u/PoleTV

been running an AI character on social and Fanvue for a while. want to give the version nobody writes about. not the hype, not the "its a scam" take, just the real mechanics.

the money isnt in subscriptions. subscriptions are maybe 10 to 15% of revenue. the actual income comes from content unlocks where fans pay for specific stuff, and a small number of people who spend way more than everyone else combined. one person can outspend 50 regular subscribers easily.

costs are near zero once the system is built. the character generates content at almost no cost per image. no studio, no model fees, no burnout. main ongoing cost is a rented GPU for occasional training runs.

what makes it not passive is the audience side. responding to messages, keeping engagement up, posting daily. thats where the revenue actually lives and it takes real time.

platform that works for AI content is Fanvue. OnlyFans actively bans AI accounts now. Fanvue officially supports and verifies AI creators.

happy to answer anything about the model, income structure, the tech, whatever people are curious about.

been running an AI character on social and Fanvue for a while. want to give the version nobody writes about. not the hype, not the "its a scam" take, just the real mechanics.

the money isnt in subscriptions. subscriptions are maybe 10 to 15% of revenue. the actual income comes from content unlocks where fans pay for specific stuff, and a small number of people who spend way more than everyone else combined. one person can outspend 50 regular subscribers easily.

costs are near zero once the system is built. the character generates content at almost no cost per image. no studio, no model fees, no burnout. main ongoing cost is a rented GPU for occasional training runs.

what makes it not passive is the audience side. responding to messages, keeping engagement up, posting daily. thats where the revenue actually lives and it takes real time.

platform that works for AI content is Fanvue. OnlyFans actively bans AI accounts now. Fanvue officially supports and verifies AI creators.

happy to answer anything about the model, income structure, the tech, whatever people are curious about.

if you're getting a slightly different face every gen even with detailed prompts, prompting isn't the fix. the model has no memory of "your character" — it's just pattern matching your description each time.

the actual fix is training a character lora on a small dataset so the identity gets baked into the model itself. prompts then control what's happening in the scene — pose, lighting, outfit — while the face stays locked.

what worked for me: ~60 images, mix of face crops and wider shots, varied lighting throughout. cut any image where the face looks slightly off because the lora learns the average and one bad frame drags everything.

training takes about an hour on a rented gpu. after that the character is just... consistent. every time.

anyone still trying to solve this with prompts alone? curious if there's an approach i missed.

spent way too long tweaking learning rates and epochs trying to fix a character that came out "almost right." turned out the fix was almost entirely in the dataset.

what changed it:

• ~60 images, not more — went past 100 once and got an overfit result that only nailed the exact poses it trained on
• mix of shot types, roughly 70% face crops and 30% wider — all closeups gives you great portraits and broken full-body shots
• vary the lighting a lot, or it can't generalize to new scenes
• cut every "almost good" image, since the model averages everything and one off frame drags the whole thing down

the dataset work did more than any optimizer or LR change. curious what others have found matters more than expected.

watched a lot of people (me included) retrain over and over chasing a better character when the real fix was upstream in the dataset.

what actually mattered:

• 60ish images, not more. went past 100 once and got an overfit lora that only did the poses it trained on.
• mix shot types — ~70% face crops, 30% wider. all closeups gives great portraits and cursed full body.
• vary lighting hard. same lighting every image and it can't generalize.
• cut every "almost good" image. the lora averages everything, so one slightly-off face drags the whole thing.

fixing the dataset did more than any optimizer or learning rate change ever did. what's everyone else found matters more than they expected?

we're past the point where producing high-quality images, video, and text is hard or expensive. it's basically free and unlimited. which means production was never really the moat.

so what's left that's scarce? attention and trust. anyone can spin up a flawless ai persona or a clean article — so can everyone else. the content commoditized itself. what doesn't scale is getting people to notice and believe you.

feels like every content-based field is about to reorganize around distribution and credibility instead of production skill. curious whether people think that's the real shift or just part of it.

running faceless social pages, the lesson that stuck: people follow a consistent identity, not a content feed.

the pages that stalled posted good content with no through-line — no recognizable style, voice, or personality. nothing to follow, just stuff to like and scroll past.

what moved growth: locking a visual style, a caption voice, and a consistent way of replying to comments so the page felt like a someone. even with no face, it has to feel like a person's behind it.

for anyone running faceless accounts — has identity or raw content quality moved your numbers more?

we hit the point where producing great images, video, text is effectively free and infinite. which means production was never the moat — distribution and trust were.

anyone can spin up a flawless ai persona, a clean article, a polished video at near-zero cost. so can everyone else. the content isn't scarce anymore, attention and credibility are, and those don't scale the way generation does.

feels like the creator economy's about to reorganize around this. winners won't be the best producers, they'll be the best distributors and trust-builders. agree or am i overstating it?

running something where each piece of output costs almost nothing once the system's set up. the economics mess with old instincts.

normal business: cost scales with output — time, people, materials. this: some setup cost upfront, then near-zero per unit. so growth isn't limited by production at all, only by distribution and demand.

early mistake i made: thinking near-zero production cost meant easy money. it doesn't — it just moves the hard part. when supply is basically infinite and free, attention is the only scarce thing left, and all the leverage sits in distribution.

anyone running something with this cost structure? how'd it shift what you focus on?

spent forever trying to prompt my way to a consistent character (same face every generation) and it's basically impossible past a point. sharing what i learned so others don't waste the time.

