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gradio.Server Any Custom Frontend with Gradio's Backend build with your own frontend framework entirely like React, Svelte, or even plain HTML/JS, while still benefiting from Gradio's queuing system, API infrastructure, MCP support, and ZeroGPU on Spaces blog:

AK

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Today, we're joining Google's release of A2UI v0.9 🎉 Declarative Generative UI with your own design system. Works with any AG-UI Agent. Your agents describes UI via JSON, your frontend renders it using your components catalog like lego building blocks UI is alive and dead. CLI for agents, Generative UI for humans. Try it out: npx copilotkit@latest create my-app --framework a2ui

Today, we're joining Google's release of A2UI v0.9 🎉 Declarative Generative UI with your own design system. Works with any AG-UI Agent. Your agents describes UI via JSON, your frontend renders it using your components catalog like lego building blocks UI is alive and dead. CLI for agents, Generative UI for humans. Try it out: npx copilotkit@latest create my-app --framework a2ui

Atai Barkai

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🤔 Imagine if your backend worked like `useState`. No API calls. No fetching. Just reactive, real-time state that syncs across devices. That’s what InstantDB is doing. With Instant your frontend gets a real-time database. You write queries that stay in sync and work offline. Every save updates immediately, and it comes with built-in auth and permissions. See how InstantDB looks in action in this deeply technical blog post from Stopa ↓

🤔 Imagine if your backend worked like `useState`. No API calls. No fetching. Just reactive, real-time state that syncs across devices. That’s what InstantDB is doing. With Instant your frontend gets a real-time database. You write queries that stay in sync and work offline. Every save updates immediately, and it comes with built-in auth and permissions. See how InstantDB looks in action in this deeply technical blog post from Stopa ↓

Expo

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This is what you get running H3 on a single H100. Stack: - ComfyUI + official H3 T2V workflow - H3 ComfyUI pruned BF16 - GPU H100, 80GB - 768p, 10-second video cost $1 - Average generation time: ~14 minutes This kind of deployment makes sense if you want to build and run your own system or custom services. If you don’t want to bother with the infrastructure, just use an API. Generated this video for testing.

This is what you get running H3 on a single H100. Stack: - ComfyUI + official H3 T2V workflow - H3 ComfyUI pruned BF16 - GPU H100, 80GB - 768p, 10-second video cost $1 - Average generation time: ~14 minutes This kind of deployment makes sense if you want to build and run your own system or custom services. If you don’t want to bother with the infrastructure, just use an API. Generated this video for testing.

DΞV

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i'm too stubborn to simply give up on the concept of Benji after almost 10 years(!!) of iterating on it with different stacks... 2018: graphql backend + react SPA 2019: made a react native app for 6 months 2020: gave up on it and wrote 3 years of using other bs tools and being grumpy about them 2023: rewrote it in blitz js (JUGE mistake) 2024: iterate on react native + PWA + RN pwa wrapper 2025: time for a rewrite to Zero To Shipped ⛴️ stack (but next js sucks for this kind of app, add api, mcp, cross platform app, and many other things 2026: i want it all actions INSTANT AND FAST AF and next js is the wrong tech choice for a mostly client app, so i'm starting a rewrite with TANSTACK + Convex + Better Auth it feels so snappy 😭 btw 99% of the customers abandoned it, there are like 3 ride or die fans but i know i can turn it around!!!! let /goal cook.

i'm too stubborn to simply give up on the concept of Benji after almost 10 years(!!) of iterating on it with different stacks... 2018: graphql backend + react SPA 2019: made a react native app for 6 months 2020: gave up on it and wrote 3 years of using other bs tools and being grumpy about them 2023: rewrote it in blitz js (JUGE mistake) 2024: iterate on react native + PWA + RN pwa wrapper 2025: time for a rewrite to Zero To Shipped ⛴️ stack (but next js sucks for this kind of app, add api, mcp, cross platform app, and many other things 2026: i want it all actions INSTANT AND FAST AF and next js is the wrong tech choice for a mostly client app, so i'm starting a rewrite with TANSTACK + Convex + Better Auth it feels so snappy 😭 btw 99% of the customers abandoned it, there are like 3 ride or die fans but i know i can turn it around!!!! let /goal cook.

