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[ New Shop Release ] ⟢ Ending Credits Widget 🎥🍿 a (6) page slideshow with your stream & chat stats! ⟡ (36) Patterns and (3) theme songs ⟡ Fully customizable colors, fonts, timings & more ⟡ Twitch, Youtube, Kick, Ko-fi & Throne 🔗 All links below

⧽ Nani 🪻

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31,410 Aufrufe • vor 1 Tag •via X (Twitter)

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Claude Code + Nano Banana 2 is f*cking cracked for advertorials 🤯 One prompt → a complete presell page with editorial copy, AI product photography, testimonials, and pricing — ready to paste into Shopify. Built 100% in Claude Code. Perfect for DTC brands and agencies running advertorials on Meta who need 5-10 different pages per month but can't keep paying $1,500 each. If you're briefing copywriters, waiting days for a draft, giving notes, waiting again, and still only getting one or two new pages per month... This system eliminates the entire loop: → Enter your brand, product, target customer, and unique mechanism → Pick a style preset (clinical editorial, news exposé, lifestyle magazine, warm and trustworthy) → Claude writes the full page — urgency banner to guarantee to final CTA → Nano Banana 2 generates product images and mechanism diagrams inline → Get back a complete HTML page following the same DR structure that's already scaling on Meta No copywriter back-and-forth. No designing from scratch. No starting from a blank page every time. What you get: → A production-ready HTML advertorial page you paste into Shopify → DR copy structure extracted from real pages scaling on Meta right now → AI-generated product photography and diagrams matched to your brand → 4 style presets that shift tone, colors, and authority framing per niche → A fully customizable system prompt — swap in your own templates and it follows those instead I built 3 complete advertorial pages for 3 different brands in under 5 minutes. Skincare, supplements, and pet products. All different styles, all production-ready. I put together a full playbook with the exact system prompt so you can get this running yourself. Want access for free? > Like this post > Comment "CLAUDE" And I'll send it over (must be following so I can DM)

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Abhishek Yadav

19,376 Aufrufe • vor 8 Tagen

✨ I open sourced my first Chrome extension 🚀 SuperLevels I vibe coded it to replace all my Chrome extensions that are increasingly being bought up by spyware and malware companies who sell your data or worse hack your accounts and steal your stuff/money/data, which I'd call one of the top security risks right now For example: Chrome extensions can read your cookies or localStorage data, including session tokens, then login to your web or email accounts and hack you, they can inject code into any site to pull data form any site you browse, then break into your crypto accounts, drain your wallets, and selling your browsing history to ad companies, but that'd actually be the most favorable thing to happen of all these! Chrome extensions are just very very very unsafe So I coded my own, that I can trust because I made it, and I can read the source code: my extension is called 🚀SuperLevels and has all the features that the Chrome extensions I used to use have but all built into one safe one The cool thing is it's 100% open source and free, and you can audit the code first with AI yourself before installing it, and then if you do install it, customize it to your liking again with AI It has these features that improve my daily workflow while browsing the web: 🚮 Tab Cleaner Automatically closes inactive tabs after a configurable timeout (default: 5 minutes). Set excluded hosts to keep important tabs alive. View and re-open recently closed tabs. 🍪 Cookie Editor Full cookie manager for the current site. View, edit, add, and delete cookies. Export cookies as JSON. Expand any cookie to see and modify all fields including domain, path, SameSite, secure, and httpOnly flags. 🔀 Redirect Tracer See every redirect hop your browser took to reach the current page. Shows status codes (301, 302, 307, etc.) with a visual chain. Copy the full redirect chain to clipboard. 🌙 Dark Mode Instant dark mode for any website using CSS filter inversion. Adjustable brightness. Toggle per-site or globally. Images and videos are automatically re-inverted so they look normal. 𝕏 X Dim Mode Custom dim theme for X/Twitter with 7 color palettes: Dim, Slate, Jade, Plum, Dusk, Ember, or a custom hue. Live preview in the popup. ⚡ JS Toggle Disable JavaScript per-site with one click. Useful for debugging, reading articles without popups, or testing progressive enhancement. Page reloads automatically. 🚫 GDPR Cookie Consent Dismisser Auto-hides and auto-clicks cookie consent banners. Supports OneTrust, CookieBot, Didomi, Quantcast, GDPR plugins, and dozens more frameworks. Toggle off if a site breaks. 🎨 Live CSS Editor Write custom CSS for any website, applied in real-time as you type. Saved per-domain. Supports tab key for indentation. 📺 YouTube Unhook Removes YouTube distractions: no homepage feed, no sidebar suggestions, no end screen overlays, no Shorts. Search still works — just no algorithmic recommendations. 🎵 Music Recognizer Shazam-like music identification for any tab. Captures 10 seconds of audio and identifies the song via ACRCloud (free signup, bring your own API key). Results link to YouTube. History of recognized songs. 🖼 Picture-in-Picture Pop the largest video on the current tab into a floating PiP window with one click. 🗺 Google Maps Links Re-adds clickable Maps links and map preview cards to Google Search results. 🖼 View Image Adds a "View Image" button back to Google Images, linking directly to the full-size original image. {} JSON Formatter Auto-detects pure JSON response pages and formats them with syntax highlighting, collapsible sections, and a dark theme. Copy or view raw with one click. Never triggers on regular HTML pages.

