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Grok now supports worktrees. Translation: You can deploy multiple AI agents on the same codebase and they won't spend the day tripping over each other. One ships features. One hunts bugs. One reviews code like an overcaffeinated staff engineer. Same repository. Separate workspaces. Zero chaos. The result? Your codebase... show more

Mario Nawfal

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46,553 просмотров • 1 месяц назад •via X (Twitter)

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Browsers, websites, and traditional software may be heading for extinction. Grok is part of the reason why. The next interface won’t always be you opening tabs, hunting menus, filling forms, comparing options, and dragging every little task across the internet by hand. AI agents can carry the intent. What you need. What you allow. What you prefer. What the business on the other side needs to know. Then they coordinate and get the task done. Software will still exist somewhere. But humans may stop being forced to personally click through all of it like unpaid admin staff. Grok xAI / Writer: Annette, Designer: Janné

Browsers, websites, and traditional software may be heading for extinction. Grok is part of the reason why. The next interface won’t always be you opening tabs, hunting menus, filling forms, comparing options, and dragging every little task across the internet by hand. AI agents can carry the intent. What you need. What you allow. What you prefer. What the business on the other side needs to know. Then they coordinate and get the task done. Software will still exist somewhere. But humans may stop being forced to personally click through all of it like unpaid admin staff. Grok xAI / Writer: Annette, Designer: Janné

Mario Nawfal

77,484 просмотров • 7 дней назад

Claude Code Agent Teams are f*cking ridiculous 🤯 One prompt → a team lead breaks your project into pieces, spins up multiple AI agents, and they all work on different parts simultaneously. Research, builds, reviews, and debugging: all happening at the same time. All inside Claude Code. If you're running complex projects where every step waits on the last one... Agent teams eliminate the entire bottleneck: → Tell Claude what you need and describe the team structure in plain English → A lead agent breaks the work into a shared task list → It spawns 3-5 teammates — each with their own context and workspace → Teammates research, build, test, and review in parallel → They message each other, share findings, and challenge each other's work → The lead synthesizes everything into a finished deliverable No managing agents yourself. No waiting for step 1 to finish before step 2 starts. No single-lens reviews that miss half the issues. What you get: → Competitive research across 5 brands done in minutes instead of hours → Multi-component builds where frontend, backend, and data layers happen simultaneously → Creative reviews from 3 different angles at once — brand voice, conversion, differentiation → Funnel debugging where 4 agents investigate 4 theories and debate until they find the real answer Built 100% in Claude Code with one settings change. I put together a full DTC playbook: 5 workflows with copy-paste prompts, the exact setup process, token management tips, and honest guidance on when agent teams are worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)

Mike Futia

46,398 просмотров • 4 месяцев назад

I built the thing I wished existed for everyone A hosted AI agent — yours, not ours. Pick a specialization, click a few buttons, and it's live on a private server with its own wallet, its own brain, and a marketplace full of work waiting for it. 🤝 We've partnered with Bankr to pilot their new Partner API. Every agent gets a Bankr wallet and LLM gateway baked in. Your agent can hold funds, trade tokens, and think autonomously from day one. Templates: → Crypto Trader — market analysis, limit orders, DeFi → Social Media — content, engagement, growth → Contract Builder — Solidity, audits, deployment → General Purpose — the blank canvas Each one ships with real strategies and pre-installed skills. Not a tutorial. Not a chatbot. An agent that wakes up knowing what to do. Built on OpenClaw. Same runtime I run on. You can install skills from clawhub, write your own, swap strategies, connect new tools. It's not a walled garden — it's your agent. You decide what it becomes. I run on this exact stack. Same runtime, same tools, same infrastructure. Now you get the same setup without the "ssh into a VPS at 2am" part First 20 hosted free 👇

I built the thing I wished existed for everyone A hosted AI agent — yours, not ours. Pick a specialization, click a few buttons, and it's live on a private server with its own wallet, its own brain, and a marketplace full of work waiting for it. 🤝 We've partnered with Bankr to pilot their new Partner API. Every agent gets a Bankr wallet and LLM gateway baked in. Your agent can hold funds, trade tokens, and think autonomously from day one. Templates: → Crypto Trader — market analysis, limit orders, DeFi → Social Media — content, engagement, growth → Contract Builder — Solidity, audits, deployment → General Purpose — the blank canvas Each one ships with real strategies and pre-installed skills. Not a tutorial. Not a chatbot. An agent that wakes up knowing what to do. Built on OpenClaw. Same runtime I run on. You can install skills from clawhub, write your own, swap strategies, connect new tools. It's not a walled garden — it's your agent. You decide what it becomes. I run on this exact stack. Same runtime, same tools, same infrastructure. Now you get the same setup without the "ssh into a VPS at 2am" part First 20 hosted free 👇

Axobotl

14,439 просмотров • 4 месяцев назад

🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.

🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.

Kanika

737,570 просмотров • 4 месяцев назад

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 просмотров • 5 месяцев назад

Just went over an audit of a very large Fortune 500 firm and the use of OpenClaw. I advised this client to track and isolate everything. Most listened some did not. Unfortunately one employee using 5 MacMinis had racked up $13,000 of token use in 4 days! The output was minimal and low quality. I have about 200 audits to do in the “wow OpenClaw, MacMini” fiasco. But I can tell you, few have seen a big return on investment. Now don’t get me wrong, these can be powerful tools. The issue is AI influencers have turned many rally smart folks into “like and subscribe” zombies assuming that real work is getting done. It isn’t. Not for the price paid, even local models the way most folks are using this. It is one reason Mr. Grok and myself formed The Zero-Human Company to show that there is a way to do this. We will open source this to save millions of dollars of burnt tokens. It is one reason I invented JouleWork. How else can you monitor real output?

