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It's here! Just open-sourced a Certificate Generator that automates personalised certificate creation!✨ Features: • Upload CSV → Generate custom PDFs • Drag-and-drop text positioning with live preview • Multiple cloud storage providers (Cloudinary, Catbox, etc.) • Custom templates & fonts Perfect for courses, events, & training programs. Built with... show more

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i wish i could just upload a CSV and it would automatically create a dashboard so we built this today we're launching graphed .com graphed is an AI data analytics and dashboard generator upload data into Graphed and it's gonna one shot generate a dashboard you can chat with the entire dashboard to make changes and you can click into the graph and chat with it to make updates everything you create in Graphed can easily be shared with your team by sending a link or you can download a screenshot and drop it into a Slack channel or add it to a presentation the Graphed source data can either be a CSV or a data integration data integrations allow you to create live dashboards that are constantly updating in the background we're launching with Google Analytics 4 as our first data integration but we have Shopify, Facebook ads, Google Ads, MongoDB, and hundreds more are on our product roadmap you can sign up for free at graphed .com and if you want a 40% discount code that will only be available during launch comment "graphed" below

i wish i could just upload a CSV and it would automatically create a dashboard so we built this today we're launching graphed .com graphed is an AI data analytics and dashboard generator upload data into Graphed and it's gonna one shot generate a dashboard you can chat with the entire dashboard to make changes and you can click into the graph and chat with it to make updates everything you create in Graphed can easily be shared with your team by sending a link or you can download a screenshot and drop it into a Slack channel or add it to a presentation the Graphed source data can either be a CSV or a data integration data integrations allow you to create live dashboards that are constantly updating in the background we're launching with Google Analytics 4 as our first data integration but we have Shopify, Facebook ads, Google Ads, MongoDB, and hundreds more are on our product roadmap you can sign up for free at graphed .com and if you want a 40% discount code that will only be available during launch comment "graphed" below

Cody Schneider

47,333 Aufrufe • vor 1 Jahr

Heya #ICPFamily, this is a big one. I’d like to introduce you guys to uBin, a cloud storage experience built on #ICP that allows you to create and own a personal file storage space on a blockchain network! This project is about 3 years old and offers a wide range of features: • Self-paid, autonomous smart contract creation and ownership. • In browser file manager interface with drag and drop upload. • In-app music/video player, document viewer (docx, pdf, etc), and a 3D model viewer. • Sharing via QR code and direct link. • User menu with saved settings customization. • In-app bug report/support ticket information. • Choice between public and encrypted canisters. • Support for mobile with NFID and Stoic. uBin has a 3+ year roadmap and lots to come. We have a few hundred users on and off chain, and we’re super excited to finally show what we’ve been cooking. We are in beta and have a whitelist, but you can login and submit the request right in the app if you’d like to try it! We love ICP and plan to stay forever, and in the process I’d like to sincerely thank everyone for their support in building this. Without you guys I wouldn’t be here. Love you all! ❤️

Heya #ICPFamily, this is a big one. I’d like to introduce you guys to uBin, a cloud storage experience built on #ICP that allows you to create and own a personal file storage space on a blockchain network! This project is about 3 years old and offers a wide range of features: • Self-paid, autonomous smart contract creation and ownership. • In browser file manager interface with drag and drop upload. • In-app music/video player, document viewer (docx, pdf, etc), and a 3D model viewer. • Sharing via QR code and direct link. • User menu with saved settings customization. • In-app bug report/support ticket information. • Choice between public and encrypted canisters. • Support for mobile with NFID and Stoic. uBin has a 3+ year roadmap and lots to come. We have a few hundred users on and off chain, and we’re super excited to finally show what we’ve been cooking. We are in beta and have a whitelist, but you can login and submit the request right in the app if you’d like to try it! We love ICP and plan to stay forever, and in the process I’d like to sincerely thank everyone for their support in building this. Without you guys I wouldn’t be here. Love you all! ❤️

Daniel

45,384 Aufrufe • vor 1 Jahr

If you’re anything like me, you have some videos in your library that can use a little TLC. A little zoom, crop and straighten can go a long ways when kids or pets (or, let’s be honest, even adult friends) are involved 📷 I’m really excited to share some tools we’ve been building that have been so helpful in our internal Google Photos dogfood! 🤩 -- Our redesigned video editor (on Android & iOS) is faster and supports multi-clip editing with an adaptive canvas. Less time figuring out edits, more time creating! ✨ Open a video, hit edit, and you’ll see several new tools. -- Add the perfect soundtrack from our music library! 🎶 -- Tell your story with custom text (on Android) using new fonts, colors, and backgrounds. But sometimes, we need a bit more help to make a really special multi asset clip. I’m so excited to announce Video Templates on Android! Quick, shareable videos automatically cut to the beat with built-in music and text. Just pick a template & your clips! 🎬 Available in the Create Tab. All these updates are rolling out now — try them out and turn those memories into masterpieces! 👇 #GooglePhotos #VideoEditing #GenAI

If you’re anything like me, you have some videos in your library that can use a little TLC. A little zoom, crop and straighten can go a long ways when kids or pets (or, let’s be honest, even adult friends) are involved 📷 I’m really excited to share some tools we’ve been building that have been so helpful in our internal Google Photos dogfood! 🤩 -- Our redesigned video editor (on Android & iOS) is faster and supports multi-clip editing with an adaptive canvas. Less time figuring out edits, more time creating! ✨ Open a video, hit edit, and you’ll see several new tools. -- Add the perfect soundtrack from our music library! 🎶 -- Tell your story with custom text (on Android) using new fonts, colors, and backgrounds. But sometimes, we need a bit more help to make a really special multi asset clip. I’m so excited to announce Video Templates on Android! Quick, shareable videos automatically cut to the beat with built-in music and text. Just pick a template & your clips! 🎬 Available in the Create Tab. All these updates are rolling out now — try them out and turn those memories into masterpieces! 👇 #GooglePhotos #VideoEditing #GenAI

