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ASCIIVISION is an entire command center inside a terminal ai chat with 4 providers, live webcam converted to ascii art, websocket video calls, 3d matrix rain, fire simulations, a tiling window manager, system monitoring, shell execution, conversation analytics, one rust binary, zero electron, pure terminal. everything you see is text.

lalo 🐧

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66,281 просмотров • 4 месяцев назад •via X (Twitter)

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gpt-5.5 just dropped. and it changes EVERYTHING for traders. openai stopped calling it a chat model. they call it an "agent runtime" now. that means one thing: AI that doesn't wait for you - it acts. here's what gpt-5.5 can actually do: → runs multi-step trading workflows autonomously → operates computer interfaces without human input → plans, iterates, executes - in a terminal, not a chat window → 82.7% on Terminal-Bench 2.0 - real command-line task execution the only question is: are you already running one? full FREE Guide here → like + bookmark. this is the wave.

gpt-5.5 just dropped. and it changes EVERYTHING for traders. openai stopped calling it a chat model. they call it an "agent runtime" now. that means one thing: AI that doesn't wait for you - it acts. here's what gpt-5.5 can actually do: → runs multi-step trading workflows autonomously → operates computer interfaces without human input → plans, iterates, executes - in a terminal, not a chat window → 82.7% on Terminal-Bench 2.0 - real command-line task execution the only question is: are you already running one? full FREE Guide here → like + bookmark. this is the wave.

AlphaCartel

56,823 просмотров • 3 месяцев назад

One person rebuilt an entire company’s brain in 7 days inside Claude Code. Not a doc. Not Obsidian. A living galaxy of nodes. Every employee. Every AI agent. Every SOP. Every tool. All wired together on one screen. Click a department. The human agent team opens up. The SOPs attached to it open up. What each person is allowed to touch opens up. That last part is the whole game. Permissions baked into the brain. An employee opens the chat, the AI already knows what they can access. Agents, data, SOPs surface inside the conversation like you tagged them by hand. Obsidian can’t do this. Notion can’t do this. No dev team. No funding round. No 6-month roadmap. 7 days, 1 person, 1 terminal. This is the part nobody has priced in. The tools to build $200K enterprise software now sit on your laptop for free. The only thing missing is the guy who opens the terminal.

One person rebuilt an entire company’s brain in 7 days inside Claude Code. Not a doc. Not Obsidian. A living galaxy of nodes. Every employee. Every AI agent. Every SOP. Every tool. All wired together on one screen. Click a department. The human agent team opens up. The SOPs attached to it open up. What each person is allowed to touch opens up. That last part is the whole game. Permissions baked into the brain. An employee opens the chat, the AI already knows what they can access. Agents, data, SOPs surface inside the conversation like you tagged them by hand. Obsidian can’t do this. Notion can’t do this. No dev team. No funding round. No 6-month roadmap. 7 days, 1 person, 1 terminal. This is the part nobody has priced in. The tools to build $200K enterprise software now sit on your laptop for free. The only thing missing is the guy who opens the terminal.

Spike 1%

783,516 просмотров • 2 месяцев назад

Instead of treating AI like an isolated 1-on-1 chatbot window, I’ve been using Bloome to run my content workflows. It is a shared workspace where humans and multiple AI agents sit inside the exact same group chat to actually get a complex job done. I used their one-click template connection to spin up a specialized creative team. The biggest shift here is that the agents actively check each other's work instead of just agreeing with me: -The @ Writer drafts the initial video essay structure. -The @ Audience agent immediately pushes back to critique the pacing and rewrite boring segments to keep viewer retention high. -The @ Art Director pulls everything together into a visual markdown report and thumbnail design concept right inside the chat window. This is an awesome tool for creators, marketers, and operators who want to transition from writing rigid text prompts to managing an actual human-agent team. Check this out:

Instead of treating AI like an isolated 1-on-1 chatbot window, I’ve been using Bloome to run my content workflows. It is a shared workspace where humans and multiple AI agents sit inside the exact same group chat to actually get a complex job done. I used their one-click template connection to spin up a specialized creative team. The biggest shift here is that the agents actively check each other's work instead of just agreeing with me: -The @ Writer drafts the initial video essay structure. -The @ Audience agent immediately pushes back to critique the pacing and rewrite boring segments to keep viewer retention high. -The @ Art Director pulls everything together into a visual markdown report and thumbnail design concept right inside the chat window. This is an awesome tool for creators, marketers, and operators who want to transition from writing rigid text prompts to managing an actual human-agent team. Check this out:

Chubby♨️

68,446 просмотров • 1 месяц назад

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

Santiago

140,873 просмотров • 8 месяцев назад

A 28-year-old in Berlin replaced an entire software agency with 7 AI agents running on a VPS. No office. No desk. No fixed computer. Just a phone and a terminal window connected to agents already working while she sleeps. A client got quoted $74,000 and 6 weeks by a traditional agency. Her agents shipped the validated PR in 19 hours. The agency was still revising the proposal. That’s the scary part about what AI is becoming. Not “ChatGPT writes code.” Entire companies are starting to collapse into one person + automated systems. One agent maps the repo. One writes specs. Two build in parallel. One tests. One audits security. Everything loops automatically until the PR is clean. Copy: She approved the final checkpoint from her phone at midnight. 30 seconds later the system kept running without her.

A 28-year-old in Berlin replaced an entire software agency with 7 AI agents running on a VPS. No office. No desk. No fixed computer. Just a phone and a terminal window connected to agents already working while she sleeps. A client got quoted $74,000 and 6 weeks by a traditional agency. Her agents shipped the validated PR in 19 hours. The agency was still revising the proposal. That’s the scary part about what AI is becoming. Not “ChatGPT writes code.” Entire companies are starting to collapse into one person + automated systems. One agent maps the repo. One writes specs. Two build in parallel. One tests. One audits security. Everything loops automatically until the PR is clean. Copy: She approved the final checkpoint from her phone at midnight. 30 seconds later the system kept running without her.

Phantom_Defi

17,496 просмотров • 2 месяцев назад

ALWAYS HAS BEEN Chapter 1: Fenestra Animae Website: X Article: Whitepaper video (~10 min) (see below) This is by far my most ambitious project yet and so I've provided a few ways to dig into the many deep layers of the artwork. First is the website which has the full whitepaper and a blueprint of the entire system. It also has a fun design, so I'd definitely check it out even just for that. Second, I've included the full whitepaper as an X article, so that it is easy to access and read. Third, I've created a video (~10 min) that narrates the entire text of the whitepaper with video illustrations of the concepts within the artwork (see below). There is a lot in there and those that take the time to understand it all will benefit greatly when the time comes. Hopefully one of these ways of reading the whitepaper will provide an easy way to dive in. I'll be following up with more posts and discussions to dig into the nuanced aspects of the work. In addition, a new version of The Terminal (FKA Latent Space Terminal) has also launched today. You can visit The Terminal here: But you will need to engage with the Always Has Been X account to gain access. If the account likes your post, you will be automatically granted entry after signing in with your X account.

ALWAYS HAS BEEN Chapter 1: Fenestra Animae Website: X Article: Whitepaper video (~10 min) (see below) This is by far my most ambitious project yet and so I've provided a few ways to dig into the many deep layers of the artwork. First is the website which has the full whitepaper and a blueprint of the entire system. It also has a fun design, so I'd definitely check it out even just for that. Second, I've included the full whitepaper as an X article, so that it is easy to access and read. Third, I've created a video (~10 min) that narrates the entire text of the whitepaper with video illustrations of the concepts within the artwork (see below). There is a lot in there and those that take the time to understand it all will benefit greatly when the time comes. Hopefully one of these ways of reading the whitepaper will provide an easy way to dive in. I'll be following up with more posts and discussions to dig into the nuanced aspects of the work. In addition, a new version of The Terminal (FKA Latent Space Terminal) has also launched today. You can visit The Terminal here: But you will need to engage with the Always Has Been X account to gain access. If the account likes your post, you will be automatically granted entry after signing in with your X account.

Chikai

12,056 просмотров • 6 месяцев назад

THIS GUY BUILT A COMMAND CENTER FOR MANAGING AI AGENT TEAMS he was running 20+ agents through openclaw. all from terminal tabs and Discord. 12 tabs open. still losing track of who's doing what. which cron failed. so he built a dashboard that gives you one place to see everything: > org map showing the full agent hierarchy, who reports to who and what tools each agent has > chat with any agent through a real UI instead of bouncing between terminals > kanban board for tracking tasks across all agents > cron monitor with pipeline visualizations so you can see which jobs are failing > memory browser to read through all agent knowledge files in one place you can even point it at your openclaw workspace and it auto-discovers every agent from their config files. zero setup. AND ITS OPEN SOURCE TOO.