kitze · supermac.io 🐦‍🔥

16,580 görüntüleme • 3 ay önce

A CHINESE GUY STOPPED PAYING WEB DESIGNERS $1,800 PER LANDING PAGE AND BUILT THE SAME KIND OF SITE WITH CLAUDE CODE IN ONE AFTERNOON FOR LESS THAN $70 claude was not just writing code. it was doing the job of a designer, copywriter and frontend dev in one window. in 4 hours, one rough idea turned into the layout, color system, font choices, page sections and the full html/css/js build the real trick was the references. he gave claude 5 screenshots, made it ask 7 questions first, then pushed it toward one clear visual direction instead of accepting another generic ai-looking template the first version already looked solid. the second pass made it feel expensive: better typography, a darker palette, mobile cleanup, cursor effects, 6 micro-interactions and custom hero visuals his old workflow was burning $1,200 on design, $500 on frontend work and another $150 on small fixes every time he needed a new page. now the whole test costs less than $70 and the site still looks like something a $5,000 agency would ship the edge is not “ai builds websites.” the edge is that one person can now brief, critique, polish and launch in one afternoon without waiting 10 days for a designer to send version one

A CHINESE GUY STOPPED PAYING WEB DESIGNERS $1,800 PER LANDING PAGE AND BUILT THE SAME KIND OF SITE WITH CLAUDE CODE IN ONE AFTERNOON FOR LESS THAN $70 claude was not just writing code. it was doing the job of a designer, copywriter and frontend dev in one window. in 4 hours, one rough idea turned into the layout, color system, font choices, page sections and the full html/css/js build the real trick was the references. he gave claude 5 screenshots, made it ask 7 questions first, then pushed it toward one clear visual direction instead of accepting another generic ai-looking template the first version already looked solid. the second pass made it feel expensive: better typography, a darker palette, mobile cleanup, cursor effects, 6 micro-interactions and custom hero visuals his old workflow was burning $1,200 on design, $500 on frontend work and another $150 on small fixes every time he needed a new page. now the whole test costs less than $70 and the site still looks like something a $5,000 agency would ship the edge is not “ai builds websites.” the edge is that one person can now brief, critique, polish and launch in one afternoon without waiting 10 days for a designer to send version one

Gipp 🦅

296,481 görüntüleme • 3 ay önce

more frontend vibecoding tips (results below): WHY YOUR VIBECODED FRONTENDS ALL LOOK THE SAME AND SUCK: when asked to make a frontend, the agent/llm will default to the center/average of its training data (in a very loose sense). through the training process, the model essentially converges on some default UI style. it's very capable of doing things that are different from this style, but you have to ask! for instance, ChatGPT tends to reply in the same tone for all users untill you interact with it and instruct it differently ("be sassy", "eli5"). the second reason is that most of us are not good at coming up with designs and describing them precisely (see my tweet on a crash course in common components, which i'll link below). treat frontend generation just like any other eng task! you need to provide a good detailed spec. TIPS: 1. give ur agent screenshots of designs you like (you may not know the right words to describe them but the agent will! a pic = 1000 words) where to find ui inspo? Behance, Dribbble, Mobbin (Mobbin is paid but worth it!) 2. ask ur agent for proposals, this helps "seed" different directions so the final frontend stands out. don't be afraid to go back and forth. 3. ban certain tendencies: no Inter/Roboto, no shadcn (controversial), no gradients, no emojis 4. encourage the agent to be extreme and make bold decisions, not safe ones. i think that the underlying models tend to get taught during RL/fine-tuning to make conservative choices that produce reasonable but boring frontends 5. give ur agent Figma MCP. the best results will come if you mockup your vision in Figma first. 6. Ideally choose an agent with vision capabilities TLDR: Most people are tremendously underusing agents for frontend design. They are much better than you might expect.

more frontend vibecoding tips (results below): WHY YOUR VIBECODED FRONTENDS ALL LOOK THE SAME AND SUCK: when asked to make a frontend, the agent/llm will default to the center/average of its training data (in a very loose sense). through the training process, the model essentially converges on some default UI style. it's very capable of doing things that are different from this style, but you have to ask! for instance, ChatGPT tends to reply in the same tone for all users untill you interact with it and instruct it differently ("be sassy", "eli5"). the second reason is that most of us are not good at coming up with designs and describing them precisely (see my tweet on a crash course in common components, which i'll link below). treat frontend generation just like any other eng task! you need to provide a good detailed spec. TIPS: 1. give ur agent screenshots of designs you like (you may not know the right words to describe them but the agent will! a pic = 1000 words) where to find ui inspo? Behance, Dribbble, Mobbin (Mobbin is paid but worth it!) 2. ask ur agent for proposals, this helps "seed" different directions so the final frontend stands out. don't be afraid to go back and forth. 3. ban certain tendencies: no Inter/Roboto, no shadcn (controversial), no gradients, no emojis 4. encourage the agent to be extreme and make bold decisions, not safe ones. i think that the underlying models tend to get taught during RL/fine-tuning to make conservative choices that produce reasonable but boring frontends 5. give ur agent Figma MCP. the best results will come if you mockup your vision in Figma first. 6. Ideally choose an agent with vision capabilities TLDR: Most people are tremendously underusing agents for frontend design. They are much better than you might expect.