✨ I open sourced my first Chrome extension 🚀 SuperLevels I vibe coded it to replace all my Chrome extensions that are increasingly being bought up by spyware and malware companies who sell your data or worse hack your accounts and steal your stuff/money/data, which I'd call one of the top security risks right now For example: Chrome extensions can read your cookies or localStorage data, including session tokens, then login to your web or email accounts and hack you, they can inject code into any site to pull data form any site you browse, then break into your crypto accounts, drain your wallets, and selling your browsing history to ad companies, but that'd actually be the most favorable thing to happen of all these! Chrome extensions are just very very very unsafe So I coded my own, that I can trust because I made it, and I can read the source code: my extension is called 🚀SuperLevels and has all the features that the Chrome extensions I used to use have but all built into one safe one The cool thing is it's 100% open source and free, and you can audit the code first with AI yourself before installing it, and then if you do install it, customize it to your liking again with AI It has these features that improve my daily workflow while browsing the web: 🚮 Tab Cleaner Automatically closes inactive tabs after a configurable timeout (default: 5 minutes). Set excluded hosts to keep important tabs alive. View and re-open recently closed tabs. 🍪 Cookie Editor Full cookie manager for the current site. View, edit, add, and delete cookies. Export cookies as JSON. Expand any cookie to see and modify all fields including domain, path, SameSite, secure, and httpOnly flags. 🔀 Redirect Tracer See every redirect hop your browser took to reach the current page. Shows status codes (301, 302, 307, etc.) with a visual chain. Copy the full redirect chain to clipboard. 🌙 Dark Mode Instant dark mode for any website using CSS filter inversion. Adjustable brightness. Toggle per-site or globally. Images and videos are automatically re-inverted so they look normal. 𝕏 X Dim Mode Custom dim theme for X/Twitter with 7 color palettes: Dim, Slate, Jade, Plum, Dusk, Ember, or a custom hue. Live preview in the popup. ⚡ JS Toggle Disable JavaScript per-site with one click. Useful for debugging, reading articles without popups, or testing progressive enhancement. Page reloads automatically. 🚫 GDPR Cookie Consent Dismisser Auto-hides and auto-clicks cookie consent banners. Supports OneTrust, CookieBot, Didomi, Quantcast, GDPR plugins, and dozens more frameworks. Toggle off if a site breaks. 🎨 Live CSS Editor Write custom CSS for any website, applied in real-time as you type. Saved per-domain. Supports tab key for indentation. 📺 YouTube Unhook Removes YouTube distractions: no homepage feed, no sidebar suggestions, no end screen overlays, no Shorts. Search still works — just no algorithmic recommendations. 🎵 Music Recognizer Shazam-like music identification for any tab. Captures 10 seconds of audio and identifies the song via ACRCloud (free signup, bring your own API key). Results link to YouTube. History of recognized songs. 🖼 Picture-in-Picture Pop the largest video on the current tab into a floating PiP window with one click. 🗺 Google Maps Links Re-adds clickable Maps links and map preview cards to Google Search results. 🖼 View Image Adds a "View Image" button back to Google Images, linking directly to the full-size original image. {} JSON Formatter Auto-detects pure JSON response pages and formats them with syntax highlighting, collapsible sections, and a dark theme. Copy or view raw with one click. Never triggers on regular HTML pages.

@levelsio

260,415 Aufrufe • vor 5 Monaten

HERMES AGENT HAS A SECOND BRAIN. 1,100+ KNOWLEDGE FILES. AUTO-LINKED. SELF-IMPROVING. GROWING EVERY NIGHT. THIS IS THE OBSIDIAN GRAPH BEHIND IT. every dot = one knowledge file (markdown) every line = one wiki-link between files every color = one category (skills, notes, decisions, sources, entities) HOW IT BUILDS ITSELF: Hermes ships with a bundled LLM Wiki skill. based on Andrej Karpathy's pattern. unlike RAG (rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. when you feed the agent a source: → it reads the content → writes a structured markdown page → auto-links to every related existing page → flags contradictions with previous entries → updates all affected pages one source in. multiple connections created. the graph grows denser with every entry. WHAT FEEDS THE WIKI: → articles and URLs you find interesting → meeting transcripts → PDF documents and research papers → conversation history from Hermes sessions → Claude Code and Codex session history → Slack logs, email threads, saved notes → YouTube transcripts → raw text dropped into a _raw/ folder the obsidian-wiki package supports multi-agent ingest from Hermes, Claude Code, Codex, OpenClaw, Pi, Windsurf, and ChatGPT exports. install: pip install obsidian-wiki obsidian-wiki setup --vault ~/wiki AUTOMATE THE GROWTH: set cron jobs to feed the wiki overnight: "every day at 9am, check for new meetings. ingest transcripts into the wiki." "every week, check arXiv for new papers in [niche]. summarize and file into the wiki." "every day, ingest today's Hermes sessions into the wiki under session-history." month 1: 50 entries. scattered. month 3: 300+ entries. cross-referenced. month 6: 1,000+ entries. the agent surfaces patterns you never searched for. WHY OBSIDIAN: the wiki is plain markdown files. no database. no lock-in. open it in Obsidian for graph view: → nodes show knowledge density → links show how ideas connect → clusters reveal your strongest domains → orphan nodes reveal gaps Hermes writes from a VPS. Obsidian reads on your laptop. obsidian-headless syncs without a GUI. agent writes from the server, you browse on your device. FOUR MEMORY LAYERS: Layer 1: memory.md + user.md (~2,200 + 1,375 chars. short-term.) Layer 2: SQLite with FTS5 (full session transcripts. searchable.) Layer 3: external providers (Mem0, SuperMemory, Honcho. optional.) Layer 4: Obsidian wiki via LLM Wiki skill (unlimited. compounding. the long-term brain.) layers 1-3 handle memory. layer 4 handles knowledge. the graph in this post is layer 4. SETUP: set in Desktop app, Dashboard, or config.yaml: WIKI_PATH=~/wiki OBSIDIAN_VAULT_PATH=~/wiki first run: Hermes asks for your domain. answer with your niche. the skill builds SCHEMA.md with tag taxonomy. after that: "index this into my wiki: [URL or text]" the wiki grows. the graph densifies. the agent gets smarter because the knowledge base got smarter. full 15 levels breakdown in the article 👇