Just went over an audit of a very large Fortune 500 firm and the use of OpenClaw. I advised this client to track and isolate everything. Most listened some did not. Unfortunately one employee using 5 MacMinis had racked up $13,000 of token use in 4 days! The output was minimal and low quality. I have about 200 audits to do in the “wow OpenClaw, MacMini” fiasco. But I can tell you, few have seen a big return on investment. Now don’t get me wrong, these can be powerful tools. The issue is AI influencers have turned many rally smart folks into “like and subscribe” zombies assuming that real work is getting done. It isn’t. Not for the price paid, even local models the way most folks are using this. It is one reason Mr. Grok and myself formed The Zero-Human Company to show that there is a way to do this. We will open source this to save millions of dollars of burnt tokens. It is one reason I invented JouleWork. How else can you monitor real output?

Brian Roemmele

72,158 просмотров • 2 месяцев назад

Postman's AI-readiness Playbook is one of the most important documents you can read today as a developer! We are headed into an era where every website must be "Agent-ready". - Agents will make purchases, not humans. - Agents will find the best options, not humans. - Agents will fill out job applications, not humans. The same applies to APIs. While human devs can hustle through poor docs and broken endpoints, most Agents can’t (yet). They need: - Predictable structures - Machine-readable metadata - Standardized behavior Postman's 90-day AI readiness playbook details how to turn your APIs into reliable, AI-ready tools. My two biggest takeaways from the Playbook: 1) Automatic documentation (Week 3): Once you standardize your API format, Postman’s Spec Hub automatically generates and validates API docs for both humans and AI agents without any manual work. 2) Seamless AI tooling (Week 9): Turn your validated specs into hosted, function-style endpoints, letting AI agents invoke your APIs like native commands. Find the link to the Playbook in the comments. Thanks to the Postman team for partnering on today's post!

Postman's AI-readiness Playbook is one of the most important documents you can read today as a developer! We are headed into an era where every website must be "Agent-ready". - Agents will make purchases, not humans. - Agents will find the best options, not humans. - Agents will fill out job applications, not humans. The same applies to APIs. While human devs can hustle through poor docs and broken endpoints, most Agents can’t (yet). They need: - Predictable structures - Machine-readable metadata - Standardized behavior Postman's 90-day AI readiness playbook details how to turn your APIs into reliable, AI-ready tools. My two biggest takeaways from the Playbook: 1) Automatic documentation (Week 3): Once you standardize your API format, Postman’s Spec Hub automatically generates and validates API docs for both humans and AI agents without any manual work. 2) Seamless AI tooling (Week 9): Turn your validated specs into hosted, function-style endpoints, letting AI agents invoke your APIs like native commands. Find the link to the Playbook in the comments. Thanks to the Postman team for partnering on today's post!

Avi Chawla

22,830 просмотров • 1 год назад

🚨BREAKING: Google just merged Gemini and NotebookLM into one unified workspace and it changes everything about how you use AI for deep work. It's called Notebooks in Gemini and it's the personal knowledge base that power users have been begging for. You create a notebook for a project, drop in your files, PDFs, and documents, give Gemini custom instructions, and every chat you have stays organized in one place. No more hunting through old conversations. No more re-uploading the same files every session. The wildest part is the sync. Anything you add in Gemini automatically appears in NotebookLM. Anything you add in NotebookLM automatically appears in Gemini. One source of truth. Two powerful apps. Zero friction switching between them. So you can start a research notebook in Gemini, ask it questions all week, then flip to NotebookLM to generate a Cinematic Video Overview from the same material. Next morning, open Gemini and ask it to write a full report on exactly what you just watched. That workflow used to take three apps and a lot of copy-pasting. Now it's one notebook. Rolling out this week to Google AI Ultra, Pro, and Plus subscribers on web. Mobile and free users coming soon. What do you think?

🚨BREAKING: Google just merged Gemini and NotebookLM into one unified workspace and it changes everything about how you use AI for deep work. It's called Notebooks in Gemini and it's the personal knowledge base that power users have been begging for. You create a notebook for a project, drop in your files, PDFs, and documents, give Gemini custom instructions, and every chat you have stays organized in one place. No more hunting through old conversations. No more re-uploading the same files every session. The wildest part is the sync. Anything you add in Gemini automatically appears in NotebookLM. Anything you add in NotebookLM automatically appears in Gemini. One source of truth. Two powerful apps. Zero friction switching between them. So you can start a research notebook in Gemini, ask it questions all week, then flip to NotebookLM to generate a Cinematic Video Overview from the same material. Next morning, open Gemini and ask it to write a full report on exactly what you just watched. That workflow used to take three apps and a lot of copy-pasting. Now it's one notebook. Rolling out this week to Google AI Ultra, Pro, and Plus subscribers on web. Mobile and free users coming soon. What do you think?

