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A New Era with V3🪄 V3's new engine introduces significant advancements in output generation. Unlike V2, where the multi-model system processed prompts to produce a single output, V3 is designed to generate multiple outputs and logically link them together. This enhancement effectively removes limitations on output size, enabling more...

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ALCHEMIST AI 🔮

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48,748 Aufrufe • vor 1 Jahr •via X (Twitter)

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3.5 Soon: Up to 8+ Layers, 16 LLMs in Parallel🪄 A fully parallel, multi-layered system with 8+ orchestration layers handling everything from prompt parsing and tool execution to code generation and live editing—all powered by 16+ LLMs running in sync for real-time, adaptive creation. ➡️v1: Single agent, single output ↕️v2: Multiple agents, single output 🔃v3: Single agent, multiple outputs 🔀v3.5: Multiple agents, multiple outputs — scalable, context-aware, and built for real-time builds🔨
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3.5 Soon: Up to 8+ Layers, 16 LLMs in Parallel🪄 A fully parallel, multi-layered system with 8+ orchestration layers handling everything from prompt parsing and tool execution to code generation and live editing—all powered by 16+ LLMs running in sync for real-time, adaptive creation. ➡️v1: Single agent, single output ↕️v2: Multiple agents, single output 🔃v3: Single agent, multiple outputs 🔀v3.5: Multiple agents, multiple outputs — scalable, context-aware, and built for real-time builds🔨

ALCHEMIST AI 🔮

13,482 Aufrufe • vor 1 Jahr

A Closer Look at Alchemist AI v3.5🔎 In v1, one agent handled everything. You’d enter a prompt like “make a snake game” and get a single block of code—one input, one output. v2 introduced multiple agents with specialized roles: prompt refinement, frontend, backend, and review. It brought more structure, but the process was still linear. Each step produced a single output. With v3, a single agent could handle multiple tasks. It generated HTML, CSS, JavaScript, searched for assets, and more—all in one go, while maintaining full context. Now in v3.5, we combine both models. Multiple agents work in parallel, each capable of producing multiple outputs at once. The prompt compiler adapts based on what you're building. A 3D game? It prioritizes game engines, rendering, and mechanics. A website or 2D app? It shifts focus to relevant frameworks and tools. The tool handler can call several services simultaneously, feeding context-aware data into the code generator for real-time execution. From single-output generation to parallel, adaptive workflows. In the next breakdown, we’ll dive into the architecture behind our proprietary engine in v3.5.
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A Closer Look at Alchemist AI v3.5🔎 In v1, one agent handled everything. You’d enter a prompt like “make a snake game” and get a single block of code—one input, one output. v2 introduced multiple agents with specialized roles: prompt refinement, frontend, backend, and review. It brought more structure, but the process was still linear. Each step produced a single output. With v3, a single agent could handle multiple tasks. It generated HTML, CSS, JavaScript, searched for assets, and more—all in one go, while maintaining full context. Now in v3.5, we combine both models. Multiple agents work in parallel, each capable of producing multiple outputs at once. The prompt compiler adapts based on what you're building. A 3D game? It prioritizes game engines, rendering, and mechanics. A website or 2D app? It shifts focus to relevant frameworks and tools. The tool handler can call several services simultaneously, feeding context-aware data into the code generator for real-time execution. From single-output generation to parallel, adaptive workflows. In the next breakdown, we’ll dive into the architecture behind our proprietary engine in v3.5.

ALCHEMIST AI 🔮

12,689 Aufrufe • vor 1 Jahr

Grok 3 is now available on Alchemist AI. Explore the power of Grok in your workflow. As an Ideation Model: Grok 3 turns rough ideas into structured, detailed prompts. It breaks down your intent into clear building blocks, understands nuance and context, and opens up multiple creative directions to explore. As a Generation Model: Grok 3 is built for logic-heavy outputs and multi-step generation. From game mechanics to character systems and worldbuilding, it’s capable of producing full-fledged games and applications with depth and precision.
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Grok 3 is now available on Alchemist AI. Explore the power of Grok in your workflow. As an Ideation Model: Grok 3 turns rough ideas into structured, detailed prompts. It breaks down your intent into clear building blocks, understands nuance and context, and opens up multiple creative directions to explore. As a Generation Model: Grok 3 is built for logic-heavy outputs and multi-step generation. From game mechanics to character systems and worldbuilding, it’s capable of producing full-fledged games and applications with depth and precision.

