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This free GitHub fork can get you to $5,000/month. Clones any voice for free, writes the script, makes the video. Zero API costs, zero camera. It's MoneyPrinterTurbo Extended - an enhanced fork of the repo that already prints faceless content on autopilot. This version closes the last paid gap:...

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39,712 görüntüleme • 1 ay önce •via X (Twitter)

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Big moment for text-to-speech. Qwen just open-sourced a text-to-speech model that lets you clone voices, design new ones, and control speech using natural language. Let me explain what I mean: You can literally tell it "speak in a cheerful tone with slight nervousness," and it actually does that. No complex audio engineering needed. What makes this special: - 3-second voice cloning - Covers 10 languages: English, German, French, and more - Latency as low as 97ms for real-time applications - Supports both streaming and non-streaming generation The model comes in two sizes (0.6B and 1.7B parameters), so you can pick based on your hardware and quality needs. Three modes to work with: 1. Custom Voice: Use pre-built premium voices with instruction-based style control 2. Voice Design: Describe the voice you want in plain English (or Chinese), and the model creates it 3. Voice Clone: Provide a 3-second reference audio and clone that voice The best part? It integrates with vLLM for production deployment and has a simple Python package you can pip install. I've shared a link to the GitHub repo in the next tweet.
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Big moment for text-to-speech. Qwen just open-sourced a text-to-speech model that lets you clone voices, design new ones, and control speech using natural language. Let me explain what I mean: You can literally tell it "speak in a cheerful tone with slight nervousness," and it actually does that. No complex audio engineering needed. What makes this special: - 3-second voice cloning - Covers 10 languages: English, German, French, and more - Latency as low as 97ms for real-time applications - Supports both streaming and non-streaming generation The model comes in two sizes (0.6B and 1.7B parameters), so you can pick based on your hardware and quality needs. Three modes to work with: 1. Custom Voice: Use pre-built premium voices with instruction-based style control 2. Voice Design: Describe the voice you want in plain English (or Chinese), and the model creates it 3. Voice Clone: Provide a 3-second reference audio and clone that voice The best part? It integrates with vLLM for production deployment and has a simple Python package you can pip install. I've shared a link to the GitHub repo in the next tweet.

Akshay 🚀

31,249 görüntüleme • 6 ay önce

Month 1: $0 Month 2: $0 Month 3: $205 Month 4: 50,532 This is what actually happens when you stop overthinking and start a faceless YouTube channel the right way. Most people quit in the first 60 days because they see zero results and assume it doesn’t work. But the ones who push through the first two months with consistency usually see their first real payout in month 3. Here’s the simple system that makes this possible: Step 1: Pick one proven niche (history, facts, motivation, or luxury) and stick to it. Step 2: Use AI to generate 30 video ideas in one sitting so you never run out of content. Step 3: Outsource or use AI to create the videos (script + voice + editing) so you can upload consistently without burning out. Step 4: Upload 3–5 videos per week and stay consistent for 90 days without checking analytics every day. The first two months are almost always quiet. The third month is where most people either quit or finally get paid. If you’re willing to be patient for 90 days, this model still works extremely well in 2026. Watch the full breakdown in the video.
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Month 1: $0 Month 2: $0 Month 3: $205 Month 4: 50,532 This is what actually happens when you stop overthinking and start a faceless YouTube channel the right way. Most people quit in the first 60 days because they see zero results and assume it doesn’t work. But the ones who push through the first two months with consistency usually see their first real payout in month 3. Here’s the simple system that makes this possible: Step 1: Pick one proven niche (history, facts, motivation, or luxury) and stick to it. Step 2: Use AI to generate 30 video ideas in one sitting so you never run out of content. Step 3: Outsource or use AI to create the videos (script + voice + editing) so you can upload consistently without burning out. Step 4: Upload 3–5 videos per week and stay consistent for 90 days without checking analytics every day. The first two months are almost always quiet. The third month is where most people either quit or finally get paid. If you’re willing to be patient for 90 days, this model still works extremely well in 2026. Watch the full breakdown in the video.