THIS GUY BUILT A COMMAND CENTER FOR MANAGING AI AGENT TEAMS he was running 20+ agents through openclaw. all from terminal tabs and Discord. 12 tabs open. still losing track of who's doing what. which cron failed. so he built a dashboard that gives you one place to see everything: > org map showing the full agent hierarchy, who reports to who and what tools each agent has > chat with any agent through a real UI instead of bouncing between terminals > kanban board for tracking tasks across all agents > cron monitor with pipeline visualizations so you can see which jobs are failing > memory browser to read through all agent knowledge files in one place you can even point it at your openclaw workspace and it auto-discovers every agent from their config files. zero setup. AND ITS OPEN SOURCE TOO.

Om Patel

46,780 просмотров • 4 месяцев назад

Train AI robots without writing a single line of code. 🤖 We just launched LeLab, the official graphical user interface for LeRobot built by Nicolas Rabault. It completely removes the command line from the robot learning workflow, taking you from raw hardware to autonomous movement visually. If you've ever wanted to get into AI robotics but were held back by complex terminal setups, this is for you. - Zero-Terminal Setup: Smart calibration with automatic USB port detection. - Easy Data Collection: Teleoperate your robot and record a dataset. - One-Click GPU Training: Don't have a massive local GPU? Scale your training instantly with Hugging Face Jobs right inside the app. Just plug in your SO-ARM101 and start teaching your robot. We put together a complete, step-by-step video guide showing exactly how to get started and train your first policy. Docs: GitHub:

Train AI robots without writing a single line of code. 🤖 We just launched LeLab, the official graphical user interface for LeRobot built by Nicolas Rabault. It completely removes the command line from the robot learning workflow, taking you from raw hardware to autonomous movement visually. If you've ever wanted to get into AI robotics but were held back by complex terminal setups, this is for you. - Zero-Terminal Setup: Smart calibration with automatic USB port detection. - Easy Data Collection: Teleoperate your robot and record a dataset. - One-Click GPU Training: Don't have a massive local GPU? Scale your training instantly with Hugging Face Jobs right inside the app. Just plug in your SO-ARM101 and start teaching your robot. We put together a complete, step-by-step video guide showing exactly how to get started and train your first policy. Docs: GitHub:

LeRobot

50,389 просмотров • 2 месяцев назад

Imagine an AI application that can type anywhere you can and use the full context of what's on your screen. This is the application we all deserve (at least if you have macOS.) Check out Omnipilot. It's an app that works with every other macOS application and uses Claude Sonet 3.5 in the background—it also supports Gemini and GPT-4o. Here is the idea: You can use the tool to ask questions about anything on your screen. Or you can use it to autocomplete the text you are typing. You don't need to copy and paste anymore or waste your time providing context to a model. It sees what you see. It works right where you are. That's pretty cool. Here are a couple of cool examples: • Use it to reply to an email • Use it in the terminal to autocomplete a command • Use it to finish a document • Use to send a message on Slack AI at the system level is bonkers. You can read a ton more on their Product Hunt launch page: Thanks to the Omnipilot team for collaborating with me on this post!

Imagine an AI application that can type anywhere you can and use the full context of what's on your screen. This is the application we all deserve (at least if you have macOS.) Check out Omnipilot. It's an app that works with every other macOS application and uses Claude Sonet 3.5 in the background—it also supports Gemini and GPT-4o. Here is the idea: You can use the tool to ask questions about anything on your screen. Or you can use it to autocomplete the text you are typing. You don't need to copy and paste anymore or waste your time providing context to a model. It sees what you see. It works right where you are. That's pretty cool. Here are a couple of cool examples: • Use it to reply to an email • Use it in the terminal to autocomplete a command • Use it to finish a document • Use to send a message on Slack AI at the system level is bonkers. You can read a ton more on their Product Hunt launch page: Thanks to the Omnipilot team for collaborating with me on this post!

Santiago

72,306 просмотров • 2 лет назад

🚨BREAKING: An open-source agentic video production system just dropped. 11 pipelines, 49 tools, and a full product ad produced for $0.69 total. It's called OpenMontage. And it's not a text-to-video tool. It's a full production orchestration system where your AI coding assistant (Claude Code, Cursor, Copilot, Windsurf) becomes the director. Describe what you want in plain language. The agent researches, scripts, generates assets, edits, and renders the final video. Here's what the pipeline actually does: → Live web research first: 15-25+ searches across YouTube, Reddit, news sites before writing a single word of script → 12 video generation providers: Kling, Runway Gen-4, Google Veo 3, MiniMax, plus local GPU options (WAN 2.1, Hunyuan, CogVideo) → 8 image generation providers: FLUX, Google Imagen 4, DALL-E 3, Stable Diffusion locally → 4 TTS providers: ElevenLabs, Google (700+ voices), OpenAI, and Piper offline for free → WhisperX word-level subtitles burned in automatically → Remotion for React-based animated composition with spring physics, transitions, TikTok-style captions → Budget governance: cost estimate before execution, per-action approval above $0.50, hard cap at $10 Here's the wildest part: One product ad. 4 AI-generated images, TTS narration, royalty-free music, word-level subtitles, Remotion data visualizations. Total cost: $0.69. Zero manual asset work. Works with zero API keys too. Piper narrates locally, Pexels/Pixabay provide free stock, Remotion animates everything. No spend required to start. 100% Open Source. AGPL v3 License. (Link in the comments)

