Daryl

building everything related to ai.

[Mufasa @mufvza]

i analysed 1,000 TIKTOK slideshows for consumer apps...

here's what i found something that change how you run your app/saas campaign since.

most people assume the slideshow with the most views brings in the most installs. i tracked every metric i could pull across 1000+ posts. views, saves, comment sentiment, slide count, where the app got mentioned in the sequence, caption length, niche. the data told a different story.

the highest converting slideshows rarely broke 100k views. some sat under 20k. meanwhile some of the viral ones with 2m+ views converted under 0.05%. viral and profitable are two different games.

here's the pattern that separated the winners.

the format was almost always: content, content, content, content, ad warmup, app push. 4 to 6 slides that feel like normal lifestyle or niche content, no mention of the app at all. then one slide near the end where the product shows up, framed as part of the story instead of an ad.

apps that opened with the product on slide 1 underperformed almost every time. the accounts winning were disguising the app inside content people were already scrolling for anyway. travel aesthetics, interior inspiration, "things nobody tells you about x" hooks, niche opinions.

the second pattern was volume, not virality. accounts running 8-10 tiktoks, posting 2x a day, same slide formats with fresh variations each time. 90% of posts stayed under 5k views, most even under 300. a handful hit 50k-500k. a rare one crossed 1m. the accounts winning weren't making one perfect post, they were running the format enough times that the algorithm found the winners for them.

the workflow behind it, if you want to copy it:

research first. search your niche on tiktok, screenshot every top slideshow, save the captions somewhere. this is the raw material for everything after.

pull matching visuals from pinterest for each slide type in that screenshot pile. figure out what slide 1 looks like, slide 2, slide 3. download a handful per slide type.

not everything from pinterest can be reposted as is. run it through an image api like openai or gemini to generate variations that keep the same vibe. 5 slide types x 100 variations gets you 500 usable images fast.

feed the competitor captions into claude code and have it write new caption variations in that same tone, keep the early slides content only, drop the app in near the end.

claude code can overlay the captions onto the images directly using ffmpeg, then hand scheduling off to a tool that allows accounts to post automatically without you touching them daily.

set this up once and you get months of content queued across every account, running the same proven format with fresh visuals each time.

the accounts losing were treating every post as a one off. the accounts winning built a system and let volume do the work.

[Daryl @grow3ithD]

@sulfurscales post a full tutorial pls

[Sulfur @sulfurscales]

how to make VIRAL tiktok shop slideshows in 2026...

most creators think slideshows are the lazy version of video content. that's backwards. they're the least saturated format on the platform right now, and the mechanics behind why they convert are completely different from what people assume.

a slideshow isn't a slower video. it's a funnel compressed into 3-8 static images, and every single slide has one specific job:

slide 1: the pain point, has to land in under a second, this is your hook and your completion rate combined slide 2-3: agitate it, make the pain point feel unavoidable, "does this happen to you too" energy slide 4: the solution, your product enters here, not before slide 5-6: proof, transformation, results, whatever makes the fix feel real final slide: the cta, buy below, no hard sell needed if the first slides did their job
no filming, no face required, no need to own the product. you can generate the pain point, the environment, even the "result," none of that has to be real for the format to work. the constraint isn't production, it's whether you can identify a pain point sharply enough that someone stops scrolling.
myths wasting people's time on this format:
"you need real footage or it won't convert." false. fully AI-generated slides are going viral daily right now. viewers aren't fact-checking whether the room or the person is real, they're reacting to whether the pain point is relatable.
"more slides means more effort means better results." false. some of the top performing slideshows are 2-3 images total. if the product doesn't need explaining, a single pain point slide plus the offer outperforms a 7-slide funnel every time.

"you need a totally original angle to stand out." false. take a slideshow or video that's already proven to convert, keep the exact structure and pacing, swap only the product. the pain point mechanics are what carry the performance, not the specific product.

"trending products only." false. the biggest unlock is going backward, not forward. pull products with a track record from months ago and check whether anyone's actually made a slideshow for them yet. most haven't, because the format itself is new.

what actually drives performance:

the first slide is the whole game, it functions like your first 2 seconds on video, weak pain point = swipe = dead post volume over polish, you're not making one perfect slideshow, you're testing pain points across products, most will flop under a few hundred views and that's the model working correctly reformatting beats creating from scratch, a proven video or slideshow you've screenshotted for reference isn't cheating, it's using a validated pain point instead of guessing one

the format is still expanding in terms of who has full posting access, which means the unsaturated window is open right now, not in six months once it's standard for everyone.

