VO3.1 Nano Banana Sora 2. There are all

of these amazing models dropping. So, I

figured why not just build a system

where we can use all of them. So, what

we're going to be looking at today is

the ultimate UGC ads system where all

you have to do is fill in some raw

information on a Google sheet like a

product photo, the ICP, the features of

that product, and a setting of the

video. And then all you have to do is

come in here and choose your model.

Whether that is V3.1, a combination of

Nano Banana and V3.1, which is super

cool. I'll show you guys exactly how we

do that in a sec here, or using Sora 2.

This lets you seamlessly test a bunch of

different creatives and product features

and settings across a ton of these

different AI video generation models.

So, the question that we're going to be

trying to answer today is which one is

best for UGC ads. So, taking a look at

this workflow, you can see that there's

basically three paths. There's the VO3.1

path, the Nano Banana Plus V3.1 path,

and then the Sora 2 path. So, we're

going to jump into a live demo. We're

going to run all three of these paths,

and I'm going to explain what every

single node is doing so that you guys

can set this up for yourself. And as

always, I'm giving away the entire

system for free. All you have to do is

join my free school community. The link

for that is down in the description. So,

before we go ahead and run the live

example, let's look at a few of our

outputs that we've already gotten with

this exact system. So, the first product

we tried was creatine gummies. Here is

what the actual product photo looks

like. So, you can see it's a creatine

gummy jar. We then have the ICP, which

is young adults wanting to stay fit. The

product features for this are delicious

gummies, easy to remember to take daily,

makes workouts better, more energetic,

stuff like that. In the video setting,

we have a young man who is parked in his

car about to go into the gym holding the

gummies. So, the first one we'll look at

is Nano Banana Plus Google V3.1.

>> I love that these creatine gummies

actually give me more energy for my sets

and they're tasty, so I actually

remember to take them every day.

>> All right, here's the same one with Sora

2.

>> I love these creatine gummies. They

actually taste amazing and I never

forget to take them. They make my

workout stronger and I feel more

energized.

>> And then here's V3.1. These taste

amazing and I actually remember them

every day for a my workouts feel

stronger and I've got more energy.

>> You may have noticed a few things with

the reference image and the way they

were speaking, but let's continue on to

the second example which was hair shine

spray. So, I'm going to go in the same

order. Nano Banana Plus VO3.1 Sor 2 and

then V3.1.

>> I love how this gives my hair that

glossy finish without any greasiness. It

dries instantly and feels weightless. I

love how this gives instant glossy shine

without any greasiness. It dries fast

and feels weightless. I love how this

adds instant gloss without feeling

greasy. It dries so fast and leaves no

sticky buildup.

>> All right, so we've seen a few examples.

We'll come back at the end and compare

more outputs and see which one we

ultimately deem being the king of these

models. But let's go ahead and do a live

example. So the first two that we did

were AI generated images. This first one

was creatine gummies, as you can see,

and the second one was our hairspray,

which looked like this. So, what we're

going to do for the third example is a

real product image, and this is actually

from an Amazon listing. So, it is a

portable neck fan like this. We have the

ICP of middle-aged adults who spend long

hours outdoors or landscapers,

construction workers. We have product

features like it's comfortable, it's

light, it delivers powerful air upward

and downward, and it regulates your body

temperature. And we have the video

setting for a friendly middle-aged woman

tending her garden in the afternoon sun.

So, hopefully you guys can see the value

prop here. it'd be really easy to just

throw in your product information right

here and then have this thing every day

create tons of UGC ad content for you.

Then what happens in the workflow is it

takes that and we have different AI

agents here that are trained to prompt

in different ways and that's how we're

optimizing you know the features and ICP

and the setting to actually go into this

UGC content. So I'm going to go ahead

and hit execute workflow. It's going to

pull in that data from the sheet. It's

going to do one row first and the first

row that it's doing is nano Banana plus

V3.1 because as you can see right here

it's basically processing this row and

that's the model that we chose was

NanoBanana plus V3.1. So I'm actually

just going to start to explain what's

going on here as this is running. So you

can see here we're pulling in data from

this sheet, right? The only thing

special going on here is we're making

sure that the status column equals ready

because we don't want to pull in all of

these rows that have already been

finished. And then we also turned on

this option that says return only the

first matching row because we don't want

to do, you know, all six of these at a

time. We want to just do one by one. You

could obviously change that if you want,

but that's the way we're rocking right

now. Anyways, we then go into this

switch node and what happens here is it

basically just checks what the model was

selected as. So if it was V3.1, it goes

up. If it was nano plus V3.1, it goes to

the middle. And if it was SOAR 2, it

goes down. As you can see, these three

paths. So, this one was obviously V3.1

plus nanobanana, which is why it went

here. And that's why we're doing this

first step, which is an image prompt.