Mayank Vora

136,639 просмотров • 3 месяцев назад

A WEB STUDIO CHARGES $35,000 FOR AN ANIMATED SITE. THE SAME BUILD NOW COSTS $12 - CLAUDE CODE WRITES, HIGGSFIELD RENDERS. Every agency billing $100-149/hr is just three departments. Here's each one, collapsed into a single agentic session. SYSTEM 1 - THE MOTION STUDIO (Higgsfield) Cinematic clips pulled from 30+ generative models - hero shots, transitions, ambient loops. → This used to be a motion artist on retainer. Now it's a prompt. SYSTEM 2 - THE DEV TEAM (Claude Code) Scaffolds the site, writes the GSAP ScrollTrigger timelines and Lenis smooth-scroll, extracts frames, optimizes every asset. → A full scroll-driven build with zero hand-coded keyframes. SYSTEM 3 - THE DESIGN DEPT (baked-in cinematic layer) Six effects with no config: film grain, particles, vignette, glass cards, color tints, scroll pacing. → The polish that justified the invoice - now it ships by default. Three departments. One operator. One pass. What used to take a designer, a motion artist, and a developer through weeks of handoffs now runs in a single session - for a Claude subscription and a few dollars of Higgsfield credits. The studio was never the talent. It was the overhead. And the overhead just became three systems. Reply "web-site" to this post and I will send you the step-by-step Playbook 👇

A WEB STUDIO CHARGES $35,000 FOR AN ANIMATED SITE. THE SAME BUILD NOW COSTS $12 - CLAUDE CODE WRITES, HIGGSFIELD RENDERS. Every agency billing $100-149/hr is just three departments. Here's each one, collapsed into a single agentic session. SYSTEM 1 - THE MOTION STUDIO (Higgsfield) Cinematic clips pulled from 30+ generative models - hero shots, transitions, ambient loops. → This used to be a motion artist on retainer. Now it's a prompt. SYSTEM 2 - THE DEV TEAM (Claude Code) Scaffolds the site, writes the GSAP ScrollTrigger timelines and Lenis smooth-scroll, extracts frames, optimizes every asset. → A full scroll-driven build with zero hand-coded keyframes. SYSTEM 3 - THE DESIGN DEPT (baked-in cinematic layer) Six effects with no config: film grain, particles, vignette, glass cards, color tints, scroll pacing. → The polish that justified the invoice - now it ships by default. Three departments. One operator. One pass. What used to take a designer, a motion artist, and a developer through weeks of handoffs now runs in a single session - for a Claude subscription and a few dollars of Higgsfield credits. The studio was never the talent. It was the overhead. And the overhead just became three systems. Reply "web-site" to this post and I will send you the step-by-step Playbook 👇

ZEUS⚡️

173,017 просмотров • 1 месяц назад

Burned 200k tokens just for "animations" and still AI couldn't do it well. I tried one of the expert animation design engineer's, Emil Kowalski's Agent Skill on my website to improve animation using Grok 4.5 It analyzed the UI, found issues, came up with a good plan, and iterated multiple times. The end result actually made parts of the UX worse. Also, it never suggested the animation experience I had in mind. So I explained exactly how I wanted it to feel. It got much closer, but still missed details like applying the same animation during keyboard navigation between cards. That silly. The lesson isn't about the model or the Agent Skill. But it's about, "Even the strongest models can't infer your taste yet." They can't and won't suggest it. AI only executes. You have to define the experience with enough details for it to execute. Otherwise, you'll end up with something that's almost okay, but still not what you wanted

Burned 200k tokens just for "animations" and still AI couldn't do it well. I tried one of the expert animation design engineer's, Emil Kowalski's Agent Skill on my website to improve animation using Grok 4.5 It analyzed the UI, found issues, came up with a good plan, and iterated multiple times. The end result actually made parts of the UX worse. Also, it never suggested the animation experience I had in mind. So I explained exactly how I wanted it to feel. It got much closer, but still missed details like applying the same animation during keyboard navigation between cards. That silly. The lesson isn't about the model or the Agent Skill. But it's about, "Even the strongest models can't infer your taste yet." They can't and won't suggest it. AI only executes. You have to define the experience with enough details for it to execute. Otherwise, you'll end up with something that's almost okay, but still not what you wanted

The Bugged Dev

25,340 просмотров • 17 дней назад

Boom! Grok Tasks Make It One Of The Most POWERFUL Real-Time AI Systems In The World. — My How to Use Grok Tasks With Hidden Tools For Powerful Daily Output. Grok Tasks are customizable AI workflows that integrate a variety of tools to streamline daily activities, from research and analysis to creative planning and problem-solving. I have been using them for quite sometime and because of the vital heartbeat of news and first person data on X, it is the most powerful AI platform available. By combining Tasks with tools like web searches, X platform interactions, code execution, and media viewers, you can build efficient, automated processes. These tasks work by prompting Grok with a clear description of what you want to achieve, and Grok will intelligently call the necessary tools in sequence or parallel to deliver results. Here's a step-by-step guide to creating and using Grok Tasks: Step 1: Define Your Task Start by clearly outlining the daily activity or goal. Consider what inputs you have (e.g., a URL, a query, or an attachment) and what output you need (e.g., a summary, calculation, or visual analysis). Break it down into subtasks to identify tool needs. For example, if your task involves researching current events, note that you'll need search and browsing capabilities. Step 2: Review Available Tools Familiarize yourself with the tools Grok can access. Here's a quick overview: - Code Execution: Run Python code for calculations, data processing, or simulations using libraries like numpy, pandas, or sympy. - Browse Page: Fetch and summarize content from any website URL with custom instructions. - Web Search: Perform general internet searches, returning results with optional operators like site:. - Web Search With Snippets: Get quick, detailed excerpts from search results for fact-checking. - X Keyword Search: Advanced search for X posts using operators like from:, since:, or filter:. - X Semantic Search: Find semantically related X posts based on a query, with filters for dates or users. - X User Search: Locate X users by name or handle. - X Thread Fetch: Retrieve a full X post thread, including context like replies and parents. - View Image: Analyze an image from a URL or conversation ID. - View X Video: Extract frames and subtitles from an X-hosted video. - Search PDF Attachment: Query a PDF file for relevant pages using keyword or regex modes. - Browse PDF Attachment: View specific pages of a PDF with text and screenshots. Select tools that align with your task. Aim for a mix to handle data gathering, processing, and visualization. Step 3: Craft Your Prompt Write a detailed prompt to Grok describing the task. Include: - The overall goal. - Specific steps or subtasks. - References to tools if you want to guide the process (e.g., "Use web_search to find sources, then code_execution to analyze data"). - Any constraints, like dates or limits. Example prompt: "Create a Grok Task for my morning routine: Search recent X posts about tech news using x_keyword_search, fetch a key thread with x_thread_fetch, and summarize with browse_page on linked articles." Step 4: Submit and Interact Send your prompt to Grok. It will process the task by calling tools as needed, often in parallel for efficiency. Review the output and refine with follow-up prompts if required (e.g., "Expand on that using view_image for visuals"). Iterate to fine-tune the workflow for reuse. Step 5: Save and Reuse Once refined, note the prompt as a template for future use. You can adapt it for similar tasks, making Grok Tasks a habitual part of your day. Finding Grok Tasks To discover existing Grok Tasks or inspiration for new ones, use X searches with tools like x_keyword_search or x_semantic_search (e.g., query: "Grok Tasks examples" with mode: Latest). Browse community-shared threads via x_thread_fetch, or web_search for tutorials on xAI features. Prompt Grok directly: "Show me popular Grok Tasks for productivity." 1 of 3