[Harshil Tomar @Hartdrawss]

I found a component library with 250+ animations that will make your frontend look insane.

And it's completely FREE !

>Ready to use components with animations built in
>Copy and drop straight into your project
>The kind of UI that makes your app look like a $50K build

Your frontend will never look the same.

[nooooob @mikeluan123]

My holy-shi moment of opus5.

Homeworld Style Space RTS

with OPUS 5 (workflow)

68.6k input, 4.6m output, 837.2m cache read, 13.6m cache write ($632.65)

---

Models: generated,
Asset: none.

Besides minor game play issues, watching model cook this is beyond my imagination.

[Rugikk @rugikkk]

THIS AI MODEL IN A DRESS PRINTS $5,000+ MONTHLY.

She walks down the street in a flowing dress. Fabric moves with every step. Hair catches the light. She glances back at the camera and keeps going.

Built with AI. Locked once. Sold forever.

Claude handles the prompts and scene variations. One consistent model generates endless street, lifestyle, and exclusive shots without a single real walk.

No travel. No schedules. Just content that converts on OnlyFans.

Real talent costs money and disappears. This asset scales at zero extra cost.

One model. One setup. $5,000+ on repeat.

[David Attias @david_attisaas]

your competition btw

[Mufasa @mufvza]

this fitness app is doing $600k/month with duolingo-like onboarding, here's why.

onboarding:

- an elephant mascot greets you first → duolingo tone in a category full of clinical spreadsheet apps.

- it shows you the ranking system before any tracking feature → you learn what you're playing for before you learn how to play.

- hold the screen to commit → a physical action, tiny sunk cost, you've already done something.

- build your own avatar → it's your app now, not theirs - 40+ questions on goals, experience, training history → every answer makes the plan feel more custom.

- you earn your first rank from the answers alone → a win before you've touched a barbell - review prompt fires right at that moment → peak motivation, highest possible rating.

- paywall loops with no exit, only "try free for 7 days".

that review placement is the actual business. it's how you get 30k+ reviews sitting at 4.7. review volume is an app store ranking input, and liftoff is top 3 on 700+ keywords. the onboarding isn't just converting downloads but it's manufacturing the ratings that produce the next batch.

these guys stopped chasing trends. found 3 or 4 formats that converted, pov training clips, day in the life, transformation arcs, and ran them into the ground with fresh execution each time.

i see app founders do this exact system adapted to the niche, somewhere in there we separated creation from scale. they built the original templates, a small team of editors multiplied them across platforms. this is where most solo founders get stuck. they either do everything themselves and burn out around 15 posts a month, or hire generically and lose whatever made the content work.

[Daryl @grow3ithD]

@sulfurscales Amazon

[Tran Mau Tri Tam ✪ @tranmautritam]

Where I go when I run out of design ideas. Save this 👇

- https://t.co/MxeRSvBDxr - best of social post design
- https://t.co/5SM6zQRHrH - daily web design inspiration
- https://t.co/21RG68ReVa - minimal websites directory
- https://t.co/c7NA6ro0zG - OG images done right
- https://t.co/D9m4nLo37C - beautifully designed decks
- https://t.co/zX9pbvqced - 1,200+ logos by top designers
- https://t.co/ru7zu4VJhD - branding & editorial projects
- https://t.co/O58AD1CIyO - real brand guidelines library
- https://t.co/OPC3oYmGIe - best of recent design, daily

What am I missing?

[Yasser Visuals @YasserVisuals]

This video generated 10 leads in a single day.

the client was happy.

[Daryl @grow3ithD]

@invideoOfficial wow

[Invideo @invideoOfficial]

Higgsfield just failed EVERY creator out there.
We read the Higgsfield terms of service - and we ARE SHOCKED.

