I'm experimenting with Gemini Pro for AI-generated UGC videos and have been getting mixed results.

This is the prompt I'm using:

   Please use the attached photo as talking photo.

    A casual, friendly young Taiwanese woman in her mid-20s, looking directly at the camera, talking. She has a natural, light makeup look, wearing smart-casual office attire like a pastel blouse. Bright, well-lit modern office or cozy cafe background. Shot on an iPhone 15 front camera, vertical video aspect ratio, cinematic lighting, photorealistic, UGC style, TikTok aesthetic, highly detailed face, 8k. --ar 9:16 --v 6.0

    Scene 1
        Script: Zoning out in meetings? Can’t keep up with your boss?
        Video: UGC-style; Taiwanese girl looking relatable but expressive.
    Scene 2
        Script: Check out this lifesaver!
        Video: Girl looks pleasantly surprised, holding up her phone/product.
    Scene 3
        Script: Just tap record, and let AI handle the heavy lifting.
        Video: Girl points to the top of the screen.
    Scene 4
        Script: Meeting over? Get a full summary in just one minute!
        Video: Faster pace, highlighting "one minute" and "summary."
    Scene 5
        Script: Replay audio and export to PDF in one click. So easy!
        Video: Girl looks relieved and relaxed.
    Scene 6
        Script: Download now for a 3-day free trial! Click the link below!
        Video: Enthusiastic, urgent tone; gestures strongly toward the bottom of the screen.

Overall, I'm actually quite impressed with the results:

• The generated scenes closely match the prompt.
• The voice sounds surprisingly natural (although not perfect).

However, one major issue is that the spoken dialogue doesn't faithfully follow the script. The model frequently skips words, paraphrases sentences, or omits parts of the script entirely, even when I explicitly provide the exact wording.

I'm wondering:

1. Are there prompt engineering techniques that improve script adherence?
2. Is this simply a current limitation of Gemini Pro's video generation model?
3. Has anyone had better success with other AI video platforms that can generate talking-head UGC videos while following the script almost word-for-word?

I'm happy to pay for a service if it produces significantly better results.

I'd especially appreciate recommendations from people who have actually compared multiple platforms for this use case (e.g. realistic talking avatars, UGC-style ads, TikTok creatives, etc.).

I'm experimenting with Gemini Pro for AI-generated UGC videos and have been getting mixed results.

This is the prompt I'm using:

   Please use the attached photo as talking photo.

    A casual, friendly young Taiwanese woman in her mid-20s, looking directly at the camera, talking. She has a natural, light makeup look, wearing smart-casual office attire like a pastel blouse. Bright, well-lit modern office or cozy cafe background. Shot on an iPhone 15 front camera, vertical video aspect ratio, cinematic lighting, photorealistic, UGC style, TikTok aesthetic, highly detailed face, 8k. --ar 9:16 --v 6.0

    Scene 1
        Script: Zoning out in meetings? Can’t keep up with your boss?
        Video: UGC-style; Taiwanese girl looking relatable but expressive.
    Scene 2
        Script: Check out this lifesaver!
        Video: Girl looks pleasantly surprised, holding up her phone/product.
    Scene 3
        Script: Just tap record, and let AI handle the heavy lifting.
        Video: Girl points to the top of the screen.
    Scene 4
        Script: Meeting over? Get a full summary in just one minute!
        Video: Faster pace, highlighting "one minute" and "summary."
    Scene 5
        Script: Replay audio and export to PDF in one click. So easy!
        Video: Girl looks relieved and relaxed.
    Scene 6
        Script: Download now for a 3-day free trial! Click the link below!
        Video: Enthusiastic, urgent tone; gestures strongly toward the bottom of the screen.

Overall, I'm actually quite impressed with the results:

• The generated scenes closely match the prompt.
• The voice sounds surprisingly natural (although not perfect).

However, one major issue is that the spoken dialogue doesn't faithfully follow the script. The model frequently skips words, paraphrases sentences, or omits parts of the script entirely, even when I explicitly provide the exact wording.

I'm wondering:

1. Are there prompt engineering techniques that improve script adherence?
2. Is this simply a current limitation of Gemini Pro's video generation model?
3. Has anyone had better success with other AI video platforms that can generate talking-head UGC videos while following the script almost word-for-word?

I'm happy to pay for a service if it produces significantly better results.

I'd especially appreciate recommendations from people who have actually compared multiple platforms for this use case (e.g. realistic talking avatars, UGC-style ads, TikTok creatives, etc.).

I'm experimenting with Gemini Pro for AI-generated UGC videos and have been getting mixed results.

This is the prompt I'm using:

   Please use the attached photo as talking photo.

