u/GrowWithMiz

I’ve been using CapCut for a while now to edit a lot of the videos I create with AI, and one thing I’ve learned is that you really don’t need to know advanced video editing to create good content.

Few years back, Editing frustrated me so much.

I literally had someone do all the video editing for me and I paid hundreds out of my pocket!

But now, i do all of the editing myself and most of what I do is actually pretty simple.

For example, if I’m creating an AI video, I might generate 5–6 different clips using different AI tools.

Instead of trying to generate one perfect long video, I bring all those clips into CapCut and build the final video there.

I’ll cut out parts of the generations I don’t like, shorten clips that feel too long, arrange everything in the right order, add my voiceover, music, sound effects, text and simple transitions.

Sometimes an AI generation might be 10 seconds long, but only 4 seconds look good.

Before, I would probably regenerate it.

Now, I’ll simply take those 4 seconds and work with them.

That alone can actually save AI credits.

I also love how much editing affects the final result.

The exact same AI clips can feel completely different depending on how quickly you cut between scenes,
where you add music, when a sound effect appears, or when text comes onto the screen.

And this is why I think learning some basic editing is really useful if you’re creating content for YouTube, Instagram or TikTok.

I am glad I took the initiative to learn and now I actually know a lot more about editing videos than I did before!

Even knowing how to cut clips properly, work with layers, add audio, use keyframes, adjust speed and understand basic transitions gives you a lot more control over what you create.

I’m still learning more myself, but the more I use CapCut, the more I realize how useful it is to understand the editing side of content creation, not just the AI generation side.

Do you use CapCut for editing? Is so, how good do you think you are with it?😃

I’ve been using CapCut for a while now to edit a lot of the videos I create with AI, and one thing I’ve learned is that you really don’t need to know advanced video editing to create good content.

Few years back, Editing frustrated me so much.

I literally had someone do all the video editing for me and I paid hundreds out of my pocket!

But now, i do all of the editing myself and most of what I do is actually pretty simple.

For example, if I’m creating an AI video, I might generate 5–6 different clips using different AI tools.

Instead of trying to generate one perfect long video, I bring all those clips into CapCut and build the final video there.

I’ll cut out parts of the generations I don’t like, shorten clips that feel too long, arrange everything in the right order, add my voiceover, music, sound effects, text and simple transitions.

Sometimes an AI generation might be 10 seconds long, but only 4 seconds look good.

Before, I would probably regenerate it.

Now, I’ll simply take those 4 seconds and work with them.

That alone can actually save AI credits.

I also love how much editing affects the final result.

The exact same AI clips can feel completely different depending on how quickly you cut between scenes,
where you add music, when a sound effect appears, or when text comes onto the screen.

And this is why I think learning some basic editing is really useful if you’re creating content for YouTube, Instagram or TikTok.

I am glad I took the initiative to learn and now I actually know a lot more about editing videos than I did before!

Even knowing how to cut clips properly, work with layers, add audio, use keyframes, adjust speed and understand basic transitions gives you a lot more control over what you create.

I’m still learning more myself, but the more I use CapCut, the more I realize how useful it is to understand the editing side of content creation, not just the AI generation side.

Do you use CapCut for editing? Is so, how good do you think you are with it?😃

For images, I mostly use Gemini Nano Banana.

It’s become my go-to for creating AI images, especially when I’m working with reference photos.

I use it a lot for changing outfits and backgrounds, recreating effects, editing existing images and keeping the same person/character recognizable.

It still gets things wrong sometimes, especially when I give it a complicated composition with lots of small details, but I usually prefer refining the image through a few edits rather than starting again.

For Videos, I use Kling inside Higgsfield AI.

Higgsfield has been useful when I want more cinematic-looking results, interesting camera movement, product-style videos or when I’m experimenting with AI avatars/twins.

For more complicated movement, I tend to use Kling 3.0.

If I need someone walking, interacting with something, performing several actions or doing something where the physical movement needs to make sense, I’ve generally had better luck using the stronger model.

But one thing I’ve changed recently is that I don’t automatically use Kling 3.0 anymore.

For shorter videos with relatively simple movement, I try Kling 3.0 Turbo first.

Turbo is much cheaper.

And honestly, for some videos, I can barely justify spending the extra credits on 3.0 because Turbo does exactly what I need.

Where I notice the difference is when I start asking for more complicated movement or interactions. That's when I'm more likely to switch from Turbo to Kling 3.0.