Frogify

45,734 görüntüleme • 1 ay önce

llama.cpp isn't just for text LLMs anymore. Pure C++ zero shot voice cloning just officially landed in mainline. Text generation was only step one. If you’re building autonomous local AI agents, real time voice assistants, or edge workflows, instant low latency audio is the missing piece. Thanks to PR #26254, Alibaba’s state of the art Qwen3 TTS model family is now natively supported directly inside the llama.cpp repository under the multimodal (mtmd) framework. No Python bloat. No massive PyTorch CUDA overhead. Just raw, hyper optimized C++ running GGUF voice weights. Here is why this native update is a massive deal for the open source local AI stack: # Multimodal Architecture (.gguf + mmproj) Qwen3-TTS splits the workload between the base language model backbone and a multimodal projection adapter. llama.cpp handles this using the llama-tts binary, mapping the text model alongside its --mmproj projector to process audio tokens seamlessly. # Zero Shot Voice Cloning in Seconds You don't need fine tuning or massive dataset training. Feed the C++ engine a single 5 to 10 second .wav audio sample using the --tts-speaker-file flag, and it accurately clones the exact timbre, tone, and accent on the fly. # Real World T4 GPU Benchmark & Resource FootprintRunning the 1.7B Base model in 8-bit quantization (Q8_0): - VRAM Footprint: ~7 GB peak VRAM during active zero-shot cloning. - Audio Quality: Studio grade, natural-sounding voice output in seconds. • - Execution: Direct execution via native compiled binaries or sub process calls. # Coming Next to llama-server (PR #26603) Beyond CLI execution, a native POST /tts HTTP endpoint is currently being added to llama-server, which will soon allow you to trigger voice generation directly via standard REST API requests! # quick note on Colab compilation: Because this code was merged into mainline very recently, pre-built third-party binaries haven't fully caught up yet. Compiling llama-tts directly from source on Google Colab's free CPU instance can take about 1 hour (or ~1-2 minutes if targeting single GPU arch like -DCMAKE_CUDA_ARCHITECTURES=75). Be patient during the build step, or compile it locally on your own rig for instant execution! To test this out yourself, I built a zero config Google Colab notebook that compiles llama.cpp, downloads the Q8_0 GGUF files from HuggingFace, and spins up an interactive Gradio Studio UI so you can record/upload 3 second clips and clone voices in real time. Stop sleeping on native C++ audio. The era of bulky Python audio pipelines is officially over. Links to the free Google Colab notebook and the official ggml org GGUF HuggingFace model repository are in the replies below! available in q4 and q8 both variants, 1 GB and 1.85 GBs respectively (requires additional ~500MB mmproj gguf) Are you building local voice agents yet? What does your current audio stack look like? Drop your setups below!
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llama.cpp isn't just for text LLMs anymore. Pure C++ zero shot voice cloning just officially landed in mainline. Text generation was only step one. If you’re building autonomous local AI agents, real time voice assistants, or edge workflows, instant low latency audio is the missing piece. Thanks to PR #26254, Alibaba’s state of the art Qwen3 TTS model family is now natively supported directly inside the llama.cpp repository under the multimodal (mtmd) framework. No Python bloat. No massive PyTorch CUDA overhead. Just raw, hyper optimized C++ running GGUF voice weights. Here is why this native update is a massive deal for the open source local AI stack: # Multimodal Architecture (.gguf + mmproj) Qwen3-TTS splits the workload between the base language model backbone and a multimodal projection adapter. llama.cpp handles this using the llama-tts binary, mapping the text model alongside its --mmproj projector to process audio tokens seamlessly. # Zero Shot Voice Cloning in Seconds You don't need fine tuning or massive dataset training. Feed the C++ engine a single 5 to 10 second .wav audio sample using the --tts-speaker-file flag, and it accurately clones the exact timbre, tone, and accent on the fly. # Real World T4 GPU Benchmark & Resource FootprintRunning the 1.7B Base model in 8-bit quantization (Q8_0): - VRAM Footprint: ~7 GB peak VRAM during active zero-shot cloning. - Audio Quality: Studio grade, natural-sounding voice output in seconds. • - Execution: Direct execution via native compiled binaries or sub process calls. # Coming Next to llama-server (PR #26603) Beyond CLI execution, a native POST /tts HTTP endpoint is currently being added to llama-server, which will soon allow you to trigger voice generation directly via standard REST API requests! # quick note on Colab compilation: Because this code was merged into mainline very recently, pre-built third-party binaries haven't fully caught up yet. Compiling llama-tts directly from source on Google Colab's free CPU instance can take about 1 hour (or ~1-2 minutes if targeting single GPU arch like -DCMAKE_CUDA_ARCHITECTURES=75). Be patient during the build step, or compile it locally on your own rig for instant execution! To test this out yourself, I built a zero config Google Colab notebook that compiles llama.cpp, downloads the Q8_0 GGUF files from HuggingFace, and spins up an interactive Gradio Studio UI so you can record/upload 3 second clips and clone voices in real time. Stop sleeping on native C++ audio. The era of bulky Python audio pipelines is officially over. Links to the free Google Colab notebook and the official ggml org GGUF HuggingFace model repository are in the replies below! available in q4 and q8 both variants, 1 GB and 1.85 GBs respectively (requires additional ~500MB mmproj gguf) Are you building local voice agents yet? What does your current audio stack look like? Drop your setups below!

Alok

47,881 görüntüleme • 5 gün önce

🚨 JUST IN: THIS FREE TOOL JUST REPLACED FOUR AI IMAGE AND VIDEO SUBSCRIPTIONS AT ONCE. Midjourney. Krea. Higgsfield. Openart. One repo. 200+ models. Zero dollars a month. Here is what it actually does. It is a full image and video studio that runs in your browser or as a desktop app. Text to image, image to image, text to video, image to video, lip sync, cinema mode with real camera controls. All of it. 4,500 people already starred this. What you get for free: → 50+ image models including Flux, Midjourney v7, Ideogram, GPT-4o, Seedream → 60+ video models including Kling, Sora, Veo, Runway, Wan, Hailuo → lip sync studio with 9 dedicated models. upload a portrait and audio and it talks → cinema studio with real camera controls. lens, focal length, aperture, film stock → feed up to 14 reference images into one generation → self-hosted. your data never leaves your machine The crazy part is there is also a hosted version that needs zero setup. Just open the link and start generating. Now the math. Midjourney Standard: $30/month Krea AI Pro: $30/month Higgsfield Plus: $49/month Openart AI: $15/month That is $124 a month. $1,488 a year. This repo does everything all four do. With more models than any of them. For free. Forever. No subscription. No vendor lock-in. MIT licensed. Download it in one click on Mac or Windows. Someone should have told me about this sooner. I feel like an idiot. ( save this )
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🚨 JUST IN: THIS FREE TOOL JUST REPLACED FOUR AI IMAGE AND VIDEO SUBSCRIPTIONS AT ONCE. Midjourney. Krea. Higgsfield. Openart. One repo. 200+ models. Zero dollars a month. Here is what it actually does. It is a full image and video studio that runs in your browser or as a desktop app. Text to image, image to image, text to video, image to video, lip sync, cinema mode with real camera controls. All of it. 4,500 people already starred this. What you get for free: → 50+ image models including Flux, Midjourney v7, Ideogram, GPT-4o, Seedream → 60+ video models including Kling, Sora, Veo, Runway, Wan, Hailuo → lip sync studio with 9 dedicated models. upload a portrait and audio and it talks → cinema studio with real camera controls. lens, focal length, aperture, film stock → feed up to 14 reference images into one generation → self-hosted. your data never leaves your machine The crazy part is there is also a hosted version that needs zero setup. Just open the link and start generating. Now the math. Midjourney Standard: $30/month Krea AI Pro: $30/month Higgsfield Plus: $49/month Openart AI: $15/month That is $124 a month. $1,488 a year. This repo does everything all four do. With more models than any of them. For free. Forever. No subscription. No vendor lock-in. MIT licensed. Download it in one click on Mac or Windows. Someone should have told me about this sooner. I feel like an idiot. ( save this )