    A casual, friendly young Taiwanese woman in her mid-20s, looking directly at the camera, talking. She has a natural, light makeup look, wearing smart-casual office attire like a pastel blouse. Bright, well-lit modern office or cozy cafe background. Shot on an iPhone 15 front camera, vertical video aspect ratio, cinematic lighting, photorealistic, UGC style, TikTok aesthetic, highly detailed face, 8k. --ar 9:16 --v 6.0

    Scene 1
        Script: Zoning out in meetings? Can’t keep up with your boss?
        Video: UGC-style; Taiwanese girl looking relatable but expressive.
    Scene 2
        Script: Check out this lifesaver!
        Video: Girl looks pleasantly surprised, holding up her phone/product.
    Scene 3
        Script: Just tap record, and let AI handle the heavy lifting.
        Video: Girl points to the top of the screen.
    Scene 4
        Script: Meeting over? Get a full summary in just one minute!
        Video: Faster pace, highlighting "one minute" and "summary."
    Scene 5
        Script: Replay audio and export to PDF in one click. So easy!
        Video: Girl looks relieved and relaxed.
    Scene 6
        Script: Download now for a 3-day free trial! Click the link below!
        Video: Enthusiastic, urgent tone; gestures strongly toward the bottom of the screen.

Overall, I'm actually quite impressed with the results:

• The generated scenes closely match the prompt.
• The voice sounds surprisingly natural (although not perfect).

However, one major issue is that the spoken dialogue doesn't faithfully follow the script. The model frequently skips words, paraphrases sentences, or omits parts of the script entirely, even when I explicitly provide the exact wording.

I'm wondering:

1. Are there prompt engineering techniques that improve script adherence?
2. Is this simply a current limitation of Gemini Pro's video generation model?
3. Has anyone had better success with other AI video platforms that can generate talking-head UGC videos while following the script almost word-for-word?

I'm happy to pay for a service if it produces significantly better results.

I'd especially appreciate recommendations from people who have actually compared multiple platforms for this use case (e.g. realistic talking avatars, UGC-style ads, TikTok creatives, etc.).

Hello,

I understand that App Store Connect allows us to perform A/B testing on app icons. Since user preferences often vary by region, is it possible to apply different winning icons to different localized storefronts once an A/B test concludes?

Thank you.

Hello,

I understand that App Store Connect allows us to perform A/B testing on app icons. Since user preferences often vary by region, is it possible to apply different winning icons to different localized storefronts once an A/B test concludes?

Thank you.

I recently came across a 1-minute video showcasing a really smooth app flow and animation that I’d love to implement in my SwiftUI app. I was hoping to use AI to generate the code, using a prompt similar to this:

>"Watch this video [video_file.mp4], analyze the app flow and animations, and create an exact, fully functional SwiftUI replica that can be compiled and run in Xcode."

However, I’m running into roadblocks depending on the AI model I use (testing via Google Antigravity):

1. Gemini 3.1 Pro: It seems to extract screenshots from the video at a low frame rate. Because it misses the in-between frames, the resulting SwiftUI code fails to capture the actual flow and nuance of the animation.
2. Claude Opus: It attempts to launch Chrome and "watch" the video but gets stuck in a loop. It keeps pausing, playing, and scrubbing the timeline, and eventually times out after 20 minutes without producing any code.

Has anyone found a clean, reliable workflow or prompt structure for getting AI to accurately analyze a UI demo video and output the correct SwiftUI animation code?

Previously, I built a UIKit-based app using UIHostingController to integrate SwiftUI. I chose a UIKit foundation for a few reasons:

1. UICollectionView offers unmatched performance compared to LazyVStack. The performance difference is obvious when a list contains 2,000 items or more.
2. For screens that require complex UI effects, I use SwiftUI for easier implementation.

The app has been in production for over a year, and I am quite happy with the outcome - high customer satisfaction, good performance, good sales.

Now, I am starting a new app where I foresee using more SwiftUI than UIKit. I will still need UICollectionView in certain areas (for instance, a horizontally paginated weekly calendar picker) due to the poor performance of LazyHStack. However, for screens that won't exceed 50 items, I can safely use LazyVStack.

My question is: Should I stick to a UIKit-based architecture with UIHostingController, or shift to a SwiftUI-based architecture and use UIViewRepresentable/UIViewControllerRepresentable?

Additionally, I am very familiar with UIKit navigation (performSegue, unwind, present). I am not sure if SwiftUI provides an exact equivalent that is just as reliable. From my past experience, navigation in SwiftUI was a massive pain. I'm not sure if anything has actually improved recently.

Which approach will best help me deliver a successful production app?

Hello everyone,

I'm currently testing iCloud/CloudKit performance for my app using NSPersistentCloudKitContainer. I am using a single Apple ID throughout the entire testing process.

I've noticed a weird observation where I seem to have three distinct datasets. I was expecting there to be only two (Development and Production), so the third one is throwing me off.