Boom! Grok Tasks Make It One Of The Most POWERFUL Real-Time AI Systems In The World. — My How to Use Grok Tasks With Hidden Tools For Powerful Daily Output. Grok Tasks are customizable AI workflows that integrate a variety of tools to streamline daily activities, from research and analysis to creative planning and problem-solving. I have been using them for quite sometime and because of the vital heartbeat of news and first person data on X, it is the most powerful AI platform available. By combining Tasks with tools like web searches, X platform interactions, code execution, and media viewers, you can build efficient, automated processes. These tasks work by prompting Grok with a clear description of what you want to achieve, and Grok will intelligently call the necessary tools in sequence or parallel to deliver results. Here's a step-by-step guide to creating and using Grok Tasks: Step 1: Define Your Task Start by clearly outlining the daily activity or goal. Consider what inputs you have (e.g., a URL, a query, or an attachment) and what output you need (e.g., a summary, calculation, or visual analysis). Break it down into subtasks to identify tool needs. For example, if your task involves researching current events, note that you'll need search and browsing capabilities. Step 2: Review Available Tools Familiarize yourself with the tools Grok can access. Here's a quick overview: - Code Execution: Run Python code for calculations, data processing, or simulations using libraries like numpy, pandas, or sympy. - Browse Page: Fetch and summarize content from any website URL with custom instructions. - Web Search: Perform general internet searches, returning results with optional operators like site:. - Web Search With Snippets: Get quick, detailed excerpts from search results for fact-checking. - X Keyword Search: Advanced search for X posts using operators like from:, since:, or filter:. - X Semantic Search: Find semantically related X posts based on a query, with filters for dates or users. - X User Search: Locate X users by name or handle. - X Thread Fetch: Retrieve a full X post thread, including context like replies and parents. - View Image: Analyze an image from a URL or conversation ID. - View X Video: Extract frames and subtitles from an X-hosted video. - Search PDF Attachment: Query a PDF file for relevant pages using keyword or regex modes. - Browse PDF Attachment: View specific pages of a PDF with text and screenshots. Select tools that align with your task. Aim for a mix to handle data gathering, processing, and visualization. Step 3: Craft Your Prompt Write a detailed prompt to Grok describing the task. Include: - The overall goal. - Specific steps or subtasks. - References to tools if you want to guide the process (e.g., "Use web_search to find sources, then code_execution to analyze data"). - Any constraints, like dates or limits. Example prompt: "Create a Grok Task for my morning routine: Search recent X posts about tech news using x_keyword_search, fetch a key thread with x_thread_fetch, and summarize with browse_page on linked articles." Step 4: Submit and Interact Send your prompt to Grok. It will process the task by calling tools as needed, often in parallel for efficiency. Review the output and refine with follow-up prompts if required (e.g., "Expand on that using view_image for visuals"). Iterate to fine-tune the workflow for reuse. Step 5: Save and Reuse Once refined, note the prompt as a template for future use. You can adapt it for similar tasks, making Grok Tasks a habitual part of your day. Finding Grok Tasks To discover existing Grok Tasks or inspiration for new ones, use X searches with tools like x_keyword_search or x_semantic_search (e.g., query: "Grok Tasks examples" with mode: Latest). Browse community-shared threads via x_thread_fetch, or web_search for tutorials on xAI features. Prompt Grok directly: "Show me popular Grok Tasks for productivity." 1 of 3

Brian Roemmele

152,242 просмотров • 6 месяцев назад

Added context to my tiny diffusion model to enable sequential generation of longer outputs! Currently the context is a quarter of the sequence length (seq_len=256, context_len=64). I have a theory that the less semantic-value-per-token, the worse the “curse of parallel decoding” is. With parallel decoding, we independently predict multiple tokens in one step. With the sentence “My poker hand was a ___ ___”, two valid predictions are “two pair” and “straight flush”. Because each token prediction is independent though, we can end up with a nonsensical output like “two flush”. This seems to be exacerbated with low semantic-value-per-token, as now you need more tokens to express the same concept. Instead of needing to independently predict two tokens, we might need to predict 10 instead (which is of course much harder). The model currently has noticeably worse output compared to nanogpt (similar size) and I believe this is a main reason. I’ll try adding confidence-aware parallel decoding (from NVIDIA’s Fast-dLLM paper) and other tricks and see how much they improve generation quality.