So, let me explain why I'm doing this.

What we're starting with is a picture of

our product because we need to make sure

that the product image looks actually

good in our final copy. Otherwise, we're

not going to be able to sell any of

that. So, in my mind, the most ideal way

to do this is to take that product image

that we're given. So, if we just want to

get a quick refresher, taking this

product image right here and using AI to

turn this into an image where someone is

wearing it or holding it and then we can

take that optimized image and turn that

into a video. And so, ideally, I would

do this also for Sora. But when you send

a image to Sora, if it looks like a

realistic human person, even if it's an

AI generated human, it's going to reject

it. Google VO3.1 however does not reject

it which is why we have this little

extra bonus method here. Now the

workaround here is if you do Sora 2 you

can use cameos. So if you haven't seen

that before then I'll drop my video I

made with Nitn and Sora 2. I'll tag it

right up here and you can see you could

use cameos. So you could create one of

yourself or you could use some other

person and have them being in your

content with your product something like

that. So anyways we're using Nano Banana

to create an image of the product being

held or worn by a person. And then we

take that image and we turn it into a

video with VO3.1. So anyways, you can

see that that actually just finished up.

So that's telling me I need to speed up

a little bit. Let's click into this AI

agent to understand how it is making an

image prompt. We're giving it two

things. We're giving it the product,

which as you can see, if I open this up,

it's coming through as portable neck

fan, and we're giving it the image

setting, which is actually just the

video setting, but it says, "A friendly

middle-aged woman is tending her garden

under the sun. She pauses, smiles at the

camera, and gestures toward the sleek

fan resting around her neck." So the AI

agent takes that information and then it

reads through its system prompt to

understand what do I need to do with

that information. I'm not going to read

this entire system prompt, but you guys

will be able to once again download this

template for free and you can dive into

this and understand why I have it set up

this way. One thing I did want to

preface though is I made this workflow

to be a template. So these system

prompts are not perfect or optimized and

it would really be on you to get in here

and customize them a little bit for your

use case, but it gives us a great place

to start. So anyways, you are an expert

in hyperrealistic UGC userenerated

content photography and your role is to

generate detailed image prompts, not the

images themselves. So you will be

provided with a product photo which

should not be changed or altered in any

way. And you will also be given a

specific setting or scene description.

So it knows that its role is to create a

prompt. So we come in here and we give

it some prompt guidelines. We talk about

human realism. We talk about product

accuracy. We talk about composition and

perspective. We talk about lighting and

environment. We talk about authentic

details, technical style. And then

finally, some critical instruction like

only outputting the image prompt, not an

actual image or you know, hey, here's

your image prompt. You know, we just

want the prompt. So, out of that, what

we get is our image prompt. And you can

see it's pretty detailed. It has stuff

like lighting. It has stuff like camera

angle and composition and stuff like

that. And we're able to take that

output, feed it into the next node,

which is our HTTP request to a service

called Key AI, which lets us access tons

of different AI image and video

generation models. So this is key. As

you can see, we have tons of stuff like

VO3.1, Sora 2 Pro, 40 image, Flux

Context, Cling Turbo. It's kind of like

the open router for image and video

generation models. So, I'm not going to

deep dive into exactly how I set up this

API call, but definitely go and watch

that sore video if you haven't because I

actually go step by step and show you

guys how I did that. I'll also tag right

up here an API video that I made, which

you should watch anyways because it

really explains APIs and agents and

stuff like that. Anyways, essentially

what we're passing over here is our JSON

body, which is the most important part.

The model that we want to use is nano

bananait. We're sending over the input

prompt, which as you can see right here

is coming through. This is the output of

the image prompt agent that we just

looked at. Now, there is one thing I did

here that's kind of special is I

replaced new lines because you can see

if I get rid of this expression real

quick, what happens is we get these

little line breaks in here and we don't

want that because that will actually

break our request to key AI. So, that's

why I use that little expression. I also

talk about that in the Sora video. And

then we're giving it the image URL,

which is the one that came from our

Google sheet right here as you can see.