ALCHEMIST AI 🔮

16,075 Aufrufe • vor 1 Jahr

Most video tools can generate clips. Very few can maintain identity. That has been the real bottleneck in AI video creation. Kling O1 changes that. For the first time, creators can carry a character, style, and visual language across scenes without constant fixes. You can reference past clips, assets, or images and the output stays consistently on-model. No visual drift. No rework loops. No “this doesn’t look like the last shot” moments. It feels less like prompting a tool and more like working with a creative collaborator that remembers context. The impact is practical, not theoretical: → Faster production cycles → Lower iteration costs → Noticeably higher output quality This is what mature AI tooling looks like. Not louder features. Not bigger claims. Just reliability where it actually matters. Consistency is no longer the problem.
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Most video tools can generate clips. Very few can maintain identity. That has been the real bottleneck in AI video creation. Kling O1 changes that. For the first time, creators can carry a character, style, and visual language across scenes without constant fixes. You can reference past clips, assets, or images and the output stays consistently on-model. No visual drift. No rework loops. No “this doesn’t look like the last shot” moments. It feels less like prompting a tool and more like working with a creative collaborator that remembers context. The impact is practical, not theoretical: → Faster production cycles → Lower iteration costs → Noticeably higher output quality This is what mature AI tooling looks like. Not louder features. Not bigger claims. Just reliability where it actually matters. Consistency is no longer the problem.

Darshal Jaitwar

141,038 Aufrufe • vor 9 Monaten

Jev + SERV is actually insane. We already showed you can increase Jev's performance with SERV Reasoning. Now we're taking it further, bringing Jev-powered Decision nodes into Graph Sharding with the upcoming SERV v3. Here's a breakdown of how it works: Jev is a decision-making model. Given a task and a set of options, it predicts which path is more likely. Think of the octopus that predicted World Cup results. Jev does that for your business, except it's not luck. It weighs every option and tells you how sure it is. It does this by assigning probabilities to outcomes. It doesn't generate text on its own, so you can't expect it to create a new outcome for you. But that's also what enables it to be lightning fast and dirt cheap. For example, in customer service you can ask Jev how to triage an incoming query and route it to the correct department. It can only select from the list of departments you provide it. This also means it can't hallucinate a new outcome outside the options it's given, which makes it incredibly interesting for OpenServ. In Graph Sharding, we take a single system prompt and break it down into multiple LLM steps with deterministic input and output shapes. Some of these steps require an LLM to produce new output, while others are simply decision routers that determine the next possible path. Traditionally, LLMs are slow and expensive. Breaking a single prompt into multiple steps increases accuracy and reliability by a ton, but it also introduces latency. Jev takes on those decision nodes, which are the backbone of a business process and therefore SERV graphs, and makes them super consistent and lightning fast, lowering the overall cost and latency of graph execution. SERV Reasoning on its own is a great force multiplier for Jev because, like all other models, it works by interpreting input instructions. The clearer those instructions are, the better the model performs. That's where SERV Reasoning comes into play. Just like amplifying any other model, we also amplify the accuracy and consistency of Jev's responses. And now we're bringing Jev-powered Decision nodes into Graph Sharding with SERV v3.
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Jev + SERV is actually insane. We already showed you can increase Jev's performance with SERV Reasoning. Now we're taking it further, bringing Jev-powered Decision nodes into Graph Sharding with the upcoming SERV v3. Here's a breakdown of how it works: Jev is a decision-making model. Given a task and a set of options, it predicts which path is more likely. Think of the octopus that predicted World Cup results. Jev does that for your business, except it's not luck. It weighs every option and tells you how sure it is. It does this by assigning probabilities to outcomes. It doesn't generate text on its own, so you can't expect it to create a new outcome for you. But that's also what enables it to be lightning fast and dirt cheap. For example, in customer service you can ask Jev how to triage an incoming query and route it to the correct department. It can only select from the list of departments you provide it. This also means it can't hallucinate a new outcome outside the options it's given, which makes it incredibly interesting for OpenServ. In Graph Sharding, we take a single system prompt and break it down into multiple LLM steps with deterministic input and output shapes. Some of these steps require an LLM to produce new output, while others are simply decision routers that determine the next possible path. Traditionally, LLMs are slow and expensive. Breaking a single prompt into multiple steps increases accuracy and reliability by a ton, but it also introduces latency. Jev takes on those decision nodes, which are the backbone of a business process and therefore SERV graphs, and makes them super consistent and lightning fast, lowering the overall cost and latency of graph execution. SERV Reasoning on its own is a great force multiplier for Jev because, like all other models, it works by interpreting input instructions. The clearer those instructions are, the better the model performs. That's where SERV Reasoning comes into play. Just like amplifying any other model, we also amplify the accuracy and consistency of Jev's responses. And now we're bringing Jev-powered Decision nodes into Graph Sharding with SERV v3.