Kanika

14,760 görüntüleme • 3 ay önce

you can run claude code inside antigravity completely Free with zero credit card and no rate limits 😳 use openrouter’s free models + antigravity. no anthropic bill. no paid api keys. takes 10 minutes to set up. what you get during this setup: - full claude code agent experience - strong coding models (including deepseek-r1, qwen2.5-coder, llama-4, grok-4 free tier) - antigravity’s clean workspace and sandbox - unlimited usage (as long as you stay on free models) - easy model swapping - zero cost full setup guide (100% free): step 1: install antigravity -go to and install it -create a new workspace step 2: install claude code - inside antigravity, install the claude code extension from the marketplace - open the built-in terminal step 3: create openrouter free account -go to - sign up with google (no card needed) - go to keys and create a new api key step 4: set the environment variables -in antigravity terminal run: export ANTHROPIC_API_KEY=sk-or-xxx export OPENROUTER_API_KEY=sk-or-xxx step 5: launch claude code with free model -run this command: claude-code --model deepseek/deepseek-r1:free or try: qwen/qwen2.5-coder:free if you already have antigravity? skip straight to step 2. after 10 minutes you’ll have a full agentic coding setup running for free. this is currently one of the cheapest ways to run serious coding agents in 2026. bookmark this before they limit the free models.
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you can run claude code inside antigravity completely Free with zero credit card and no rate limits 😳 use openrouter’s free models + antigravity. no anthropic bill. no paid api keys. takes 10 minutes to set up. what you get during this setup: - full claude code agent experience - strong coding models (including deepseek-r1, qwen2.5-coder, llama-4, grok-4 free tier) - antigravity’s clean workspace and sandbox - unlimited usage (as long as you stay on free models) - easy model swapping - zero cost full setup guide (100% free): step 1: install antigravity -go to and install it -create a new workspace step 2: install claude code - inside antigravity, install the claude code extension from the marketplace - open the built-in terminal step 3: create openrouter free account -go to - sign up with google (no card needed) - go to keys and create a new api key step 4: set the environment variables -in antigravity terminal run: export ANTHROPIC_API_KEY=sk-or-xxx export OPENROUTER_API_KEY=sk-or-xxx step 5: launch claude code with free model -run this command: claude-code --model deepseek/deepseek-r1:free or try: qwen/qwen2.5-coder:free if you already have antigravity? skip straight to step 2. after 10 minutes you’ll have a full agentic coding setup running for free. this is currently one of the cheapest ways to run serious coding agents in 2026. bookmark this before they limit the free models.

painn

32,057 görüntüleme • 2 ay önce

1.7 billion free tokens per month. A month ago i showed you how to route claude code through free providers. someone just shipped the cleanest version of this setup yet… it's called Freellmapi 13,400+ stars on github, MIT licensed, takes 2 minutes to install. what it does: stacks the free tiers of 16 different LLM providers behind one local API. point claude code, codex, or cursor at that one endpoint, and it automatically routes your calls across all 16 free pools. The 16 providers it covers: Google, Groq, Cerebras, Mistral, OpenRouter, GitHub Models, Cloudflare, Cohere, NVIDIA, HuggingFace, Ollama Cloud, Kilo, Pollinations, LLM7, OVH, and OpenCode Zen. if you sign up to all 16 and add your free API keys, you get roughly 1.7 billion free tokens per month combined. ▫️ How to install (one command) curl -fsSL bash this runs the whole thing locally on your machine through Docker. once it's up, open paste your provider keys on the Keys page, and grab the unified API key from the dashboard. that's the key you point your apps at. With this, claude code stops hitting your monthly cap because every prompt routes through the 16 free pools instead of your paid plan. and if one provider rate-limits mid-conversation, freellmapi falls over to the next one automatically so your session never breaks. repo: Free, MIT-licensed, runs on your laptop or a $5 VPS.
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1.7 billion free tokens per month. A month ago i showed you how to route claude code through free providers. someone just shipped the cleanest version of this setup yet… it's called Freellmapi 13,400+ stars on github, MIT licensed, takes 2 minutes to install. what it does: stacks the free tiers of 16 different LLM providers behind one local API. point claude code, codex, or cursor at that one endpoint, and it automatically routes your calls across all 16 free pools. The 16 providers it covers: Google, Groq, Cerebras, Mistral, OpenRouter, GitHub Models, Cloudflare, Cohere, NVIDIA, HuggingFace, Ollama Cloud, Kilo, Pollinations, LLM7, OVH, and OpenCode Zen. if you sign up to all 16 and add your free API keys, you get roughly 1.7 billion free tokens per month combined. ▫️ How to install (one command) curl -fsSL bash this runs the whole thing locally on your machine through Docker. once it's up, open paste your provider keys on the Keys page, and grab the unified API key from the dashboard. that's the key you point your apps at. With this, claude code stops hitting your monthly cap because every prompt routes through the 16 free pools instead of your paid plan. and if one provider rate-limits mid-conversation, freellmapi falls over to the next one automatically so your session never breaks. repo: Free, MIT-licensed, runs on your laptop or a $5 VPS.

Axel Bitblaze 🪓

47,734 görüntüleme • 1 ay önce

I just turned one UGC ad into 5 different languages in 20 minutes 🤯 This workflow is insane: Take any winning UGC ad... Clone the creator's voice... Translate it to any language... And lip sync so it looks like they actually speak it. Perfect for e-comm brands & agencies scaling ads into new markets without reshooting anything. Say you've got a winning ad in English. You want to run it in Germany, France, Spain, Japan—wherever. But that means hiring new creators, re-filming the same script, hoping the energy matches the original. Or running the English ad and hoping people don't care. (They do.) ElevenLabs handles all of it: → Upload your original video → Clone the creator's voice instantly → Translate to any target language → AI generates the dubbed audio in their voice → Lip sync warps their mouth to match the new language perfectly Same creator. Same energy. Completely different language. What this unlocks: - One winning UGC ad → every market you want to test - No reshooting for localization - No hiring native-speaking creators per country - Lip sync that actually looks real I recorded a 12-minute Loom walking through exactly how to do this step-by-step inside ElevenLabs. > Comment "LABS" > Like this post And I'll send it over (must be following so I can DM)
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I just turned one UGC ad into 5 different languages in 20 minutes 🤯 This workflow is insane: Take any winning UGC ad... Clone the creator's voice... Translate it to any language... And lip sync so it looks like they actually speak it. Perfect for e-comm brands & agencies scaling ads into new markets without reshooting anything. Say you've got a winning ad in English. You want to run it in Germany, France, Spain, Japan—wherever. But that means hiring new creators, re-filming the same script, hoping the energy matches the original. Or running the English ad and hoping people don't care. (They do.) ElevenLabs handles all of it: → Upload your original video → Clone the creator's voice instantly → Translate to any target language → AI generates the dubbed audio in their voice → Lip sync warps their mouth to match the new language perfectly Same creator. Same energy. Completely different language. What this unlocks: - One winning UGC ad → every market you want to test - No reshooting for localization - No hiring native-speaking creators per country - Lip sync that actually looks real I recorded a 12-minute Loom walking through exactly how to do this step-by-step inside ElevenLabs. > Comment "LABS" > Like this post And I'll send it over (must be following so I can DM)