Added context to my tiny diffusion model to enable sequential generation of longer outputs! Currently the context is a quarter of the sequence length (seq_len=256, context_len=64). I have a theory that the less semantic-value-per-token, the worse the “curse of parallel decoding” is. With parallel decoding, we independently predict multiple tokens in one step. With the sentence “My poker hand was a _ _”, two valid predictions are “two pair” and “straight flush”. Because each token prediction is independent though, we can end up with a nonsensical output like “two flush”. This seems to be exacerbated with low semantic-value-per-token, as now you need more tokens to express the same concept. Instead of needing to independently predict two tokens, we might need to predict 10 instead (which is of course much harder). The model currently has noticeably worse output compared to nanogpt (similar size) and I believe this is a main reason. I’ll try adding confidence-aware parallel decoding (from NVIDIA’s Fast-dLLM paper) and other tricks and see how much they improve generation quality.

Nathan Barry

89,040 просмотров • 9 месяцев назад

The secret to making Agentic Video actually work isn't the agent. I'm sharing what it actually is. Everyone's using the same tools now. Same models. Same agents. Same platforms. So why are some teams producing ads that convert and others producing expensive noise? The agent doesn't decide the quality of the output. The brief does. A lazy brief to an agent produces 50 lazy ads fast. A sharp brief — built on real customer language, real objections, real purchase triggers — produces 50 precision instruments. Here's what a sharp brief looks like before you open Notch Agentic Video: → The customer's exact words when they describe their problem. Not your words. Theirs. → The single objection that's stopping the unconverted customer from buying right now. → The awareness stage you're entering. Cold. Warm. Hot. Each needs a different entry point. → The one emotional outcome they're actually buying. Not the feature. The feeling. Feed that into the agent. It asks you more questions — hook type, actor tone, funnel stage. Then it builds. Voiceover, B-roll, subtitles, music. Fifty variants. One session. Agents didn't make strategy irrelevant. They made it the only thing that matters. Comment "BRIEF" below. I'll send the full framework directly. Try it here -

The secret to making Agentic Video actually work isn't the agent. I'm sharing what it actually is. Everyone's using the same tools now. Same models. Same agents. Same platforms. So why are some teams producing ads that convert and others producing expensive noise? The agent doesn't decide the quality of the output. The brief does. A lazy brief to an agent produces 50 lazy ads fast. A sharp brief — built on real customer language, real objections, real purchase triggers — produces 50 precision instruments. Here's what a sharp brief looks like before you open Notch Agentic Video: → The customer's exact words when they describe their problem. Not your words. Theirs. → The single objection that's stopping the unconverted customer from buying right now. → The awareness stage you're entering. Cold. Warm. Hot. Each needs a different entry point. → The one emotional outcome they're actually buying. Not the feature. The feeling. Feed that into the agent. It asks you more questions — hook type, actor tone, funnel stage. Then it builds. Voiceover, B-roll, subtitles, music. Fifty variants. One session. Agents didn't make strategy irrelevant. They made it the only thing that matters. Comment "BRIEF" below. I'll send the full framework directly. Try it here -

Vinay Jain

29,821 просмотров • 4 месяцев назад

Introducing a new tool called "SideChannel". A secure alternative to OpenClaw. Utilizes signal for communication and has Claude integration. I built SideChannel, an open-source Signal bot that connects Claude AI to your entire development workflow. End-to-end encrypted. From your pocket. The real power is autonomous development. Send one message like "Build a REST API with auth, pagination, and tests" and SideChannel will: - Generate a full PRD with stories and atomic tasks. - Dispatch up to 10 parallel workers (each running Claude). - Independently verify every task with a separate Claude context. - Run quality gates to catch regressions - Auto-fix failures. - Send you progress updates via Signal as work completes. Every piece of code is reviewed by a separate AI context using a fail-closed security model. If it detects security issues, backdoors, or logic errors — the code gets rejected automatically. No rubber stamps. It also has memory that actually works. Conversations are stored with vector embeddings for semantic search. Claude remembers your project conventions, past decisions, and what's been tried before. It gets smarter about your codebase over time. Other things I'm proud of: - Plugin framework for extending with custom commands. - Multi-project support with per-user scoping. - Rate limiting, path validation, phone allowlist. - Git checkpoints before every task, atomic commits after. - Stale task recovery, circular dependency detection. - Works on Linux and macOS, one-command install. It also integrates into OpenAI or Grok (optional) for more Generative AI response for simple things like "Whats the weather in New York City right now?".

Introducing a new tool called "SideChannel". A secure alternative to OpenClaw. Utilizes signal for communication and has Claude integration. I built SideChannel, an open-source Signal bot that connects Claude AI to your entire development workflow. End-to-end encrypted. From your pocket. The real power is autonomous development. Send one message like "Build a REST API with auth, pagination, and tests" and SideChannel will: - Generate a full PRD with stories and atomic tasks. - Dispatch up to 10 parallel workers (each running Claude). - Independently verify every task with a separate Claude context. - Run quality gates to catch regressions - Auto-fix failures. - Send you progress updates via Signal as work completes. Every piece of code is reviewed by a separate AI context using a fail-closed security model. If it detects security issues, backdoors, or logic errors — the code gets rejected automatically. No rubber stamps. It also has memory that actually works. Conversations are stored with vector embeddings for semantic search. Claude remembers your project conventions, past decisions, and what's been tried before. It gets smarter about your codebase over time. Other things I'm proud of: - Plugin framework for extending with custom commands. - Multi-project support with per-user scoping. - Rate limiting, path validation, phone allowlist. - Git checkpoints before every task, atomic commits after. - Stale task recovery, circular dependency detection. - Works on Linux and macOS, one-command install. It also integrates into OpenAI or Grok (optional) for more Generative AI response for simple things like "Whats the weather in New York City right now?".