🚨BREAKING: An open-source agentic video production system just dropped. 11 pipelines, 49 tools, and a full product ad produced for $0.69 total. It's called OpenMontage. And it's not a text-to-video tool. It's a full production orchestration system where your AI coding assistant (Claude Code, Cursor, Copilot, Windsurf) becomes the director. Describe what you want in plain language. The agent researches, scripts, generates assets, edits, and renders the final video. Here's what the pipeline actually does: → Live web research first: 15-25+ searches across YouTube, Reddit, news sites before writing a single word of script → 12 video generation providers: Kling, Runway Gen-4, Google Veo 3, MiniMax, plus local GPU options (WAN 2.1, Hunyuan, CogVideo) → 8 image generation providers: FLUX, Google Imagen 4, DALL-E 3, Stable Diffusion locally → 4 TTS providers: ElevenLabs, Google (700+ voices), OpenAI, and Piper offline for free → WhisperX word-level subtitles burned in automatically → Remotion for React-based animated composition with spring physics, transitions, TikTok-style captions → Budget governance: cost estimate before execution, per-action approval above $0.50, hard cap at $10 Here's the wildest part: One product ad. 4 AI-generated images, TTS narration, royalty-free music, word-level subtitles, Remotion data visualizations. Total cost: $0.69. Zero manual asset work. Works with zero API keys too. Piper narrates locally, Pexels/Pixabay provide free stock, Remotion animates everything. No spend required to start. 100% Open Source. AGPL v3 License. (Link in the comments)

Guri Singh

112,201 просмотров • 3 месяцев назад

OpenClaw just got a desktop app. And nobody's talking about it. It's called Claw X. It's free. And it changes everything about how you use AI agents. Here's the problem it solves: Running OpenClaw required command line. That's like owning a Ferrari but the only way to drive it is reading a manual written in Japanese. Claw X fixes that with a clean desktop UI. One-click install. No terminal. No commands. No tech skills. Here's what you get inside: A dashboard showing your agent's activity, skills, and scheduled tasks all in one place. One-click connections to Telegram, Discord, and WhatsApp. Visual settings for switching AI providers — Anthropic, OpenAI, Google, or even free local models via Ollama. Scheduled task management without touching a single config file. And the setup takes 2 minutes. Just paste the GitHub link into OpenClaw and say "install this." It sets itself up. You've been avoiding OpenClaw because the setup looked complicated. That excuse is

OpenClaw just got a desktop app. And nobody's talking about it. It's called Claw X. It's free. And it changes everything about how you use AI agents. Here's the problem it solves: Running OpenClaw required command line. That's like owning a Ferrari but the only way to drive it is reading a manual written in Japanese. Claw X fixes that with a clean desktop UI. One-click install. No terminal. No commands. No tech skills. Here's what you get inside: A dashboard showing your agent's activity, skills, and scheduled tasks all in one place. One-click connections to Telegram, Discord, and WhatsApp. Visual settings for switching AI providers — Anthropic, OpenAI, Google, or even free local models via Ollama. Scheduled task management without touching a single config file. And the setup takes 2 minutes. Just paste the GitHub link into OpenClaw and say "install this." It sets itself up. You've been avoiding OpenClaw because the setup looked complicated. That excuse is

Julian Goldie SEO

94,479 просмотров • 5 месяцев назад

Okay so this got way out of hand as per usual 😊 So I accidentally built an entire DOS text-based user interface (TUI) running on the web called PieterOS: 💾 It has a collective file system so anyone that opens it can save and edit and the drive is constantly synced, it has Notepad, Paint, a DOS Terminal emulator, File Commander (ala Norton) And PieterGPT where you can talk to AI I also made Program Generator 9000, and the idea is you write a prompt and it on-the-fly generates a new program inside PieterOS, but it doesn't work well yet Oh and it has Hacker News, of course 😂 I always wanted to build a TUI like this but never could before AI, but now I can 😍 Please be kind and remember everyone can see each other's files!