So my workflow has become pretty simple:

AI image → Nano Banana

Simple/short animation → Kling 3.0 Turbo first

More complicated movement/interactions → Kling 3.0

Cinematic camera effects / certain avatar workflows → Other models in Higgsfield (Still testing and experimenting)

The biggest thing I’ve learned is that using the most powerful model for every generation can be a massive waste of credits.

I used to think better model = better choice.

Now I think more in terms of:

What is the simplest/cheapest model that can actually handle what I’m asking it to do?

If Turbo can do it, I use Turbo.

If it can't, then I spend the extra credits on Kling 3.0.

Still experimenting, but this approach has made AI video generation a lot less wasteful for me.

What AI tools are you using for image and video generation?

For images, I mostly use Gemini Nano Banana.

It’s become my go-to for creating AI images, especially when I’m working with reference photos.

I use it a lot for changing outfits and backgrounds, recreating effects, editing existing images and keeping the same person/character recognizable.

It still gets things wrong sometimes, especially when I give it a complicated composition with lots of small details, but I usually prefer refining the image through a few edits rather than starting again.

For Videos, I use Kling inside Higgsfield AI.

Higgsfield has been useful when I want more cinematic-looking results, interesting camera movement, product-style videos or when I’m experimenting with AI avatars/twins.

For more complicated movement, I tend to use Kling 3.0.

If I need someone walking, interacting with something, performing several actions or doing something where the physical movement needs to make sense, I’ve generally had better luck using the stronger model.

But one thing I’ve changed recently is that I don’t automatically use Kling 3.0 anymore.

For shorter videos with relatively simple movement, I try Kling 3.0 Turbo first.

Turbo is much cheaper.

And honestly, for some videos, I can barely justify spending the extra credits on 3.0 because Turbo does exactly what I need.

Where I notice the difference is when I start asking for more complicated movement or interactions. That's when I'm more likely to switch from Turbo to Kling 3.0.

So my workflow has become pretty simple:

AI image → Nano Banana

Simple/short animation → Kling 3.0 Turbo first

More complicated movement/interactions → Kling 3.0

Cinematic camera effects / certain avatar workflows → Other models in Higgsfield (Still testing and experimenting)

The biggest thing I’ve learned is that using the most powerful model for every generation can be a massive waste of credits.

I used to think better model = better choice.

Now I think more in terms of:

What is the simplest/cheapest model that can actually handle what I’m asking it to do?

If Turbo can do it, I use Turbo.

If it can't, then I spend the extra credits on Kling 3.0.

Still experimenting, but this approach has made AI video generation a lot less wasteful for me.

What AI tools are you using for image and video generation?

For images, I mostly use Gemini Nano Banana.

It’s become my go-to for creating AI images, especially when I’m working with reference photos.

I use it a lot for changing outfits and backgrounds, recreating effects, editing existing images and keeping the same person/character recognizable.

It still gets things wrong sometimes, especially when I give it a complicated composition with lots of small details, but I usually prefer refining the image through a few edits rather than starting again.

For Videos, I use Kling inside Higgsfield AI.

Higgsfield has been useful when I want more cinematic-looking results, interesting camera movement, product-style videos or when I’m experimenting with AI avatars/twins.

For more complicated movement, I tend to use Kling 3.0.

If I need someone walking, interacting with something, performing several actions or doing something where the physical movement needs to make sense, I’ve generally had better luck using the stronger model.

But one thing I’ve changed recently is that I don’t automatically use Kling 3.0 anymore.

For shorter videos with relatively simple movement, I try Kling 3.0 Turbo first.

Turbo is much cheaper.

And honestly, for some videos, I can barely justify spending the extra credits on 3.0 because Turbo does exactly what I need.

Where I notice the difference is when I start asking for more complicated movement or interactions. That's when I'm more likely to switch from Turbo to Kling 3.0.

So my workflow has become pretty simple:

AI image → Nano Banana

Simple/short animation → Kling 3.0 Turbo first

More complicated movement/interactions → Kling 3.0

Cinematic camera effects / certain avatar workflows → Other models in Higgsfield (Still testing and experimenting)

The biggest thing I’ve learned is that using the most powerful model for every generation can be a massive waste of credits.

I used to think better model = better choice.

Now I think more in terms of:

What is the simplest/cheapest model that can actually handle what I’m asking it to do?

If Turbo can do it, I use Turbo.

If it can't, then I spend the extra credits on Kling 3.0.

Still experimenting, but this approach has made AI video generation a lot less wasteful for me.

What AI tools are you using for image and video generation?

I’ve been creating a LOT of AI videos lately, and one thing that frustrates me is when I have the exact scene in my head…but the AI gives me something completely different.

Then I generate again.

Fix one thing.

Generate again.

