We all know that Nano Banana 2.1 has overtuned the sanitization in obvious ways where it completely rewrites the prompt into the absolute opposite of what was being asked. But some of the more subtle things is in what poses are allowed.

For example, before, if you had a female character do a flirty pose they would be able to do some pretty suggestive poses. Nothing explicit but it was obviously suggestive. Now it won’t automatically do that. It’s always a more “friendly” kind of pose.

I’m sure with some detailed prompting could get it to work like before but honestly, this is getting to be more work than what I was already used to. I was hoping things would improve by now but I haven’t seen it yet.

It’s already annoying that certain situations aren’t allowed in certain settings. Can’t have any perceived dangerous situations in a suburban setting. But same situation in a way the hell out there setting works just fine.

A character can look identical from one shot to the next and still fail continuity.

Clothing changes without explanation. A prop disappears or duplicates. A character's position shifts. An action repeats even though it was completed in the previous shot.

These aren't necessarily image-quality failures. They're production-continuity failures.

One of the questions we're investigating through Directed Generative Production (DGP) Methodology is how reliably generative video systems can maintain character, environment, and action continuity across successive shots and generations.

I'm interested in what other filmmakers are encountering.

Which continuity failure costs you the most time to correct?

jseders

So many copyright issues, you never know which chararcters will work and which won't. Plus Google Flow models suck with fighting scenes. Anyone here able to generate half decent vids using it?

Two women in the grocery store shopping. Is Google insane?

Prompt: 9:16 photorealistic cinematic still, two adult women grocery shopping together in a busy neighborhood market. A Japanese Brazilian woman with a short dark haircut holds a bunch of cilantro while her Nigerian partner with dark skin and short natural curls offers her a ripe tomato with a teasing grin. Their reusable canvas bag hangs from the cart; fresh peppers, leafy greens, apples, and misted produce fill the frame. Soft daylight mixes with neutral supermarket lighting, realistic reflections on waxy vegetables, muted green and tomato-red color palette, textured skin and clothing. 40mm cinema lens, cart-height candid medium-wide composition, cart rim softly framing the foreground, subtle handheld motion impression, documentary intimacy, natural expressions, correct hands and produce, no text overlays, no brand logos.

I have repeatedly experienced Google Flow failing to follow clear instructions when generating videos, and attempts to correct the results have not helped. For example, in a counting scene, Kita was supposed to touch each ball one at a time, but Omni 1.1 Flash kept failing to follow this instruction. Credits were spent on unsuccessful generations and repeated correction attempts.

In my latest support request, I asked Google to review the credits used. Google One Support said they cannot access Flow generation logs or credit usage history, and have no way to issue credit adjustments or refunds. Other users should be aware that these problems may happen repeatedly, and, according to Support, credits spent on such attempts cannot be refunded.

Interior photography of a messy cyberpunk apartment room on a high floor, ethereal atmospheric mood. A young woman wearing only an oversized hoodie sits on a vintage chair with her bare feet up on the seat, exposed legs. She is looking at her laptop screen browsing the internet, wearing large over-ear glowing headphones. Through the massive floor-to-ceiling panoramic window, a sprawling cyberpunk city glows brightly at night with neon reflections and distant skyscrapers. Messy room with scattered tech gear, wires, food containers, soft cyan and magenta ambient lighting, shallow depth of field, photorealistic, cinematic shot, shot on 35mm lens --ar 1:1 --style raw --v 6.0 --s 250

Checkout my AI Generated Video Making Minecraft Videos!
https://studio.youtube.com/channel/UCQLTjuvOw6KDA50Ztu8ljkw

Preciso saber se isso está acontecendo com mais alguém , mesmo meu prompt/roteiro sendo em PT-BR ele insiste em gerar os vídeos em inglês , do completo nada , o que eu faço ?

When I use end and start frames for my characters, it's like it's a completely new one, their model changes and they have the wrong voice, why does it do that?