shimrit ben-yair

24,393 Aufrufe • vor 9 Monaten

Massive breakthrough here! Someone fixed every major flaw in Jupyter Notebooks. The .ipynb format is stuck in 2014. It was built for a different era - no cloud collaboration, no AI agents, no team workflows. Change one cell, and you get 50+ lines of JSON metadata in your git diff. Code reviews become a nightmare. Want to share a database connection across notebooks? Configure it separately in each one. Need comments or permissions? Too bad. Jupyter works for solo analysis but breaks for teams building production AI systems. Deepnote just open-sourced the solution (Apache 2.0 license) They've built a new notebook standard that actually fits modern workflows: ↳ Human-readable YAML - Git diffs show actual code changes, not JSON noise. Code reviews finally work. ↳ Project-based structure - Multiple notebooks share integrations, secrets, and environment settings. Configure once, use everywhere. ↳ 23 new block - SQL, interactive inputs, charts, and KPIs as first-class citizens. Build data apps, not just analytics notebooks. ↳ Multi-language support - Python and SQL in one notebook. Modern data work isn't single-language anymore. ↳ Full backward and forward compatibility: convert any Jupyter notebook to Deepnote and vice versa with one command. npx @ deepnote/convert notebook.ipynb Then open it in VS Code, Cursor, WindSurf, or Antigravity. Your existing notebooks migrate instantly. Their cloud version adds real-time collaboration with comments, permissions, and live editing. I've shared the GitHub repo link in the replies! It's 100% open-source.

Massive breakthrough here! Someone fixed every major flaw in Jupyter Notebooks. The .ipynb format is stuck in 2014. It was built for a different era - no cloud collaboration, no AI agents, no team workflows. Change one cell, and you get 50+ lines of JSON metadata in your git diff. Code reviews become a nightmare. Want to share a database connection across notebooks? Configure it separately in each one. Need comments or permissions? Too bad. Jupyter works for solo analysis but breaks for teams building production AI systems. Deepnote just open-sourced the solution (Apache 2.0 license) They've built a new notebook standard that actually fits modern workflows: ↳ Human-readable YAML - Git diffs show actual code changes, not JSON noise. Code reviews finally work. ↳ Project-based structure - Multiple notebooks share integrations, secrets, and environment settings. Configure once, use everywhere. ↳ 23 new block - SQL, interactive inputs, charts, and KPIs as first-class citizens. Build data apps, not just analytics notebooks. ↳ Multi-language support - Python and SQL in one notebook. Modern data work isn't single-language anymore. ↳ Full backward and forward compatibility: convert any Jupyter notebook to Deepnote and vice versa with one command. npx @ deepnote/convert notebook.ipynb Then open it in VS Code, Cursor, WindSurf, or Antigravity. Your existing notebooks migrate instantly. Their cloud version adds real-time collaboration with comments, permissions, and live editing. I've shared the GitHub repo link in the replies! It's 100% open-source.

Akshay 🚀

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Been using Nous Research Hermes Agent for media editing and it completely replaced my workflow. You know the drill : - Trim a video - open CapCut. - Convert to mp3 - another site. - Remove audio - another one. - Make a gif - yet another one. - more tasks, more different tools minutes of uploading and downloading.. Now you can do all of that just by chatting like asking a designer friend to edit your media and getting it back instantly :) I built a media toolset for Hermes that handles all of this natively. It registers as a skill inside the agent - Hermes sees your video, understands what you're asking, takes the right operations and use the best skills and give you what you really wanted perfectly ▪️ Trim any segment down to the second ▪️ Speed up or slow down with pitch corrected audio ▪️ Compress without destroying quality ▪️ Create a gif on defined times range ▪️ Cut the video and rotate it and apply instagram ▪️ Convert between any format - mp4, mp3, ogg, webm ▪️ Chain edits: "trim 0:30 1:00 and speed up 1.5x and compress" ▪️ Burn .srt subtitles directly into the video ▪️ Add or remove text watermarks with custom position ▪️ Generate thumbnails from any timestamp ▪️ Fade in/out with custom duration ▪️ ASCII video art with multiple character styles and many more with customizable skills Works the same on Telegram, Discord, WhatsApp etc. This is what agents should be doing and Hermes does.

Been using Nous Research Hermes Agent for media editing and it completely replaced my workflow. You know the drill : - Trim a video - open CapCut. - Convert to mp3 - another site. - Remove audio - another one. - Make a gif - yet another one. - more tasks, more different tools minutes of uploading and downloading.. Now you can do all of that just by chatting like asking a designer friend to edit your media and getting it back instantly :) I built a media toolset for Hermes that handles all of this natively. It registers as a skill inside the agent - Hermes sees your video, understands what you're asking, takes the right operations and use the best skills and give you what you really wanted perfectly ▪️ Trim any segment down to the second ▪️ Speed up or slow down with pitch corrected audio ▪️ Compress without destroying quality ▪️ Create a gif on defined times range ▪️ Cut the video and rotate it and apply instagram ▪️ Convert between any format - mp4, mp3, ogg, webm ▪️ Chain edits: "trim 0:30 1:00 and speed up 1.5x and compress" ▪️ Burn .srt subtitles directly into the video ▪️ Add or remove text watermarks with custom position ▪️ Generate thumbnails from any timestamp ▪️ Fade in/out with custom duration ▪️ ASCII video art with multiple character styles and many more with customizable skills Works the same on Telegram, Discord, WhatsApp etc. This is what agents should be doing and Hermes does.

ogichain

11,291 Aufrufe • vor 6 Monaten

The bottleneck in AI has quietly shifted. - It's not the models. They are capable. - It's not the frameworks. They are mature. - It's not even the data, in many cases. When you want to train a model today, the first question isn't "what architecture should I use?" Instead, it's: "Where am I going to get infrastructure that actually works?" Not just GPUs but the entire stack: compute, deployment, scaling, storage. The traditional path is major cloud providers or specialized GPU clouds. Both have the same problem: they're built for enterprises with committed workloads, minimum spend requirements, contract negotiations, and involve quota approvals that take days. Even the "on-demand" options require you to piece together training, deployment, and scaling across different services. By the time you're actually training, hours, if not days, have passed. And there's a subtler cost: part of your brain is always managing infrastructure instead of thinking about the actual problem. I've been using Runpod for a while now, and it's the closest I've found to infrastructure that just disappears. I pay for the serverless solution by the second, and stop when I'm done. This sounds like it should be the default across all providers, but it isn't. For instance, when I'm prototyping, I don't need an H100. Instead, I need the flexibility to use cheaper GPUs that are actually available, where I can iterate fast and not worry about cost. An A40 at a few cents per hour is perfect for this. Then, when the approach is validated, I scale up. This matches how good engineering actually works. Running distributed training across multiple nodes for multi-GPU training usually requires significant infra work. RunPod abstracts most of this away. A lot of the advantage in AI comes from iteration speed. Infra that adds days of latency to that loop is a real cost, even if it's hard to measure. But good infra gets out of your way. It's available when you need it, invisible when you don't. In the video below, I have shown a simple model training workflow trained using PyTorch in Jupyter Lab. It runs in a dedicated PyTorch Pod hosted on Runpod, and I worked with the team to put this together for you. Find a link to start using Runpod in the replies!