HERMES AGENT HAS A SECOND BRAIN. 1,100+ KNOWLEDGE FILES. AUTO-LINKED. SELF-IMPROVING. GROWING EVERY NIGHT. THIS IS THE OBSIDIAN GRAPH BEHIND IT. every dot = one knowledge file (markdown) every line = one wiki-link between files every color = one category (skills, notes, decisions, sources, entities) HOW IT BUILDS ITSELF: Hermes ships with a bundled LLM Wiki skill. based on Andrej Karpathy's pattern. unlike RAG (rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. when you feed the agent a source: → it reads the content → writes a structured markdown page → auto-links to every related existing page → flags contradictions with previous entries → updates all affected pages one source in. multiple connections created. the graph grows denser with every entry. WHAT FEEDS THE WIKI: → articles and URLs you find interesting → meeting transcripts → PDF documents and research papers → conversation history from Hermes sessions → Claude Code and Codex session history → Slack logs, email threads, saved notes → YouTube transcripts → raw text dropped into a _raw/ folder the obsidian-wiki package supports multi-agent ingest from Hermes, Claude Code, Codex, OpenClaw, Pi, Windsurf, and ChatGPT exports. install: pip install obsidian-wiki obsidian-wiki setup --vault ~/wiki AUTOMATE THE GROWTH: set cron jobs to feed the wiki overnight: "every day at 9am, check for new meetings. ingest transcripts into the wiki." "every week, check arXiv for new papers in [niche]. summarize and file into the wiki." "every day, ingest today's Hermes sessions into the wiki under session-history." month 1: 50 entries. scattered. month 3: 300+ entries. cross-referenced. month 6: 1,000+ entries. the agent surfaces patterns you never searched for. WHY OBSIDIAN: the wiki is plain markdown files. no database. no lock-in. open it in Obsidian for graph view: → nodes show knowledge density → links show how ideas connect → clusters reveal your strongest domains → orphan nodes reveal gaps Hermes writes from a VPS. Obsidian reads on your laptop. obsidian-headless syncs without a GUI. agent writes from the server, you browse on your device. FOUR MEMORY LAYERS: Layer 1: memory.md + user.md (~2,200 + 1,375 chars. short-term.) Layer 2: SQLite with FTS5 (full session transcripts. searchable.) Layer 3: external providers (Mem0, SuperMemory, Honcho. optional.) Layer 4: Obsidian wiki via LLM Wiki skill (unlimited. compounding. the long-term brain.) layers 1-3 handle memory. layer 4 handles knowledge. the graph in this post is layer 4. SETUP: set in Desktop app, Dashboard, or config.yaml: WIKI_PATH=~/wiki OBSIDIAN_VAULT_PATH=~/wiki first run: Hermes asks for your domain. answer with your niche. the skill builds SCHEMA.md with tag taxonomy. after that: "index this into my wiki: [URL or text]" the wiki grows. the graph densifies. the agent gets smarter because the knowledge base got smarter. full 15 levels breakdown in the article 👇

