Spent the last few weeks deep in this - tried a handful of tools and models, wrote and refined shot lists, built out a short with a real structure, dialogue, the works. Wanted to share what I landed on, because I think it’s a trap a lot of us fall into without noticing.

The creative freedom side is real and it’s intoxicating. You can direct a “film” with a level of control that would’ve required a crew, actors, a location budget, and months of scheduling two years ago. You have an idea at 9pm and by midnight you have a shot that looks like it belongs in something real. That part isn’t hype - it’s genuinely new, and it’s fun in a way that’s hard to overstate.

But here’s what I didn’t see coming: I caught myself assuming that because something was satisfying to make, it would also be satisfying for someone else to watch. Those are not the same thing, and the gap between them is where the trap lives.

A few things I had to be honest with myself about:

The economics are built for compulsion, not creation. Credit-based pricing means every decision to “just try one more generation” is small enough to not feel like a decision. $2 here, $4 there. It adds up fast, and the structure rewards chasing a “perfect” result rather than working within constraints which, ironically, is usually where better creative work comes from.

The field is saturated in a way that’s easy to underestimate. Everyone with a subscription and some patience can make something that looks polished now. Technical quality stopped being a differentiator months ago. That means the bar for actually standing out isn’t “well-executed” anymore - it’s genuine novelty, and that’s a much higher and rarer bar than most of us (myself included) want to admit while we’re mid-project.

Finishing something doesn’t obligate you to release it. I got far enough into a piece to realize the idea itself (not the execution) wasn’t one I actually wanted out in the world. That’s a legitimate outcome. Pulling the plug isn’t wasted effort if the process taught you something about your own judgment.

I don’t think this tech is a dead end, and I’m not swearing off it. But I went in thinking the constraint was my skill or my access to good tools, and the actual constraint turned out to be figuring out why I was making something before I made it. Worth asking that up front instead of after you’ve burned a few hundred dollars in credits finding out the hard way.

Curious if others here have hit the same wall.

Not a trailer — a finished short film with a story: a foreigner's first Mumbai monsoon, structured like old Hindi cinema with hand-painted chapter cards (one arrives painted on the back of a truck).

What worked for me on 2.5: (1) the mixed-reference stack is the killer feature — a source video clip as the world/identity anchor plus stills for the gag compositions, in one roll; (2) for continuing an existing shot, feeding the clip itself as reference kept faces and grade almost perfectly — that's how I extended my surrender-dance scene into a whole new gag; (3) character consistency: ONE clean face reference used alone beat every multi-ref combo I tried; (4) explicit physics rules in the prompt ("every umbrella stays open and gripped in its owner's hand, never folds, never changes hands") cut slop dramatically; (5) comedy that survives generation = single-subject actions — a kid faking a high-five lands in one take, synchronized crowd choreography rarely survives.

I'm looking for serious AI animators who are trying to make anime specifically but literally all I'm finding is p**n. Can anyone point me in the correct direction?

My first piece of work. An Anthology Series starring The Oracle.

VIEWERS' DISCRETION IS ADVISED

All feedback is appreciated.

I’m looking for something that can make animated or cartoon-style videos without having to create the visuals in one tool and handle all the audio separately.

Veo 3 is one of the options I’ve been looking at, but I’m curious if there are other AI video generators that can produce decent audio as part of the same workflow.

What are you guys using for this?

I've been doing more ai filmmaking lately, and and honestly the bad shots aren't even the problem anymore.
if a face melts or the camera suddenly goes off the rails, cool, easy delete.
the ones that actually annoy me are the shots that look great by themselves. I can always find some dumb reason to keep those.
was cutting a short together in Framia and caught myself holding onto half these shots for literally no reason other than "but it looks dope though" lol.

ended up cutting a few anyway and yeah, the whole thing flowed way better.
how do you guys decide when a shot looks good but still needs to go?

Every month, someone in this sub asks which tool or model will get them the best output for their film.

I work as an AI director at a Korean media company and I test a ton of AI tools and workflows to figure out what actually holds up in real video production.

So I thought I’d share a list of all the best ones I’ve found. Basically, this is everything I would hand a newbie on day one.

Standard disclaimer: this stuff moves fast. Pricing, credits, limits, and features change constantly. Check before you pay for anything, and if you are reading this six months from now, assume half of it has shifted.

Pre-production

Most of my AI films start by locking the look, the character, the wardrobe and the shot language so a video model never has to guess. These are the tools I use in pre-production to lock my look before I spend a single video credit.