Finally, we're just saying we want this

to be vertical because a lot of times

the UGC content is kind of selfie style

and it's for like a Tik Tok or an

Instagram reel. So that's what we do

there. Once key gets this request, it

basically says to us, okay, cool. I got

all this information. We're working on

that right now. And so the next step

that we move into here is a wait node.

You can see that I have this set up for

5 seconds. So it goes ahead and it waits

for 5 seconds and then it checks in on

key and says, "Hey, do you have my order

done yet?" And we're able to get to that

by sending over the task ID of the

previous order. So it's like when you go

to a food truck and you order your food

and it says, "Okay, your order number

43." This is basically you walking back

up to the truck and saying, "Hey, I'm

order 43. Is it done?" And they'll

either say yes or no. And that's why we

use this little if node right here,

which is basically our yes or no check.

And we're looking to see if the state

equals success. Because if you look at

the first time we checked in, the state

equals waiting. The second time that we

checked in, the state equaled waiting.

And finally, the third time we checked

in, the state equals success, which

means that our order is ready. And so

notice that we have false branch or true

branch, and it's true when it's done. So

what we do is if it's false, we have

this line that goes back to the wait. So

this is why you can see it waited three

times, which means this took about 15

seconds to generate. And so the first

time it wasn't ready, it came back.

Second time it wasn't ready. We checked

in again. And then the third time after

it waited again, it was done. And so

when that's done, what we end up doing

is we want to real quick analyze that

image to see what is actually in there.

So here's the actual image that it

created for us, which looks awesome.

It's a green portable neck fan. She's in

her garden, and it even matches the

writing, as you can see. See, if we go

back to the source image, there's a

little bit of gold text right there.

There's these circles. So, that looks

really good. And so, I basically grabbed

this open AI note and said, "Describe

what's in the image. Describe the

environment." Stuff like that. And we

get back, the image features a woman

standing outdoors in what appears to be

a garden. The environment has raised

garden beds, blah blah blah. The woman

is wearing a light blue shirt. She has

her hair pulled back. Around her neck,

she has a green wearable device that

looks like a personal neck fan. Blah

blah blah. So, the reason why I wanted

to analyze the image real quick is

because the next step is to use another

AI agent to create a video prompt. And

in order to create a video prompt that

is consistent with our image, not only

are we going to give it that image, but

we also want to give it a quick analysis

of what is actually in that image so

that its prompt is consistent. And I

have tried doing this without the

analyze image step and it still works.

But doing this, it just seems to be

higher quality. So, anyways, we are

hitting another AI agent. This time

we're giving it a little bit more

information because keep in mind this

agent isn't just creating a video

prompt. It's also creating the dialogue

that the person in that video is going

to say. And so in order to do that, we

give it the product. We give it the

product ICP. We give it the product

features. We give the video setting. And

here's where we give it the reference

image description. So this is the

analysis of that image. So it looks at

all that information and it says, "Okay,

what do I do with that?" And so now we

have our system prompt. Once again, not

going to read the whole thing, but you

guys can have access to it for free. So,

we said that your role as an expert UGC

video creator. Your task is to generate

a prompt for an AI video model like

VO3.1. Your goal is to create a

realistic selfie style video that

appears to be filmed by an influencer

using one hand to hold the phone and the

other to interact with the product. The

video needs to feel authentic, which is

why UGC ads are converting so well right

now because it's just real people

speaking real raw thoughts. Anyways, we

gave it some requirements like subject

and framing. We talk about the visual

style. We talk about tone and dialogue.

We give it some technical specs. We give

it some embedded elements in the prompt.

As you can see, we tell it that it's

going to get a reference image and it

needs to match that appearance and tone.

And then a real quick output prompt,

which is pretty concise. And honestly,

it looks like I might have accidentally

cut off the last sentence here, but

hopefully it still came out all right.

And so after that, we get this output.

You can see it starts off with a natural

selfie style 9x6 vertical video, 8

seconds long. friendly middle-aged

woman, gardener. She's filming on her

phone. She's wearing a light blue shirt.