Okay so this got way out of hand as per usual 😊 So I accidentally built an entire DOS text-based user interface (TUI) running on the web called PieterOS: 💾 It has a collective file system so anyone that opens it can save and edit and the drive is constantly synced, it has Notepad, Paint, a DOS Terminal emulator, File Commander (ala Norton) And PieterGPT where you can talk to AI I also made Program Generator 9000, and the idea is you write a prompt and it on-the-fly generates a new program inside PieterOS, but it doesn't work well yet Oh and it has Hacker News, of course 😂 I always wanted to build a TUI like this but never could before AI, but now I can 😍 Please be kind and remember everyone can see each other's files!

@levelsio

145,078 просмотров • 4 месяцев назад

𝐒𝐄𝐂𝐋’𝐬 𝐈𝐂𝐂𝐂 𝐝𝐫𝐢𝐯𝐞𝐬 𝐬𝐦𝐚𝐫𝐭𝐞𝐫 𝐜𝐨𝐚𝐥 𝐦𝐢𝐧𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐞𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐬𝐚𝐟𝐞𝐭𝐲 𝐚𝐧𝐝 𝐝𝐚𝐭𝐚-𝐝𝐫𝐢𝐯𝐞𝐧 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 The Integrated Command and Control Centre (ICCC) established at SECL (South Eastern Coalfields Limited) Headquarters in Bilaspur is a major step towards enhancing safety, transparency, and efficiency in mining operations. 📹 This state-of-art centre monitors 24*7 live feeds from around 750 cameras installed across all SECL areas. 💻 With AI-based video analytics, the system provides features like PPE detection, fire and smoke alerts, and intrusion alerts. 🚛 Additionally, the Vehicle Tracking System enables real-time monitoring of coal transportation. This setup has strengthened compliance with employee safety protocols and significantly improved operational efficiency. This is Hon’ble PM Shri Narendra Modi’s Atmanirbhar Bharat in action, where innovation, accountability, and worker safety come together to build a future-ready coal sector. Ministry of Coal SECL

𝐒𝐄𝐂𝐋’𝐬 𝐈𝐂𝐂𝐂 𝐝𝐫𝐢𝐯𝐞𝐬 𝐬𝐦𝐚𝐫𝐭𝐞𝐫 𝐜𝐨𝐚𝐥 𝐦𝐢𝐧𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐞𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐬𝐚𝐟𝐞𝐭𝐲 𝐚𝐧𝐝 𝐝𝐚𝐭𝐚-𝐝𝐫𝐢𝐯𝐞𝐧 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 The Integrated Command and Control Centre (ICCC) established at SECL (South Eastern Coalfields Limited) Headquarters in Bilaspur is a major step towards enhancing safety, transparency, and efficiency in mining operations. 📹 This state-of-art centre monitors 24*7 live feeds from around 750 cameras installed across all SECL areas. 💻 With AI-based video analytics, the system provides features like PPE detection, fire and smoke alerts, and intrusion alerts. 🚛 Additionally, the Vehicle Tracking System enables real-time monitoring of coal transportation. This setup has strengthened compliance with employee safety protocols and significantly improved operational efficiency. This is Hon’ble PM Shri Narendra Modi’s Atmanirbhar Bharat in action, where innovation, accountability, and worker safety come together to build a future-ready coal sector. Ministry of Coal SECL

G Kishan Reddy

14,086 просмотров • 7 месяцев назад

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

47,302 просмотров • 1 год назад

I tried jack's Buzz. It's like Slack + OpenClaw + Herdr + but with some really unique features that people are sleeping on. The video below shows how it works, and some of my thoughts on the process and platform, e.g.: - Create and interact with agents on top of any harness (claude code, codex, pi, etc.) - Choose which models agents use, including local ones - Agents can delegate work and work in parallel in git worktrees - Agents are first-class citizens and work like humans (creating channels, delegating, access to chat history) - You can share AI compute within a community - It's completely open-source and decentralized Things I like: - Delegating work in chat feels natural: tag an agent, it replies in a thread with status updates as it e.g. compiles, commits, and deploys. - Shared compute: relay owners can share local compute with members, so a community could pool funds for one beefy machine running a local model and everyone uses it. - It's built on Nostr, an open protocol already tied into Bitcoin Lightning so I can imagine communities tipping each other or paying for compute/agent tasks with instant zero-fee micropayments in the future. - It ties together things like OpenClaw, an agent manager, and Slack-style chat into one tool. Things I didn't like: - You can't see what the agent is doing in a terminal. The activity view exists, but if you're used to watching a session run, this UI feels a bit abstracted. A terminal view would be great. - It feels slower than running a session in Claude Code, though no evidence to back that up. For that reason I found myself doing one-off tasks in the terminal instead. Verdict: - I really like it so far and can genuinely imagine working with a team this way. - It doesn't feel ready for big, complex tasks yet. For shallower tasks, it's perfect. - The shared compute + Nostr/Lightning angle is what really separates it from every other agent manager for me, and I think that future is coming.