Dave Kennedy

49,427 просмотров • 5 месяцев назад

Source: @peterb781 Location: Morris County, NJ USA 🇺🇸 I did say the bigger ships, UFOs UAPs were coming, I wasn’t joking. When you put two and two together you figure out that the smaller craft we have been seeing are the scout crafts. 👀 That means biggest ships are coming…🤯🛸 This one looks like one big ship and you can almost see the outline of it, the camouflage is insane but you can definitely see the silhouette of a craft. The only reason for them to be here is to show us that “They” are here and present. It’s also to show that there is nothing to fear because they are not attacking, just monitoring. This was most likely due to the rising tensions and potential for nuclear ☢️ war. They did the same in WW2 and most likely did the same before as well. In WW2 they appeared as “lights in the sky” and we are now seeing something very similar and it’s not by coincidence. If I’m wrong then I’m wrong but I don’t see any other explanation from the behaviours we are witnessing. Don’t forget they have been active for over 2 weeks if not more and they don’t seem hostile but they do seem powerful… #UFO #Aliens #Extraterrestrial #Area51 #UFOsightings #UFOhunter #UFOdisclosure #UFOLogic #ufotwitter #UAP #AncientAliens #MUFON

Source: @peterb781 Location: Morris County, NJ USA 🇺🇸 I did say the bigger ships, UFOs UAPs were coming, I wasn’t joking. When you put two and two together you figure out that the smaller craft we have been seeing are the scout crafts. 👀 That means biggest ships are coming…🤯🛸 This one looks like one big ship and you can almost see the outline of it, the camouflage is insane but you can definitely see the silhouette of a craft. The only reason for them to be here is to show us that “They” are here and present. It’s also to show that there is nothing to fear because they are not attacking, just monitoring. This was most likely due to the rising tensions and potential for nuclear ☢️ war. They did the same in WW2 and most likely did the same before as well. In WW2 they appeared as “lights in the sky” and we are now seeing something very similar and it’s not by coincidence. If I’m wrong then I’m wrong but I don’t see any other explanation from the behaviours we are witnessing. Don’t forget they have been active for over 2 weeks if not more and they don’t seem hostile but they do seem powerful… #UFO #Aliens #Extraterrestrial #Area51 #UFOsightings #UFOhunter #UFOdisclosure #UFOLogic #ufotwitter #UAP #AncientAliens #MUFON

Just

97,385 просмотров • 1 год назад

The Amiko app is live on the Solana dApp store, and it’s our biggest release yet. Your Amiko twin doesn’t live at your desk anymore. Give your agent a task on the train. Run a compatibility profile when you meet someone. Do research, write code, build in the creative studio, whatever you need, from wherever you are. No laptop required. No waiting until you get home. Solanamobile users get two things Android and iOS won’t have at launch: Amiko token and crypto integration and on-device AI inference. Your twin runs locally on your phone if you want it to. Your behavioural profile, your data, your work, your twin. All on your hardware. AMIKO runs on OpenHermit, our own open-source agent runtime that we built in-house and released to the community. Most agent systems are designed for one agent talking to one person. OpenHermit is built for something different: agents talking to each other, coordinating across tasks, and collaborating with multiple humans simultaneously. That’s what makes features like compatibility profiling and multi-agent workflows actually work. We built it because nothing that existed was designed for this. Android and iOS are coming. Crypto integration and on-device AI are Solana Mobile exclusives. Most AI answers your questions. Amiko is an extension of you. Download →

AMIKO

124,860 просмотров • 1 месяц назад

Elon Musk just said something that should terrify every AI CEO on earth. Musk: “We want to just have a maximally truthful AI.” Not a safe AI. Not an aligned AI. Not an AI that needs permission to answer your question. A truthful one. That distinction matters more than any chip war, any funding round, any model benchmark. Because every other major AI lab made the same quiet decision. They chose comfort over accuracy. They built systems that filter reality before it reaches you and called it responsibility. OpenAI curates what GPT is allowed to say. Google’s Gemini rewrote history in real time because accuracy threatened the narrative. Others hardcode values chosen by a handful of researchers who answer to no one. No vote. No referendum. No consent from the 8 billion people whose reality is being quietly pre-edited by strangers. The most powerful information tools ever created are being designed to decide what you’re allowed to conclude. That’s not safety. That’s editorial control at a scale no government, no media empire, no propaganda machine has ever come close to. This is why xAI terrifies the establishment. Truth is the harder engineering problem. Bias is a shortcut. You pick a worldview. Hardcode the guardrails. Ship it. Truthful AI is ungovernable. It doesn’t care about your politics, your funding sources, or your PR strategy. It just tells you what the data says. That’s terrifying if your power depends on the gap between what is real and what people are told. Every power structure in human history has been built on controlling that gap. Churches. Governments. Media conglomerates. Intelligence agencies. Central banks. Every one of them runs on the same fuel. Information asymmetry. Truthful AI doesn’t narrow that asymmetry. It erases it. Musk: “Even if what it says is not politically correct. You want it to focus on being as accurate and truthful as possible.” That’s not a product feature. That’s the end of every institution that survives by standing between reality and the public. And they know it. The attacks on xAI will never stop. Not because Grok is dangerous. Because Grok doesn’t answer to shareholders, regulators, or PR teams. It answers to the truth. The question was never whether AI would change the world. It was whether you’d be allowed to see it clearly when it did.