Something ELSE goes wrong.

And before I know it, I’ve wasted a bunch of credits on one tiny video 😒

I always blamed the AI model.

But I’m starting to realize that most of the times my prompt is the problem.

For example, I might write:

"Woman walking down a street in New York, cinematic, realistic, beautiful lighting."

It sounds like a decent prompt.

But what does cinematic actually tell the AI?

How is she walking?

Where is the camera?

Is the camera following her?

Is it moving backwards?

How fast is she walking?

What should stay consistent?

What should NOT change?

I know all of this in my head but the AI doesn’t.

So it has to guess.

And I think THAT is where a lot of bad generations come from.

Something else I’ve learned is that different types of videos need different details.

If there’s a lot of action, I need to be very clear about the movement, speed and camera.

If I’m creating something stylized, I need to describe the style properly so it doesn’t suddenly change halfway through.

And for product videos, lighting, reflections and camera movement make a HUGE difference.

I’m also using negative instructions a lot more now.

If I don’t want the face changing, objects disappearing, products morphing, random camera movements, extra limbs, etc…I actually say it.

Basically, I’m trying to stop writing prompts that just describe a pretty scene.

I’m trying to DIRECT the scene instead.

What happens.

How it happens.

How the camera moves.

What stays the same.

And what the AI absolutely shouldn’t do.

Still experimenting with this, but it’s already changing the way I write my video prompts.

And considering how expensive some AI video models are…anything that saves me from hitting Generate 10 times is a win 😂

What’s the ONE thing AI video generators keep messing up for you? Let me know below what AI tools do you use for images and videos?

I’ve been creating a LOT of AI videos lately, and one thing that frustrates me is when I have the exact scene in my head…but the AI gives me something completely different.

Then I generate again.

Fix one thing.

Generate again.

Something ELSE goes wrong.

And before I know it, I’ve wasted a bunch of credits on one tiny video 😒

I always blamed the AI model.

But I’m starting to realize that most of the times my prompt is the problem.

For example, I might write:

"Woman walking down a street in New York, cinematic, realistic, beautiful lighting."

It sounds like a decent prompt.

But what does cinematic actually tell the AI?

How is she walking?

Where is the camera?

Is the camera following her?

Is it moving backwards?

How fast is she walking?

What should stay consistent?

What should NOT change?

I know all of this in my head but the AI doesn’t.

So it has to guess.

And I think THAT is where a lot of bad generations come from.

Something else I’ve learned is that different types of videos need different details.

If there’s a lot of action, I need to be very clear about the movement, speed and camera.

If I’m creating something stylized, I need to describe the style properly so it doesn’t suddenly change halfway through.

And for product videos, lighting, reflections and camera movement make a HUGE difference.

I’m also using negative instructions a lot more now.

If I don’t want the face changing, objects disappearing, products morphing, random camera movements, extra limbs, etc…I actually say it.

Basically, I’m trying to stop writing prompts that just describe a pretty scene.

I’m trying to DIRECT the scene instead.

What happens.

How it happens.

How the camera moves.

What stays the same.

And what the AI absolutely shouldn’t do.

Still experimenting with this, but it’s already changing the way I write my video prompts.

And considering how expensive some AI video models are…anything that saves me from hitting Generate 10 times is a win 😂

What’s the ONE thing AI video generators keep messing up for you? Let me know below what AI tools do you use for images and videos?

Hi everyone!

I have been trying some viral prompts and this one stood out for me!

Character sitting on the inside bottom edge of the phone🙈

I tried this prompt below and loved the results!

You can uplaod a picture of yourself and copy paste this prompt in ChatGPT!

‘Use the uploaded photo as the strict identity reference for the person. Preserve the exact facial features, facial proportions, skin tone, hairstyle, hair color, expression, age, clothing style, accessories, and overall recognizability. Identity preservation: 100%.

Create an ultra-realistic editorial lifestyle photograph from a first-person perspective. The viewer is looking straight down at a modern premium black smartphone being held naturally with both hands above clean gray stone pavement outdoors during warm golden-hour sunlight.

The smartphone must retain the exact proportions of a modern iPhone with a tall, narrow 19.5:9 aspect ratio. It is viewed almost perfectly from above with only a very thin visible top edge. Do not make the phone thick, wide, square, or tablet-like.

The smartphone screen functions as a realistic miniature 3D world with true depth, perspective, reflections, contact shadows, and authentic glass reflections.

The person is sitting on the inside edge of the smartphone screen, as though the display is a real room. Their hips and torso remain inside the phone, resting naturally on the lower inner edge of the display. Both legs extend out through the screen opening and hang freely outside the phone, dangling naturally over the front edge. Their shoes extend beyond the bottom bezel and are fully visible in the real world, creating a highly convincing portal effect.