Mike Futia

11,130 görüntüleme • 7 ay önce

Claude Opus 5 x NexLev MCP might be the most unfair combo for building faceless YouTube channels right now So I’m giving away the FULL AI Story channel production system behind it Here’s EVERYTHING that you’ll get inside: → The exact Claude setup that turns Opus 5 into a full faceless YouTube production operator. → NexLev MCP niche validation prompts that find new channels getting 100k+ views without guessing niches manually. → 48-hour velocity check prompt to spot which AI Story angles are actually moving right now. → RPM filtering system so you avoid low-value niches and only build around $12-$20+ RPM opportunities. → Opus 5 JSON script framework for 8,000+ word videos with locked characters, pacing rules, emotional beats, and cliffhangers. → Documentary research brief prompt that verifies dates, names, timelines, and quotes before the script gets written. → ElevenLabs MCP voiceover workflow with narrator matching by niche so the voice fits the audience instead of sounding random. → Higgsfield MCP visual system using Seedance 2.0, Flux 2, and Nano Banana Pro to create animated intros, scene images, and consistent characters. → Thumbnail prompt structure for ChatGPT Image 2.0 so the final video has clean text, high emotion, and a clickable 1280x720 layout. → Full assembly checklist for taking the script, voiceover, animated clips, captions, and thumbnail into an upload-ready video in under 30 minutes. All built from the AI YouTube production playbooks used across: → 120+ Elevate members → $12k/mo average per student → 800M+ total views across the system Like + comment "CLAUDE" and I’ll send you the whole thing (Must be following so I can DM)
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Claude Opus 5 x NexLev MCP might be the most unfair combo for building faceless YouTube channels right now So I’m giving away the FULL AI Story channel production system behind it Here’s EVERYTHING that you’ll get inside: → The exact Claude setup that turns Opus 5 into a full faceless YouTube production operator. → NexLev MCP niche validation prompts that find new channels getting 100k+ views without guessing niches manually. → 48-hour velocity check prompt to spot which AI Story angles are actually moving right now. → RPM filtering system so you avoid low-value niches and only build around $12-$20+ RPM opportunities. → Opus 5 JSON script framework for 8,000+ word videos with locked characters, pacing rules, emotional beats, and cliffhangers. → Documentary research brief prompt that verifies dates, names, timelines, and quotes before the script gets written. → ElevenLabs MCP voiceover workflow with narrator matching by niche so the voice fits the audience instead of sounding random. → Higgsfield MCP visual system using Seedance 2.0, Flux 2, and Nano Banana Pro to create animated intros, scene images, and consistent characters. → Thumbnail prompt structure for ChatGPT Image 2.0 so the final video has clean text, high emotion, and a clickable 1280x720 layout. → Full assembly checklist for taking the script, voiceover, animated clips, captions, and thumbnail into an upload-ready video in under 30 minutes. All built from the AI YouTube production playbooks used across: → 120+ Elevate members → $12k/mo average per student → 800M+ total views across the system Like + comment "CLAUDE" and I’ll send you the whole thing (Must be following so I can DM)

gold.

21,510 görüntüleme • 13 gün önce

Your baby knows your voice, even before they enter the world. As the senses activate between 24-26 weeks of gestation, the tone of our own mothers’ voice is one of the very first things we experience as humans (second only to her heartbeat, most likely). And a whole host of research (which you’ll be able to learn about in my next book, Wonderment) documents their recognition of - and preference for - mom’s voice while still in utero. But my favorite study on this topic measured this preference in the days immediately following birth. Using a specially rigged electronic pacifier, researchers established a baseline rate of sucking for each participating infant… then they inserted a new variable. When the newborns began sucking faster than their baseline, a recording of their own mother’s voice (reading a story) was activated. If they began to suck more slowly, a stranger’s voice would read the same passages. 80% of the children in the study successfully modified their behavior to hear their own mother’s voice. The next day these kids were brought back to try again, only this time the situation was reversed. This time to hear their mother they had to suck more slowly. And after some experimentation, 100% successfully modified their behaviors to privilege the sweetest sound they knew: their own mom’s voice. I loved this video from the Leslie Rodriguez on IG that shows baby’s response at 3 weeks. Rest assured she knew and loved your voice even before you met!
0:19

Your baby knows your voice, even before they enter the world. As the senses activate between 24-26 weeks of gestation, the tone of our own mothers’ voice is one of the very first things we experience as humans (second only to her heartbeat, most likely). And a whole host of research (which you’ll be able to learn about in my next book, Wonderment) documents their recognition of - and preference for - mom’s voice while still in utero. But my favorite study on this topic measured this preference in the days immediately following birth. Using a specially rigged electronic pacifier, researchers established a baseline rate of sucking for each participating infant… then they inserted a new variable. When the newborns began sucking faster than their baseline, a recording of their own mother’s voice (reading a story) was activated. If they began to suck more slowly, a stranger’s voice would read the same passages. 80% of the children in the study successfully modified their behavior to hear their own mother’s voice. The next day these kids were brought back to try again, only this time the situation was reversed. This time to hear their mother they had to suck more slowly. And after some experimentation, 100% successfully modified their behaviors to privilege the sweetest sound they knew: their own mom’s voice. I loved this video from the Leslie Rodriguez on IG that shows baby’s response at 3 weeks. Rest assured she knew and loved your voice even before you met!