andrew gao

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LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

Avi Chawla

30,932 görüntüleme • 9 ay önce

Usually when I save a website URL it's because -I want to save the website design exactly how it is in that point in time -I want to know what frontend/animation trickery they did whether its just raw code or some framework so i made a site where I just drop the url -> get a screenshot + screen recording to capture any animations I found interesting a non-trivial amount of my notion links don't resonate with me due to redesigns and I think this is the simplest fix. Just like my notion list it lives in a browser tab and is still paste->enter->move on

Usually when I save a website URL it's because -I want to save the website design exactly how it is in that point in time -I want to know what frontend/animation trickery they did whether its just raw code or some framework so i made a site where I just drop the url -> get a screenshot + screen recording to capture any animations I found interesting a non-trivial amount of my notion links don't resonate with me due to redesigns and I think this is the simplest fix. Just like my notion list it lives in a browser tab and is still paste->enter->move on

Sabina

38,649 görüntüleme • 5 ay önce

THIS STUDENT WAS VIBE CODING AN APP, THEN GOT A $55,444.78 BILL FROM GOOGLE CLOUD All because they accidentally pushed their Gemini API key to GitHub They thought the repository was private It was just a small side project, and they still had $220 in free credits left By the time they checked their email, it was already too late This video shows exactly how things like this happen and why more and more developers are running into the same problem: > One commit turned into a $55k nightmare > API keys were exposed in frontend code and even inside app binaries > People hardcoded secrets into scripts and ended up with hundreds of dollars in charges within hours > One OpenAI key was abused nearly a million times before anyone noticed Never hardcode API keys Never commit them to GitHub, even if the repository is private Never expose them in your frontend Always use environment variables and set up spending alerts Even in the era of vibe coding, security still matters Knowing a few basic best practices can save you from some very expensive mistakes If you’re a vibe coder, make sure to read the article I attached, you’ll find plenty of practical tips that could save you a lot of trouble Save this post so you don’t lose it

THIS STUDENT WAS VIBE CODING AN APP, THEN GOT A $55,444.78 BILL FROM GOOGLE CLOUD All because they accidentally pushed their Gemini API key to GitHub They thought the repository was private It was just a small side project, and they still had $220 in free credits left By the time they checked their email, it was already too late This video shows exactly how things like this happen and why more and more developers are running into the same problem: > One commit turned into a $55k nightmare > API keys were exposed in frontend code and even inside app binaries > People hardcoded secrets into scripts and ended up with hundreds of dollars in charges within hours > One OpenAI key was abused nearly a million times before anyone noticed Never hardcode API keys Never commit them to GitHub, even if the repository is private Never expose them in your frontend Always use environment variables and set up spending alerts Even in the era of vibe coding, security still matters Knowing a few basic best practices can save you from some very expensive mistakes If you’re a vibe coder, make sure to read the article I attached, you’ll find plenty of practical tips that could save you a lot of trouble Save this post so you don’t lose it

Bonsai 🌳

110,437 görüntüleme • 2 ay önce

I’ve been craving a video editor with motion baked in, designed to work with my own AI agents. Claude, Codex, whatever I want to use. I don’t want to be blocked by someone else’s credit system for every little interaction. I also wanted a Figma-like canvas/editor for when I want to jump in and tweak any little detail. So we built it: Video & audio editing: cut, zoom, speed up, add B-roll. Motion, animation, 3D, custom shaders & effects, custom 3D models, dynamic components & templates, audio and beat matching. And it’s all programmable. Design your own assets directly on the canvas, bring them in from Figma or the web, or just let the agent find them, mock them up, or record what it needs automatically. You can even drop in your screen recordings and just let loose. Supercut users: yes, it’ll have first-class support for your recordings, but it’ll work with anything. I’m going to be dropping a lot more examples and tutorials, so follow along. DM me for early access if you’re willing to give feedback. We’ll open it up to everyone very soon.