The transition where the legs pass through the display is perfectly seamless, making it appear that the smartphone is a real portal between two worlds. Realistic contact shadows appear where the legs cross the screen boundary, with subtle reflections on the glass and natural clothing folds around the portal opening.

The person smiles warmly while looking directly upward toward the camera. One hand is raised in a friendly wave with fingers naturally spread, while the other hand rests casually beside the body on the inner floor of the smartphone for support. The pose feels relaxed, welcoming, and playful.

The phone displays a realistic camera application with a visible shutter button, framing guides, zoom controls, focus indicators, camera modes, and authentic smartphone UI elements, making it appear that the miniature person is being viewed live through the camera.

The hands holding the phone feature realistic skin texture, fingernails, natural grip, soft shadows, and physically accurate lighting. The surrounding gray pavement remains softly blurred with shallow depth of field to keep attention on the smartphone and portal effect.

Warm golden-hour sunlight creates realistic highlights along the phone edges, subtle reflections on the display glass, and perfectly matched lighting across both the real environment and the miniature world inside the phone.

Ultra-realistic photography, premium lifestyle advertising, cinematic composition, Canon EOS R5, 35mm lens, shallow depth of field, HDR, 8K resolution, realistic skin texture with natural pores, hyper-detailed smartphone materials, physically accurate lighting, seamless photo composite, and an extremely convincing “sitting inside the phone with legs dangling outside” portal effect.’

Enjoy!!

Hi everyone! 👋 I’m Miz!

I’ve been experimenting a lot with AI image and video generation lately, especially trying different prompts and figuring out what actually produces good results.

I’ve built up quite a collection of prompts that I’ve personally tested, so I thought I’d start sharing some of the ones that work well for me here.

I’ll include the prompt + result whenever possible so you can see exactly what it creates. Feel free to copy it, tweak it, or experiment with it yourself.

Hopefully it saves someone else a little trial and error! 😊

This is one of the prompts that I loved the most! It involves you and a smartphone!

Here’s the prompt to make yourself POP OUT of your smartphone.

Step #1: Upload your picture and Copy and paste the prompt in ChatGPT/Gemini

‘Use the uploaded photo as the strict identity reference for the person. Preserve the exact facial features, facial proportions, skin tone, hairstyle, hair color, expression, age, clothing style, and overall recognizability. Identity preservation: 100%.

Create an ultra-realistic editorial lifestyle photograph from a first-person perspective. The viewer is looking straight down at a modern premium black smartphone being held naturally with both hands above a clean gray stone pavement outdoors during warm golden-hour sunlight.

The smartphone must retain the exact proportions of a modern iPhone with a tall, narrow 19.5:9 aspect ratio. It is viewed almost perfectly from above with only a very thin visible top edge. Do not make the phone thick, wide, square, or tablet-like.

The smartphone screen functions as a realistic miniature 3D world with true depth, perspective, reflections, shadows, and authentic glass reflections.

The person is dramatically popping out of the smartphone screen. Their feet remain inside the display while the upper body emerges naturally out of the phone. The torso extends above the screen, creating a convincing portal effect. Both arms are fully outside the phone, raised high while making playful peace signs with both hands.

The person's head and shoulders are completely outside the display, with hair flowing naturally upward from the motion. They are looking directly toward the camera with a huge open-mouth smile, conveying excitement, energy, and surprise as if greeting the viewer from inside the phone.

The transition where the body passes through the screen is perfectly seamless, with realistic contact shadows, perspective, clothing folds, and lighting, making the smartphone appear to be a real portal.

The phone displays a realistic camera application with a visible shutter button, framing guides, zoom controls, focus indicators, camera modes, and authentic smartphone UI elements, making it appear as though the person is being photographed live.

The hands holding the phone feature realistic skin texture, fingernails, natural grip, and soft shadows. The surrounding pavement remains softly blurred with shallow depth of field to emphasize the phone and portal effect.

Warm golden-hour sunlight creates realistic highlights along the phone edges, subtle reflections on the display glass, and perfectly matched lighting across both the real environment and the emerging person.

Ultra-realistic photography, premium lifestyle advertising, cinematic composition, Canon EOS R5, 35mm lens, shallow depth of field, HDR, 8K resolution, realistic skin texture with natural pores, hyper-detailed smartphone materials, physically accurate lighting, seamless photo composite, and an extremely convincing "popping out of the phone" portal effect.’

Have fun creating and sharing!