And then down here is where you can see

what the dialogue says. So, I love how

it's so light. I almost forget it's on,

but it pushes a ton of air and the

battery lasts all afternoon. So, that

basically took the product features that

we had given it and it made a quick

little blurb for this influencer to say

in the video. Now, we're going to take

this video prompt and we're going to

feed that into key once again and we're

going to send it to VO3.1. So, here is

our HTTP request where we're submitting

an order to VO3.1.

I'm going to open up this body, and you

can see that we have a prompt, which is

exactly what we just got from the lefth

hand side. Now, the reason it looks all

messy like this is because I'm actually

using three replace functions. I'm just

going to replace new lines, which we

already talked about. I'm going to

replace double quotes right here. It

previously said, I love how it's so

light and pushes a ton of air, and this

was wrapped in double quotes, but we

took those away because that will also

break the JSON body. And then I also had

to add another one. Sometimes based on

your chat model, it can be really weird

and output these double curly quotes

which don't actually get captured with

this previous replace function. So I

threw in this one just as an extra

guardrail which you guys will already

have all this set up. So you should be

good to go. But now we're basically

ensuring that our request will go

through. You can see once again we're

giving it the image URL except for this

one is actually the image you know it's

this one that Nano Banana made for us.

And then for the model we're saying V3

fast. We're using fast instead of

quality because it's cheaper and it's

faster and it's still really good. And I

know this says V3, but trust me, this is

using V3.1. And then aspect ratio 9x6.

We wanted to make sure that it matches

the source image. So now that we have

that, it basically does the exact same

thing. It gives us back a order number

or some sort of ticket. And we go ahead

and wait for 10 seconds right here. We

then go ahead and check back in on this

request, giving it our order number to

make to see if it's done or not. And

then you can see this happened eight

times. And so we basically checked in

eight times. So a total of 80 seconds.

So almost a minute and a half. And then

when we realize that the order is

actually done, we go ahead and we write

back to Google Sheets. And let me show

you real quick how we set up this Google

sheet right back. So we're using the

operation to update the row. And we

choose our sheet. Of course, we shoot we

choose our document. And then it says

that we have to match on a certain

column. So what we decide to do is match

on the column number. So you can see

right here, all of these rows have a

different unique number. And when the

workflow gets triggered, if we go all

the way back down to our initial get

rows, you can see that this row came in

and it was row number 10 or technically

row number 11, but the number was 10.

And so we're basically going to drag in

the number right here and say, okay, the

row that we want to update is the row

where the number column equals 10. And

so that's why it was able to write back

to this row right here, which you can

now see has been changed to status

finished. And we have our finished file

right here. because in Nitn we manually

set the status to be finished and then

we drag in the finished video URL that

we just got back from our key request.

And so that's basically the full process

and that's the most complicated one

because both the top one and the bottom

one are just doing reference image to

video rather than reference image to

image and then taking that image to

video. So anyways, we just covered the

hardest one and then we'll look at the

other ones. But real quick, let's just

go look at the actual output because of

course I'm very curious. I love how it's

so light I almost forget it's on, but it

pushes tons of air and the battery lasts

all afternoon.

>> That's really impressive. I was nervous

to see because it's different from

someone holding a product. She's

actually wearing it. But I mean, the

voice was really good. The tonality was

good. I thought that this was an

impressive result. But let's move on to

the next one, which is Sora 2. So, what

I'm going to do is go back into the

workflow and I'm going to execute it.

What this is going to do is pull in the

next And you can see it got pushed down

to Sora 2 because when it does this

check for the model, it knows that the

model was right here marked off as Sora

2. So I'm honestly not going to spend as

much time in these next two flows

because you guys pretty much already

understand exactly what's going on. We

have this video prompt agent which once

again is looking at the product, the

product ICP, the product features, and

the video setting. The only difference

here is that it doesn't have a analysis

of the reference image because it'll

just be given that. But the system

prompt once again we basically say

you're an advanced UGC video creator.

You're optimizing for video prompts for

Sora 2. Here is what you'll be given.