• Midjourney: Best for stylistic look development, moodboards, poster frames, character looks, environments, and art direction.
• Recraft: Good when characters or environments need to feel more photographic. Skin texture is usually where image models give themselves away and this one keeps it real.
• Nano Banana 2 / Pro: Fast, accurate, and strong for final frames. Good for character sheets because it can hold a reference across edits instead of reinventing the person.
• Magnific Upscaler: Great for polishing up key frames and upscaling hero images up to 4K. Most of the time you won't need it since Nano Banana already outputs at 4K but when a frame just needs that extra upscaling, that’s where this comes in handy.

Pro tip: solve the film in stills first. If the storyboard does not work as images, the video model is not going to become your cinematographer out of pity.

Scene Generation

Once the stills are locked, this is where the shots come from.
Each of these models has its pros and cons, but these are the ones I reach for the most.

• Seedance 2.0: It is the bast all round model out there. Strng for action, motion-heavy shots, stunts, crashes, longer takes, and generations with multiple reference inputs. FYI, I am still testing Seedance 2.5.
• Kling 3.0: This is the one I trust with performances. Dialogue, effects and ambience generate in the same pass as the picture, so a line in quotation marks comes back spoken with the face matching it. Motion Control takes that further: hand it a reference video of someone acting and your character performs it. Costs little enough per second that I do my roughing out here.
• Veo 3.1: Use this when a shot has to look choreographed and not generated. It takes precise camera instructions and holds references quite accurately. The only drawback is that it is capped at 8 seconds.
• Wan 3.0:  If you're making horror or anything with real violence in it, this is the one that won't refuse you halfway through a sequence due to TOS.
• Runway: It is the safe default. Good references, strong shot editing, and useful when you want to change a shot instead of rerolling it from scratch.

Audio & SFX

Bad audio makes AI video feel cheap instantly. People will forgive a weird background. They will not forgive a dead voiceover. These tools make sure that doesn’t happen.

• ElevenLabs. All my voice work runs through this. It clones off thirty seconds of clean audio and still sets the bar for narration that doesn't sound narrated.
• Suno. Go here when a scene needs an actual song rather than a bed under it. It leads the field on vocals and structure, and it hands you something finished instead of a loop you have to build around.
• Udio. This is the producer's version of the same thing: section-level regeneration and stems, so a weak chorus gets fixed without touching the rest. Check its export terms first though, because downloads have been restricted while the licensing gets sorted.
• MiniMax Audio. I reach for this when one piece has to go out in a lot of languages. Wider coverage than ElevenLabs at lower cost, notably better on Asian languages, and it copes with imperfect source audio when you're cloning off a bad recording.
• Artlist / Epidemic Sound. Thus are licensed rather than generated, and still the right answer when something has to clear for distribution and you need paperwork on the music rather than an assurance about training data.

Agentic Workflows

These have access to most of the models listed above but I would only recommend these if you are doing serious work, longer projects, recurring formats, or production at scale. 

Using an agentic workflow for one-offs is like booking a full crew to film your lunch.

• invideo Agent: Useful for longer projects where continuity matters. You brief it with an idea, script, or shot breakdown, then build the film step by step. It keeps everything you feed it and everything you create saved in memory, and routes work across multiple image, video, and audio models.
• Luma Agent: Easiest to pick up. The frames-based canvas is a nice way to work, and Ray 3.2 image-to-video/HDR output is very strong. Good for visual quality, cinematic motion, and shot-level work.

I’m working on a multi-scene visual project where the subject, location and time period can change completely from one sequence to the next.

Individual AI-generated shots can look convincing on their own, but the harder problem is making them feel as though they belong to the same film.

I’ve been trying to control things like:

• color palette and grade
• lighting philosophy
• lens / camera language
• composition
• texture and production design
• overall visual density

But when the subject changes radically, there’s still a point where the sequence starts feeling like a collection of separate generated images rather than one cinematic world.

For those of you working on multi-scene AI films:

What do you treat as the strongest continuity anchor when characters, locations and even time periods keep changing?

Do you primarily lock the camera language? Lighting? Grade? Production design? Or is there another layer that has made the biggest difference for you?

I’m working on a cloud-only AI compositing workflow and trying to solve environmental continuity across a full edited scene.

The footage is shot normally with multiple setups: wides, mediums, close-ups, reverses, profiles, different camera positions, and different lenses.

The goal is to keep the original actors, performances, framing, and camera movement, but replace the practical location with a new AI-generated environment and make every shot feel like it was photographed in the same physical space.

My current setup:

• Nano Banana 2 / Pro in Google Flow for still compositing, environment replacement, and relighting
• Seedance 2.0 through Comfy Cloud for video
• MacBook Air, so the workflow needs to stay essentially cloud-based

The issue is that getting one shot to work is relatively easy. The difficult part is making an entire sequence maintain believable spatial continuity.

