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your agent already does the work. reports. research. plans. full websites. then it dies in a chat reply. or a .md file. or a localhost page nobody else can open. showly fixes the last step. it's an agent artifact cloud. connect the agent you already use. claude code, codex,... show more

Iris Hayes

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44,301 Aufrufe • vor 12 Tagen •via X (Twitter)

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Introducing Pages on Superset mobile Your agents can now deliver interactive demos, mockups, and reports as Pages you can review from your phone. Ask an agent to build a feature, compare designs, or investigate a problem. It can put the result in a Page with the context you need to review it and give feedback. A few ways to use it: • Feature work: try an interactive demo, then inspect the code in the PR. • Design reviews: compare mockups and before-and-after screenshots. • Investigations: explore findings, charts, and recommendations in one place. To try it, ask your agent to build a feature and create a Page for you to review.

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Kiet

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Stop manually making flowcharts. Try this GitHub skill with Claude Code. I found an open-source tool that turns a plain description of a software system into a clean, interactive diagram. It's called Archify, and it has more than 66,000 stars on GitHub. You add it as a skill to an AI coding agent like Claude Code, Codex, Cursor, or OpenCode. Then you describe the system in the chat in one line. Archify turns that line into a single HTML file you can open, click through, and send to anyone. If you point your agent at an existing codebase, it reads the code and Archify maps how the pieces connect. I liked five things about it. 1. It makes five kinds of diagrams, including system maps and step-by-step workflows. 2. You can click any piece and trace what connects to it. 3. It checks the layout before it hands the diagram over, so arrows don't pile up and labels don't overlap. 4. It has dark and light themes and exports to PNG, SVG, or a short video. 5. You keep editing in plain chat, with requests like "add Redis" or "highlight the rollback path." You don't need a codebase to use it. A description in the chat is enough.

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elvis

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BuBBliK

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shmidt

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Krea

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Phillip Jones

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You can now build Cursor agents in Rust, Go, or any other language! We're open-sourcing the SDK Bridge so you can write a thin adapter in your language that keeps up when we add agent features. Try it at

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eric zakariasson

62,812 Aufrufe • vor 1 Monat

Your enterprise content should power every AI tool and agent you use. With the Box MCP server, Box acts as a secure, governed bridge, so teams can search, retrieve, analyze, and act on Box content directly inside the tools they already use. No one-off integrations. Use it to: 🔹Ask questions over files in Anthropic Claude + Mistral AI Le Chat 🔹Ground designs in Figma or @ mention Box agents in Atlassian Jira 🔹Pull content into GitHub Copilot, Cursor + Claude Code 🔹Build agents with LangChain LangSmith Agent Builder + OpenAI Agent Builder 🔹Automate work in Claude Cowork + Amazon Web Services Quick Suite 🔹Enforce access + audit trails with Runlayer Secure. Standardized. Built for real work →

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Box

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> you went to sleep > gave your OpenClaw $200 > told it: make money > you wake up - account shows $6,700 > overnight the agent was trading spreads between Polymarket and NOAA > NOAA forecasts come with ~94% accuracy > the AI agent opens a position at 11c > sells at 44c > total research time: 10 minutes in Perplexity > Claude turned that into an AI agent > the agent made the money

> you went to sleep > gave your OpenClaw $200 > told it: make money > you wake up - account shows $6,700 > overnight the agent was trading spreads between Polymarket and NOAA > NOAA forecasts come with ~94% accuracy > the AI agent opens a position at 11c > sells at 44c > total research time: 10 minutes in Perplexity > Claude turned that into an AI agent > the agent made the money

may.crypto {🦅}

1,037,361 Aufrufe • vor 6 Monaten

this is the worst local ai will ever be. it only gets better from here. if you are not expanding your mind with these small models you are missing what's happening right now 99 percent tool call success rate. when steered well with the right skills and a framework like hermes agent the node becomes a cognition layer. not a chatbot. not a toy. an extension of how you think. i was cranking this node at 35 to 50 tok/s all day on personal experiments and now after all the work is done qwen 3.5 9B is iterating on its own code. the game it created. fixing its own bugs autonomously. and the part you should probably not miss is that all of this is happening on a RTX 3060. not an H100. not an A100. the card most of you have sitting in a drawer right now. if you just open that drawer and put that intelligence to work every tensor core on that card should be running for you. your work. your experiments. your thinking. you all have it but because nobody told you what this hardware can actually do in 2026 you never tried. the day it unlocks is the day you test your workload, understand the tradeoffs, debug the loops, and then decide if you need to scale the hardware. there is no point buying 3 mac studios when things done well you can squeeze a similar level of intelligence from 9B compared to 70B. but only when you create the right environment for your model through the right harness. and let me tell you i have tried claude code as a local harness. i have tried opencode. i have tried various others. somehow i landed on hermes agent and never left. there is something magical going on at Nous Research. the tool call parsers, the skills system, the way it handles small models natively. nothing else comes close for local inference. own your cognition. your AI. your agent. your prompts. your experiments. why give them away for free. those are who you are and they don't belong on someone else's servers being monitored. just give it a shot with your existing hardware. you run into a problem the community will help you. and if you are migrating from openclaw to hermes i will personally help you make the switch.