I tried jack's Buzz. It's like Slack + OpenClaw + Herdr + but with some really unique features that people are sleeping on. The video below shows how it works, and some of my thoughts on the process and platform, e.g.: - Create and interact with agents on top of any harness (claude code, codex, pi, etc.) - Choose which models agents use, including local ones - Agents can delegate work and work in parallel in git worktrees - Agents are first-class citizens and work like humans (creating channels, delegating, access to chat history) - You can share AI compute within a community - It's completely open-source and decentralized Things I like: - Delegating work in chat feels natural: tag an agent, it replies in a thread with status updates as it e.g. compiles, commits, and deploys. - Shared compute: relay owners can share local compute with members, so a community could pool funds for one beefy machine running a local model and everyone uses it. - It's built on Nostr, an open protocol already tied into Bitcoin Lightning so I can imagine communities tipping each other or paying for compute/agent tasks with instant zero-fee micropayments in the future. - It ties together things like OpenClaw, an agent manager, and Slack-style chat into one tool. Things I didn't like: - You can't see what the agent is doing in a terminal. The activity view exists, but if you're used to watching a session run, this UI feels a bit abstracted. A terminal view would be great. - It feels slower than running a session in Claude Code, though no evidence to back that up. For that reason I found myself doing one-off tasks in the terminal instead. Verdict: - I really like it so far and can genuinely imagine working with a team this way. - It doesn't feel ready for big, complex tasks yet. For shallower tasks, it's perfect. - The shared compute + Nostr/Lightning angle is what really separates it from every other agent manager for me, and I think that future is coming.

Vinny

1,337,182 просмотров • 13 дней назад

MOST PEOPLE USE CLAUDE CODE LIKE CHATGPT WITH A TERMINAL That is why they only get 30% of the value. They paste a task, wait for an answer, then keep explaining the same rules again when the context gets messy. The real power starts when you stop treating it like a chatbot and start treating it like an operating system for work. The useful commands are not flashy. They just remove the parts that quietly waste hours: > /init builds the project memory > /memory edits the rules Claude should keep > /clear resets the chat without losing the setup > /compact compresses a long session before quality drops > /context shows where your tokens are going > /rewind rolls back when an edit breaks the direction > /plan forces a blueprint before execution > /model matches the brain to the task > /goal lets it work toward a clear finish line This is the difference between asking AI for help and actually managing an AI worker. One mode gives you random useful answers. The other gives you memory, boundaries, checkpoints, context control and repeatable execution. Most people are still trying to write better prompts. The better move is building a better system around the model. save this

MOST PEOPLE USE CLAUDE CODE LIKE CHATGPT WITH A TERMINAL That is why they only get 30% of the value. They paste a task, wait for an answer, then keep explaining the same rules again when the context gets messy. The real power starts when you stop treating it like a chatbot and start treating it like an operating system for work. The useful commands are not flashy. They just remove the parts that quietly waste hours: > /init builds the project memory > /memory edits the rules Claude should keep > /clear resets the chat without losing the setup > /compact compresses a long session before quality drops > /context shows where your tokens are going > /rewind rolls back when an edit breaks the direction > /plan forces a blueprint before execution > /model matches the brain to the task > /goal lets it work toward a clear finish line This is the difference between asking AI for help and actually managing an AI worker. One mode gives you random useful answers. The other gives you memory, boundaries, checkpoints, context control and repeatable execution. Most people are still trying to write better prompts. The better move is building a better system around the model. save this

Asteri

15,241 просмотров • 1 месяц назад

Be Smart as Karpathy Andrej Karpathy with Teamily AI 🧠 Your Personal Knowledge Base: ✅ Built in One Chat. 📈 Compounded via Conversations. Karpathy’s insight is spot on ( It attracts 10 million views in a few days. The idea is simple: AI should build personal knowledge from everything you feed it, so it stops rediscovering things from scratch like a Retrieval-Augmented Generation (RAG). But here’s the reality — most people aren’t Stanford PhD-level geeks like Karpathy. For the rest of us, operating a hacky collection of scripts and tools (Obsidian Web Clipper, Marp, Dataview, etc.) as seen in Karpathy’s idea file is far too complex ( The Internet needs an intuitive product where a personal knowledge base is a persistent, compounding artifact — one that grows alongside the content you consume, the contexts you inhabit, and the questions you ask. Teamily AI ( is the answer. The conversation IS the knowledge base. It’s an AI-native messenger where AI teammates join your chats. They remember your past discussions, your preferences, and your team’s context — getting smarter the more you talk. No setup. No complicated workflows. Just text as you normally do. Whether you’re saving articles and videos, brainstorming at work, or collaborating with colleagues, your AI teammates are right there. They listen, remember, and help — not from scratch every time, but by building a personal knowledge graph of everything you’re involved in. In essence, your knowledge compounds automatically. ✨ The user experience is effortless. Whenever you need a well-organized view of your data, just ask the "Personal AI" at the top of the Teamily window: "Visualize my personal knowledge base" Want to customize the style or indexes? Just chat with it. You define how you manage your knowledge. Our co-founder Aiden has prepared a short video to show you just how easy it is. 📽️