Armagan Amcalar

365,108 Aufrufe • vor 10 Tagen

messy inputs 👉🏽 polished outputs built a prototype with the idea of letting users bring together images from Lummi into a canvas, quickly wireframe a concept, and then generate polished images as a photo, illustration, 3d render, whatever—with the right lighting, shadows, cohesive colors, and all that good stuff the output is still not great... but this is where I see the future of creative tools heading—kind of like how you give ChatGPT an idea for an email—all the messy bits—and it writes it for you in any tone or style you want in a clear way. now imagine that but for design or imagery
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messy inputs 👉🏽 polished outputs built a prototype with the idea of letting users bring together images from Lummi into a canvas, quickly wireframe a concept, and then generate polished images as a photo, illustration, 3d render, whatever—with the right lighting, shadows, cohesive colors, and all that good stuff the output is still not great... but this is where I see the future of creative tools heading—kind of like how you give ChatGPT an idea for an email—all the messy bits—and it writes it for you in any tone or style you want in a clear way. now imagine that but for design or imagery

Pablo Stanley

12,115 Aufrufe • vor 1 Jahr

I made a second version! This time, I improved the opening to make it more eye-catching, added extra padding to the character shots so the video won’t get cropped across different social platforms, and updated the prompt into English. I also improved the canvas workflow. Previously, I had to generate multiple images and videos one by one, then pick the best results. Now the canvas supports generating multiple results in a single run, which has greatly improved my workflow efficiency. Now you only need to swap the image, and the same video prompt can still produce great results. Which anime cosplay should I make next? Full workflow and prompts:
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I made a second version! This time, I improved the opening to make it more eye-catching, added extra padding to the character shots so the video won’t get cropped across different social platforms, and updated the prompt into English. I also improved the canvas workflow. Previously, I had to generate multiple images and videos one by one, then pick the best results. Now the canvas supports generating multiple results in a single run, which has greatly improved my workflow efficiency. Now you only need to swap the image, and the same video prompt can still produce great results. Which anime cosplay should I make next? Full workflow and prompts:

underwood

180,883 Aufrufe • vor 4 Monaten

Kling 3.0 for AI UGC videos is absolutely insane 🤯 I spent 25,000+ credits in Kling perfecting the ultimate prompting framework to get the best AI UGC outputs possible. And the 3.0 update just made everything even better. Perfect for DTC brands and agencies who want high-quality AI UGC without paying $500/video for actual UGC. Here's what Kling 3.0 unlocks for AI UGCL → "AI Director" system that understands full scripts and auto-schedules camera angles (shot/reverse shot) in one generation → 3 to 15 second cinematic clips with full temporal coherence → Improved character and element locking so your subject stays consistent across shots and angles → Native 4K output for both video and stills — actually usable for professional ad creative And best of all: perfect character consistency ACROSS different shots. What this means for AI UGC: - Multi-shot storytelling in a single generation cycle - Longer clips that actually hold together - Consistent characters across your entire ad - Output quality that's ready for paid media This is the closest AI video has gotten to replacing a real shoot for performance creative. I recorded a full breakdown of the prompting framework I built after burning through 25,000 credits. Want access to all the prompts I use to create AI UGC with Kling? > Like this post > Comment "KLING" And I'll send it over (must be following so I can DM)
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Kling 3.0 for AI UGC videos is absolutely insane 🤯 I spent 25,000+ credits in Kling perfecting the ultimate prompting framework to get the best AI UGC outputs possible. And the 3.0 update just made everything even better. Perfect for DTC brands and agencies who want high-quality AI UGC without paying $500/video for actual UGC. Here's what Kling 3.0 unlocks for AI UGCL → "AI Director" system that understands full scripts and auto-schedules camera angles (shot/reverse shot) in one generation → 3 to 15 second cinematic clips with full temporal coherence → Improved character and element locking so your subject stays consistent across shots and angles → Native 4K output for both video and stills — actually usable for professional ad creative And best of all: perfect character consistency ACROSS different shots. What this means for AI UGC: - Multi-shot storytelling in a single generation cycle - Longer clips that actually hold together - Consistent characters across your entire ad - Output quality that's ready for paid media This is the closest AI video has gotten to replacing a real shoot for performance creative. I recorded a full breakdown of the prompting framework I built after burning through 25,000 credits. Want access to all the prompts I use to create AI UGC with Kling? > Like this post > Comment "KLING" And I'll send it over (must be following so I can DM)