Dan Wuori

282,635 görüntüleme • 1 yıl önce

BREAKING: Claude + Arcads can now run your entire ecom brand tiktok like a $500/hour social media manager. I reverse-engineered how top social media brands use AI to build million-follower accounts. Here’s the crazy part: This system produces 550+ cinematic, product-ready ads per day from a single prompt. Here’s the full pipeline: → AI generates a realistic UGC persona — face, voice, personality → Arcads clones a natural voiceover in seconds → CapCut auto-edits: captions, pacing, hooks — done → our phone farm method pushes every finished video straight to TikTok Shop → Cruva Social 1 identifies which hooks are already winning in your niche before you film anything The result: 500+ videos a month, per brand, at a fraction of what one UGC creator used to cost. Most brands are still paying $300–500 per video. Testing 10 hooks takes $5,000 and three weeks. With this system, you test 100 hooks in the same timeframe. The ones that win get scaled. Automatically. AI is the new creative director. TikTok doesn’t reward the best video. It rewards the brand that shows up the most — with content that converts. Static agencies are dead. Creator dependency is a liability… and it’s soooo 2025. No more waiting on creators. No more $500 videos that flop after 200 views. The brands that automate content at scale will be the biggest winners of 2026. If you want the full breakdown: Like & comment “SYSTEM” I’ll send you the complete workflow, every prompt, and a step-by-step walkthrough. Free. (Follow first so I can DM.)
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BREAKING: Claude + Arcads can now run your entire ecom brand tiktok like a $500/hour social media manager. I reverse-engineered how top social media brands use AI to build million-follower accounts. Here’s the crazy part: This system produces 550+ cinematic, product-ready ads per day from a single prompt. Here’s the full pipeline: → AI generates a realistic UGC persona — face, voice, personality → Arcads clones a natural voiceover in seconds → CapCut auto-edits: captions, pacing, hooks — done → our phone farm method pushes every finished video straight to TikTok Shop → Cruva Social 1 identifies which hooks are already winning in your niche before you film anything The result: 500+ videos a month, per brand, at a fraction of what one UGC creator used to cost. Most brands are still paying $300–500 per video. Testing 10 hooks takes $5,000 and three weeks. With this system, you test 100 hooks in the same timeframe. The ones that win get scaled. Automatically. AI is the new creative director. TikTok doesn’t reward the best video. It rewards the brand that shows up the most — with content that converts. Static agencies are dead. Creator dependency is a liability… and it’s soooo 2025. No more waiting on creators. No more $500 videos that flop after 200 views. The brands that automate content at scale will be the biggest winners of 2026. If you want the full breakdown: Like & comment “SYSTEM” I’ll send you the complete workflow, every prompt, and a step-by-step walkthrough. Free. (Follow first so I can DM.)

Noah Frydberg | Tiktok Shop For Brands

18,101 görüntüleme • 3 ay önce

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.
0:14

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.

Akshay 🚀

52,426 görüntüleme • 5 ay önce

I just vibe-coded a Shopify Reviews Scraper that swipes all your competitors' customer reviews instantly. 🤯 Paste any competitor's product URL → pull every review in under 30 seconds → export to CSV. Built 100% in Codex. Perfect for brands and agencies who want to mine competitor voice-of-customer data at scale and turn it into winning ad creative. Here's how it works: → Drop a Shopify product URL into the tool → Set your review limit (50, 100, 500+) → Hit scrape — it launches a browser, finds the review widget, pulls every review → Export clean rows: rating, body, author, date → Feed the CSV to Claude and ask "what do customers love and hate about this product" → Turn the output into ad angles, hooks, and headlines No more paying $99/mo for clunky review scraping SaaS that locks you behind credits. What you get: - Any Shopify store's reviews in 30 seconds - Clean structured data (rating, body, author, date) - CSV or JSON export — drops straight into Sheets or an LLM - Unlimited scrapes, no per-review fees - A voice-of-customer firehose you can turn into ad creative on demand This is essentially a competitor review intelligence engine in a box. I'm giving away the full GitHub repo so you can clone it and run it yourself for free. Want the repo? > Like this post > Comment "SCRAPE" And I'll send it over (must be following so I can DM)
0:14

I just vibe-coded a Shopify Reviews Scraper that swipes all your competitors' customer reviews instantly. 🤯 Paste any competitor's product URL → pull every review in under 30 seconds → export to CSV. Built 100% in Codex. Perfect for brands and agencies who want to mine competitor voice-of-customer data at scale and turn it into winning ad creative. Here's how it works: → Drop a Shopify product URL into the tool → Set your review limit (50, 100, 500+) → Hit scrape — it launches a browser, finds the review widget, pulls every review → Export clean rows: rating, body, author, date → Feed the CSV to Claude and ask "what do customers love and hate about this product" → Turn the output into ad angles, hooks, and headlines No more paying $99/mo for clunky review scraping SaaS that locks you behind credits. What you get: - Any Shopify store's reviews in 30 seconds - Clean structured data (rating, body, author, date) - CSV or JSON export — drops straight into Sheets or an LLM - Unlimited scrapes, no per-review fees - A voice-of-customer firehose you can turn into ad creative on demand This is essentially a competitor review intelligence engine in a box. I'm giving away the full GitHub repo so you can clone it and run it yourself for free. Want the repo? > Like this post > Comment "SCRAPE" And I'll send it over (must be following so I can DM)

Mike Futia

29,845 görüntüleme • 2 ay önce

This guy built an AI pipeline that generates hyperrealistic fashion models in 47 minutes and now dropshippers pay him $1,400 to clone the entire system. He got tired of watching e-com brands lose $8K per photoshoot when a single product angle changed so he built a 9-node workflow that generates 127 product videos from one Pinterest photo without hiring a single model. Here's the exact breakdown: → Claude writes a 34-parameter JSON brand DNA before any image is touched target psychographics, price anchor, vibe matrix, anti-inspiration blacklist → Pinterest becomes the model source library but you can't just download and animate → Kling 2.6 takes that static JPG and turns it into 5-second video but only after the prompt architecture is locked → Negative prompt node runs 41 exclusion terms: no plastic skin, no CGI glow, no symmetry artifacts, no doll face, no synthetic lighting → That one step kills the "AI look" that tanks engagement by 67% in the first 3 seconds → TikTok Studio uploads 19 videos in one batch with zero manual captioning because the brand voice was pre-programmed in step one → Atlas scrapes Amazon product links and auto-generates a Shopify store with hero images, pricing tiers, scarcity copy, and mobile-optimized checkout in 90 seconds → The store goes live before the first TikTok video finishes processing The key move 94% of people skip: you can't animate the photo before you inject the negative prompt. If you send a raw Pinterest image straight into image-to-video the face morphs into a wax figure. The fabric loses texture. The hands grow extra fingers. The whole thing screams "AI" and your CTR dies. His system runs the exclusion filter first so the model moves like she's shot on an iPhone 15 Pro in natural light. One brand hit 2.6M views on TikTok in 11 days with zero paid ads and converted at 3.7% because the videos looked like organic UGC not polished studio content. Brands now pay him $1,400 for the full pipeline setup + $340/month to keep the store synced with new product drops and seasonal video batches. The entire system runs on $23/month in API costs and one laptop. No photographer. No model agency. No product samples. Just a prompt template, a Pinterest account, and the discipline to filter out the AI artifacts before you render movement.
0:10