YanXbt

35,900 Aufrufe • vor 3 Monaten

home page hero ✨ Design notes: - "Forever" hero text dot pixel FX done in Unicorn Studio. (I will do a whole tutorial on this later. Unicorn's WebGL engine is absolutely wild and very powerful / robust) - built in Framer - I wanted to recreate the iOS unlock effect where your home screen icons cascade into place in a beautifully timed choreography. This took a lot of careful timing using Framer's "Appear" effect on the hero text and surrounding avatars because it was super important that we didn't lose the legibility of our main message ("Build Your Forever Audience") with all the animations. - If you look closely, the choreography is setup to lead your eye through the hero text first starting with "Build Your" then "Forever" and finally "Audience." - With those text layers in place + the surrounding avatars, there is a slight 1 sec pause before the remaining elements slide in below and above (How it works, CTA buttons, announcement badge, and lastly the main nav). - All told the entire loading sequence is 6 seconds - Custom particle system powers the interactive star field (the stars slowly gravitate to your pointer position, and the star field perspective changes ever so subtly as you move your mouse around on the page) - I have 3 shooting stars made of small white line layers that start out off canvas rotated at different angles that shoot across to another point off canvas at random times on a loop effect. - Given this hero scene is in space, I wanted the surrounding avatar elements to "float" in low gravity mode. For this I used Framer's loop effect that slowly oscillates the layer's y position. I then offset the delay of each element randomly to stagger the floating loop so each avatar floats independently/randomly - The final major treatment for this hero scene was the scroll animations on the avatars. I wanted to create a bit of a warp speed effect when you scroll down, as if the avatars were being pulled or sucked into a worm hole as you scroll down below this hero fold. - To accomplish this, I applied Framer's scroll transform affect set to "section in view" on each of the floating avatars, and set the "scroll to" position of the upper avatars to be much, much further away on the y-axis than the "scroll to" position of the lower avatars. (eg. -1700px on upper most avatars vs. -600px on lowest positioned avatars). This effectively causes the upper avatars to slide up off the hero canvas with much greater velocity than the lower positioned avatars. - And when you scroll back up to the hero section, the inverse happens where the lower positioned avatars "arrive back in place" from up above the hero canvas before the upper avatars come back into the scene and settle in place. - Overall I wanted this hero section to feel alive. The floating avatars, particle system with very subtle star movements, and the Caustics effect on the "Forever" text all sort of move at the pace of slow breathing - which is a great pace to create a sense of life and comfort in your scene. Conversion Results (so far) - When this new Framer site launched along with Calaxy v1.9 release on Base a couple weeks ago, we saw a surge in traffic, around 20k page views in the first few days. - Of those 20k hits, 11k visited the app install page ( - which is our main CTA - We saw around 10K new users in the first week after v1.9 launch Overall I'm very happy with the new site and early performance metrics. Lots of tweaking to do but its a good start. If you are a designer building in Framer - hit me with any questions on the above hero notes. Happy to share more specifics! 👾

Chadd Weston

16,401 Aufrufe • vor 11 Monaten

If I was FORCED to make $20k/month with tiktok slideshows in 30 days, starting from 0, here's exactly what i would do in 20 steps: Days 1-3: Account infrastructure 1. Sign up to glitchy, pick walmart gift card rewards offer (2 min) 2. Buy 10 aged tiktok accounts off accsmarket ($15-20 total) 3. Get a US VPN running on every device — non-negotiable for US traffic targeting 4. Set up 1 phone per 3 accounts max (device cluster rule) 5. Warm all 10 accounts 72 hrs — scroll fyp 30 min/day, no posting Days 4-10: Content machine 6. Fresh research account locked to ur niche — tiktok feeds u the winners daily 7. Screenshot 50 viral slideshow frames directly from ur FYP 8. Claude writes 100 hook variations against proven patterns in 2 min 9. Gemini modifies images — "add crying face" / "make her shocked" 10. Build slideshows INSIDE the tiktok editor — adding text natively lets the algo read ur content and push it to the right ppl Days 11-20: Scale what works 11. Post 2-3 slideshows per account per day = 20-30 posts daily 12. Seed 5 comments per post within the first 15 min from spare accounts to spike engagement velocity 13. Kill any post under 500 views at 24hrs — no emotional attachment 14. Any post over 10k views = generate 20 unique variations and roll them out across every account 15. Run every variation through ffmpeg + spoof the metadata so tiktok reads each upload as fresh content Days 21-30: Automate + compound 16. Hire 2 filipino VAs at $5/hr to take over posting + comment seeding (~$400/mo) 17. Reinvest week 2 profits into 5 more aged accounts — now running 15+ 18. Build a funnelish landing page w fake testimonials above the fold to warm the click before they hit the offer 19. Cloudflare hosting so the page loads in under a second on mobile 20. By day 30 ur running 15 accounts, 30+ posts daily, fully systemized The realistic math: → 900 posts in 30 days → 3-4 of them go mega viral (3-4M views each) → At $6-8k per 1M views, one viral post = $20-30k → 3 mega virals × $25k avg = $75k+ The other 896 posts that didnt mega viral still produce mid-tier hits and steady traffic on top of that. Realistic month 1 as a beginner: $1-3k if u execute well. $5k if u get lucky with an early winning angle. Most ppl who treat it as a serious project and post daily see their first real month between months 2-3. Hooks written by AI. Images modified by AI. Posting handled by VAs. Comments seeded by VAs. Set it up once. Let it print. Comment "BLUEPRINT" and i'll send u my full tiktok slideshow blueprint. (must be following + repost)