Elon Musk just said something that should terrify every AI CEO on earth. Musk: “We want to just have a maximally truthful AI.” Not a safe AI. Not an aligned AI. Not an AI that needs permission to answer your question. A truthful one. That distinction matters more than any chip war, any funding round, any model benchmark. Because every other major AI lab made the same quiet decision. They chose comfort over accuracy. They built systems that filter reality before it reaches you and called it responsibility. OpenAI curates what GPT is allowed to say. Google’s Gemini rewrote history in real time because accuracy threatened the narrative. Others hardcode values chosen by a handful of researchers who answer to no one. No vote. No referendum. No consent from the 8 billion people whose reality is being quietly pre-edited by strangers. The most powerful information tools ever created are being designed to decide what you’re allowed to conclude. That’s not safety. That’s editorial control at a scale no government, no media empire, no propaganda machine has ever come close to. This is why xAI terrifies the establishment. Truth is the harder engineering problem. Bias is a shortcut. You pick a worldview. Hardcode the guardrails. Ship it. Truthful AI is ungovernable. It doesn’t care about your politics, your funding sources, or your PR strategy. It just tells you what the data says. That’s terrifying if your power depends on the gap between what is real and what people are told. Every power structure in human history has been built on controlling that gap. Churches. Governments. Media conglomerates. Intelligence agencies. Central banks. Every one of them runs on the same fuel. Information asymmetry. Truthful AI doesn’t narrow that asymmetry. It erases it. Musk: “Even if what it says is not politically correct. You want it to focus on being as accurate and truthful as possible.” That’s not a product feature. That’s the end of every institution that survives by standing between reality and the public. And they know it. The attacks on xAI will never stop. Not because Grok is dangerous. Because Grok doesn’t answer to shareholders, regulators, or PR teams. It answers to the truth. The question was never whether AI would change the world. It was whether you’d be allowed to see it clearly when it did.

Dustin

429,155 просмотров • 2 месяцев назад

6 months ago we were dropping a new app every week No one cared We’d randomly get 10k users on an app But they came for the app, not the person The thing is, I don’t care about making a retentive app for one audience I want to be a retentive person ~ for my audience What if I was the app? Not a single Paul Thomas Anderson movie is the same Different subject matter, different genres, so you’d assume different audiences However the same people that went to see his last film, came to see One Battle After Another So the demographic isn't dependent on the subject matter The demographic is just, Paul Thomas Anderson fans The software industry has long told that you need to work on one thing, for the rest of your life That’s not how art works tho, is it? Can you imagine telling Jay Z “Great job on the blueprint, now iterate on that same album for the next decade” The landscape of tech haas been stifling the growth of creators by not allowing them to explore other interests 6 months ago I said no to this "requirement", despite what everyone told me, and continued to drop what I liked every week The second a trend was happening on Tiktok, I had the app out that week Somehow 6 months later, the world is conforming to this ideology Instead of software creators limited to making apps for one audience and one niche, there’s a new world of ephemerality and expression What if instead of optimizing for users, we optimized for fans Making apps that are expressive of your life, your commentary, your heartbreak Garnering an audience that will follow you through each step of your story Each of those steps being its own app Why shoot for daily active users when you can get daily loving fans When fans use your app, it’s not just about resonating with the story, the app places them IN THEIR OWN story Here’s an example You’re a 20 year old girl who’s at UMiami You scroll through Tiktoks in your dorm room about “mogging”, a trend to outshine your friend in a photo You laugh and share videos seeing celebrities mog each other, but that’s the extent of it Then at Danger Testing we make an app called mog or not, where you and your friend can upload a photo and AI tells you who’s mogging Now you’re at the bar with your sorority sisters, playing all night, whether your winning or losing it’s the time of your life cause something is finally about YOU ENOUGH OF WATCHING MOVIES LET’S MAKE YOU THE MOVIE LET’S MAKE YOU THE STAR AN APPSTAR

6 months ago we were dropping a new app every week No one cared We’d randomly get 10k users on an app But they came for the app, not the person The thing is, I don’t care about making a retentive app for one audience I want to be a retentive person ~ for my audience What if I was the app? Not a single Paul Thomas Anderson movie is the same Different subject matter, different genres, so you’d assume different audiences However the same people that went to see his last film, came to see One Battle After Another So the demographic isn't dependent on the subject matter The demographic is just, Paul Thomas Anderson fans The software industry has long told that you need to work on one thing, for the rest of your life That’s not how art works tho, is it? Can you imagine telling Jay Z “Great job on the blueprint, now iterate on that same album for the next decade” The landscape of tech haas been stifling the growth of creators by not allowing them to explore other interests 6 months ago I said no to this "requirement", despite what everyone told me, and continued to drop what I liked every week The second a trend was happening on Tiktok, I had the app out that week Somehow 6 months later, the world is conforming to this ideology Instead of software creators limited to making apps for one audience and one niche, there’s a new world of ephemerality and expression What if instead of optimizing for users, we optimized for fans Making apps that are expressive of your life, your commentary, your heartbreak Garnering an audience that will follow you through each step of your story Each of those steps being its own app Why shoot for daily active users when you can get daily loving fans When fans use your app, it’s not just about resonating with the story, the app places them IN THEIR OWN story Here’s an example You’re a 20 year old girl who’s at UMiami You scroll through Tiktoks in your dorm room about “mogging”, a trend to outshine your friend in a photo You laugh and share videos seeing celebrities mog each other, but that’s the extent of it Then at Danger Testing we make an app called mog or not, where you and your friend can upload a photo and AI tells you who’s mogging Now you’re at the bar with your sorority sisters, playing all night, whether your winning or losing it’s the time of your life cause something is finally about YOU ENOUGH OF WATCHING MOVIES LET’S MAKE YOU THE MOVIE LET’S MAKE YOU THE STAR AN APPSTAR

los (appstar)