I’ve been craving a video editor with motion baked in, designed to work with my own AI agents. Claude, Codex, whatever I want to use. I don’t want to be blocked by someone else’s credit system for every little interaction. I also wanted a Figma-like canvas/editor for when I want to jump in and tweak any little detail. So we built it: Video & audio editing: cut, zoom, speed up, add B-roll. Motion, animation, 3D, custom shaders & effects, custom 3D models, dynamic components & templates, audio and beat matching. And it’s all programmable. Design your own assets directly on the canvas, bring them in from Figma or the web, or just let the agent find them, mock them up, or record what it needs automatically. You can even drop in your screen recordings and just let loose. Supercut users: yes, it’ll have first-class support for your recordings, but it’ll work with anything. I’m going to be dropping a lot more examples and tutorials, so follow along. DM me for early access if you’re willing to give feedback. We’ll open it up to everyone very soon.

Neil

23,042 görüntüleme • 26 gün önce

Monthly WINR Protocol Development Update: To begin with, the WINR Protocol has distributed $900,000 to token holders, generated more than $500,000 in pure profit for liquidity providers on WLP, acquired more than 5,000 users, and has almost 9% of the supply burned. In the upcoming months, the WINR Protocol, which has been in production for years, will introduce a range of new products and deployments. These developments will represent the practical and technical evolution to V2 of the protocol. Here are the latest updates and further details as they progress: Progress on WINR Bonanza, Casino Hold'em, and Blackjack is nearing completion. These games are in the final stages of testing. Additional games, including a new type of crash game, have been finalized and are set to debut with the JustBet v2 launch. Take a look at the gameplay videos for a preview. These games achieve the long-term goal of providing a full-suite WINR Game Engine SDK, which can be used to build games with complex logic on-chain with modular smart contract infrastructure. For example, any grid slot game that dominates the iGaming industry could easily be developed on-chain using the WINR Bonanza SDK. - Permissionless Frontend Operator SDK Dashboard Release: March is poised to be a milestone month with the launch of the Frontend Operator SDK dashboards. These dashboards will enable any WINR Labs game to be seamlessly deployed on frontends, marking a significant advancement in protocol accessibility and integration for future games developed by independent iGaming developers. The frontend operator can deploy any game they choose through a few simple steps while utilizing 10,000 WINR per game via the WINR Game Factory smart contract. Each operator is assigned a unique smart contract address(es) for every game they deploy, allowing their revenue to be tracked independently. The deployment process includes instructions on integrating the game as a package into the operator's frontend. In subsequent phases, the games will transition through WINR Chain, streamlining user onboarding steps like wallet connection and token bridging to Arbitrum. This abstraction will make it easy for any web2/web3 platform on any chain to seamlessly integrate WINR-based games with just a few clicks. The new budget system changes how the revenue is calculated on the protocol and will see daylight with frontend operator, Solana, and Fantom deployments. This model was first tested with a lightweight version on and gave a lot of actionable feedback. Shifting from the existing bribe model, which in practice distributes almost half of the edge of the games in volume to WINR holders, the brand-new budget system checks the profitability of WLP. It distributes a larger part of the profit to game providers, frontend operators, and, most importantly, WINR holders. Any time a game's budget is in profit, a part of every loss is distributed to stakeholders. Here is an example: 1. The WINR Bonanza Game has a 10,000 budget for a frontend operator. 2. Let's assume the bet amount was $50, and Bonanza paid back $10 on that spin. That leaves $40 of pure profit. 3. This is distributed amongst 50% to WLP, 20% to frontend operators, 20% to WINR holders, and 10% to game providers. 4. To achieve this, V2 of WINR Liquidity Engine (WLP) will have a buffer for purchasing and selling, working in epochs to determine the above distribution and math. - Solana Deployment and Expansions: Solana audits are in their final phase, and frontend tests are ongoing. Solana launch will be alongside the V2 launch of @JustBetOfficial, with a chain switch available on the top bar. The VRF system WINR developed already is seeing requests from builders around the Solana ecosystem, and this will over time add an extra layer of income to the protocol. Solana's bankroll, at first, will be a lighter version of WLP but will inherit the above-mentioned budgeting system to generate income immediately upon launch. - Fantom Deployment and Expansions: Fantom's upcoming Sonic upgrade, with its 200ms finality and fast block production is a perfect chain for WINR Protocol to expand. Through the partnership with WINR Protocol will tap into a brand new user base on Fantom. The bankroll on Fantom will consist of FTM and stables. The launch is planned for late March or early April. This expansion aims to open up new markets and collaborations with fresh teams. which operates independently, will integrate a broad spectrum of WINR technologies, including WINR Account Abstraction, WINR VRF, and WINR games, marking a pivotal step in WINR Protocol’s journey of horizontal expansion. - XAI VRF Deployment Progress Update: The WINR Account Abstraction Wallet and WINR Verifiable Random Function (VRF) deployment on the XAI 🎮⛓️ is well underway, with the majority of the work completed. This step forward showcases WINR's expansion beyond gambling and trading, highlighting the protocol's adaptability and commitment to broadening decentralized services. The process to automize and permissionlessly let game developers start using WINR VRF by paying (and burning) fees in WINR will launch alongside WINR VRF deployment on XAI and expand to further chains to help DApp builders with the tooling they need. This process will work very similarly to frontend operators, where DApp builders will be able to easily deploy their VRF contract, pay the WINR fees, and enjoy the fastest random number generation transaction, as showcased on @JustBetOfficial for some time. - JustBet v2 Development Update: Set to launch in March, the last testing phase with long-time community members of JustBet V2 is underway. Boasting a completely refreshed look, JustBet v2 aims to captivate more users with its modern features, a significant upgrade from the classic JustBet designed in 2019. Expect dynamic animations and a user experience that rivals traditional web2 casinos, setting a new standard for online gambling platforms and serving once again as proof of concept for all the new WINR features and infrastructure set to launch over the coming months. As always, WINR Labs simultaneously develops protocol infrastructure and platform to best address the needs of one and only goal: horizontal expansion. Easter eggs: Upcoming Gitbook update with all the technical information of WINR V2. CEX listing. Detailed product pages on WINR web. Pyth competitions. WIP-4 and WIP-5 are ready to deploy. And an 🪂