If I was FORCED to make $20k/month with tiktok slideshows in 30 days, starting from 0, here's exactly what i would do in 20 steps: Days 1-3: Account infrastructure 1. Sign up to glitchy, pick walmart gift card rewards offer (2 min) 2. Buy 10 aged tiktok accounts off accsmarket ($15-20 total) 3. Get a US VPN running on every device — non-negotiable for US traffic targeting 4. Set up 1 phone per 3 accounts max (device cluster rule) 5. Warm all 10 accounts 72 hrs — scroll fyp 30 min/day, no posting Days 4-10: Content machine 6. Fresh research account locked to ur niche — tiktok feeds u the winners daily 7. Screenshot 50 viral slideshow frames directly from ur FYP 8. Claude writes 100 hook variations against proven patterns in 2 min 9. Gemini modifies images — "add crying face" / "make her shocked" 10. Build slideshows INSIDE the tiktok editor — adding text natively lets the algo read ur content and push it to the right ppl Days 11-20: Scale what works 11. Post 2-3 slideshows per account per day = 20-30 posts daily 12. Seed 5 comments per post within the first 15 min from spare accounts to spike engagement velocity 13. Kill any post under 500 views at 24hrs — no emotional attachment 14. Any post over 10k views = generate 20 unique variations and roll them out across every account 15. Run every variation through ffmpeg + spoof the metadata so tiktok reads each upload as fresh content Days 21-30: Automate + compound 16. Hire 2 filipino VAs at $5/hr to take over posting + comment seeding (~$400/mo) 17. Reinvest week 2 profits into 5 more aged accounts — now running 15+ 18. Build a funnelish landing page w fake testimonials above the fold to warm the click before they hit the offer 19. Cloudflare hosting so the page loads in under a second on mobile 20. By day 30 ur running 15 accounts, 30+ posts daily, fully systemized The realistic math: → 900 posts in 30 days → 3-4 of them go mega viral (3-4M views each) → At $6-8k per 1M views, one viral post = $20-30k → 3 mega virals × $25k avg = $75k+ The other 896 posts that didnt mega viral still produce mid-tier hits and steady traffic on top of that. Realistic month 1 as a beginner: $1-3k if u execute well. $5k if u get lucky with an early winning angle. Most ppl who treat it as a serious project and post daily see their first real month between months 2-3. Hooks written by AI. Images modified by AI. Posting handled by VAs. Comments seeded by VAs. Set it up once. Let it print. Comment "BLUEPRINT" and i'll send u my full tiktok slideshow blueprint. (must be following + repost)

affprinter

27,770 Aufrufe • vor 4 Monaten

here's how you can scale to 10k/month on tiktok shop with slideshows so most affiliates are stuck doing the same thing every day. film, edit, post, make like $60-80 in commissions. and the problem isn't effort, it's that your time is the bottleneck. you can't film 15 videos a day. so your output caps and your money caps with it. meanwhile there's a guy in canada who made $18k in his first two weeks. never filmed anything. never showed his face. never even held a product. canada doesn't even support tiktok shop, he's running us tiktok from there. all slideshows. and when i say slideshows i mean 4-7 images posted like a normal tiktok with a product link attached. that's it. someone buys off it, you get paid. making one takes maybe 5% of the skill of making a video. now here's the catch. tiktok gated the feature. most accounts can't attach products to photo posts, you'll get a "product links not available in photo mode" error. some accounts randomly have it. quick way to check: open tiktok studio on desktop (has to be desktop, mobile won't work), hit upload. if you see "videos or photos" you have access. click photos, upload your images, attach the link. if you only see video upload, you're not in yet. uk and europe are getting it randomly right now, us is only top gmv creators for the moment. check every day because tiktok doesn't tell you when you get it, the option just shows up. worst case you build the system now and execute day one when your account unlocks. because the people getting random access with no clue what they're doing are posting random images and making nothing. the format is easy, that doesn't mean it's mindless. the format itself is one thing repeated over and over: pain point first, product second. slide one hits an insecurity. back acne from the gym. car turning into an oven all summer. makeup that never sits right. the person scrolling sees it and goes "wait that's literally me." middle slides twist the knife a bit more. then "so i tried this thing everyone's using," show it working, before and after, and the last slide is just the offer. sale, free shipping, link below. done. that structure sells cold traffic. people who've never seen the product buy off one slideshow because you sold the problem, not the product. and here's the part most people don't clock when they're scrolling past these: none of it is real. the guy holding the ceiling fan doesn't own a ceiling fan. the back acne was generated onto the model. the smoothies were never made. it's all ai images. which kills every excuse at once. no face, no product in hand, no waiting on shipping, no country restrictions. the workflow is dumb simple. screenshot a slideshow style you like, drop it in chatgpt, say "make me 3x4 images in this style." then describe your pain point scene. couple walking to a car that's been baking in the sun, whatever it is. then grab the product image off the tiktok listing, feed it in, "now show them using this." repeat per slide. no fancy prompts, the reference images do all the work. two small things that matter more than they should. keep everything 3:4 or the mixed sizes make the whole post look off. and don't bake text into the images, add it inside tiktok. native text looks like a person posted it. baked text looks like an ad. people can feel the difference even if they can't explain it. if you want it to look even more real, take a photo of your actual kitchen or desk and only generate the product into it. real room, ai product. nobody can tell. for ideas, don't invent anything. steal structure, swap one variable. the number one post in the uk right now is a simpsons style slideshow about linen trousers. take that exact skeleton and run it with a sports set or summer shorts instead. same format, different product, suddenly it's unsaturated again. or take viral videos and turn them into slides. one guy took a viral video about a sink drainage thing, rebuilt it as images, and beat the original with 1.7m views. first week on the platform. the biggest edge though is going backwards. pull products that went viral 2-3 months ago, take the exact hooks that already converted millions of views, and rerun them as slideshows. nobody's done them in this format because the format barely exists. you're not testing ideas, you're re-releasing proven hits. then it just comes down to volume. no filming, no editing, no product costs means each post is basically free. so post 10-15 a day. most will flop, who cares. one will do 500k views in two days and when it does you remake it 50 times and drain it. every gated feature on tiktok runs the same cycle. early access prints, wide rollout saturates, then it's just another format everyone does. slideshows are still in the first part of that cycle.