Be Smart as Karpathy Andrej Karpathy with Teamily AI 🧠 Your Personal Knowledge Base: ✅ Built in One Chat. 📈 Compounded via Conversations. Karpathy’s insight is spot on ( It attracts 10 million views in a few days. The idea is simple: AI should build personal knowledge from everything you feed it, so it stops rediscovering things from scratch like a Retrieval-Augmented Generation (RAG). But here’s the reality — most people aren’t Stanford PhD-level geeks like Karpathy. For the rest of us, operating a hacky collection of scripts and tools (Obsidian Web Clipper, Marp, Dataview, etc.) as seen in Karpathy’s idea file is far too complex ( The Internet needs an intuitive product where a personal knowledge base is a persistent, compounding artifact — one that grows alongside the content you consume, the contexts you inhabit, and the questions you ask. Teamily AI ( is the answer. The conversation IS the knowledge base. It’s an AI-native messenger where AI teammates join your chats. They remember your past discussions, your preferences, and your team’s context — getting smarter the more you talk. No setup. No complicated workflows. Just text as you normally do. Whether you’re saving articles and videos, brainstorming at work, or collaborating with colleagues, your AI teammates are right there. They listen, remember, and help — not from scratch every time, but by building a personal knowledge graph of everything you’re involved in. In essence, your knowledge compounds automatically. ✨ The user experience is effortless. Whenever you need a well-organized view of your data, just ask the "Personal AI" at the top of the Teamily window: "Visualize my personal knowledge base" Want to customize the style or indexes? Just chat with it. You define how you manage your knowledge. Our co-founder Aiden has prepared a short video to show you just how easy it is. 📽️

Teamily AI

15,631 просмотров • 4 месяцев назад

Why is nobody talking about Polymarket's official API? You open Polymarket Wait for it to load... Click on a market... Wait again... Try to check another one... More waiting... By the time you see the price, it's already stale The opportunity moved while you were clicking through pages Someone else got there first There's a better way // Found the gem hiding in plain sight - library py-clob-client Official from Polymarket. MIT license I spent a week working with multiple markets Checking prices across different positions Monitoring various categories Tracking market movements Then discovered this library Game changer for workflow efficiency // Real example from last week: UI approach: Checking markets one by one through the interface API approach: Monitoring all relevant markets simultaneously with live updates Having comprehensive real-time data makes a meaningful difference Speed and information clarity are valuable advantages // Want to go deeper? Build an arbitrage bot You'll need Rust for execution speed Deploy the server geographically close to Polymarket's infrastructure Every millisecond counts when opportunities last 1-2 seconds. I built mine in Go for monitoring and analysis. Works great for that. But if you're hunting arbitrage at scale against other bots, Rust + low latency setup is the only way. The infrastructure race is real // "But I can't code" With today's AI tools you actually can Cursor, ChatGPT, Claude, Gemini, Kimi, Grok - they write code for you You just describe what you want AI generates it You copy-paste and run Join Polymarket to create: Programming is no longer a barrier Anyone can build now

Why is nobody talking about Polymarket's official API? You open Polymarket Wait for it to load... Click on a market... Wait again... Try to check another one... More waiting... By the time you see the price, it's already stale The opportunity moved while you were clicking through pages Someone else got there first There's a better way // Found the gem hiding in plain sight - library py-clob-client Official from Polymarket. MIT license I spent a week working with multiple markets Checking prices across different positions Monitoring various categories Tracking market movements Then discovered this library Game changer for workflow efficiency // Real example from last week: UI approach: Checking markets one by one through the interface API approach: Monitoring all relevant markets simultaneously with live updates Having comprehensive real-time data makes a meaningful difference Speed and information clarity are valuable advantages // Want to go deeper? Build an arbitrage bot You'll need Rust for execution speed Deploy the server geographically close to Polymarket's infrastructure Every millisecond counts when opportunities last 1-2 seconds. I built mine in Go for monitoring and analysis. Works great for that. But if you're hunting arbitrage at scale against other bots, Rust + low latency setup is the only way. The infrastructure race is real // "But I can't code" With today's AI tools you actually can Cursor, ChatGPT, Claude, Gemini, Kimi, Grok - they write code for you You just describe what you want AI generates it You copy-paste and run Join Polymarket to create: Programming is no longer a barrier Anyone can build now