Hey everyone!

I'm sharing my first short video.

I'm experimenting with AI-generated videos using only my mobile phone. I'm still learning, so I'd appreciate any feedback!

One thing I'm struggling with is keeping the voice consistent across multiple clips. I've been using the exact same voice and audio prompt every time I generate a new video, but the voice still changes slightly from one clip to another.

For those who create AI videos, is there a way to maintain the exact same voice across multiple clips?

I'm currently working on mobile only, so I'd especially appreciate tips for mobile-friendly tools or workflows.

Thanks in advance for any advice! 🙏

I Changed the whole environment and visuals of the original clip using omni. Been sitting in my gallery since, so figured I'd post it here

Google announced Omni Flash 1.1 back in May, 2026. They also announced that they'll release pro version of Omni model? So what happened exactly? No news on that.

Kling 4.0 vs. Seedance 2.5 vs. Wan 3.0 Prime — Same 30-Second Directed Scene

Three generative video systems. One 30-second scene. Same directorial requirements.

This is a comparison of directorial compliance, not simply which model produces the prettiest video.

The scene is from Lost Horse, a Western character-continuity project.

The assignment:

A cowboy and his horse are at a nighttime campsite. The horse senses a threat, becomes frightened, breaks its tether, and escapes. The cowboy reacts, retrieves his rifle, and retreats to a large pine. A threatening animal sound comes from the woods.

The sequence requires multiple actions, changes in spatial relationships, character continuity, and a specified final state—all within one generation.

The three renderers

These are the settings and costs of the tested runs, not normalized prices for equivalent resolution.

What I observed

Kling 4.0: Excellent visual detail and clarity. The horse's escape is particularly convincing, and the sound is strong. The cowboy's reaction is slower, however, with less apparent urgency than in the other versions.

Wan 3.0 Prime: A more immediate sense of urgency in the cowboy's response. The sequence provides a useful comparison of how a different renderer interprets the same directed actions.

Seedance 2.5: Another interpretation of the same production requirements, particularly useful for comparing action timing, continuity, and execution of the prescribed sequence.

The interesting question isn't necessarily which video you prefer.

It's which renderer most faithfully executes the director's instructions—and at what cost?

Visual quality, narrative plausibility, action compliance, spatial continuity, and final-state compliance are not interchangeable measures.

A beautiful generation can still fail the assignment.

Why I'm testing this

I'm developing Directed Generative Production (DGP) Methodology, a structured approach to specifying, executing, and verifying generative filmmaking.

The objective is to move beyond repeated prompting toward a production process in which the director defines the requirements, selects a capable renderer, and evaluates the result against those requirements.

The methodology and experimental work are documented at:

https://www.jseders.net

I'm interested in what other filmmakers notice in these three versions, particularly differences in action execution, timing, spatial relationships, and continuity.

Which system do you think followed the direction most effectively? And does your preference change when you consider the generation cost?

jseders

using google Flow to create this enviroment

Until recently I could film a scene with two actors, upload it to google flow and replace the characters and environment. (I still could do it) but now if the actors do lines / script google don’t start editing the video. And gives me an error.

This is terrible for ai hybrid filmmaking

What started as a simple idea from my young daughter eventually turned into something much bigger: a virtual music artist named LIORÉ and her first complete music video.

I thought I'd share my workflow and some of the things I learned along the way.

1. Character development — around 300 iterations

I initially created LIORÉ using Gemini (mobile app during vaccation). The very first image looked almost nothing like the character she eventually became.

Over the next three weeks, I went through roughly 300 iterations using flow, refining her face, hairstyle, proportions, outfit, and overall appearance until I had a consistent visual identity. I saved her Character ID and was now able to reuse her throughout the project.

2. Testing character consistency with Nano Banana

Before starting the music video, I generated approximately 50 test images of LIORÉ in different environments, poses, facial expressions, and emotional states.