Mike Futia

25,633 Aufrufe • vor 8 Monaten

Okay, I am fairly confident in my hypothesis now. The secret sauce behind Qwen 3.8 27B becomes almost immediately evident during testing. It is not the training data. In fact, I doubt any SFT was involved at all. The model was simply allowed GRPO with a more liberal reasoning context length. As I have explained to you before, distillation through GRPO is powerful, and in certain contexts vastly superior to K/L divergence distillation. Qwen used the outputs of Qwen 3.8 Max as the reinforcement learning objective for Qwen 3.8 27B and told the model reason as much as it has to in order to match the output. Remember, Intelligence is solution, not compression. This is like nesting the output of a function as an additional input to itself, and it is absolutely brilliant.
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Okay, I am fairly confident in my hypothesis now. The secret sauce behind Qwen 3.8 27B becomes almost immediately evident during testing. It is not the training data. In fact, I doubt any SFT was involved at all. The model was simply allowed GRPO with a more liberal reasoning context length. As I have explained to you before, distillation through GRPO is powerful, and in certain contexts vastly superior to K/L divergence distillation. Qwen used the outputs of Qwen 3.8 Max as the reinforcement learning objective for Qwen 3.8 27B and told the model reason as much as it has to in order to match the output. Remember, Intelligence is solution, not compression. This is like nesting the output of a function as an additional input to itself, and it is absolutely brilliant.

Aesther

123,124 Aufrufe • vor 1 Monat

SpaceX has introduced a new website for its next-generation Starlink V3 satellites, along with new information about the satellite. • 1 Tbps downlink capacity (~10× higher than Starlink V2). • 160 Gbps uplink capacity (~22× higher than Starlink V2). • 2,048 downlink beams + 2,048 uplink beams (vs. 192 downlink/144 uplink beams on V2). • Upgraded phased array antennas enable the increased user capacity and beam count. • New SpaceX-designed beamformer chips power the phased arrays. • Modem chips handle ~64× more throughput per chip, allowing more efficient simultaneous service and real-time beam allocation based on demand. • Each satellite includes 6 high-capacity 400 Gbps laser links, enabling a redundant petabit-scale laser mesh network for global routing. • Each satellite also has 4 quad-band RF backhaul antennas operating across Ka, E, V, and W bands. • RF backhaul capacity increases to 1.2 Tbps (>8× Starlink V2). • Backhaul uplink supports 60 GHz of spectrum across frequencies and polarizations (4.3× more than V2). • New solar arrays generate ~2× the power of the V2 satellite arrays. • Solar arrays are manufactured using a continuous roll of solar blanket, cut into 19-meter sections, with 4 sections stitched together per array. • Solar arrays are optimized to reduce atmospheric drag in low Earth orbit. • A Starship launch carrying V3 satellites will deploy ~20× more network capacity than a Falcon 9 launch carrying V2 satellites. • V3 technology will support future Starlink Mobile Gen 2 satellites, delivering terrestrial-like LTE speeds directly to unmodified smartphones. Website:
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SpaceX has introduced a new website for its next-generation Starlink V3 satellites, along with new information about the satellite. • 1 Tbps downlink capacity (~10× higher than Starlink V2). • 160 Gbps uplink capacity (~22× higher than Starlink V2). • 2,048 downlink beams + 2,048 uplink beams (vs. 192 downlink/144 uplink beams on V2). • Upgraded phased array antennas enable the increased user capacity and beam count. • New SpaceX-designed beamformer chips power the phased arrays. • Modem chips handle ~64× more throughput per chip, allowing more efficient simultaneous service and real-time beam allocation based on demand. • Each satellite includes 6 high-capacity 400 Gbps laser links, enabling a redundant petabit-scale laser mesh network for global routing. • Each satellite also has 4 quad-band RF backhaul antennas operating across Ka, E, V, and W bands. • RF backhaul capacity increases to 1.2 Tbps (>8× Starlink V2). • Backhaul uplink supports 60 GHz of spectrum across frequencies and polarizations (4.3× more than V2). • New solar arrays generate ~2× the power of the V2 satellite arrays. • Solar arrays are manufactured using a continuous roll of solar blanket, cut into 19-meter sections, with 4 sections stitched together per array. • Solar arrays are optimized to reduce atmospheric drag in low Earth orbit. • A Starship launch carrying V3 satellites will deploy ~20× more network capacity than a Falcon 9 launch carrying V2 satellites. • V3 technology will support future Starlink Mobile Gen 2 satellites, delivering terrestrial-like LTE speeds directly to unmodified smartphones. Website:

Sawyer Merritt

242,948 Aufrufe • vor 2 Monaten

Seedance 2.5 is now on CapCut. We’ve been testing Seedance 2.5 on CapCut, and what impressed us most is how much more control it gives creators. Being able to generate and edit everything in one place makes the workflow feel much faster and more natural. The timestamp-based controls, support for up to 50 references, and video generation of up to 90 seconds are especially useful. We also noticed better multilingual performance, plus viewport rendering and green screen options for more advanced workflows. Definitely a strong update for anyone creating AI video content. If you found this useful, leave a like and retweet it so more creators can discover the update! 🔁 Web: App: #CapCut #Seedance25 #CapCutAI #CapCutDidThat
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Seedance 2.5 is now on CapCut. We’ve been testing Seedance 2.5 on CapCut, and what impressed us most is how much more control it gives creators. Being able to generate and edit everything in one place makes the workflow feel much faster and more natural. The timestamp-based controls, support for up to 50 references, and video generation of up to 90 seconds are especially useful. We also noticed better multilingual performance, plus viewport rendering and green screen options for more advanced workflows. Definitely a strong update for anyone creating AI video content. If you found this useful, leave a like and retweet it so more creators can discover the update! 🔁 Web: App: #CapCut #Seedance25 #CapCutAI #CapCutDidThat

DothAI

76,116 Aufrufe • vor 2 Monaten

LayerAI Works with DeepSeek to Supercharge the LayerAI Product Suite 🌐 LayerAI integrates DeepSeek by leveraging several of its features and capabilities, focusing on areas where DeepSeek's strengths align with LayerAI's objectives. 👉 Learn more about our work with DeepSeek: - Model Deployment: DeepSeek-V3 & Coder-V2 for superior code generation, debugging, and language tasks. - DeepSeek-Coder-V2: Coding in 338 languages with a 128K context for complex structures. - Efficient Inference: Enhanced performance with DeepSeek's MLA & MoE tech. - IDE Assist: Real-time coding help, error catch, and auto-complete. - GitHub Sync: Better collab with seamless version control and reviews. This integration elevates our AI tools, making coding, learning, and teamwork smarter. More:
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LayerAI Works with DeepSeek to Supercharge the LayerAI Product Suite 🌐 LayerAI integrates DeepSeek by leveraging several of its features and capabilities, focusing on areas where DeepSeek's strengths align with LayerAI's objectives. 👉 Learn more about our work with DeepSeek: - Model Deployment: DeepSeek-V3 & Coder-V2 for superior code generation, debugging, and language tasks. - DeepSeek-Coder-V2: Coding in 338 languages with a 128K context for complex structures. - Efficient Inference: Enhanced performance with DeepSeek's MLA & MoE tech. - IDE Assist: Real-time coding help, error catch, and auto-complete. - GitHub Sync: Better collab with seamless version control and reviews. This integration elevates our AI tools, making coding, learning, and teamwork smarter. More:

LayerAI | AI2Earn

47,910 Aufrufe • vor 1 Jahr

This is the easiest way to make $10k/month with organic affiliate and AI Arcads launched an ai ugc studio that lets you build an entire army of hyper-real AI actors Then you turn any static image into a high-quality video showcasing any product go to TikTok and make an account + warm it up using arcads you can run an entirely AI UGC account using the same character over and over, making it seem like an authentic TT page Mix the content up with slideshows and videos with the same character Here's the AI stack gameplan: - Claude to help you write scripts - Arcads to generate an image of an AI girlie that fits your product demographic Scroll tiktok and save + download every video / slideshow you see made by clippers promoting a product (there's literally loads) Your going to find an offer on whop for making money online or spirituality and target it towards girls feed all these videos you scraped into a custom google gemini gem trained to deconstruct hooks / angles for you for easy hook inspiration + ideas Deconstruct the hooks, put them into Claude and ask it to give you hooks for the same style of video put for your products your promoting For the videos do caption and reaction + showcase formats Generate the reactions using the character you made in arc ads then manually record the showcasing of the product or proof of the product working Also for caption generate a 8-10 second video you can put text over Include your CTA in the video for reaction style and captions for caption style Plus generate images with the same character and make slideshows directed to your product Now rinse and repeat this make multiple accounts with multiple different avatars and print
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This is the easiest way to make $10k/month with organic affiliate and AI Arcads launched an ai ugc studio that lets you build an entire army of hyper-real AI actors Then you turn any static image into a high-quality video showcasing any product go to TikTok and make an account + warm it up using arcads you can run an entirely AI UGC account using the same character over and over, making it seem like an authentic TT page Mix the content up with slideshows and videos with the same character Here's the AI stack gameplan: - Claude to help you write scripts - Arcads to generate an image of an AI girlie that fits your product demographic Scroll tiktok and save + download every video / slideshow you see made by clippers promoting a product (there's literally loads) Your going to find an offer on whop for making money online or spirituality and target it towards girls feed all these videos you scraped into a custom google gemini gem trained to deconstruct hooks / angles for you for easy hook inspiration + ideas Deconstruct the hooks, put them into Claude and ask it to give you hooks for the same style of video put for your products your promoting For the videos do caption and reaction + showcase formats Generate the reactions using the character you made in arc ads then manually record the showcasing of the product or proof of the product working Also for caption generate a 8-10 second video you can put text over Include your CTA in the video for reaction style and captions for caption style Plus generate images with the same character and make slideshows directed to your product Now rinse and repeat this make multiple accounts with multiple different avatars and print

Pounds

32,407 Aufrufe • vor 8 Monaten

P-Image-Upscale is the fastest and cheapest image upscaler in the world: supporting outputs up to 128 MP under 1 seconds. A couple of weeks ago we released p-image-upscale, and it now works better than ever. It’s the fastest image upscaler in the world, supporting outputs up to 128 MP while keeping pricing simple and predictable: - $0.005/image for 1–4 MP - $0.01/image for 4–8 MP - $0.02/image for 8–16 MP - $0.04/image for 16–32 MP - $0.06/image for 32–64 MP - $0.12/image for 64–128 MP That means you can go from low-res input to production-ready output with extreme speed, while preserving detail and keeping costs easy to understand. Available on: - Pruna AI | - each::labs | - inference shell | - Replicate | - Runware | - Segmind | - WaveSpeedAI | - Wiro AI — Ship AI Faster | If you’re building workflows where image quality, price, latency, and scale all matter, p-image-upscale is built for you.
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P-Image-Upscale is the fastest and cheapest image upscaler in the world: supporting outputs up to 128 MP under 1 seconds. A couple of weeks ago we released p-image-upscale, and it now works better than ever. It’s the fastest image upscaler in the world, supporting outputs up to 128 MP while keeping pricing simple and predictable: - $0.005/image for 1–4 MP - $0.01/image for 4–8 MP - $0.02/image for 8–16 MP - $0.04/image for 16–32 MP - $0.06/image for 32–64 MP - $0.12/image for 64–128 MP That means you can go from low-res input to production-ready output with extreme speed, while preserving detail and keeping costs easy to understand. Available on: - Pruna AI | - each::labs | - inference shell | - Replicate | - Runware | - Segmind | - WaveSpeedAI | - Wiro AI — Ship AI Faster | If you’re building workflows where image quality, price, latency, and scale all matter, p-image-upscale is built for you.