This guy built an AI pipeline that generates hyperrealistic fashion models in 47 minutes and now dropshippers pay him $1,400 to clone the entire system. He got tired of watching e-com brands lose $8K per photoshoot when a single product angle changed so he built a 9-node workflow that generates 127 product videos from one Pinterest photo without hiring a single model. Here's the exact breakdown: → Claude writes a 34-parameter JSON brand DNA before any image is touched target psychographics, price anchor, vibe matrix, anti-inspiration blacklist → Pinterest becomes the model source library but you can't just download and animate → Kling 2.6 takes that static JPG and turns it into 5-second video but only after the prompt architecture is locked → Negative prompt node runs 41 exclusion terms: no plastic skin, no CGI glow, no symmetry artifacts, no doll face, no synthetic lighting → That one step kills the "AI look" that tanks engagement by 67% in the first 3 seconds → TikTok Studio uploads 19 videos in one batch with zero manual captioning because the brand voice was pre-programmed in step one → Atlas scrapes Amazon product links and auto-generates a Shopify store with hero images, pricing tiers, scarcity copy, and mobile-optimized checkout in 90 seconds → The store goes live before the first TikTok video finishes processing The key move 94% of people skip: you can't animate the photo before you inject the negative prompt. If you send a raw Pinterest image straight into image-to-video the face morphs into a wax figure. The fabric loses texture. The hands grow extra fingers. The whole thing screams "AI" and your CTR dies. His system runs the exclusion filter first so the model moves like she's shot on an iPhone 15 Pro in natural light. One brand hit 2.6M views on TikTok in 11 days with zero paid ads and converted at 3.7% because the videos looked like organic UGC not polished studio content. Brands now pay him $1,400 for the full pipeline setup + $340/month to keep the store synced with new product drops and seasonal video batches. The entire system runs on $23/month in API costs and one laptop. No photographer. No model agency. No product samples. Just a prompt template, a Pinterest account, and the discipline to filter out the AI artifacts before you render movement.

Shade

536,735 görüntüleme • 2 ay önce

The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.
0:24

The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.

Oren Melamed

29,555 görüntüleme • 6 ay önce

Anni is the founder of bottom-up policymaking in Maldives. Before democracy, everything was decided by the president and handed down to the people from the top. But Anni changed that. He taught the people that they themselves should decide their own future. This is the kind of leader he is. A few days after he and Faya shared new ideas at the Bodu Badhalu press conference, Anni and Faya are out meeting ordinary people. He sits with them, listens carefully to their thoughts and opinions on those ideas, and writes everything down. In this video, you can see an elderly man suggesting a special assembly for big changes and Anni notes it down too. Anni truly believes the people should have a voice in shaping the country’s future. That is what makes him a great leader. #RestoreMDP
0:14

Anni is the founder of bottom-up policymaking in Maldives. Before democracy, everything was decided by the president and handed down to the people from the top. But Anni changed that. He taught the people that they themselves should decide their own future. This is the kind of leader he is. A few days after he and Faya shared new ideas at the Bodu Badhalu press conference, Anni and Faya are out meeting ordinary people. He sits with them, listens carefully to their thoughts and opinions on those ideas, and writes everything down. In this video, you can see an elderly man suggesting a special assembly for big changes and Anni notes it down too. Anni truly believes the people should have a voice in shaping the country’s future. That is what makes him a great leader. #RestoreMDP

Hassan Kurusee

53,293 görüntüleme • 3 ay önce

BREAKING footage from Tijuana Mexico (Happening now)! The third group of illegals are bring brought in by Joe Biden and the Democrats under the CVP1 app. Everyone you see walking up the ramp is part of it. They had a group the same size at 5 AM and another group the same size at 8 AM and it happens every day! This was the eighth stop on our Mexican border tour and every single CVP1 port is active, but San Ysidro is the worst! No wonder San Diego City Council voted to become a “super sanctuary city” that will no longer allow law-enforcement to work with ICE. They are the city profiting most off of this invasion with every single one of the illegals receiving federal grants. San Diego and every other sanctuary supporting community needs to be defunded on day one and any politician that gets in the way of ICE doing their job needs to be prosecuted immediately! *Stay tuned for the rest of @Oscarelblue’s and my reports, showing you the truth the mainstream media and the traitors in Washington don’t want you to see! Law & Border - Real America’s Voice News Real America's Voice (RAV)
0:18

BREAKING footage from Tijuana Mexico (Happening now)! The third group of illegals are bring brought in by Joe Biden and the Democrats under the CVP1 app. Everyone you see walking up the ramp is part of it. They had a group the same size at 5 AM and another group the same size at 8 AM and it happens every day! This was the eighth stop on our Mexican border tour and every single CVP1 port is active, but San Ysidro is the worst! No wonder San Diego City Council voted to become a “super sanctuary city” that will no longer allow law-enforcement to work with ICE. They are the city profiting most off of this invasion with every single one of the illegals receiving federal grants. San Diego and every other sanctuary supporting community needs to be defunded on day one and any politician that gets in the way of ICE doing their job needs to be prosecuted immediately! *Stay tuned for the rest of @Oscarelblue’s and my reports, showing you the truth the mainstream media and the traitors in Washington don’t want you to see! Law & Border - Real America’s Voice News Real America's Voice (RAV)