The bottleneck in AI has quietly shifted. - It's not the models. They are capable. - It's not the frameworks. They are mature. - It's not even the data, in many cases. When you want to train a model today, the first question isn't "what architecture should I use?" Instead, it's: "Where am I going to get infrastructure that actually works?" Not just GPUs but the entire stack: compute, deployment, scaling, storage. The traditional path is major cloud providers or specialized GPU clouds. Both have the same problem: they're built for enterprises with committed workloads, minimum spend requirements, contract negotiations, and involve quota approvals that take days. Even the "on-demand" options require you to piece together training, deployment, and scaling across different services. By the time you're actually training, hours, if not days, have passed. And there's a subtler cost: part of your brain is always managing infrastructure instead of thinking about the actual problem. I've been using Runpod for a while now, and it's the closest I've found to infrastructure that just disappears. I pay for the serverless solution by the second, and stop when I'm done. This sounds like it should be the default across all providers, but it isn't. For instance, when I'm prototyping, I don't need an H100. Instead, I need the flexibility to use cheaper GPUs that are actually available, where I can iterate fast and not worry about cost. An A40 at a few cents per hour is perfect for this. Then, when the approach is validated, I scale up. This matches how good engineering actually works. Running distributed training across multiple nodes for multi-GPU training usually requires significant infra work. RunPod abstracts most of this away. A lot of the advantage in AI comes from iteration speed. Infra that adds days of latency to that loop is a real cost, even if it's hard to measure. But good infra gets out of your way. It's available when you need it, invisible when you don't. In the video below, I have shown a simple model training workflow trained using PyTorch in Jupyter Lab. It runs in a dedicated PyTorch Pod hosted on Runpod, and I worked with the team to put this together for you. Find a link to start using Runpod in the replies!

Avi Chawla

13,696 Aufrufe • vor 8 Monaten

Cloud GPU training is a scam. A single M4 MacBook does 2.9 TFLOPS. Seven friends with MacBooks match an NVIDIA A100. Alexander Hayes just open-sourced a tool that makes this work over Wi-Fi. It's called AirTrain. Here's how it works: Traditional distributed training (DDP) syncs gradients after every single step. For a 124M parameter model, that's ~500MB exchanged per step. You need 50 GB/s of sustained bandwidth. Impossible over Wi-Fi. AirTrain uses the DiLoCo algorithm. Each Mac trains independently for 500 steps, then syncs only the difference. One sync per 500 steps instead of one per step. 500x less network communication. Wi-Fi actually works. The entire sync takes ~2 seconds. Here's what makes it wild: → Zero-config discovery. Devices find each other automatically via mDNS/Bonjour. Same protocol as AirDrop. → Fault tolerant. Nodes can join and leave mid-training without killing the run. → Checkpoint relay. Train for a few hours, export a checkpoint, hand it off to someone else to continue. Like a relay race for ML training. → Built on Apple's MLX framework. Native to M1/M2/M3/M4/M5 unified memory. No host-to-device copy overhead. → Local dashboard. Real-time loss curves, peer monitoring, throughput metrics in your browser. Here's the wildest part: An M4 Max with 128GB unified memory can train a 70B parameter model without offloading. An NVIDIA RTX 4090 has 24GB VRAM. Apple Silicon gets ~245-460 GFLOPS per watt. Training on MacBooks costs almost nothing in electricity compared to cloud GPUs. And there are hundreds of millions of Apple Silicon Macs in the world. The math: Traditional DDP: 1 sync per step = 50 GB/s required AirTrain (DiLoCo): 1 sync per 500 steps = 0.1 GB/s required Wi-Fi handles 0.1 GB/s. That's it. That's the breakthrough. They even built a community platform at with live session browsing, checkpoint sharing, and a contributor leaderboard. Training a 124M parameter GPT-2? Instead of renting cloud GPUs at $3/hr, pool three MacBooks in a coffee shop and train for free. MIT licensed. Built in Python. 1 contributor. Early stage but the idea is insane. 100% Open Source. (Link in the comments)

Cloud GPU training is a scam. A single M4 MacBook does 2.9 TFLOPS. Seven friends with MacBooks match an NVIDIA A100. Alexander Hayes just open-sourced a tool that makes this work over Wi-Fi. It's called AirTrain. Here's how it works: Traditional distributed training (DDP) syncs gradients after every single step. For a 124M parameter model, that's ~500MB exchanged per step. You need 50 GB/s of sustained bandwidth. Impossible over Wi-Fi. AirTrain uses the DiLoCo algorithm. Each Mac trains independently for 500 steps, then syncs only the difference. One sync per 500 steps instead of one per step. 500x less network communication. Wi-Fi actually works. The entire sync takes ~2 seconds. Here's what makes it wild: → Zero-config discovery. Devices find each other automatically via mDNS/Bonjour. Same protocol as AirDrop. → Fault tolerant. Nodes can join and leave mid-training without killing the run. → Checkpoint relay. Train for a few hours, export a checkpoint, hand it off to someone else to continue. Like a relay race for ML training. → Built on Apple's MLX framework. Native to M1/M2/M3/M4/M5 unified memory. No host-to-device copy overhead. → Local dashboard. Real-time loss curves, peer monitoring, throughput metrics in your browser. Here's the wildest part: An M4 Max with 128GB unified memory can train a 70B parameter model without offloading. An NVIDIA RTX 4090 has 24GB VRAM. Apple Silicon gets ~245-460 GFLOPS per watt. Training on MacBooks costs almost nothing in electricity compared to cloud GPUs. And there are hundreds of millions of Apple Silicon Macs in the world. The math: Traditional DDP: 1 sync per step = 50 GB/s required AirTrain (DiLoCo): 1 sync per 500 steps = 0.1 GB/s required Wi-Fi handles 0.1 GB/s. That's it. That's the breakthrough. They even built a community platform at with live session browsing, checkpoint sharing, and a contributor leaderboard. Training a 124M parameter GPT-2? Instead of renting cloud GPUs at $3/hr, pool three MacBooks in a coffee shop and train for free. MIT licensed. Built in Python. 1 contributor. Early stage but the idea is insane. 100% Open Source. (Link in the comments)