Pruna AI

24,089 Aufrufe • vor 4 Monaten

Kling 3.0 is out but Sora 2 is still the GOAT when it comes to AI UGC 🤯 And this custom GPT turns your sh*tty Sora 2 prompts into scroll-stopping UGC 🤯 Tell it your product --> get a timeline-based prompt with shot composition, camera angles, lighting, and timing breakdowns. Copy, paste, generate. Perfect for DTC brands and agencies who are tired of AI video output that looks like garbage. Here's the problem: Most people prompt Sora 2 like "make a UGC video of someone using my skincare product" and wonder why the output is unusable. Sora 2 needs hyper-specific instructions—shot type, lighting, scene details, timing cues. Without that, you get slop. This GPT fixes it: → Input your product (supplement, skincare, SaaS, whatever) → It generates a detailed Sora 2 prompt with full scene breakdown → Includes shot composition, camera movement, and timing → Optimized for 9:16 TikTok/Reels format → Copy directly into Sora 2 and generate No 80,000 word "prompting frameworks", just results. What you get: > Professional UGC prompts in 10 seconds > Consistent output quality every time > Prompts built for vertical video formats > Works for any product type Want free access to the Sora 2 Prompt Generator GPT? > Like this post > Comment "UGC" And I'll send it over (must be following so I can DM)
0:15

Kling 3.0 is out but Sora 2 is still the GOAT when it comes to AI UGC 🤯 And this custom GPT turns your sh*tty Sora 2 prompts into scroll-stopping UGC 🤯 Tell it your product --> get a timeline-based prompt with shot composition, camera angles, lighting, and timing breakdowns. Copy, paste, generate. Perfect for DTC brands and agencies who are tired of AI video output that looks like garbage. Here's the problem: Most people prompt Sora 2 like "make a UGC video of someone using my skincare product" and wonder why the output is unusable. Sora 2 needs hyper-specific instructions—shot type, lighting, scene details, timing cues. Without that, you get slop. This GPT fixes it: → Input your product (supplement, skincare, SaaS, whatever) → It generates a detailed Sora 2 prompt with full scene breakdown → Includes shot composition, camera movement, and timing → Optimized for 9:16 TikTok/Reels format → Copy directly into Sora 2 and generate No 80,000 word "prompting frameworks", just results. What you get: > Professional UGC prompts in 10 seconds > Consistent output quality every time > Prompts built for vertical video formats > Works for any product type Want free access to the Sora 2 Prompt Generator GPT? > Like this post > Comment "UGC" And I'll send it over (must be following so I can DM)

Mike Futia

22,444 Aufrufe • vor 8 Monaten

this video is 100% AI made it in under 10 minutes all you need is: - sora 2 - a dialed prompt - optionally an upscaler if you're still paying $500+ per UGC clip to creators who take 5 days to deliver you're literally burning money the quality has gotten to the point where it's genuinely hard to tell the difference one person with the right prompts and workflow can now output what entire creative teams used to do we've built an entire system around this and my whop members are landing brand deals with AI content that clients can't even tell isn't real i'm running AI UGC like this for coaching/bizopp offers right now and the CPAs are competing with real creator content, if you're selling anything online and you're not using AI content yet you're leaving money on the table
0:14

this video is 100% AI made it in under 10 minutes all you need is: - sora 2 - a dialed prompt - optionally an upscaler if you're still paying $500+ per UGC clip to creators who take 5 days to deliver you're literally burning money the quality has gotten to the point where it's genuinely hard to tell the difference one person with the right prompts and workflow can now output what entire creative teams used to do we've built an entire system around this and my whop members are landing brand deals with AI content that clients can't even tell isn't real i'm running AI UGC like this for coaching/bizopp offers right now and the CPAs are competing with real creator content, if you're selling anything online and you're not using AI content yet you're leaving money on the table