Ben Bergquam - Real America’s Voice (RAV-TV) News

3,095,240 görüntüleme • 1 yıl önce

A 30-year-old Chinese man turned himself into an AI girl, and the result will shock you He built a $3,700/month Fanvue business in his bedroom He didn't use wigs or cosplay. He used AI to build a completely new identity on top of his own footage Same room, same camera, but a totally different creator on screen His workflow is stupidly simple: Claude designs the character, ComfyUI generates the face, and Kling turns stills into viral reels In his first month, he barely cleared $320. But in the second month, one video hit 500,000 views Money started rolling in: he gained 50 paid Fanvue subscribers before any real automation even started The secret weapon? A custom Claude system that analyzes chat data, optimizes pricing, and drafts replies to fans in the girl's voice He only spends 30 minutes a day scheduling reels and running the machine This is no longer content creation. It is identity arbitrage The full workflow and tools he used are available in the article
0:11

A 30-year-old Chinese man turned himself into an AI girl, and the result will shock you He built a $3,700/month Fanvue business in his bedroom He didn't use wigs or cosplay. He used AI to build a completely new identity on top of his own footage Same room, same camera, but a totally different creator on screen His workflow is stupidly simple: Claude designs the character, ComfyUI generates the face, and Kling turns stills into viral reels In his first month, he barely cleared $320. But in the second month, one video hit 500,000 views Money started rolling in: he gained 50 paid Fanvue subscribers before any real automation even started The secret weapon? A custom Claude system that analyzes chat data, optimizes pricing, and drafts replies to fans in the girl's voice He only spends 30 minutes a day scheduling reels and running the machine This is no longer content creation. It is identity arbitrage The full workflow and tools he used are available in the article

shmidt

105,533 görüntüleme • 1 ay önce

🚨 NOW YOU RUN A COMPANY WITH ZERO EMPLOYEES Paperclip is a 100% open-source framework (70k+ stars) that makes this possible. Rather than just prompting a model, you hire a CEO, engineers, and a QA reviewer. Every worker is an AI agent, and Paperclip is the Node.js and React control plane that keeps them aligned. Stop chaining messy scripts together and build a living organization: → Stand up a CEO agent to set strategy → Hire engineers and designers via Claude or Codex → Build in an automated QA loop before any ticket closes → Manage the entire portfolio from your phone When an agent slips, you do not rewrite your whole pipeline: you just correct its persona prompt, exactly like coaching a junior hire. It is exactly the kind of tooling the space needs right now. Free, open-source, and self-hosted. Repo link in 🧵↓
0:17

🚨 NOW YOU RUN A COMPANY WITH ZERO EMPLOYEES Paperclip is a 100% open-source framework (70k+ stars) that makes this possible. Rather than just prompting a model, you hire a CEO, engineers, and a QA reviewer. Every worker is an AI agent, and Paperclip is the Node.js and React control plane that keeps them aligned. Stop chaining messy scripts together and build a living organization: → Stand up a CEO agent to set strategy → Hire engineers and designers via Claude or Codex → Build in an automated QA loop before any ticket closes → Manage the entire portfolio from your phone When an agent slips, you do not rewrite your whole pipeline: you just correct its persona prompt, exactly like coaching a junior hire. It is exactly the kind of tooling the space needs right now. Free, open-source, and self-hosted. Repo link in 🧵↓

Charly Wargnier

37,174 görüntüleme • 1 ay önce

20 days ago, I connected Claude Code to my newly created instagram handle.. I gained 4.3M views and 6500+ followers in less than a month [ i post Ai generated animated stories ] Full workflow: i let claude study my account before i write another reel.. This is the cleanest content workflow i've built on claude. give it your IG first. 4 prompts handle the rest.. niche research, the reel script, the hook, and the daily automation.. the whole loop is basically, give claude your IG → find what's working → write retention-optimized scripts → engineer the hook → automate the daily output.. ▫️ Setup: give claude your instagram open claude code. claude code has a built-in web tool that browses any public URL. or install any agentic browser like Browser Harness or Firecrawl or Comet browser paste this with your handle filled in: "Browse and pull the last 30 reels and posts. Analyze my recurring topics, top-performing hooks, formats, and engagement patterns. Then map out my actual audience and what they consistently respond to." claude reads your profile, pulls every reel down, and now has the context to personalize every prompt below to YOUR account, not a generic niche. if you're on claude desktop, the same works with firecrawl MCP connected. ▫️ Prompt 1 find what actually goes viral in your niche: "Analyze the highest-performing Instagram Reels, TikToks, and Reddit posts in the [niche] niche from the last 30 days. Identify repeating hooks, visual styles, emotional triggers, and content formats that consistently generate high engagement. Then summarize the 5 strongest content angles optimized for AI-generated content and short-form videos." run this after the setup. you get 5 angles backed by what's already working in your niche, cross-checked against what's already working on YOUR account. ▫️ Prompt 2 write a high-retention reel script "Write a short-form Instagram Reel script about [topic] with an aggressive hook in the first 2 seconds. Create immediate curiosity, tension, or controversy to stop scrolling, then deliver a fast and satisfying payoff. Keep it under 30 seconds and optimize the structure for watch time, replays, comments, and shares. Finish with a subtle CTA." the line that matters: "optimize the structure for watch time, replays, comments, and shares." claude writes for the metrics, not just the word count. ▫️ Prompt 3 engineer better hooks "Study the top-performing Reels in [niche] and break down the hook structure, pacing, and emotional triggers used in the first 3 seconds. Then generate 5 new hook variations that are even more curiosity-driven, emotionally charged, and optimized to stop scrolling instantly. Focus on triggers like surprise, fear, ego, urgency, or desire." most reels die in the first 2 seconds. this prompt has claude reverse-engineer what already works, then give you 5 sharper versions to swap in. ▫️ Prompt 4 automate the whole workflow "Build a complete AI-powered content workflow for Instagram in the [niche] niche. The system should identify trending topics daily, generate high-retention scripts, create matching AI visuals, turn them into short-form videos, and generate optimized captions and hashtags. Structure everything as a repeatable workflow designed for consistent daily posting and growth." once the niche and script structure are validated, this turns it into a daily loop. one prompt that handles topic → script → visual → video → caption. these 4 prompts are the building blocks. the setup is what makes them yours. your real value is in the [niche] you plug in. content workflow built in one weekend, daily posting on autopilot from monday.
0:12