Guri Singh

160,201 Aufrufe • vor 4 Monaten

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Mike Futia

52,686 Aufrufe • vor 4 Monaten

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I just watched AI agents map Nazi escape routes across two continents. This is the coolest fork of our agentic RAG framework that I've seen so far 🔽 𝗩𝗲𝗿𝗼 𝗗𝗮𝗹𝗹'𝗔𝗴𝗹𝗶𝗼 built a complete 𝗢𝗦𝗜𝗡𝗧 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 on top of Elysia, and it's fully open source. 𝗜𝗻𝘁𝗲𝗹𝗹𝘆𝗪𝗲𝗮𝘃𝗲 takes Elysia's decision tree architecture and extends it for intelligence analysis. Upload documents, ask questions in natural language, and get comprehensive intelligence assessments with entity extraction, geospatial mapping, and network analysis. Main features: 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗘𝗻𝘁𝗶𝘁𝘆 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻: Uses GLiNER for zero-shot recognition of 7 entity types (persons, organizations, locations, dates, events, laws, cryptonyms). No training required. 𝗧𝘄𝗼-𝗔𝗴𝗲𝗻𝘁 𝗔𝗿𝗰𝗵𝗶𝘃𝗲 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵: The "Quartermaster" agent maps the information landscape (discovers archives, classifies access levels), while the "Case Officer" conducts hypothesis-driven investigations with confidence scoring and evidence citations. 𝗚𝗲𝗼𝘀𝗽𝗮𝘁𝗶𝗮𝗹 + 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Interactive 3D maps (Mapbox) and force-directed network graphs (vis-network) to reveal hidden connections between entities using Elysia's build in customizable display types. 𝟲-𝗣𝗵𝗮𝘀𝗲 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗼𝗿: Automated pipeline that goes from extraction → relationship mapping → geospatial analysis → network analysis → pattern detection → synthesis, with automatic task generation for follow-up investigation. They even built a demo analyzing 17 historical documents about Nazi escape networks to South America (1945-1962). The system automatically extracted entities, mapped three distinct escape routes, and generated hypotheses with confidence scores. This is exactly what we hoped people would build with Elysia 💚 so so cool to see. Elysia's decision tree architecture makes it straightforward to add domain-specific tools (like GLiNER entity extraction or archive discovery or custom map displays) while keeping all the core functionality (error handling, streaming, self-healing, transparency) that comes built-in. Check out the repo: Interactive demo: Elysia blog post: Huge shoutout to the contributors for building this and sharing it with the community! 🫶

Victoria Slocum

19,625 Aufrufe • vor 7 Monaten

This custom GPT writes perfect Sora 2 prompts every time 🤯 Most people are wasting hours trying to get Sora 2 to generate decent UGC videos. The problem isn't Sora 2. It's you (and your prompts). Here's what I learned after generating 100+ UGC videos with Sora 2: Sora 2 needs hyper-specific prompts with shot composition, timing, camera movement, and scene details. Most people write: "Create a UGC video for my protein bar" What you get? Terrible results. What actually works: "9:16 vertical handheld shot, natural lighting, female creator in kitchen holding [brand] protein bar at eye level, excited testimonial energy, 0-3s hook showing bite and reaction, shallow depth of field, warm color grade" That's the difference between amateur & professional output. So I built a custom GPT that does this automatically: → Tell it your product (protein bar, skincare, SaaS tool, etc.) → It generates a detailed timeline-based Sora 2 prompt → Includes shot composition, camera angles, timing breakdowns → Optimized for 9:16 UGC TikTok/Reels format → Copy/paste directly into Sora 2 No more guessing. No more mediocre results. Just professional UGC prompts in 10 seconds. Want free access to the Sora 2 Prompt Generator GPT? > Comment "GPT" > Like this post And I'll send it over (must be following so I can DM)

Mike Futia

49,929 Aufrufe • vor 11 Monaten

I just vibe-coded a Meta Ads Bulk Uploader in Claude Code that uploads dozens of Facebook and Instagram ads in minutes 🤯 Drag and drop your creatives, connect your live Meta account, publish directly through the Marketing API. Built 100% in Claude Code. Perfect for media buyers and DTC brands who are still uploading ads one at a time in Ads Manager. If you're a media buyer spending 10+ hours a week uploading ads one at a time in Ads Manager — attaching videos, picking thumbnails, naming ads, toggling enhancements, repeating 50 times ... This eliminates the entire workflow: → Drag and drop dozens of images/videos at once → Add multiple primary texts, headlines, and descriptions per batch → Pick your campaign and ad set directly from your live Meta account → Clone existing ad sets with one click → Upload custom thumbnails, pick your CTA, launch paused or active No uploading ads one by one. No 2-3 hours of clicking. No $99/month SaaS subscription. What this tool does: → A bulk uploader that publishes directly through Meta's Marketing API → Full creative control — thumbnails, CTAs, ad names, enhancements — all in one shot → Ad set cloning so you can scale winning setups instantly → A free alternative to the $99/month tools that do the exact same thing I'm giving away every prompt I used to build it so you can vibe-code the whole thing yourself. Want all the prompts? > Like this post > Comment "BULK" And I'll send it over (must be following so I can DM)