here's how you can scale to 10k/month on tiktok shop with slideshows so most affiliates are stuck doing the same thing every day. film, edit, post, make like $60-80 in commissions. and the problem isn't effort, it's that your time is the bottleneck. you can't film 15 videos a day. so your output caps and your money caps with it. meanwhile there's a guy in canada who made $18k in his first two weeks. never filmed anything. never showed his face. never even held a product. canada doesn't even support tiktok shop, he's running us tiktok from there. all slideshows. and when i say slideshows i mean 4-7 images posted like a normal tiktok with a product link attached. that's it. someone buys off it, you get paid. making one takes maybe 5% of the skill of making a video. now here's the catch. tiktok gated the feature. most accounts can't attach products to photo posts, you'll get a "product links not available in photo mode" error. some accounts randomly have it. quick way to check: open tiktok studio on desktop (has to be desktop, mobile won't work), hit upload. if you see "videos or photos" you have access. click photos, upload your images, attach the link. if you only see video upload, you're not in yet. uk and europe are getting it randomly right now, us is only top gmv creators for the moment. check every day because tiktok doesn't tell you when you get it, the option just shows up. worst case you build the system now and execute day one when your account unlocks. because the people getting random access with no clue what they're doing are posting random images and making nothing. the format is easy, that doesn't mean it's mindless. the format itself is one thing repeated over and over: pain point first, product second. slide one hits an insecurity. back acne from the gym. car turning into an oven all summer. makeup that never sits right. the person scrolling sees it and goes "wait that's literally me." middle slides twist the knife a bit more. then "so i tried this thing everyone's using," show it working, before and after, and the last slide is just the offer. sale, free shipping, link below. done. that structure sells cold traffic. people who've never seen the product buy off one slideshow because you sold the problem, not the product. and here's the part most people don't clock when they're scrolling past these: none of it is real. the guy holding the ceiling fan doesn't own a ceiling fan. the back acne was generated onto the model. the smoothies were never made. it's all ai images. which kills every excuse at once. no face, no product in hand, no waiting on shipping, no country restrictions. the workflow is dumb simple. screenshot a slideshow style you like, drop it in chatgpt, say "make me 3x4 images in this style." then describe your pain point scene. couple walking to a car that's been baking in the sun, whatever it is. then grab the product image off the tiktok listing, feed it in, "now show them using this." repeat per slide. no fancy prompts, the reference images do all the work. two small things that matter more than they should. keep everything 3:4 or the mixed sizes make the whole post look off. and don't bake text into the images, add it inside tiktok. native text looks like a person posted it. baked text looks like an ad. people can feel the difference even if they can't explain it. if you want it to look even more real, take a photo of your actual kitchen or desk and only generate the product into it. real room, ai product. nobody can tell. for ideas, don't invent anything. steal structure, swap one variable. the number one post in the uk right now is a simpsons style slideshow about linen trousers. take that exact skeleton and run it with a sports set or summer shorts instead. same format, different product, suddenly it's unsaturated again. or take viral videos and turn them into slides. one guy took a viral video about a sink drainage thing, rebuilt it as images, and beat the original with 1.7m views. first week on the platform. the biggest edge though is going backwards. pull products that went viral 2-3 months ago, take the exact hooks that already converted millions of views, and rerun them as slideshows. nobody's done them in this format because the format barely exists. you're not testing ideas, you're re-releasing proven hits. then it just comes down to volume. no filming, no editing, no product costs means each post is basically free. so post 10-15 a day. most will flop, who cares. one will do 500k views in two days and when it does you remake it 50 times and drain it. every gated feature on tiktok runs the same cycle. early access prints, wide rollout saturates, then it's just another format everyone does. slideshows are still in the first part of that cycle.