[Miko @Mho_23]

Sora 2 was so far ahead of its time

this model came out in September and the outputs still look just as good if not better than anything today

the main issue with it was the lack of controllability and how expensive it was

if OpenAI decided to bring Sora back but this time added voice references and multi references, they would 100% be the leading model again

here is a video I made with it using my V2 system

It's sad to see such an amazing model go away

[Laur @laurgrowth]

the finance niche has the best affiliate payouts on the internet

and the audience is the most desperate to click

people with money stress don't scroll passively

they are actively hunting for a solution

they will click your link
they will read your landing page
they will convert

the format that's working right now:

→ ai character that looks like a normal person who just found something that fixed their situation
→ not a financial guru
→ not someone flexing
→ just a relatable person sharing what they actually found

it reads like a recommendation not an ad

and that's exactly why it prints

rt + comment "finance" and i'll send the workflow
(must be following for dm)

[David @justddev]

almost 11m views on a video promoting an app?

osta makes $20k/mo by repeating the same format over and over

“since when did TikTok get this new update?”

another reminder that there’s space even in the most crowded markets if you nail the marketing

[David Ch @chhddavid]

BREAKING: Claude Opus 5 one-shots motion videos

Generated this video in 19 minutes, only did 2 changes.

[Sulfur @sulfurscales]

how to CRACK the tiktok algorithm in 2026...

the algorithm in 2026 is not judging your account. it's judging your first 500 views. everyone overthinks this.

here's the actual method to crack it:

every video starts from ZERO. doesn't matter if your last one hit 1M or your account has 200k followers. tiktok takes the new post, runs it through content moderation first, THEN drops it to a small cold test pool. that pool isn't random. it's people who already watch your exact niche, because tiktok's whole goal is keeping people on the app, so it shows your video to the people most likely to sit through it.

then it reads 4 signals, in this order of weight:

completion rate (did they finish it)
rewatches (did they loop it)
shares (did they send it to someone)
velocity (how FAST all of that came in)

clear the wave, it pushes ~5x bigger. clear that, 5x again. it keeps expanding until the numbers drop below the bar for that wave, then it stops. that's it. that's "going viral." it's just a video that kept clearing waves. nothing mystical.

the part that breaks people's brains: this resets EVERY post. tiktok is not youtube shorts. on youtube the channel carries momentum. on tiktok the VIDEO carries itself. your last banger does not pre-load the next one. all followers do is get you shown FIRST in the test pool, which is a head start, not a guarantee. every video still earns its reach from scratch.

now the myths that waste your time:

"warm up a new account by scrolling for 2-3 days before posting." MYTH. tiktok has said this directly, there is no warm-up requirement. the only real device-level flag is ban evasion, and that only triggers if your device/IP is tied to a previously banned account. clean device = post day one, no penalty.

"posting too much hurts the algorithm." also wrong. there is no volume throttle on your account. LOW volume is the real risk. every post is a fresh roll at the test pool. fewer posts = fewer rolls = fewer chances to hit a wave that clears. the accounts that grow fast post 1-3x a day, not once a week.

"you need trending audio to go viral." no. trending audio helps discovery marginally but a strong hook on a silent slideshow will beat a weak video on the #1 sound every time. the sound doesn't save a bad first 2 seconds.

what ACTUALLY moves it:

the first 2 seconds are the whole game. that IS your completion rate. weak hook, the test pool bounces, the video dies in wave 1 and never recovers. front-load the payoff, cut the intro, no "hey guys."

shares > likes, by a lot. a like is passive, it barely registers. a share tells tiktok "spread this" and it's the single signal that widens the wave hardest. build for the share: a take people want to send to someone, a "wait what" fact, a screenshot-able line.

velocity beats total. 200 views in the first hour tells the algo more than 2,000 over a week. post when your specific audience is actually awake, check your analytics, don't guess "peak times."

the format is disposable, the system isn't. 90% of your posts will die under 5,000 views, most under 300. that's not failure, that's the model working. you're not making one perfect video, you're feeding the test pool enough clean shots that a few clear all the waves. 10 accounts x 2 posts a day = 20 rolls daily. one hits 500k and pays for the other 19.

and if monetization is the goal: creator rewards in 2026 is 10k followers + 100k views in the last 30 days, ROLLING (a viral month 6 months ago counts for nothing). only videos 60 SECONDS or longer earn a cent. and you have to be based in an eligible country to even apply: US, UK, germany, france, japan, korea, brazil, a few others. pakistan, india, most of MENA are not on the list. so "target US for higher RPM" isn't just a payout tip, geo is a hard gate on whether the program exists for you at all.

stop trying to game it. feed it clean videos with a killer first 2 seconds and let the test pool do the sorting. the algo is dumber and more fair than people think.

[Daryl @grow3ithD]

@sulfurscales apps

[EP @eptwts]

you can access it for free here: https://t.co/1odFjxQMR6