I just vibe-coded a Meta Ads Bulk Uploader in Claude Code that uploads dozens of Facebook and Instagram ads in minutes 🤯 Drag and drop your creatives, connect your live Meta account, publish directly through the Marketing API. Built 100% in Claude Code. Perfect for media buyers and DTC brands who are still uploading ads one at a time in Ads Manager. If you're a media buyer spending 10+ hours a week uploading ads one at a time in Ads Manager — attaching videos, picking thumbnails, naming ads, toggling enhancements, repeating 50 times ... This eliminates the entire workflow: → Drag and drop dozens of images/videos at once → Add multiple primary texts, headlines, and descriptions per batch → Pick your campaign and ad set directly from your live Meta account → Clone existing ad sets with one click → Upload custom thumbnails, pick your CTA, launch paused or active No uploading ads one by one. No 2-3 hours of clicking. No $99/month SaaS subscription. What this tool does: → A bulk uploader that publishes directly through Meta's Marketing API → Full creative control — thumbnails, CTAs, ad names, enhancements — all in one shot → Ad set cloning so you can scale winning setups instantly → A free alternative to the $99/month tools that do the exact same thing I'm giving away every prompt I used to build it so you can vibe-code the whole thing yourself. Want all the prompts? > Like this post > Comment "BULK" And I'll send it over (must be following so I can DM)

Mike Futia

42,871 Aufrufe • vor 6 Monaten

This will retire 90% of RAG systems with dignity (and a sad song playlist). Powered by DSPy: If you're still building "text in, text out" chatbots that only perform blind vector and text searches, you're not gonna make it! My team just dropped Elysia, and it's not just an incremental successor to Verba… It's a whole rethink of how we interact with our data using AI. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗘𝗹𝘆𝗶𝘀𝗮? An open-source platform for building agentic RAG architectures. It learns from your preferences, intelligently categorizes, labels, and searches through your data, and provides complete transparency into its decision-making process. The long & exciting feature list: • 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝘁 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗧𝗿𝗲𝗲 𝗔𝗴𝗲𝗻𝘁𝘀: Elysia’s core is a customizable decision tree, and it visualizes its entire reasoning process, showing you why it chooses a specific tool or path. It enables advanced error handling, self-healing from failed queries, and prevents infinite loops. You can also add custom tools and branches to build complex, state-aware workflows. • 𝗗𝗮𝘁𝗮 𝗔𝘄𝗮𝗿𝗲𝗻𝗲𝘀𝘀: Before it even attempts a query, Elysia performs a full analysis of your data collections. This eliminates the blind search problem plaguing most RAG systems and allows for far more complex and accurate query generation. • 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗗𝗮𝘁𝗮 𝗗𝗶𝘀𝗽𝗹𝗮𝘆𝘀: Your RAG pipeline shouldn't be limited to text, right? That’s why Elysia analyzes each query's results and chooses the best way to display them, from tables and charts to product cards and GitHub tickets. It also features a comprehensive data explorer with search, sorting, and filtering capabilities. • 𝗛𝘆𝗽𝗲𝗿-𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘃𝗶𝗮 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸: It uses your positively-rated queries as few-shot examples to improve future responses. This allows you to use smaller, faster models that perform like larger ones over time, cutting costs without sacrificing quality for most use cases. • 𝗖𝗵𝘂𝗻𝗸-𝗢𝗻-𝗗𝗲𝗺𝗮𝗻𝗱: Elysia chunks documents at query time. It performs initial searches on document-level vectors and only chunks relevant documents on the fly, storing them in a parallel quantized collection with cross references for future use. 𝗧𝗵𝗲 𝗦𝘁𝗮𝗰𝗸 Elysia is built from scratch on Weaviate, using its native features like named vectors, a variety of search types, filters, cross references, quantization, etc. It uses DSPy for LLM interactions and is delivered as a production-ready application via FastAPI, serving a NextJS frontend as static HTML. Also available as a Python package via pip: 𝗽𝗶𝗽 𝗶𝗻𝘀𝘁𝗮𝗹𝗹 𝗲𝗹𝘆𝘀𝗶𝗮-𝗮𝗶 Type: 𝗲𝗹𝘆𝘀𝗶𝗮 𝘀𝘁𝗮𝗿𝘁 Connect your Weaviate cluster and go explore what’s possible.

This will retire 90% of RAG systems with dignity (and a sad song playlist). Powered by DSPy: If you're still building "text in, text out" chatbots that only perform blind vector and text searches, you're not gonna make it! My team just dropped Elysia, and it's not just an incremental successor to Verba… It's a whole rethink of how we interact with our data using AI. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗘𝗹𝘆𝗶𝘀𝗮? An open-source platform for building agentic RAG architectures. It learns from your preferences, intelligently categorizes, labels, and searches through your data, and provides complete transparency into its decision-making process. The long & exciting feature list: • 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝘁 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗧𝗿𝗲𝗲 𝗔𝗴𝗲𝗻𝘁𝘀: Elysia’s core is a customizable decision tree, and it visualizes its entire reasoning process, showing you why it chooses a specific tool or path. It enables advanced error handling, self-healing from failed queries, and prevents infinite loops. You can also add custom tools and branches to build complex, state-aware workflows. • 𝗗𝗮𝘁𝗮 𝗔𝘄𝗮𝗿𝗲𝗻𝗲𝘀𝘀: Before it even attempts a query, Elysia performs a full analysis of your data collections. This eliminates the blind search problem plaguing most RAG systems and allows for far more complex and accurate query generation. • 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗗𝗮𝘁𝗮 𝗗𝗶𝘀𝗽𝗹𝗮𝘆𝘀: Your RAG pipeline shouldn't be limited to text, right? That’s why Elysia analyzes each query's results and chooses the best way to display them, from tables and charts to product cards and GitHub tickets. It also features a comprehensive data explorer with search, sorting, and filtering capabilities. • 𝗛𝘆𝗽𝗲𝗿-𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘃𝗶𝗮 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸: It uses your positively-rated queries as few-shot examples to improve future responses. This allows you to use smaller, faster models that perform like larger ones over time, cutting costs without sacrificing quality for most use cases. • 𝗖𝗵𝘂𝗻𝗸-𝗢𝗻-𝗗𝗲𝗺𝗮𝗻𝗱: Elysia chunks documents at query time. It performs initial searches on document-level vectors and only chunks relevant documents on the fly, storing them in a parallel quantized collection with cross references for future use. 𝗧𝗵𝗲 𝗦𝘁𝗮𝗰𝗸 Elysia is built from scratch on Weaviate, using its native features like named vectors, a variety of search types, filters, cross references, quantization, etc. It uses DSPy for LLM interactions and is delivered as a production-ready application via FastAPI, serving a NextJS frontend as static HTML. Also available as a Python package via pip: 𝗽𝗶𝗽 𝗶𝗻𝘀𝘁𝗮𝗹𝗹 𝗲𝗹𝘆𝘀𝗶𝗮-𝗮𝗶 Type: 𝗲𝗹𝘆𝘀𝗶𝗮 𝘀𝘁𝗮𝗿𝘁 Connect your Weaviate cluster and go explore what’s possible.