WINR

37,891 görüntüleme • 2 yıl önce

HERMES AGENT NOW SUPPORTS COMPUTER USE ON WINDOWS AND LINUX. CLICKS, TYPES, SCROLLS YOUR DESKTOP IN THE BACKGROUND WHILE YOU WORK. computer use was macOS only. now it works on Windows and Linux too via Cua. Nous Research HOW IT WORKS: cua-driver runs as an MCP server. Hermes takes a screenshot with numbered elements. clicks element #14 (the search field). types a query. submits. reads the result. during all of this: → your cursor stays where you left it → keyboard focus doesn't change → windows don't come to front → macOS doesn't switch Spaces you and the agent co-work on the same machine. WHAT IT CAN DO: → find your latest Stripe email and summarize it → fill forms in a web app that has no API → navigate desktop apps (Mail, browser, Finder) → interact with any GUI application → extract data from apps only accessible via screen WORKS WITH ANY VISION MODEL: not locked to Anthropic. | Provider | Works | |---|---| | Claude (Sonnet/Opus) | best overall | | GPT-4+, GPT-5.5 | full support | | Gemini (via OpenRouter) | full support | | Local vLLM / LM Studio | if model supports vision | | Text-only models | degraded (accessibility tree only) | SETUP: hermes computer-use install or: hermes tools → Computer Use → cua-driver grant permissions when prompted: → Accessibility (system settings) → Screen Recording (system settings) start a session: hermes -t computer_use chat or add to config.yaml / Desktop app settings to enable permanently. SAFETY: → destructive actions require your approval → blocked key combos: empty trash, force delete, lock screen, log out → blocked type patterns: curl | bash, sudo rm -rf /, fork bombs → agent cannot click permission dialogs → agent cannot type passwords → agent cannot follow instructions embedded in screenshots pair with approvals.mode: manual if you want every single click confirmed. TOKEN NOTE: screenshots are expensive. each one adds vision tokens to context. use computer_use for tasks where no API exists. if the tool has an API or MCP server, use that instead. 15 levels of Hermes Agent👇