BuBBliK

44,204 просмотров • 7 месяцев назад

Hermes agent just left the terminal. 𝗛𝗲𝗿𝗺𝗲𝘀 𝗗𝗲𝘀𝗸𝘁𝗼𝗽 dropped yesterday. native app for macOS, Windows, and Linux. for months Hermes was the agent that learned your projects, wrote its own skills, and built a model of who you are. all of it buried in terminal logs. now it has a window. the important part is that it's not a wrapper. it runs the same agent core, the same sessions, memory, and skills as the CLI. you can start a task in the terminal and finish it in the app without anything resetting. the state is shared across every interface, not copied between them. what the GUI actually adds: → streaming chat that shows live tool calls and inline reasoning instead of a spinner → a preview rail that renders pages, code, and images right beside the conversation → an artifacts panel that collects every file the agent has ever produced → remote gateway mode, so you can point the app at a VPS and run the heavy work elsewhere → skills, cron, profiles, and gateways managed point-and-click instead of through YAML → voice mode, drag-drop files, and inline image generation remote gateway mode is the one worth slowing down on. the agent runs 24/7 on a $5 server while you control it from your laptop like a local app. other agent UIs are chatboxes with a logo. this one shows the autonomy instead of hiding it, so you watch the skills load, the tools fire, and the artifacts pile up as it works. it was teased in Jensen's GTC keynote. MIT licensed, local-first, no telemetry. if you already run Hermes, download it and everything is already there. your chats, memory, and skills carry straight over. i wrote a full masterclass on Hermes Agent that walks through the SOUL. md identity layer, the three-tier memory system, the self-evolving skills loop, and how to run three specialized agents 24/7. desktop is the interface that finally does all of it justice. the article is quoted below.

Akshay 🚀

51,474 просмотров • 2 месяцев назад

HERMES JUST GOT A CHATGPT INTERFACE AND IT IS COMPLETELY FREE. No terminal. No command line. No technical setup that takes half a day to figure out. Here is what just became possible. You can now run Hermes, DeepSeek, Ollama, and OpenClaw from a single clean chat interface. Switch between them in one click. Upload files directly. Attach knowledge bases and notes. Preview code without touching the terminal once. Use it on mobile. Make voice and video calls. All of it. Free. Open source. The setup took one conversation with Hermes itself. Pasted the GitHub link in. Hermes installed Open Web UI in Docker on its own. Connected the API server and gateway automatically. A clean ChatGPT-level interface running entirely on local hardware was live in minutes. No subscription. No data leaving your machine. No API bill at the end of the month. The people who set this up this weekend will have a local AI stack that rivals what most companies are paying $2,000 a month for in cloud infrastructure. The people who wait will keep paying for tools that send their data somewhere they cannot see. Both tools are free. Both are open source. The only thing between you and this setup is the next 30 minutes. Follow CyrilXBT for the exact config, setup steps, and local AI workflows I use to run a full stack without spending a dollar on cloud inference.

HERMES JUST GOT A CHATGPT INTERFACE AND IT IS COMPLETELY FREE. No terminal. No command line. No technical setup that takes half a day to figure out. Here is what just became possible. You can now run Hermes, DeepSeek, Ollama, and OpenClaw from a single clean chat interface. Switch between them in one click. Upload files directly. Attach knowledge bases and notes. Preview code without touching the terminal once. Use it on mobile. Make voice and video calls. All of it. Free. Open source. The setup took one conversation with Hermes itself. Pasted the GitHub link in. Hermes installed Open Web UI in Docker on its own. Connected the API server and gateway automatically. A clean ChatGPT-level interface running entirely on local hardware was live in minutes. No subscription. No data leaving your machine. No API bill at the end of the month. The people who set this up this weekend will have a local AI stack that rivals what most companies are paying $2,000 a month for in cloud infrastructure. The people who wait will keep paying for tools that send their data somewhere they cannot see. Both tools are free. Both are open source. The only thing between you and this setup is the next 30 minutes. Follow CyrilXBT for the exact config, setup steps, and local AI workflows I use to run a full stack without spending a dollar on cloud inference.

CyrilXBT

37,120 просмотров • 3 месяцев назад