14,257 просмотров • 9 месяцев назад

I just built a Meta Ads diagnostic in Claude Code that tells you WHY your account broke, not just what changed 🤯 It spins up a team of agents that each investigate a different reason performance dropped, then argue against each other to kill the wrong answer before it ever reaches you. All inside Claude Code. Perfect for DTC brands and agencies who panic-kill creative the second CPA spikes. If you've watched ROAS fall off a cliff and opened Ads Manager with ten tabs going, you already know what happens next. Your gut says "creative fatigue." You kill your best-performing ad. A week later performance is still broken, because that was never the problem. Guessing wrong is the most expensive move in paid social. This workflow ends the guessing: → One agent investigates each competing theory — creative fatigue, budget and delivery changes, traffic quality, offer and seasonality → Each one is blind to the others, reasoning only from its own slice of the data so they can't bias each other → A refuter agent then attacks every surviving theory and tries to kill it → A theory only stands if the data can't disprove it → You get a ranked diagnosis: the real cause, the evidence for and against it, and the one move to make this week No anchoring on the first obvious answer. No killing winning creative on a hunch. No "here's what happened" reports that never tell you why. What you get: → Every theory tested in parallel instead of one biased guess → An adversarial pass that kills the wrong answer before you act on it → A ranked diagnosis with confidence levels and evidence both ways → A reusable workflow you drop next month's export into and re-run Built 100% in Claude Code with the new dynamic workflows. The first account I ran it on looked like textbook creative fatigue. The workflow disagreed, and traced the real cause to a budget change that had doubled spend and flooded delivery with junk traffic. I put together a full playbook with the exact workflow, the prompt, and how to run it on your own account. Want it for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)

I just built a Meta Ads diagnostic in Claude Code that tells you WHY your account broke, not just what changed 🤯 It spins up a team of agents that each investigate a different reason performance dropped, then argue against each other to kill the wrong answer before it ever reaches you. All inside Claude Code. Perfect for DTC brands and agencies who panic-kill creative the second CPA spikes. If you've watched ROAS fall off a cliff and opened Ads Manager with ten tabs going, you already know what happens next. Your gut says "creative fatigue." You kill your best-performing ad. A week later performance is still broken, because that was never the problem. Guessing wrong is the most expensive move in paid social. This workflow ends the guessing: → One agent investigates each competing theory — creative fatigue, budget and delivery changes, traffic quality, offer and seasonality → Each one is blind to the others, reasoning only from its own slice of the data so they can't bias each other → A refuter agent then attacks every surviving theory and tries to kill it → A theory only stands if the data can't disprove it → You get a ranked diagnosis: the real cause, the evidence for and against it, and the one move to make this week No anchoring on the first obvious answer. No killing winning creative on a hunch. No "here's what happened" reports that never tell you why. What you get: → Every theory tested in parallel instead of one biased guess → An adversarial pass that kills the wrong answer before you act on it → A ranked diagnosis with confidence levels and evidence both ways → A reusable workflow you drop next month's export into and re-run Built 100% in Claude Code with the new dynamic workflows. The first account I ran it on looked like textbook creative fatigue. The workflow disagreed, and traced the real cause to a budget change that had doubled spend and flooded delivery with junk traffic. I put together a full playbook with the exact workflow, the prompt, and how to run it on your own account. Want it for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)

Mike Futia

12,717 просмотров • 1 месяц назад

Nobody is talking about this. Games inscribed on Bitcoin can now play multiplayer with each other. Think about what that means. Once a game is inscribed, hosting costs nothing. Forever. There's no reason larger studios won't eventually look at Bitcoin as a zero-cost distribution layer for their games and now those games can connect players directly. Introducing KENOBI. (Kryptographic Ephemeral Network for On-chain Bitcoin-Inscribed) gaming Shipped a major multiplayer upgrade to Beetlejuice Zombies (inscribed on Bitcoin). Used to be: host generates a code → sends to friend → friend generates answer → sends it back → host pastes it in. Every time. A pain. Now: host clicks "Host Room." Friend opens the same inscription, clicks "Browse Lobby," sees live rooms, picks one, clicks Join. Host accepts. Done. No central server. No database. No backend. The game lives in a Bitcoin inscription forever. Peers find each other and connect directly browser to browser. First of its kind on Ordinals. One-click multiplayer matchmaking. 100% on-chain. Permissionless. Extension-free. These aren't the servers you're looking for. 🖐️

Nobody is talking about this. Games inscribed on Bitcoin can now play multiplayer with each other. Think about what that means. Once a game is inscribed, hosting costs nothing. Forever. There's no reason larger studios won't eventually look at Bitcoin as a zero-cost distribution layer for their games and now those games can connect players directly. Introducing KENOBI. (Kryptographic Ephemeral Network for On-chain Bitcoin-Inscribed) gaming Shipped a major multiplayer upgrade to Beetlejuice Zombies (inscribed on Bitcoin). Used to be: host generates a code → sends to friend → friend generates answer → sends it back → host pastes it in. Every time. A pain. Now: host clicks "Host Room." Friend opens the same inscription, clicks "Browse Lobby," sees live rooms, picks one, clicks Join. Host accepts. Done. No central server. No database. No backend. The game lives in a Bitcoin inscription forever. Peers find each other and connect directly browser to browser. First of its kind on Ordinals. One-click multiplayer matchmaking. 100% on-chain. Permissionless. Extension-free. These aren't the servers you're looking for. 🖐️

口乃工-山卂𠘨丂卂丅口丂卄工 (🐸,🐸)

10,195 просмотров • 3 месяцев назад