MAX

104,719 Aufrufe • vor 7 Monaten

We’ve released two new updates on Stable Assistant! ♻️Reinvent: Bring together existing tools such as “new image with same structure” and other generation tools. This new menu is designed to make it easier to reapply the same creative treatment to your images with just a few clicks. ✖️Batch: Generate multiple new versions of an image, apply edits across all creations, or even reinvent them with the same adjustments. Whether you're zooming out, inpainting, or working with structured designs, Batch helps you make consistent edits across your entire project. 🔗 Explore these new features with a 3-day free trial on Stable Assistant:
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We’ve released two new updates on Stable Assistant! ♻️Reinvent: Bring together existing tools such as “new image with same structure” and other generation tools. This new menu is designed to make it easier to reapply the same creative treatment to your images with just a few clicks. ✖️Batch: Generate multiple new versions of an image, apply edits across all creations, or even reinvent them with the same adjustments. Whether you're zooming out, inpainting, or working with structured designs, Batch helps you make consistent edits across your entire project. 🔗 Explore these new features with a 3-day free trial on Stable Assistant:

Stability AI

25,355 Aufrufe • vor 2 Jahren

Claude Code + Nano Banana 2 is f*cking cracked 🤯 I built a skill inside Claude Code that writes JSON image prompts for Nano Banana 2, and the outputs look like they came from a professional photo shoot. One plain-text prompt. Claude rewrites it as structured JSON with lighting, camera, composition, style, and negative prompts. Then fires it off to Nano Banana 2. All inside Claude Code. Perfect for DTC brands and agencies who need high-volume ad creative without booking a shoot. If you're using Nano Banana 2 for product shots and lifestyle images but every generation feels like pulling a slot machine lever — random lighting, inconsistent style, plastic skin, misspelled labels ... This skill fixes the entire output: → You describe what you want in plain English → Claude rewrites it as a structured JSON prompt (lighting, camera angle, lens, depth of field, color grading — all of it) → Fires it to Nano Banana 2 via API → Saves the prompt + image in organized folders → You iterate on the style until it's dialed, then every output matches No more slot machine prompting. No more inconsistent brand imagery. No more burning credits on unusable generations. What you get: - Photo-realistic product shots and lifestyle images on demand - Full control over style, lighting, composition, and camera settings - Saved JSON prompts you can reuse across every campaign - A skill that gets smarter the more feedback you give it Built 100% in Claude Code with a custom skill + Python scripts. I put together a full playbook showing the exact skill, the JSON schema, and the workflow to set this up yourself. Want the full playbook? > Like this post > Comment "BANANA" And I'll send it over (must be following so I can DM)
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Claude Code + Nano Banana 2 is f*cking cracked 🤯 I built a skill inside Claude Code that writes JSON image prompts for Nano Banana 2, and the outputs look like they came from a professional photo shoot. One plain-text prompt. Claude rewrites it as structured JSON with lighting, camera, composition, style, and negative prompts. Then fires it off to Nano Banana 2. All inside Claude Code. Perfect for DTC brands and agencies who need high-volume ad creative without booking a shoot. If you're using Nano Banana 2 for product shots and lifestyle images but every generation feels like pulling a slot machine lever — random lighting, inconsistent style, plastic skin, misspelled labels ... This skill fixes the entire output: → You describe what you want in plain English → Claude rewrites it as a structured JSON prompt (lighting, camera angle, lens, depth of field, color grading — all of it) → Fires it to Nano Banana 2 via API → Saves the prompt + image in organized folders → You iterate on the style until it's dialed, then every output matches No more slot machine prompting. No more inconsistent brand imagery. No more burning credits on unusable generations. What you get: - Photo-realistic product shots and lifestyle images on demand - Full control over style, lighting, composition, and camera settings - Saved JSON prompts you can reuse across every campaign - A skill that gets smarter the more feedback you give it Built 100% in Claude Code with a custom skill + Python scripts. I put together a full playbook showing the exact skill, the JSON schema, and the workflow to set this up yourself. Want the full playbook? > Like this post > Comment "BANANA" And I'll send it over (must be following so I can DM)

NOVA

64,187 Aufrufe • vor 6 Monaten