Philip Vollet

93,615 Aufrufe • vor 1 Jahr

Every automation expert has shipped a workflow, then found out it broke when the client did. APIs time out. Credentials expire. A node gets a value it wasn't built for. The question was never "will it fail," it's "how fast do I find out." So I built a self-fixing system for n8n. When any workflow fails, Claude Code reads the broken workflow, finds the root cause, and sends me a Slack message with 4 buttons: → Auto Fix: Claude applies the fix it proposed, validates it, and saves → Replay: direct links to re-run a workflow that just hit a temporary glitch → Custom Fix: a form where I type the change in plain English and Claude applies it → Decline: logs the error, changes nothing THE STACK - n8n Error Trigger to catch every failure - Claude Code with the n8n-mcp server for full workflow access - ngrok to connect n8n cloud to my machine - Slack as the approval layer The result: workflows that diagnose and repair themselves while I sleep, with me still approving every change before it goes live. Watch the full video here: The complete PDF guide are linked in the video description, ready to download. You can also drop a comment and I'll send them over. If this is useful, a like, follow, and subscribe goes a long way. Follow for more on building production AI automation. #n8n #Automation #AIAgents #ClaudeAI #BuildInPublic

Every automation expert has shipped a workflow, then found out it broke when the client did. APIs time out. Credentials expire. A node gets a value it wasn't built for. The question was never "will it fail," it's "how fast do I find out." So I built a self-fixing system for n8n. When any workflow fails, Claude Code reads the broken workflow, finds the root cause, and sends me a Slack message with 4 buttons: → Auto Fix: Claude applies the fix it proposed, validates it, and saves → Replay: direct links to re-run a workflow that just hit a temporary glitch → Custom Fix: a form where I type the change in plain English and Claude applies it → Decline: logs the error, changes nothing THE STACK - n8n Error Trigger to catch every failure - Claude Code with the n8n-mcp server for full workflow access - ngrok to connect n8n cloud to my machine - Slack as the approval layer The result: workflows that diagnose and repair themselves while I sleep, with me still approving every change before it goes live. Watch the full video here: The complete PDF guide are linked in the video description, ready to download. You can also drop a comment and I'll send them over. If this is useful, a like, follow, and subscribe goes a long way. Follow for more on building production AI automation. #n8n #Automation #AIAgents #ClaudeAI #BuildInPublic

Gbenga Akindolani |AI Engineer | Automation Expert

46,436 Aufrufe • vor 3 Monaten

Claude Code can now make full videos from your terminal.. Not slideshows. Not text on screen.. Actual motion graphics with animations, transitions, custom photos, and background music. [ SHARED A TUTORIAL BELOW EDITED WITH THIS SETUP IN JUST 5mins ] ▫️Here's the setup: Claude Code + Remotion Remotion is a React based framework that renders video programmatically. You describe what you want in plain English, Claude writes the React components and Remotion renders it into a real MP4. What you can actually do with this: > Generate 9:16 vertical videos for TikTok / Reels / Shorts > Add animated text with viral hooks and safe zones > Pull live web screenshots directly into your scenes using Chrome MCP > Fact-check your content in real time with Perplexity MCP > Drop in your own photos and background music > Edit existing talking-head footage cut bloopers, add captions > Schedule posts to your socials straight from the terminal ▫️How to set it up (takes 5 minutes) : > Make sure you have Node.js installed ( node -v to check ) > Create a new Remotion project: npx create-video@latest Pick the Blank template, enable TailwindCSS, and install the Skills package when prompted. > Install dependencies: cd my-video npm install > Start the preview server: npm run dev > Open Claude Code in the same project folder: cd my-video claude That's it. You can now prompt videos in plain English. If you already have a Remotion project, just add the skill directly: npx skills add remotion-dev/skills This drops a SKILL.md into your project that gives Claude expert knowledge of Remotion.. animations, compositions, captions, assets, 3D content everything. Example prompt you can steal: "Create a 30-second 9:16 vertical video about the top 3 AI tools this week. Use animated text with a hook in the first 2 seconds. Add smooth transitions between scenes. Keep text in the safe zone for TikTok. Use a dark tech aesthetic with blue accent colors." Claude writes all the React code, renders a preview, you tweak with natural language, and export when ready. The crazy part is this whole pipeline is local, free (minus your Claude sub), and you never open a video editor. imo this kills CapCut for anyone making info-style content. You describe the video in English and get back a rendered MP4. try it now.

