credits and then as mentioned i mean this is just one way i could do it i'm using genjutsu here, but you guys could also use WAN 3 .0 if you wanted, and then cut that down an order of approximately three.

So it'd be a little under a hundred. If you wanted to do that, you go down to WAN 3 .0 prompt for Higgs field. So I'm just going to copy that in, and then I'd paste that back into codecs, just like I did a moment ago.

It's gone ahead and actually generated that style for me. As you guys could see here, style is a little bit different from the example that I provided earlier. Obviously, every time you generate an image, it's going to be a little bit different, but that's still pretty cool.

So now I'm going to say, yes, go ahead and do the whole thing. I'll 60 sec, then join and serve. Now worth noting, you could actually download a slightly dumber version of this one, 2 .2 animate 14 bill and run it locally on your computer.

And so that's actually what I have done with this inference pipeline, because I've tried to optimize this to run. basically as quickly as humanly possible. So while these big providers are obviously fantastic at getting you up and running and then showing you guys what is possible, you know, if you did want to serve like a dedicated pipeline and do this really quickly across all your videos, you can just direct an agent over to this link right over here, huggingface .co slash one dash AI slash one 2 .2 dash anime dash 14 bill.

And you guys can actually legitimately download this and then do whatever the heck you want with it. You can run it on other hardware as well. I've experimented with a variety of different ways of doing this.

If you're trying to run it on your own, it could take a fair amount of time as well. Just keep that in mind. But yeah, that is how you do it.

It basically just allows you to animate and then replace characters. And you can do whatever sorts of optimizations that you want to it to make it even faster. So obviously, I don't want to make this super ridiculously technical.

So I'm not going to include information on all of that here. But I wanted to make sure that you guys... I just knew that was an option as well.

Okay, and first clip is in. This whole video is going to be animated just like this. And the reason I'm making it is because I think this is a glimpse into the future of what most media will look like.

Not this exact style, obviously. I'm not going to be painted in this exact way. But pretty soon, we're all going to have the choice to consume media in format.

And as you guys can see, there were some minor issues with mouth movements and stuff like that. I find that this tends to happen when... um you're using kind of more stylized artistic forms like this you know i'd say the one that i'm using right now is also quite stylized and artistic but this one seems a little bit softer around the edges and i think that's probably impacting its ability to like track my mouth um also i don't know maybe i'm just not really moving my mouth around that much still pretty reasonable quality i would say so i'm going to wait for it to continue and make the other two segments and then combine them all so that's one reason i wanted to do that the second reason is i want to show you guys how to do it Naturally, this was done using GPT -6 Astra, as well as a couple of cool...

Cool, cool, cool. So hopefully it's clearer. You know, this is now interpreted and inherited the style that I trained it on.

And yeah, you guys could do something like this yourselves. You guys could upload this to YouTube. You guys could clip this in a variety of different formats.

I genuinely think this is probably one of the simplest and easiest things that anybody could do right now to make themselves fundamentally stand out. But obviously, there's some packaging things that I think people need to get right. If you have any questions whatsoever, just leave them down below.

I actually get my ideas for future videos from comments from people just like yourself. Really excited at, I think, the next phase of human creativity in media. We're seeing some extremely cool breakthroughs in AI virtually every day, and I thought this would be a cool way to expand that conversation.

If you guys like this sort of thing and want to learn how to monetize your own media production, automation business, AI service business, or anything that has to do with the technology that you saw today, definitely check out Maker School. It's my 90 -day accountability program that shows you everything you need to do in order to land your first customer.

By the end of that 90 days, if you have yet to acquire your first customer, I actually give you all your money back. So it's 100 % money back guaranteed. Anywho, thank you again, and I'll catch everybody here in the next video.

The Hook

The bait, then the rug-pull.

Every frame of this video, including the presenter's own face, has already been run through the exact AI style-transfer pipeline it's about to explain, framed as proof the technique holds up across a full 21-minute video, not just a demo clip.

Frameworks

Named ideas worth stealing.

02:44list

The Astra Production Pipeline

Split
Genjutsu
Stitch
Silero VAD + FFmpeg
Review + export

The five-step loop GPT-6 Astra runs unattended: split the source video into chunks, render each through Genjutsu, stitch the outputs together, trim silences with Silero VAD and FFmpeg, then review and export.

Steal forany AI-agent-driven media pipeline that needs a repeatable split/render/inspect/retry loop

CTA Breakdown

How they asked for the click.

VERBAL ASK

20:34product

“check out Maker School... it's my 90-day accountability program... 100% money back guaranteed”

Soft build starting around 20:05 ('I actually get my ideas from comments... really excited about the next phase of human creativity') into a direct pitch at 20:34, placed only after the full technical demo is complete.

MENTIONED ON CAMERA

02:29toolGenjutsu (Higgsfield) ↗

05:47toolHiggsfield platform ↗

14:10linkMaker Zero (free prompts) ↗

18:10toolWAN 2.2 Animate 14B (self-hosted) ↗

20:34productMaker School ↗

FROM THE DESCRIPTION

PRIMARY CTAWhere the creator wants you to go next.

Storyboard