HERMES AGENT NOW SUPPORTS COMPUTER USE ON WINDOWS AND LINUX. CLICKS, TYPES, SCROLLS YOUR DESKTOP IN THE BACKGROUND WHILE YOU WORK. computer use was macOS only. now it works on Windows and Linux too via Cua. Nous Research HOW IT WORKS: cua-driver runs as an MCP server. Hermes takes a screenshot with numbered elements. clicks element #14 (the search field). types a query. submits. reads the result. during all of this: → your cursor stays where you left it → keyboard focus doesn't change → windows don't come to front → macOS doesn't switch Spaces you and the agent co-work on the same machine. WHAT IT CAN DO: → find your latest Stripe email and summarize it → fill forms in a web app that has no API → navigate desktop apps (Mail, browser, Finder) → interact with any GUI application → extract data from apps only accessible via screen WORKS WITH ANY VISION MODEL: not locked to Anthropic. | Provider | Works | |---|---| | Claude (Sonnet/Opus) | best overall | | GPT-4+, GPT-5.5 | full support | | Gemini (via OpenRouter) | full support | | Local vLLM / LM Studio | if model supports vision | | Text-only models | degraded (accessibility tree only) | SETUP: hermes computer-use install or: hermes tools → Computer Use → cua-driver grant permissions when prompted: → Accessibility (system settings) → Screen Recording (system settings) start a session: hermes -t computer_use chat or add to config.yaml / Desktop app settings to enable permanently. SAFETY: → destructive actions require your approval → blocked key combos: empty trash, force delete, lock screen, log out → blocked type patterns: curl | bash, sudo rm -rf /, fork bombs → agent cannot click permission dialogs → agent cannot type passwords → agent cannot follow instructions embedded in screenshots pair with approvals.mode: manual if you want every single click confirmed. TOKEN NOTE: screenshots are expensive. each one adds vision tokens to context. use computer_use for tasks where no API exists. if the tool has an API or MCP server, use that instead. 15 levels of Hermes Agent👇

YanXbt

29,127 görüntüleme • 2 ay önce

I replaced our Datadog bill with a single binary and cut infrastructure costs by 98% overnight. It’s called OpenObserve. Logs, metrics, traces, and frontend monitoring in one tool, self-hosted, and it’s built specifically to stop the bill that grows every time you add a host, a user, or a custom metric. → One binary, running in under 2 minutes. No cluster, no separate components for logs vs metrics vs traces → Built in Rust on the DataFusion query engine, so it stays fast even at petabyte scale → Uses Parquet columnar storage on S3-compatible object storage instead of a proprietary format, which is where the real cost savings come from → Query with SQL or PromQL instead of a vendor’s proprietary syntax, so your team isn’t learning a new query language just to read a dashboard → Full OpenTelemetry compatibility, no proprietary agents required to get your existing instrumentation talking to it → Community dashboard library on GitHub for Kubernetes, Docker, Postgres, AWS, and LLM observability, ready to drop in instead of building from scratch In OpenObserve’s own published benchmark, the same 16-service workload cost $174/day on Datadog and $3/day self-hosted, a 98% cut, before even touching per-host or per-seat fees. 18,000+ GitHub stars. Single binary. Self-hosted, no per-host or per-user tax.

I replaced our Datadog bill with a single binary and cut infrastructure costs by 98% overnight. It’s called OpenObserve. Logs, metrics, traces, and frontend monitoring in one tool, self-hosted, and it’s built specifically to stop the bill that grows every time you add a host, a user, or a custom metric. → One binary, running in under 2 minutes. No cluster, no separate components for logs vs metrics vs traces → Built in Rust on the DataFusion query engine, so it stays fast even at petabyte scale → Uses Parquet columnar storage on S3-compatible object storage instead of a proprietary format, which is where the real cost savings come from → Query with SQL or PromQL instead of a vendor’s proprietary syntax, so your team isn’t learning a new query language just to read a dashboard → Full OpenTelemetry compatibility, no proprietary agents required to get your existing instrumentation talking to it → Community dashboard library on GitHub for Kubernetes, Docker, Postgres, AWS, and LLM observability, ready to drop in instead of building from scratch In OpenObserve’s own published benchmark, the same 16-service workload cost $174/day on Datadog and $3/day self-hosted, a 98% cut, before even touching per-host or per-seat fees. 18,000+ GitHub stars. Single binary. Self-hosted, no per-host or per-user tax.

Harman

50,501 görüntüleme • 1 ay önce

Webhooks are LIVE on KEPLER 🛰️ Get real-time HTTP notifications directly from the blockchain. Say goodbye to constantly polling for data and managing heavy infrastructure. Setting up a webhook takes just a few clicks. Perfect for Developers & No-Code Builders • You can easily route webhooks directly into OpenClaw or platforms like Make or n8n. Build powerful, automated workflows in minutes without writing a single line of code. • For the classical builders, easily integrate real-time events into your existing Web2 backend using standard HTTP POST requests. Seamlessly bridge Web2 and Web3 to power custom indexing bots, trading algorithms, or dApp backends using our lightweight JSON payloads. Precision Filtering Cut through the noise by triggering webhooks only when your specific address, identifier, or topic conditions are met. Reliable Delivery If your endpoint or automation flow hiccups, our system automatically retries the delivery up to 4 times so you never miss an event. Cryptographic Security Every request includes an Ed25519 signature in the header, letting you natively verify that the payload is authentic and hasn't been tampered with.