And we go over basically the same exact

headers. Subject and framing, visual

style, uh tone and dialogue, technical

specs prompt construction

instructions, and an example output

prompt as you can see down there. So

what that does is it once again it

outputs us a video prompt. And you can

see in this one there actually are new

lines. So, good thing we have that

guardrail baked in to get rid of those

new lines. As you can see in this HTTP

request to key, we fill in our body by

saying, okay, the model we want to use

is store to image to video. Here is the

prompt. And of course, we're using all

of those nasty replace functions once

again. We've got the image URL, which

we're grabbing from the Google sheet,

which once again looks like this right

there. And we're basically just sending

all of that over. And so, it's going to

take that video prompt and it's going to

take that source image and it's going to

turn that into a video. We're doing the

exact same thing here where, you know,

we submitted the order, we have to wait

10 seconds and then check in and we're

going to go ahead and constantly be

checking until we know that our video is

done. On average, I have been seeing

that V3 fast is finishing in anywhere

from a minute to 2 minutes. And Sora 2

has been taking typically a little bit

more than that, maybe a minute and a

half to 3 minutes. There are a few

things to consider. Sometimes if you do

something like a cameo, it's going to

take longer. If you've got a really long

video prompt, it'll take longer. Also,

what can influence it is how many people

in the world are trying to use keys

endpoints. that can make it take longer,

too. But typically, Google V3 fast is

faster, but it's the exact same flow

from there. We're pulling it back in.

We're doing the same match to update the

row, and then we're just updating the

status of finished. And we are putting

in the final video link into the Google

sheet. There you go. It looks like it

just finished up. Let's go back into the

Google sheet. It just got marked as

finished. And we have our file. So,

let's take a look at the Sora 2 output.

>> Man, this thing is so light and the

airflow hits my face perfectly. Keeps me

cool while I work. And the battery lasts

for hours, so I don't have to worry

about it dying out here.

>> Man, well, that was another really good

one. A little bit confused where this

thing came from. That was a bit of a

hallucination, but as you can see, this

was the reference image, and it looks

really good in this video. Super

authentic, and it looks like she's

obviously standing there taking a selfie

video. All right, so the final one for

this example is V3.1. So, I'm going to

go ahead and zoom out a little bit, hit

execute workflow, and it should shoot it

up this top branch now. And I'm honestly

not even going to break this down

because it's the exact same thing. I

copied over basically the exact same

system prompt. I just switched out 10

seconds, which is how long the Sor

videos are, for 8 seconds for how long

the V3.1 videos are. And then I switched

out sore 2 for V3.1. But I wanted to

keep these prompts across all of these

flows as consistent as possible to kind

of limit the variability that we have in

order to truly see the power of these

models when we have as many things

consistent as we can. So, I'm just going

to let this finish up and I will check

in with you guys when we get our

finished output from V3.1. All right, so

you can see that that one just finished

up. Once again, took about 80 seconds.

Let's go ahead and make sure we got this

updated. And let's take a look at the

V3.1 output.

>> I love how light this is turning. It

actually blows enough air to keep me

cool for hours while I'm working.

>> Okay, so it's not too bad. I honestly

think that right now my my order is this

exact order that we have here, which is

Nano plus V3.1, then Sora 2, then just

V3.1. A lot of these VO ones have like

this super HDR weird orange glow looking

effect. I'm not sure if you guys had

noticed that. Here's another example of

the VO3.1. It's not it's not terrible,

but just in comparison to some of the

other ones, it definitely looks a bit

more orange. And then another thing I

noticed is this is the V3.1 example, and

I explicitly told it to not change

anything about the reference image

itself, but we can see the creatine

gummies is a jar and then in the video

it's a bag. And so it does have the same

branding and same font as you can see.

He even actually, this is funny, he's

got the logo on his hoodie, which is

honestly a nice touch, but this is a

bag. And in the source image, it was a

jar. And the other creatine ones didn't

have a bag. They had the the correct

jar, too. And I know we didn't look at

the forearm strengthener example, but

this was another one where, for example,

Nano Plus V3.1. Let me just show you

guys this one. I love that the

adjustable resistance actually makes my

grip get stronger week to week, and it's

small enough to use right at my desk.

like super good, super natural, and the

product photo looked exactly like it did

that I gave it, which looked like this,

as you can see right here. But then that

same one with VO3.1 without Nano Banana.

Once again, it looks a bit it has some

weird shadows and it looks orange.

>> I love how the adjustable resistance

actually lets me progress without extra

gear.

>> But it the product photo also once again

does not exactly match the source image.

So that's kind of like a huge no no for

me. And another thing that you guys will

notice when you send a source image and

you turn that into a video both with

V3.1 and Sora is the first frame is the

reference image. And this is that first

creatine example we looked at with sore

2. And you'll notice the very first

frame is once again the reference image.