20 days ago, I connected Claude Code to my newly created instagram handle.. I gained 4.3M views and 6500+ followers in less than a month [ i post Ai generated animated stories ] Full workflow: i let claude study my account before i write another reel.. This is the cleanest content workflow i've built on claude. give it your IG first. 4 prompts handle the rest.. niche research, the reel script, the hook, and the daily automation.. the whole loop is basically, give claude your IG → find what's working → write retention-optimized scripts → engineer the hook → automate the daily output.. ▫️ Setup: give claude your instagram open claude code. claude code has a built-in web tool that browses any public URL. or install any agentic browser like Browser Harness or Firecrawl or Comet browser paste this with your handle filled in: "Browse and pull the last 30 reels and posts. Analyze my recurring topics, top-performing hooks, formats, and engagement patterns. Then map out my actual audience and what they consistently respond to." claude reads your profile, pulls every reel down, and now has the context to personalize every prompt below to YOUR account, not a generic niche. if you're on claude desktop, the same works with firecrawl MCP connected. ▫️ Prompt 1 find what actually goes viral in your niche: "Analyze the highest-performing Instagram Reels, TikToks, and Reddit posts in the [niche] niche from the last 30 days. Identify repeating hooks, visual styles, emotional triggers, and content formats that consistently generate high engagement. Then summarize the 5 strongest content angles optimized for AI-generated content and short-form videos." run this after the setup. you get 5 angles backed by what's already working in your niche, cross-checked against what's already working on YOUR account. ▫️ Prompt 2 write a high-retention reel script "Write a short-form Instagram Reel script about [topic] with an aggressive hook in the first 2 seconds. Create immediate curiosity, tension, or controversy to stop scrolling, then deliver a fast and satisfying payoff. Keep it under 30 seconds and optimize the structure for watch time, replays, comments, and shares. Finish with a subtle CTA." the line that matters: "optimize the structure for watch time, replays, comments, and shares." claude writes for the metrics, not just the word count. ▫️ Prompt 3 engineer better hooks "Study the top-performing Reels in [niche] and break down the hook structure, pacing, and emotional triggers used in the first 3 seconds. Then generate 5 new hook variations that are even more curiosity-driven, emotionally charged, and optimized to stop scrolling instantly. Focus on triggers like surprise, fear, ego, urgency, or desire." most reels die in the first 2 seconds. this prompt has claude reverse-engineer what already works, then give you 5 sharper versions to swap in. ▫️ Prompt 4 automate the whole workflow "Build a complete AI-powered content workflow for Instagram in the [niche] niche. The system should identify trending topics daily, generate high-retention scripts, create matching AI visuals, turn them into short-form videos, and generate optimized captions and hashtags. Structure everything as a repeatable workflow designed for consistent daily posting and growth." once the niche and script structure are validated, this turns it into a daily loop. one prompt that handles topic → script → visual → video → caption. these 4 prompts are the building blocks. the setup is what makes them yours. your real value is in the [niche] you plug in. content workflow built in one weekend, daily posting on autopilot from monday.

Axel Bitblaze 🪓

199,569 görüntüleme • 1 ay önce

This guy cracked the code on AI virtual influencers using real-time face filters and now D2C brands pay him $2,000 per UGC video. He got tired of watching D2C brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs hyperrealistic AI girls in real-time from his own webcam, generating viral content without actresses, studios, or makeup artists. His monthly revenue hit $89,000 last month from a network of 7 AI personas across TikTok and Instagram, while the average UGC creator caps at $6K juggling 4 brand deals. Here is the exact breakdown: → The hardware is the moat, but most people butcher the setup in the first frame. You need the face mesh locked at 60fps with zero artifacting → Persona comes first, and if you mess this up nothing saves it. Name, backstory, voice tone, niche before a single clip is shot → Face selection is not random. You A/B test features (eye spacing, jawline, hair contrast with face-framing highlights) because some faces convert better in 9:16 → You are picking who your audience trusts, not who looks cool. That is your targeting baked into bone structure → Real-time physics run before the script, and this is what kills the uncanny valley that destroys watch time in 2 seconds → The filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick. → Batching is the move 96 percent skip: one performance, multiple personas, three platforms. → The system pushes 12 pieces of content before lunch, while traditional brands test 2 creators per week and wonder why their CPAs are stuck at $94 The economics are stupid: each video costs him $4 in compute, sells for $1,500 to $3,000, and takes 14 minutes to produce. That is a 37,500 percent margin, while UGC agencies pay creators $400 to $800 per clip and net $200 after revisions. One supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to LA. They were previously paying $1,200 per UGC video and burning $6,000 per week on content that did not scale. Now they spend $210 for 14 variants and their CPA dropped from $89 to $27. The avatars hold real products. Warm window light on the persona, cold neon on the operator. Mouth shapes sync to consonants, not just vowels. Just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break.
0:10

This guy cracked the code on AI virtual influencers using real-time face filters and now D2C brands pay him $2,000 per UGC video. He got tired of watching D2C brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs hyperrealistic AI girls in real-time from his own webcam, generating viral content without actresses, studios, or makeup artists. His monthly revenue hit $89,000 last month from a network of 7 AI personas across TikTok and Instagram, while the average UGC creator caps at $6K juggling 4 brand deals. Here is the exact breakdown: → The hardware is the moat, but most people butcher the setup in the first frame. You need the face mesh locked at 60fps with zero artifacting → Persona comes first, and if you mess this up nothing saves it. Name, backstory, voice tone, niche before a single clip is shot → Face selection is not random. You A/B test features (eye spacing, jawline, hair contrast with face-framing highlights) because some faces convert better in 9:16 → You are picking who your audience trusts, not who looks cool. That is your targeting baked into bone structure → Real-time physics run before the script, and this is what kills the uncanny valley that destroys watch time in 2 seconds → The filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick. → Batching is the move 96 percent skip: one performance, multiple personas, three platforms. → The system pushes 12 pieces of content before lunch, while traditional brands test 2 creators per week and wonder why their CPAs are stuck at $94 The economics are stupid: each video costs him $4 in compute, sells for $1,500 to $3,000, and takes 14 minutes to produce. That is a 37,500 percent margin, while UGC agencies pay creators $400 to $800 per clip and net $200 after revisions. One supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to LA. They were previously paying $1,200 per UGC video and burning $6,000 per week on content that did not scale. Now they spend $210 for 14 variants and their CPA dropped from $89 to $27. The avatars hold real products. Warm window light on the persona, cold neon on the operator. Mouth shapes sync to consonants, not just vowels. Just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break.

Shade

135,682 görüntüleme • 2 ay önce