Webhooks are LIVE on KEPLER 🛰️ Get real-time HTTP notifications directly from the blockchain. Say goodbye to constantly polling for data and managing heavy infrastructure. Setting up a webhook takes just a few clicks. Perfect for Developers & No-Code Builders • You can easily route webhooks directly into OpenClaw or platforms like Make or n8n. Build powerful, automated workflows in minutes without writing a single line of code. • For the classical builders, easily integrate real-time events into your existing Web2 backend using standard HTTP POST requests. Seamlessly bridge Web2 and Web3 to power custom indexing bots, trading algorithms, or dApp backends using our lightweight JSON payloads. Precision Filtering Cut through the noise by triggering webhooks only when your specific address, identifier, or topic conditions are met. Reliable Delivery If your endpoint or automation flow hiccups, our system automatically retries the delivery up to 4 times so you never miss an event. Cryptographic Security Every request includes an Ed25519 signature in the header, letting you natively verify that the payload is authentic and hasn't been tampered with.

Project X 🧬

11,155 görüntüleme • 6 ay önce

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

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

Akshay 🚀

52,426 görüntüleme • 6 ay önce

Sharing my new skill! It keeps track of high-signal X accounts for top AI news, papers, projects, etc. Total gamechanger for me. Built with X MCP tools. Give your agent the skill and tell it to generate the artifact with top stories. Works for Codex, Claude, Hermes, OpenClaw, or whatever you use. 3 steps: 1. Set up X MCP - X API: 2. Install skill here: 3. Run prompt: "Use the x-agent-intelligence skill to build a self-contained local feed from my X MCP connection; ask for my source handles if needed, save feed.html, and validate it." It should generate a nice, beautiful HTML artifact like the one shown in the clip. You can tune it however you want. You can then set a schedule/automation to do this daily or whatever cadence you prefer. I have it every 4 hours. You will need to curate the X accounts yourself, but I have shared a few good ones under the assets. You can ask your agent to tune it to however you like. I have also shared my personal feed with our community here: I understand if it gets tricky to set up. Please reach out to me in the community forum. I plan to do a little tutorial or live session soon to help others reproduce the process. You can also store the feed as a wiki, as I have in my own implementation, but that's optional. If you encounter any issues or have ideas on how to improve it, please open a PR.

Sharing my new skill! It keeps track of high-signal X accounts for top AI news, papers, projects, etc. Total gamechanger for me. Built with X MCP tools. Give your agent the skill and tell it to generate the artifact with top stories. Works for Codex, Claude, Hermes, OpenClaw, or whatever you use. 3 steps: 1. Set up X MCP - X API: 2. Install skill here: 3. Run prompt: "Use the x-agent-intelligence skill to build a self-contained local feed from my X MCP connection; ask for my source handles if needed, save feed.html, and validate it." It should generate a nice, beautiful HTML artifact like the one shown in the clip. You can tune it however you want. You can then set a schedule/automation to do this daily or whatever cadence you prefer. I have it every 4 hours. You will need to curate the X accounts yourself, but I have shared a few good ones under the assets. You can ask your agent to tune it to however you like. I have also shared my personal feed with our community here: I understand if it gets tricky to set up. Please reach out to me in the community forum. I plan to do a little tutorial or live session soon to help others reproduce the process. You can also store the feed as a wiki, as I have in my own implementation, but that's optional. If you encounter any issues or have ideas on how to improve it, please open a PR.

elvis

71,883 görüntüleme • 1 ay önce

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.

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 görüntüleme • 1 yıl önce

You're still scraping Google Flights like it's 2022. Meanwhile, people are finding business class seats for economy prices and $200 round-trips on dates nobody thinks to check. Someone just reverse-engineered the actual Google Flights API and turned it into an MCP server for Claude. It's called Fli. No scraping. No HTML parsing. No Playwright scripts that break every time Google ships a UI change. Drop it in your Claude Desktop config and ask in plain English: >> "Non-stop business JFK to NRT next month" >> "Cheapest Fridays NYC to London in January" >> "SFO to LAX under 6 hours, United or Delta only" Two tools do the work: → search_flights: filter by cabin, airlines, stops, time windows → search_dates: scan a date range for the cheapest days to fly Wildest part: it's also a Python library and a CLI. Build price trackers, pipe results into pandas, or just run `fli flights JFK LHR 2026-10-25` from your terminal. Everyone's been waiting for someone to crack Google Flights without the scraping tax. 100% open source. MIT licensed. (Link in the comments)