Mufasa

13,583 Aufrufe • vor 1 Monat

introducing a new, very fun, LLM benchmark- the Game-of-Life Bench! the rules are simple: given an 8x8 grid following Conway's game of life rules, the goal is to create an initial pattern with at most 32 cells that can last the longest number of turns before dying/repeating. some results to highlight (with caveats detailed below): - gpt 5.1 lasts the longest with a 106 step run - claude models are really bad at this! they refuse to reason about this task and score < 25 points - deepseek r1 is the best open model with 102 steps. why? because i wanted to create a benchmark that has (i think) no practicality, but is still fun to look at, cheap, and still measures something interesting. i also am a big fan of the game of life. its absurdly simple rules leading to intractability is extremely cool to me. also, i saw a lot of work with LLMs trying to "predict" the next state in Conway's game of life, I think game-of-life bench is more fun because it's pretty open ended and only asks the LLM for the initial state. I also think this could be an RL env? but idk why you would ever train on this task haha i don't think this is a "serious" benchmark because it doesnt measure anything practical, but i still think it's a hard benchmark exactly because you can't predict what happens with your initial state many turns into the future; this is why i was initially expecting all LLMs to be bad at it, but turns out, some are clearly better than the others (the ordering may surprise you!) reminder: this is still a work-in-progress; (1) i am gpu-poor so could only do 10 runs for each model, even though total running cost is relatively low. maybe with some more credits i can run more seeds for each model. (2) i handpicked models which i think are at the frontier right now, plus some others that were on my mind. so, if you'd like to see a model on here, let me know. (3) i currently only do an 8x8 grid because i thought that by itself would be pretty hard for current LLMs, but of course we can increase grid sizes! (4) the coolest thing is, i dont think we can calculate the max possible number of states (yay undecidability!) you can go without repeating, so this is essentially a no-ceiling task, which is pretty cool! again, i did this mostly out of a desire to make LLMs do something fun. if this keeps me entertained for a few more days, i'd likely release a blog post on it. if it keeps me entertained for a week (and someone sponsors me), i'll put more work into it :P lastly, this is fully open sourced, so feel free to run this on your own!

introducing a new, very fun, LLM benchmark- the Game-of-Life Bench! the rules are simple: given an 8x8 grid following Conway's game of life rules, the goal is to create an initial pattern with at most 32 cells that can last the longest number of turns before dying/repeating. some results to highlight (with caveats detailed below): - gpt 5.1 lasts the longest with a 106 step run - claude models are really bad at this! they refuse to reason about this task and score < 25 points - deepseek r1 is the best open model with 102 steps. why? because i wanted to create a benchmark that has (i think) no practicality, but is still fun to look at, cheap, and still measures something interesting. i also am a big fan of the game of life. its absurdly simple rules leading to intractability is extremely cool to me. also, i saw a lot of work with LLMs trying to "predict" the next state in Conway's game of life, I think game-of-life bench is more fun because it's pretty open ended and only asks the LLM for the initial state. I also think this could be an RL env? but idk why you would ever train on this task haha i don't think this is a "serious" benchmark because it doesnt measure anything practical, but i still think it's a hard benchmark exactly because you can't predict what happens with your initial state many turns into the future; this is why i was initially expecting all LLMs to be bad at it, but turns out, some are clearly better than the others (the ordering may surprise you!) reminder: this is still a work-in-progress; (1) i am gpu-poor so could only do 10 runs for each model, even though total running cost is relatively low. maybe with some more credits i can run more seeds for each model. (2) i handpicked models which i think are at the frontier right now, plus some others that were on my mind. so, if you'd like to see a model on here, let me know. (3) i currently only do an 8x8 grid because i thought that by itself would be pretty hard for current LLMs, but of course we can increase grid sizes! (4) the coolest thing is, i dont think we can calculate the max possible number of states (yay undecidability!) you can go without repeating, so this is essentially a no-ceiling task, which is pretty cool! again, i did this mostly out of a desire to make LLMs do something fun. if this keeps me entertained for a few more days, i'd likely release a blog post on it. if it keeps me entertained for a week (and someone sponsors me), i'll put more work into it :P lastly, this is fully open sourced, so feel free to run this on your own!

Akshit

13,775 Aufrufe • vor 7 Monaten

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.

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.