Here is what I am seeing:

1. iCloud Console (Development): Shows Data Set A. (Note: I am looking at the private database / com.apple.coredata.cloudkit.zone. I had to add the recordName index to browse this data).
2. Real iPhone (App Store / TestFlight fresh install): Shows Data Set B.
3. Real iPhone & Simulator (Xcode fresh install): Shows Data Set C.

(Note: I can't browse the iCloud console for Production right now because it lacks the recordName index, and I don't want to modify Production at this moment).

My questions:

• Why is there a 3rd set of data (Set C) on Xcode builds? I expected it to match the Development console (Set A).
• Is it possible the "iCloud console (Development)" is delayed and showing an old dataset?
• How should I best debug this discrepancy?

Any insights would be greatly appreciated!

UPDATE:

I believe the CloudKit console has an issue when displaying a large number of rows (around 1,677).

If I don't perform any filtering and make sure I am on page one (by scrolling to the bottom and ensuring there is only a 'next' button and no 'previous' button), sorting by 'Created' only shows records up to the year 2024.

However, if I apply a text filter to search for the latest record, my 2026 records appear correctly.

I have attached a screenshot for your reference.

https://preview.redd.it/rzva06fg4x1h1.png?width=1471&format=png&auto=webp&s=89d2ad2b8c18d9584dc02833357c2ef8f99080c2

https://preview.redd.it/zd092rdh4x1h1.png?width=1471&format=png&auto=webp&s=4aa669ec7bedd6ee82d7edbca2d5d6867465d5a9

That's mean, iCloud Console (Development) is showing a truncated version of Data Set C.

Hi everyone,

I usually avoid AirBnB when traveling because I find the quality inconsistent and I hate not having a front desk if something goes wrong.

I've noticed that Bangkok has a lot of "Serviced Apartments" (like a hotel/apartment hybrid). They look way more spacious and are often cheaper than regular hotels, yet they still seem to offer a front desk and daily housekeeping.

I'm looking at places like:

• Grande Centre Point Hotel Ratchadamri
• Sathorn Vista, Bangkok - Marriott Executive Apartments

I've never stayed in this type of accommodation before. For those who have:

1. What is the actual experience difference compared to a regular 4 or 5-star hotel?
2. Is there a "catch" I should know about since the price for the space seems lower?
3. Service quality: Is the "front desk help" and housekeeping actually comparable to a hotel, or is it more "lite"?

I'm planning a one-week stay. Would love to hear your experiences!

Hi everyone,

Currently, we are using ReviewManager.launchReviewFlow to ask for a user review whenever a user completes a meaningful operation in our app.

Historically, this flow has worked perfectly. Based on our analytics events, if we call launchReviewFlow 300 times a day, we generally collect around 30 ~ 60 reviews per day.

However, over the past week, we've observed a significant drop in the number of recorded reviews on the Google Play Console.

We double-checked our analytics, and the trigger count per day is still completely stable with no fluctuations. The prompts are definitely still firing.

It is currently unclear what is driving this:

• API Behavior: Has the internal behavior, dialog surfacing, or quota limit of ReviewManager.launchReviewFlow changed?
• Stricter Spam Filters: Has Google recently updated the Play Store policy or strengthened their review filters to aggressively hide/remove reviews it considers invalid?

I’ve attached a screenshot below to illustrate the drop we are seeing.

https://preview.redd.it/7h02qot9h8yg1.png?width=1864&format=png&auto=webp&s=d95b63a821eadf4d30273f5bf444e9d31cd69bda

I was wondering, has anyone else had the same observation on your side recently? Any insights would be hugely appreciated!

Hi everyone,

Currently, we are using ReviewManager.launchReviewFlow to ask for a user review whenever a user completes a meaningful operation in our app.

Historically, this flow has worked perfectly. Based on our analytics events, if we call launchReviewFlow 300 times a day, we generally collect around 30 ~ 60 reviews per day.

However, over the past week, we've observed a significant drop in the number of recorded reviews on the Google Play Console.

We double-checked our analytics, and the trigger count per day is still completely stable with no fluctuations. The prompts are definitely still firing.

It is currently unclear what is driving this:

• API Behavior: Has the internal behavior, dialog surfacing, or quota limit of ReviewManager.launchReviewFlow changed?
• Stricter Spam Filters: Has Google recently updated the Play Store policy or strengthened their review filters to aggressively hide/remove reviews it considers invalid?

I’ve attached a screenshot below to illustrate the drop we are seeing.

https://preview.redd.it/omjdpdqf34yg1.png?width=1864&format=png&auto=webp&s=ce24b4a4d7c92a1ad698b4374390366578c9e388

I was wondering, has anyone else had the same observation on your side recently? Any insights would be hugely appreciated!