this is the worst local ai will ever be. it only gets better from here. if you are not expanding your mind with these small models you are missing what's happening right now 99 percent tool call success rate. when steered well with the right skills and a framework like hermes agent the node becomes a cognition layer. not a chatbot. not a toy. an extension of how you think. i was cranking this node at 35 to 50 tok/s all day on personal experiments and now after all the work is done qwen 3.5 9B is iterating on its own code. the game it created. fixing its own bugs autonomously. and the part you should probably not miss is that all of this is happening on a RTX 3060. not an H100. not an A100. the card most of you have sitting in a drawer right now. if you just open that drawer and put that intelligence to work every tensor core on that card should be running for you. your work. your experiments. your thinking. you all have it but because nobody told you what this hardware can actually do in 2026 you never tried. the day it unlocks is the day you test your workload, understand the tradeoffs, debug the loops, and then decide if you need to scale the hardware. there is no point buying 3 mac studios when things done well you can squeeze a similar level of intelligence from 9B compared to 70B. but only when you create the right environment for your model through the right harness. and let me tell you i have tried claude code as a local harness. i have tried opencode. i have tried various others. somehow i landed on hermes agent and never left. there is something magical going on at Nous Research. the tool call parsers, the skills system, the way it handles small models natively. nothing else comes close for local inference. own your cognition. your AI. your agent. your prompts. your experiments. why give them away for free. those are who you are and they don't belong on someone else's servers being monitored. just give it a shot with your existing hardware. you run into a problem the community will help you. and if you are migrating from openclaw to hermes i will personally help you make the switch.

Sudo su

58,717 Aufrufe • vor 6 Monaten

holy sh*t. Jev's founder Diogo Almeida dropped a Google Doc on coding agents one of these PDFs has the map everyone needs: where Jev sits in an agent loop ↓ agents do the work, Jev makes the calls, the LLM only writes: 1 → task in: one Noul before anything runs. in scope, or does a human need to see it first? 2 → dispatch: a Choice picks who takes the step (research, write or review). act at 0.85+, everything below goes to review 3 → act: Jev gates the tool call (allow, confirm or block). the LLM only writes the arguments 4 → check: a Score decides what comes back (drop, summary or keep). whatever Jev is unsure of goes to a human 5 → finish: Jev says done above 0.8, then code proves the file actually exists the LLM shows up in 2 of 5 stages. everything else is a typed answer, plain code or a person. don't refactor your agent. hand Jev the one fork it hits most (usually the tool gate or dispatch) and watch 3 numbers for a week: cost per completed task, time per completed task, and how often escalation fired and whether it was right. if escalation never fires, the threshold is too loose and your agent is quietly running unsupervised.

holy sh*t. Jev's founder Diogo Almeida dropped a Google Doc on coding agents one of these PDFs has the map everyone needs: where Jev sits in an agent loop ↓ agents do the work, Jev makes the calls, the LLM only writes: 1 → task in: one Noul before anything runs. in scope, or does a human need to see it first? 2 → dispatch: a Choice picks who takes the step (research, write or review). act at 0.85+, everything below goes to review 3 → act: Jev gates the tool call (allow, confirm or block). the LLM only writes the arguments 4 → check: a Score decides what comes back (drop, summary or keep). whatever Jev is unsure of goes to a human 5 → finish: Jev says done above 0.8, then code proves the file actually exists the LLM shows up in 2 of 5 stages. everything else is a typed answer, plain code or a person. don't refactor your agent. hand Jev the one fork it hits most (usually the tool gate or dispatch) and watch 3 numbers for a week: cost per completed task, time per completed task, and how often escalation fired and whether it was right. if escalation never fires, the threshold is too loose and your agent is quietly running unsupervised.

Archive

31,914 Aufrufe • vor 6 Tagen

made this with text to lottie and claude code my workflow: design something in figma or just make a rough draft. then ask claude to animate it you'd be surprised how easy it is to add easings, masks, transforms, text effects and all the motion details you can also ask claude to export it as a gif, mp4, png sequence, resize it in different aspect ratios claude and codex already creates something with taste and if you know what you want to create, this workflow is really useful and btw, it's free

made this with text to lottie and claude code my workflow: design something in figma or just make a rough draft. then ask claude to animate it you'd be surprised how easy it is to add easings, masks, transforms, text effects and all the motion details you can also ask claude to export it as a gif, mp4, png sequence, resize it in different aspect ratios claude and codex already creates something with taste and if you know what you want to create, this workflow is really useful and btw, it's free

Doruk

14,966 Aufrufe • vor 3 Monaten

First Sachi 3D file is ready which you are able to use your character where you want in any metaverse, for rendering or in animation as a few example. Use the link below to try it out👇

First Sachi 3D file is ready which you are able to use your character where you want in any metaverse, for rendering or in animation as a few example. Use the link below to try it out👇

LUX

10,799 Aufrufe • vor 3 Jahren

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 Aufrufe • vor 7 Monaten