And so when we do nanobanana plus Google

V3.1 it still does that but our

reference image is this. So it just is

able to you know pick up right from here

and it looks way more natural. So the

point being you could kind of like

automate the content creation and you

could have it auto post as well with

this branch, but I probably wouldn't

auto post Google V3 like this or sore 2

like this because of that whole first

frame, first couple milliseconds thing.

Now some people argue that it's good

because then you have a thumbnail, but

then every single thumbnail on your feed

would look the exact same and that I

think would just come across really bad.

So that's why I think right now my

favorite is honestly Nanobanana plus

V3.1.

Now I think Sora would give it a run for

its money if it allowed you to upload a

realistic photo of a human. Because if

we go back to this first example with

the portable neck fan when Nano Banana

made that image, even though this is a

fake person and an AI generated image,

if you tried to feed that into Soore 2,

it would block you because of content

restrictions. So that's why this combo

has my vote right now. But another thing

to consider, of course, is cost. So

comparing these options, I guess there

were technically three, but let's just

look at these two because V3 is in here

for both. But option one is nanobanana

plus V3 fast. When you're going through

KI, which is the one that we were on

right up here, a nano banana image is

going to cost you 2 cents. So not bad.

And an 8second V3 fast video will cost

you 30. So total cost per piece of

content with this system would be 32.

Now, for option two, if you're using

Sora 2 and you're going through KAI,

which is the cheapest I've seen it, so

definitely do that. It will cost you 15

cents for 10-second video. So, really

not bad at all. About half the cost of

VO3 fast. So, option one is roughly two

times more expensive than Sora 2. So,

the question is, is it two times higher

quality and will it result in two times

more conversions? Or maybe it's not

exactly a two times match because it's a

lot cheaper than how much money you'd

make per sale or whatever it is. But

there is a bit of a trade-off there

because you can essentially make double

the amount of short form UDC content

with SOR 2 for the same price as using

Nano Banana and V3 Fast. So anyways, I

just wanted to sort of give you guys all

the info, give you the template, show

you the system, and explain the

differences between these two models.

And of course, I'm really really bullish

on all of this because the fact of the

matter is you guys can get in here and

make these prompts better. You can play

around with different chat models if you

want. We used GPT5 Mini for all of them

as you can see here. And think about in

6 months from now, a year from now, how

much better these models will be when

Sora 4 comes out and when V4 comes out.

They're just going to get better and

better and better and cheaper and

cheaper and cheaper. Anyways, I don't

want this video to go too long, but I

did say that you guys could access this

entire template for free. So, all you

have to do is join my free school

community. The link for that will be

down in the description. There will also

be a full setup guide right over here

when you download this template. And

when you join my free school community,

this is what it will look like. You'll

just have to click on YouTube resources

or you can search for the title of this

video. And when you click on the post

associated with the video, you will have

right here the JSON file to download and

you import that into niten and any other

guides or PDFs that you need. I will

also write here similar to this post, I

will include the link to copy this

Google sheet template so that you guys

can plug everything in and have a very

minimal amount of custom configuration

and just start, you know, producing

these types of results. And if you want

to see me actually build this system

live and just kind of talk about what

I'm doing, why I'm doing it, and my

thought process, then definitely check

out my plus community. The link for this

will also be down in the description.

We've got a great community of over 200

members who are building with naden

every day, asking questions, sharing

what they're learning, helping each

other out, and a lot of these people are

building businesses with NAND right now.

We've also got a classroom section with

three full courses. We've got agent

zero, which is the foundations for

beginners. We have 10 hours to 10

seconds where you learn how to identify,

design, and build time-saving

automations. We have one person AI

agency which is for our premium members

laying the foundation to build a

scalable AI automation business. And

then here's the course I was just

talking about with projects where we

actually dive into step-by-step setups

of practical workflows that you can

actually use. Probably one of the best

ways to actually learn NN in and out. We

also have one live call per week.

They're super fun. Everyone gets on

there and we ask questions and we have

some cool conversations about the space,

the industry, all this kind of stuff.

So, I'd love to see you guys in those

live calls in the community. But that's

going to do it for today. So, if you

enjoyed this one or you learned

something new, please give it a like. It

definitely helps me out a ton. And as

always, I appreciate you guys making it

to the end of the video. I'll see you on

the next one. Thanks everyone.