For example:

• 35mm wide looking down a hallway
• 85mm close-up from the opposite direction
• Side-profile two-shot
• Reverse angle
• Another wide from a different position

I need the generated environment to respond correctly to each camera position rather than just creating five vaguely similar hallways.

I’m trying to maintain:

• Architecture and room layout
• Doors, windows, furniture, columns, etc.
• Screen direction and spatial relationships
• Lighting direction
• Perspective
• Approximate lens behavior
• Depth and scale
• Subject relighting/contact with the environment
• Overall color and atmosphere

It doesn’t need to be geometrically perfect. It just needs enough faux spatial continuity that the audience believes all the shots were captured on the same set.

For anyone doing this with tools like Nano Banana, Seedance, Kling, Veo, etc., what workflow has been the most reliable?

Do you:

• Generate a master environment first?
• Create several canonical reference angles of the location?
• Build a rough floor plan or 3D blockout first?
• Generate clean environment plates before adding actors?
• Use previous generated shots as references for subsequent angles?
• Handle environment replacement and actor relighting as separate passes?

I’m especially interested in workflows that work without a powerful local GPU.

Basically: what is the best way to fake one coherent virtual location across multiple independently generated live-action shots?

Friend of mine and I submitted our epic documentary idea to xprize It takes place in the future where we can communicate with the dolphins and other animals. Then we discover something wonderful, that all the animals have a segment of a mysterious word and that word put together just might mean "creator."

Hi rryone, when Sora first launched in Europe i was eager to jump aboard the train to fulfill my dream of creating my own first full length film. A year and a half" later i am still struggling with the opening credits. I have worked day and night, pushed in ridiculous money, tried out practically every single model and service mid-tier and tried to run locally but have perhaps prioritized wrong since i seem to lack the sufficient equipment and it all looks like shit or every model are so constrained by censorship its pathetic. Which services should i prioritize, which should i cancel and what should i invest in? Any suggestions would be warmly welcome at this point. Kind regards /M

Hi, so I have been creating AI films for a while now. I have used Chatgpt, nano banana, comfyui with flux 2.

However, sometimes regardless how i prompt chatgpt to redo/remaster original concept (usually it would be a sketch, or reference photos, or midjourneys), Chatgpt frame would stay looking comical, burnt, with a AI floral-like artifact.

it would be too slow and expensive to frequently make images from comfyui with flux 2, and nano banana isnt following the prompt well enough for me. I use this to create original film content so a lot of my stuff start from sketch and storyboards and chatgpt so far is the only reliable and consistent tool. i have tried a bunch of remaster, redo, detect artifact, detect compression artifact prompts but no luck, upscaling with topaz also does not help

how do you exactly remaster it into a photoreal/filmic look and ahcieve a visually realistic materials like in gossip goblin etc? at the very least free from artifacts

Ellen Bracy survived combat overseas only to find herself facing a supernatural threat at home.

This isn't necessarily a finished version, it is currently my final draft and i'm mainly looking for feedback on it before I make it public.

Over the last few weeks I've been taking time off work to move my channel in a new direction, to horror and mystery with smart protagonists.

Currently set to Unlisted because I want feedback first to see what's what And if anything needs changing or can be cut I really want to know as it’s important to me to get this right. If your going to downvote or upvote at least tell me why.

She's smart, she's capable and she's ready to fight back.

A gritty realistic take on facing the supernatural, with a protagonist that makes smart, tactical decisions when the veil drops.

Discarded on the home front. Medically discharged, wrestling with trauma, and facing eviction, she is forced into the cold realities of life on the streets. To stay afloat, she takes on desperate, under-the-table private detective work—until a routine gig spirals into a brutal, blood-soaked encounter with something that defies the laws of nature.

Ellen’s first instinct is clinical: combat psychosis, brain tumor….anything to explain what she saw.

But as she methodically retraces the evidence, cross-referencing obscure forensic oddities with grim folklore, logic points to a terrifying truth. She isn’t losing her mind. The monsters are real, they are predatory, and nobody else is coming to stop them.

Instead of running, Ellen falls back on the oath she swore to defend her country.

With her last few dollars and a soldier’s tactical mindset, she treats the supernatural not as a curse, but as an enemy combatant to be analysed, prepared for, and eliminated. Blending urban scrap, bespoke ballistic modifications, and occult research, she builds an arsenal.

In the gritty tradition of classic creature-feature hunts, Ellen isn't waiting to become prey. She is adapting, loading out, and taking the fight into the dark.

The movie is a homage to TV shows like Supernatural, buffy the vampire slayer and video games such as Phasmophobia.

And also to smart Protagonists.

Created with Ai using Seedance and Omni Flash for scenes that dont requite much input.

Music created using Google Gemini and google labs music Lyria 3.5 and is free to use.