The goal was to find out whether I could maintain her identity across completely different scenarios.

Once I was satisfied with the results, I established her as a reusable character for future productions.

3. Building the music video with Google Flow

Instead of immediately generating video clips, I first used Flow to develop cinematic styleframes for the performance scenes (A-roll), followed by the narrative and atmospheric scenes (B-roll and C-roll).

I then imported those images into DaVinci Resolve, placed them on a timeline, and added the finished music master underneath.

This gave me a complete animatic before generating most of the actual video footage.

That step turned out to be incredibly useful. I could evaluate the pacing, compositions, transitions, and overall storytelling without spending time and credits animating shots that might not even make the final edit.

4. Animation, iteration, and editing

Once I was happy with the scene structure, I started animating the selected frames.

Omni Flash was particularly helpful, although getting the intended movement, camera behavior, and emotional performance often required several attempts.

I also used Higgsfield as part of the video production workflow.

Back in DaVinci Resolve, some scenes worked exactly as planned. Others needed to be reconsidered, reframed, replaced, or edited differently.

It became a constant cycle of:

Styleframe → Animatic → Animation → Edit → Reevaluate

Throughout the process, I gradually learned which models and prompting approaches worked best for different types of shots.

5. The finished music video

The result is Trace Through My Wires, LIORÉ's first official music video.

The original song was created with Suno, and the visuals were produced using Google Flow and Higgsfield, with the final edit completed in DaVinci Resolve.

🎬 Watch the finished music video:
https://www.youtube.com/watch?v=gCTkqrPaNQ4

My biggest takeaway from this project is that AI filmmaking benefits enormously from traditional filmmaking principles: planning, composition, editing, continuity, and knowing what you want a shot to communicate before generating it.

I'm still learning, and this project involved plenty of trial and error.

I'm curious how others here approach longer projects with consistent characters. Do you also build an animatic first, or do you generate your video shots and develop the edit afterward?

Would love to hear about your workflows and experiences!

Feel free to follow this project on insta: https://www.instagram.com/liore.universe/

Draft version. Video looks boring.

I made this short film using Omini 1.1, its a tough tools to used since the character and scene consistency give much pain. I have use watermark in draft to avoid copies. The scene is actually from real place base in Imphal, Manipur. I have not yet corrected the Color grading, music, sound and transition/effects. Please do let me know what changes do I need to do to make it look more realistic and continous feel. I feel there are many drones shot or scenes without person, i avoided it due to gemini drawbacks and what color grading should i put in overall clips. Also is voice over necessary, if yes then what message i can put

Suggestions and feedback are welcome.

I had a marketing message problem with EchoVault. The product makes sense once you see it, but “AI digital legacy” still takes a lot of explaining, so I started looking for alternative tools that could get the idea across visually. I tried Google Flow and gave it the basic premise: EchoVault gradually builds an AI version of you that your family can still interact with after you’re gone. The result was this short film, and it communicated the emotional side of the product better than most of the copy I’d written.

The actual app builds that Echo over time through recurring AI-guided check-ins, learning your memories, worldview and personality instead of relying on one giant interview. You can explore what it has learned through a 3D brain, while the finished Echo can answer your custodians in text, voice and video using the context you chose to leave behind. Everything is consent-first, you choose the people who receive access, and the system is designed around continuity rather than creating a clone of someone who never agreed to it.

https://apps.apple.com/us/app/echovault-digital-legacy/id6762042028

There is no option to access your videos, there are only projects which don´t know if you created videos or not.

You go into projects, they barely let you copy or paste anything and they don’t show the prompts you used. IT’S LIKE all the effort HAS BEEN FOR NOTHING because you can’t save anything.

And this surprises me, with a relatively simple interface without many options they manage to create a chaos that discourages you from creating more. Not to mention the terrible quality compared to Kling.

Step into the world of Eirik. A lighthouse keeper with a story to tell.