Claude Code can now make full videos from your terminal.. Not slideshows. Not text on screen.. Actual motion graphics with animations, transitions, custom photos, and background music. [ SHARED A TUTORIAL BELOW EDITED WITH THIS SETUP IN JUST 5mins ] ▫️Here's the setup: Claude Code + Remotion Remotion is a React based framework that renders video programmatically. You describe what you want in plain English, Claude writes the React components and Remotion renders it into a real MP4. What you can actually do with this: > Generate 9:16 vertical videos for TikTok / Reels / Shorts > Add animated text with viral hooks and safe zones > Pull live web screenshots directly into your scenes using Chrome MCP > Fact-check your content in real time with Perplexity MCP > Drop in your own photos and background music > Edit existing talking-head footage cut bloopers, add captions > Schedule posts to your socials straight from the terminal ▫️How to set it up (takes 5 minutes) : > Make sure you have Node.js installed ( node -v to check ) > Create a new Remotion project: npx create-video@latest Pick the Blank template, enable TailwindCSS, and install the Skills package when prompted. > Install dependencies: cd my-video npm install > Start the preview server: npm run dev > Open Claude Code in the same project folder: cd my-video claude That's it. You can now prompt videos in plain English. If you already have a Remotion project, just add the skill directly: npx skills add remotion-dev/skills This drops a SKILL.md into your project that gives Claude expert knowledge of Remotion.. animations, compositions, captions, assets, 3D content everything. Example prompt you can steal: "Create a 30-second 9:16 vertical video about the top 3 AI tools this week. Use animated text with a hook in the first 2 seconds. Add smooth transitions between scenes. Keep text in the safe zone for TikTok. Use a dark tech aesthetic with blue accent colors." Claude writes all the React code, renders a preview, you tweak with natural language, and export when ready. The crazy part is this whole pipeline is local, free (minus your Claude sub), and you never open a video editor. imo this kills CapCut for anyone making info-style content. You describe the video in English and get back a rendered MP4. try it now.

Axel Bitblaze 🪓

31,250 Aufrufe • vor 5 Monaten

-> someone cloned claude -> design interface and -> made it completely free -> it's work on YouTube -> and also suitable for kids -> it’s called open design -> and it’s live on github -> same clean split-screen ui -> you get in claude artifacts -> prompt on the left, live -> design/code preview on -> the right, type what you -> want to build and it -> generates the ui in real -> time, but here’s the twist -> you pick the ai model -> not locked into one -> company, want to use -> gemini, mistral, llama, -> deepseek any model -> with an api work -> if you’re running local -> models with ollama -> that works too -> no subscription walls -> the big difference -> vs claude artifacts -> works with any free -> ai model you’re not -> paying $20/mo just to -> design, use free tiers -> local models, or whatever -> you already have access to -> fully local, your prompts -> and code never leave -> your machine unless -> you want them to -> no data training -> no cloud storage -> privacy by default -> no usage limits -> claude cuts you off -> after a few designs -> here you can generate, -> iterate, break things -> and rebuild all day -> the only limit is your -> don’t like how a button -> works, change it -> want to add your own -> components, go ahead -> you own the tool -> so if you’ve been gatekept -> by paywalls or worried -> about sensitive prompts -> going to some company’s -> servers, this fixes that. -> same workflow, more -> control, zero monthly fee

-> someone cloned claude -> design interface and -> made it completely free -> it's work on YouTube -> and also suitable for kids -> it’s called open design -> and it’s live on github -> same clean split-screen ui -> you get in claude artifacts -> prompt on the left, live -> design/code preview on -> the right, type what you -> want to build and it -> generates the ui in real -> time, but here’s the twist -> you pick the ai model -> not locked into one -> company, want to use -> gemini, mistral, llama, -> deepseek any model -> with an api work -> if you’re running local -> models with ollama -> that works too -> no subscription walls -> the big difference -> vs claude artifacts -> works with any free -> ai model you’re not -> paying $20/mo just to -> design, use free tiers -> local models, or whatever -> you already have access to -> fully local, your prompts -> and code never leave -> your machine unless -> you want them to -> no data training -> no cloud storage -> privacy by default -> no usage limits -> claude cuts you off -> after a few designs -> here you can generate, -> iterate, break things -> and rebuild all day -> the only limit is your -> don’t like how a button -> works, change it -> want to add your own -> components, go ahead -> you own the tool -> so if you’ve been gatekept -> by paywalls or worried -> about sensitive prompts -> going to some company’s -> servers, this fixes that. -> same workflow, more -> control, zero monthly fee

BeingInvested

12,134 Aufrufe • vor 3 Monaten

google just released 15 AI tools that are completely FREE and can save thousands of $$$ every single monthly. all open-source. MIT licensed. save this in your bookmark." 1️⃣ pomelli ( builds your entire brand identity from just your website URL, then generates on-brand social posts, campaigns, and images. a free jasper + a junior brand marketer. no watermark, no gen cap in beta. 2️⃣ stitch ( describe an interface, get production-ready HTML/CSS/Tailwind + a figma export. google's free figma killer. 350 designs a month without paying a cent. 3️⃣ opal ( build no-code AI mini-apps and multi-step workflows just by describing them in plain english. basically a free n8n with Gemini baked in. no usage caps. 4️⃣ antigravity ( agentic IDE that plans, edits across files, and builds full apps from a single prompt. the "cursor-killer," free tier runs Gemini 3 Pro + Claude Sonnet 4.5. 5️⃣ mixboard ( canva x pinterest for AI. generate and remix images into moodboards, then edit right on the canvas with plain language. free while in beta. 6️⃣ disco ( turns your messy open browser tabs into custom interactive AI apps. competitor tabs become a comparison matrix, travel tabs become an itinerary. zero code. 7️⃣ notebookLM ( upload PDFs, videos, and notes, get instant summaries, mind maps, quizzes, even a podcast of your own material. replaces notion AI + perplexity + readwise. 8️⃣ Learn Your Way ( turns any topic into a personalized, AI-built course. immersive text, audio lessons, mind maps, and quizzes adapted to how you actually learn. free tutoring. 🔟 Google AI Studio ( prototype and ship AI apps in seconds with a free API key and a 1M-token context window. replaces the openai playground + paid API credits. 1️⃣1️⃣ Jules ( assign it a github issue, it spins up a VM, writes a plan, makes the changes, and opens a PR. a free devin. 15 tasks a day. 1️⃣2️⃣ Gemini CLI ( claude-code in your terminal. reads your codebase, runs commands, ships PRs. genuinely open source (Apache 2.0) and free. 1️⃣3️⃣ Code Wiki ( point it at any public github repo, get a living, self-updating wiki with architecture diagrams and a Gemini chat, every section hyperlinked to the code. 1️⃣4️⃣ Firebase Studio ( AI cockpit for your backend and cloud logic. heads up: existing users only, google is winding it down, so don't start a new project here. 1️⃣5️⃣ Gemini Code Assist ( free github copilot: 180k code completions a month + AI code reviews in VS Code, JetBrains, and github. the free tier that actually out-specs copilot. Follow me and turn on 🔔 post notifications.