the issue: even with super detailed prompts, image models drift the face every gen. you can get close, never locked. prompt engineering controls a lot but not identity persistence.

what actually works is training a lora on a small dataset of your character — then the identity is baked into the model, not the prompt. prompts then control scene/pose/lighting while the face stays fixed.

rule of thumb i landed on: prompt for what's happening, train for who it is. anyone found prompt-only methods that actually hold a face? genuinely curious if i missed something.

run a few faceless pages and the biggest thing i've learned: a faceless page still needs to feel like a someone, not a content dispenser.

the ones that stall post technically good content but have no consistent identity — no recognizable style, voice, or personality. people might like a post but there's no reason to follow because there's no "person" to follow.

what actually works: lock a visual style, a caption voice, a way you reply to comments. consistency of identity beats raw content quality on faceless accounts every time. people follow people, even when there's no face.

anyone running faceless pages — what's moved your follower growth more, content quality or identity consistency?

been running a content operation where each piece costs almost nothing to produce once the system's set up. the unit economics are unlike any business i've run before and it's been a mental adjustment.

normal content business: your cost scales with output (time, hiring, production). this one: fixed setup cost upfront, then near-zero marginal cost per piece. so the entire game becomes distribution and audience, not production.

the trap is thinking near-zero production cost = easy money. it's not — it just moves the hard part. when anyone can produce infinite content cheaply, attention and trust become the only scarce things.

anyone else running something with this kind of cost structure? how'd it change how you think about the business?

figured out a cost setup for generating consistent character content and wanted to share where local makes sense vs renting.

worth local: inference/generation once your lora's trained. fast, no per-image cost, full control. a 4090 handles batches fine.

worth renting: the lora training itself. it's a short heavy burst (~1hr), so renting an A100 for an hour beats tying up your own card or running it slow.

hybrid ends up cheapest — rent for the occasional training run, generate everything else at home. anyone training fully local? curious what hardware makes that actually practical.

been running faceless social pages for a bit and the thing that actually moved the needle wasn't better content, it was making the page feel like a consistent person/identity.

same visual style every post, same "voice" in captions, same vibe in how you reply to comments. people follow a person, not a content feed. even a faceless page needs to feel like someone's behind it.

the accounts i've seen stall are the ones posting good content with zero identity — no reason to follow vs just liking the one post. anyone else found identity beats raw quality on faceless pages?

not saying ai influencers are better — they're obviously not, no real life, no real opinions. the point is brands don't actually need authentic, they need consistent and predictable.

an ai persona never goes off-brand, never burns out, never gets cancelled, costs almost nothing per post. for the huge mid-tier brand deal market that's already competitive and only getting cheaper.

the interesting question to me is what it does to humans. one theory: it pushes real authenticity upmarket. if ai can pump out polished lifestyle content for free, the only scarce thing left is an actual life, real stakes, real vulnerability.

so maybe the "aesthetic lifestyle account that posts 3x a week" gets commoditized, and the creators who survive are the genuinely irreplaceable ones. or maybe audience trust just collapses across the board. curious what people think.

trained a bunch of bad loras before figuring out it's almost always the dataset, not the settings.

stuff that wrecked mine:

• too many images. went over 100 thinking more = better, got an overfit lora that could only do the exact poses it trained on. 60ish is the sweet spot.
• all face closeups, no wider shots. great portraits, cursed full body. mix in maybe 30% wider.
• same lighting in every pic. lora couldn't generalize. vary it hard.
• leaving in "almost good" images. the lora averages everything so one off-looking face drags the whole thing.

fixing the dataset did more than any setting change ever did. what else have people found matters more than expected?

wanted something that didn't need my face or fixed hours so i went down this path instead of grinding a second job. honest update.

first 6 weeks were just learning the tech — comfyui, training a character model so the face actually stays the same across every post. once that clicked the content side got fast and repeatable.

what surprised me: the tech was the easy part. the real work is posting consistently and actually engaging the audience. that's where it's won or lost, not the image generation.

where i'm at now — turned what i learned into a small community of people doing the same thing. it's not passive, the grind is real, but overhead is almost nothing and it scales different than a normal side gig.

happy to answer anything about the build or the business side.

the "it's a gimmick" takes miss how the actual business works.

you build one consistent ai character (needs real model training, not just prompting), run it like a normal social account, monetize through subscription/content platforms. the advantage isn't that it's better than a human creator, it's that the content costs basically nothing to make, it never burns out, and one person can run several at once.

the part people underrate: consistency is genuinely hard, and the money's in managing the audience relationship, not the content itself. content's the easy part.

bigger picture that interests me — when making content costs near zero, the whole bottleneck shifts to distribution and trust. that goes way beyond this niche.

curious how people think this shakes out for creators in general.

face drift was killing me for months so figured i'd share what finally fixed it.

dataset: 60 images, mostly tight face crops with some wider shots mixed in. vary the lighting a lot. and cut any image where the face looks even slightly off — the lora averages everything so one bad pic drags it all down.

z-image turbo training: 12 epochs, lr 1e-4, dim 32, alpha 16. about an hour on a rented gpu. trains faster than flux and smaller files but it's way less forgiving of a messy dataset.

at generation: lora weight 0.75-0.85 then a face detailer pass after to clean up whatever slips through.

what's everyone landing on for dataset size? seen people swear by 25 all the way to 150.