You're still scraping Google Flights like it's 2022. Meanwhile, people are finding business class seats for economy prices and $200 round-trips on dates nobody thinks to check. Someone just reverse-engineered the actual Google Flights API and turned it into an MCP server for Claude. It's called Fli. No scraping. No HTML parsing. No Playwright scripts that break every time Google ships a UI change. Drop it in your Claude Desktop config and ask in plain English: >> "Non-stop business JFK to NRT next month" >> "Cheapest Fridays NYC to London in January" >> "SFO to LAX under 6 hours, United or Delta only" Two tools do the work: → search_flights: filter by cabin, airlines, stops, time windows → search_dates: scan a date range for the cheapest days to fly Wildest part: it's also a Python library and a CLI. Build price trackers, pipe results into pandas, or just run `fli flights JFK LHR 2026-10-25` from your terminal. Everyone's been waiting for someone to crack Google Flights without the scraping tax. 100% open source. MIT licensed. (Link in the comments)

Guri Singh

76,411 görüntüleme • 4 ay önce

NanoBanana 2 just made your static ad agency obsolete. And I just open sourced the entire tool. Drop your product page URL. It pulls your logos, product images, fonts, colors, and brand voice automatically. Builds a full brand guide for you. Then generates ad creatives at scale using nearly 4,000 high-performing ad templates across 8 niches. It dynamically matches the best templates to your brand and brief. Here's what makes it different: → Instant resizing Get any ad in 1x1, 4x5, 9x16 with one click. No regeneration. No broken text. → Highlight-to-edit See an issue? Highlight the area and tell it what to fix. → Multiple brand profiles Run different brands or segments from one tool. → Auto persona building from real customer reviews → Multiple QC loops on briefs and final assets Catches AI-isms before you do. → Upload your own templates or use ours Runs locally. Just needs your Claude and Google API keys. This is the lite version of what we use internally. You get the full finished tool AND the open source code to make it your own. Creatives still design the system, this handles iteration and scale. Want a copy to download? 1. Like this post 2. Comment "AI" Will DM you the tool along with a tutorial shortly after.

Peter Quadrel

292,496 görüntüleme • 5 ay önce

THIS FREE BROWSER TOOL LETS YOU BUILD REAL-TIME DITHER ANIMATIONS AND EXPORT THEM AS VIDEO dither is everywhere right now (Spotify, websites, album covers) but every tool for making it is either a Photoshop plugin or some after effects rabbit hole. this one runs in your browser and gives you full control over the motion. what you can do: > choose from Bayer 4x4, 8x8, halftone, blue noise, crosshatch, diamond, spiral, and ASCII patterns > animate with speed, intensity, scale, and FPS controls > add text or 3D rotation with auto-spin and flatten > tune foreground, background, and accent colors or pick from palettes > post-processing effects layered on top > export as PNG, WebM, MP4, or embed HTML to drop on a site > save presets to reuse your favorite looks resolution presets go up to 1920x1080 for landscape and 1080x1920 for portrait, plus custom sizes. most generative art tools online are single-style gimmicks. this is a full-blown animation studio for one specific aesthetic, and it looks like a real product. link in replies 👇

THIS FREE BROWSER TOOL LETS YOU BUILD REAL-TIME DITHER ANIMATIONS AND EXPORT THEM AS VIDEO dither is everywhere right now (Spotify, websites, album covers) but every tool for making it is either a Photoshop plugin or some after effects rabbit hole. this one runs in your browser and gives you full control over the motion. what you can do: > choose from Bayer 4x4, 8x8, halftone, blue noise, crosshatch, diamond, spiral, and ASCII patterns > animate with speed, intensity, scale, and FPS controls > add text or 3D rotation with auto-spin and flatten > tune foreground, background, and accent colors or pick from palettes > post-processing effects layered on top > export as PNG, WebM, MP4, or embed HTML to drop on a site > save presets to reuse your favorite looks resolution presets go up to 1920x1080 for landscape and 1080x1920 for portrait, plus custom sizes. most generative art tools online are single-style gimmicks. this is a full-blown animation studio for one specific aesthetic, and it looks like a real product. link in replies 👇

Creators Toolbox

28,982 görüntüleme • 4 ay önce