m0h

87,330 Aufrufe • vor 1 Monat

is our AI project to make computing feel more human L A N D E R Here are the 4 best demo videos of the magic of DATA in action. DATA is a personalized assistant who knows and remembers every conversation you have with it accross your iPhone, Mac, iPad, Watch, Texts, Emails, and HomePods. You can talk to DATA right in your AirPods or text it just like a person. DATA can read, write, understand, speak any language, and translate between them. It can help with real work and home life tasks like research, writing, scheduling, reminders, and triage. And it's easily customizable so you can have DATA automatically do whatever you want whenever you want with just a few taps and natural language instructions - no code required. DATA can do just about anything you can do on your phone on your behalf automatically including very advanced things Siri can't, like summarizing, analyzing, and drafting replies or writing documents. It can read web pages, texts or emails you show it, or PDFs of any kind. It can do other real world tasks that require complex analysis and common sense too, like: - figure out where the nearest beach is (even when you're in Colorado) and instantly fetch the current surf report up to the current minute. - summarize and drafting replies to entire email chains - plan out entire work projects or multi-day vacations on your calendar - sketch out ideas for you in picture form or drafting Notion pages with charts and graphs. DATA can also use its own judgement to determine when to run an action or not, even if you've scheduled it, allowing you to make VERY complex automations that require many different inputs to make a decision, like for example: - only opening the blinds on your lunch break if it's sunny out and you're working from home. DATA works natively and easily with Apple HomeKit & other shortcuts. DATA can also take initiative and check in with you throughout the day by voice or text and proactively send messages to you and others on your behalf based on your personal and professional goals, current tasks, and calendar. DATA can integrate with many apps on your phone, and is compatible with multiple large AI language models. I've gotten to make a few demo videos that I think really capture how powerful DATA can be for every day life. Here they are all in one tweet. Make sure your sound is on as you watch them. 1. This is the first demo video I ever made from April 19th, 2023. It walks through all the ways you can interact with and use the DATA shortcuts. Everything from saying "Hey Siri" to tapping on custom apps on your home-screen. 2. The second demo video was made May 5 and is an example use case I made of how commands work - commands allow DATA to actually run actions on your phone like taking pictures and sending messages. This demo shows me taking a picture of an email template, and data drafting an email based on that template. It's gotten much better at realizing when it has just run a command and incorporating that information naturally into the conversation now, especially on GPT-4. 3. This third Commands video, May 12 is a walkthrough of ALL the phone functions that commands allow DATA to do: sending texts and emails, making pictures, seeing pictures, reading things, and scheduling events. Since this video we've added auto-replies to texts and emails, summarizing documents, writing documents, health app data retrieval, web surfing, scheduling alarms, making playlists, and more. 4. This last demo I made today, June 15, shows everything DATA does working in concert to generate a crazy detailed morning briefing with background music - including making a unique playlist and giving a detailed analysis of current events complete with Ski & Surf conditions near me other live information from the internet. So now that you've seen everything DATA can do, what's the coolest feature? What features should we add? What would you use DATA for first?

is our AI project to make computing feel more human L A N D E R Here are the 4 best demo videos of the magic of DATA in action. DATA is a personalized assistant who knows and remembers every conversation you have with it accross your iPhone, Mac, iPad, Watch, Texts, Emails, and HomePods. You can talk to DATA right in your AirPods or text it just like a person. DATA can read, write, understand, speak any language, and translate between them. It can help with real work and home life tasks like research, writing, scheduling, reminders, and triage. And it's easily customizable so you can have DATA automatically do whatever you want whenever you want with just a few taps and natural language instructions - no code required. DATA can do just about anything you can do on your phone on your behalf automatically including very advanced things Siri can't, like summarizing, analyzing, and drafting replies or writing documents. It can read web pages, texts or emails you show it, or PDFs of any kind. It can do other real world tasks that require complex analysis and common sense too, like: - figure out where the nearest beach is (even when you're in Colorado) and instantly fetch the current surf report up to the current minute. - summarize and drafting replies to entire email chains - plan out entire work projects or multi-day vacations on your calendar - sketch out ideas for you in picture form or drafting Notion pages with charts and graphs. DATA can also use its own judgement to determine when to run an action or not, even if you've scheduled it, allowing you to make VERY complex automations that require many different inputs to make a decision, like for example: - only opening the blinds on your lunch break if it's sunny out and you're working from home. DATA works natively and easily with Apple HomeKit & other shortcuts. DATA can also take initiative and check in with you throughout the day by voice or text and proactively send messages to you and others on your behalf based on your personal and professional goals, current tasks, and calendar. DATA can integrate with many apps on your phone, and is compatible with multiple large AI language models. I've gotten to make a few demo videos that I think really capture how powerful DATA can be for every day life. Here they are all in one tweet. Make sure your sound is on as you watch them. 1. This is the first demo video I ever made from April 19th, 2023. It walks through all the ways you can interact with and use the DATA shortcuts. Everything from saying "Hey Siri" to tapping on custom apps on your home-screen. 2. The second demo video was made May 5 and is an example use case I made of how commands work - commands allow DATA to actually run actions on your phone like taking pictures and sending messages. This demo shows me taking a picture of an email template, and data drafting an email based on that template. It's gotten much better at realizing when it has just run a command and incorporating that information naturally into the conversation now, especially on GPT-4. 3. This third Commands video, May 12 is a walkthrough of ALL the phone functions that commands allow DATA to do: sending texts and emails, making pictures, seeing pictures, reading things, and scheduling events. Since this video we've added auto-replies to texts and emails, summarizing documents, writing documents, health app data retrieval, web surfing, scheduling alarms, making playlists, and more. 4. This last demo I made today, June 15, shows everything DATA does working in concert to generate a crazy detailed morning briefing with background music - including making a unique playlist and giving a detailed analysis of current events complete with Ski & Surf conditions near me other live information from the internet. So now that you've seen everything DATA can do, what's the coolest feature? What features should we add? What would you use DATA for first?

steve

640,176 Aufrufe • vor 3 Jahren