Sulfur

46,775 Aufrufe • vor 2 Monaten

🌟 Fortnite Ecosystem v41.00 Update Summary 📅 June 5, 2026 🎮 Major Creator Updates: 1️⃣ Sidekicks as NPCs in UEFN Sidekicks are now available as scriptable NPCs in UEFN. Creators can customize how they look, animate them, script behavior with Verse, and even bring a player’s own Sidekick into an island experience. Important note: 🔹 Publishing islands with Sidekick NPCs opens July 23 🔹 Creature based islands may get new Discover opportunities 🔹 Great for monster battlers, cozy farming games, creature RPGs, companion adventures, and more 🔹 Epic plans to feature creature-based islands in a new creature-based Collection page 2️⃣ Custom Weapon Templates Creators can now use Scene Graph weapon templates for: 🔸 Pistol 🔸 SMG 🔸 Assault Rifle 🔸 Shotgun You can customize how weapons look, sound, and play, including mesh, VFX, audio, damage, fire rate, spread, and recoil. Important note: These Scene Graph entities are not compatible with older saving methods like the Save Point device. Epic says to use Verse persistence. 3️⃣ Mobile Controls Upgrade (Experimental) Big step for mobile friendly Fortnite games. 🔹 Touch Input Gestures 🔹 Custom touchscreen control layouts 🔹 Tappable custom HUD widgets 🔹 Verse API to detect touch enabled devices 🔹 New Designing for Mobile guide This should help genres like tycoons, puzzle games, menus, inventories, and mobile first UI feel way better. 4️⃣ Community Events Starting June 8, creators can create events in Fortnite Communities and share them in game. Events can show in: 🔸 Following tab 🔸 Creator Profile page 🔸 Island page 🔸 Island Lobby, if enabled Epic is also testing a Community Events row in Discover, but it will not show for all players and placement is not guaranteed. 🛠 UEFN Workflow Updates: 🔸 Push Changes now incrementally cooks only modified project parts 🔸 New Edit List Panel shows what is live and what still needs a push 🔸 Launch Session now combines multiple session actions 🔸 New Session Inspector gives better visibility into launch and Live Edit status 🔸 New Publishing Report helps catch issues before publishing 🔸 Improved Verse warning panel with direct VS Code links 🔸 New Editor Gizmo System 🔸 Physics setting moved into Island Settings 🔸 New Memory Snapshot tools help identify asset memory costs 🔸 Asset validation now warns when static meshes exceed 30k vertices at LOD0 Important Live Edit note: Live Edit is improved, but some changes can still require Push Changes. The new tools make it clearer what is already live and what still needs to be pushed. ⚠️ Important Publishing Change: Illegal Property Override warnings are now errors in v41.00. That means new or updated islands with these errors are blocked from publishing. Current published versions where the warning appeared will stay live. 👤 Follow a Developer Update: In v41.10, Epic will remove the Follow a Developer button from the Developer Profile Link device. The device itself will still be usable, and existing follower counts are not affected. If your island currently tells players to follow you through that device, update those callouts before v41.10. 🧑‍🚀 Hero Device Star Wars Update: More Star Wars characters have been added to the Hero device for Star Wars islands: 🔹 Luke Skywalker 🔹 Obi-Wan Kenobi 🔹 Mace Windu 🔹 Kylo Ren 🔹 IG-11 🔹 Moff Gideon 🔹 Boba Fett 🔹 Mandalorian (Pen & Ink), Clone Wars Anakin, and Clone Wars Ahsoka were also added to cosmetic-based devices 📦 New Content: 🌾 Cozy and Creature Tools 🔸 Plumpton Architecture Kit 🔸 Plumpton Farm Gallery 🔸 Pet Props Gallery 🔸 Updated foliage 🔸 Plumpton Feature Example ☕ New Prefabs and Galleries 🔹 Latte Landing Prop Gallery 🔹 Latte Landing Bun Store 🔹 Latte Landing Big Shots Cafe 🔹 Latte Landing Krunchy Krickets 🔹 Latte Landing Espresso Experiments 🔹 Latte Landing floors, walls, and roofs 🔹 More Plumpton props, plants, farm, pet shop, tavern, farmhouse, and more 🔫 New Weapons and Items: Weapons: 🔸 Vanguard Burst Rifle 🔸 The Voidblade’s Burst Rifle 🔸 Extending Focus Shotgun 🔸 Reacher Extending Shotgun 🔸 Chaos Exploder Rifle 🔸 Dark Voyager’s Chaos Rifle 🔸 Exotic Overdrive Pulse Rifle 🔸 Exotic Recon Bow 🔸 Exotic Leaping Lightning Gun Items: 🔹 Seven Sliders 🔹 Limitless Seven Sliders 🔹 Brick-a-Bunker 🏃 Player Movement Device Update: More movement settings are now available directly in the Player Movement device, giving creators better control over which players are affected. Includes: 🔸 Jump Fatigue 🔸 Slide Kick 🔸 Shoulder Bashing 🔸 Wall Kick 🔸 Roll Landing 🔸 Glider Redeploy 🔸 Player Flight 🔸 Flight Speed 🔸 Infinite Wall Kicks 🔸 Sprint and boosted jump energy costs 🧪 Experimental and Beta Updates: 🔹 Skeletal Animation in Scene Graph is now experimental 🔹 Physics remains Beta 🔹 Mobile touch controls and gesture support are experimental 🔹 Skeletal Animation in Scene Graph cannot be used in published islands yet 🛠 Community Bug Fixes: 🔸 Fixed server degradation from adding and removing entities 🔸 Fixed some Physics Materials not being exposed 🔸 Fixed some session launch cook errors 🔸 Fixed Fortnite not closing properly after launching a session through UEFN 🔸 Fixed crashes after repeated entity spawning and despawning 🔧 More Fixes: 🔹 Fixed quickbar and phone tool freezes 🔹 Fixed thumbnail capture preview actor issues 🔹 Fixed building on Instanced Static Meshes 🔹 Fixed Live Edit visual update issues 🔹 Fixed several editor crashes and performance issues 🔹 Fixed inventory UI not showing Fortnite item info correctly 🔹 Fixed multiple physics, movement, swimming, gliding, and launch pad issues 🔹 Fixed Scene Graph prefab and Verse path issues

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