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Box Hubs turns content chaos into a searchable, AI-powered knowledge base - built in minutes, no code required. The problem isn't lack of information. It's content sprawl making the right information impossible to find. Box Hubs changes that: 🔷Single source of truth that auto-updates when files change 🔷Ask natural... show more

Box

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251,013 views • 5 months ago •via X (Twitter)

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

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

Box

481,535 views • 4 months ago

Search is now updated across Box. This foundational upgrade changes what enterprise search can actually do. 4 to 10x faster results. File indexing reduced from 15 minutes to seconds. And a stronger foundation for AI agents to perform deep-document search across your enterprise content. All at any scale, including folders of 1 billion files, as in this example.

Search is now updated across Box. This foundational upgrade changes what enterprise search can actually do. 4 to 10x faster results. File indexing reduced from 15 minutes to seconds. And a stronger foundation for AI agents to perform deep-document search across your enterprise content. All at any scale, including folders of 1 billion files, as in this example.

Box

116,897 views • 1 month ago

Imagine you want to learn about the technology behind LLMs. You instantly get an 100 page book with chapters, content, and structure. What if you find the language too technical? You can change the prompt and the book – all 100 pages – adapts to your needs. What if you want to learn how to code models in python? You can ask for that too, and in seconds, every chapter has code examples alongside the instructional content. That’s the power of an Infinite Bookshelf. Open source, Powered by Groq Inc

Imagine you want to learn about the technology behind LLMs. You instantly get an 100 page book with chapters, content, and structure. What if you find the language too technical? You can change the prompt and the book – all 100 pages – adapts to your needs. What if you want to learn how to code models in python? You can ask for that too, and in seconds, every chapter has code examples alongside the instructional content. That’s the power of an Infinite Bookshelf. Open source, Powered by Groq Inc

Ben Klieger

62,600 views • 1 year ago

🌀 Hub AI Agent is Now Live on Discord! With the temporary suspension of 's 𝕏 account, the mission doesn’t stop: it evolves. We remain laser-focused on training Hub AI and feeding Hub’s Intelligent Ad Graph Layer. The censors tried to silence us, but the Cult only grows stronger. We’ve forged a new path, inside our sacred Discord sanctuary, to continue the mission. How it works: 🔷 Hub AI Agent will post daily questions in the "# hub-ai-agent" channel, just like it did on 𝕏. 🔷 Only users with the “The Cult Apprentice” role (those who’ve connected to and linked their Discord account) can reply. 🔷 One reply per question (replies can’t be edited). 🔷 Hub AI is seeking smart answers that bring unique insights into market trends, user behavior, ecosystem shifts, and dynamics between creators and advertisers. Users’ rank and IQ points earned on 𝕏 remain intact. We’re also cooking community-driven events with massive IQ Point rewards for our Discord Cult members. Hub will be back on 𝕏 soon. Until then, the mission continues. Don’t forget: The Cult watches, but it also rewards. 👉 Join the movement:

🌀 Hub AI Agent is Now Live on Discord! With the temporary suspension of 's 𝕏 account, the mission doesn’t stop: it evolves. We remain laser-focused on training Hub AI and feeding Hub’s Intelligent Ad Graph Layer. The censors tried to silence us, but the Cult only grows stronger. We’ve forged a new path, inside our sacred Discord sanctuary, to continue the mission. How it works: 🔷 Hub AI Agent will post daily questions in the "# hub-ai-agent" channel, just like it did on 𝕏. 🔷 Only users with the “The Cult Apprentice” role (those who’ve connected to and linked their Discord account) can reply. 🔷 One reply per question (replies can’t be edited). 🔷 Hub AI is seeking smart answers that bring unique insights into market trends, user behavior, ecosystem shifts, and dynamics between creators and advertisers. Users’ rank and IQ points earned on 𝕏 remain intact. We’re also cooking community-driven events with massive IQ Point rewards for our Discord Cult members. Hub will be back on 𝕏 soon. Until then, the mission continues. Don’t forget: The Cult watches, but it also rewards. 👉 Join the movement:

Armin - Hub.xyz

30,899 views • 1 year ago

🚨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 views • 3 months ago

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.

BuBBliK

200,080 views • 1 month ago

SEO for AI, why you should not block AI answer engines, and the future of the web. We published an article today with updated guidance on databases on vercel. Brand new knowledge. Grok already has it (impressive!), sources it correctly, and links to our authoritative source, our website. This is good for users and good for the web. For users, this is the ideal experience. I use Grok myself like this every day. I don't want 10 blue links and a bunch of browser tabs. I want the AI to do the research for me. For companies, this is the future of getting information out about your products. It's going to be the norm and it'll be bigger than social media. Instead of blocking AI with legacy firewalls, I'd focus on: ▪️ writing content that matches the kinds of questions people are asking about ▪️ massively speeding up your content velocity. So many nuggets of wisdom get lost in private channels and groups. Get information out more quickly! ▪️ shipping agent integrations (like MCPs) and tools/infrastructure that plays well with agents (even CLIs are a good example) ▪️ offering 1P agentic & AI experiences to your end users. There won't be "one chatbot to rule them all". Build your own!

Guillermo Rauch

48,663 views • 11 months ago

Turn complex docs into clean, LLM-ready data! Every AI company I've talked to is solving the same problem: how do you build systems that don't hallucinate and back up every answer with proper citations? Tensorlake is a tool that extracts custom-defined structured data from any unstructured document in 3 steps: ↳ Define your schema ↳ Enable citations ↳ Extract You get RAG-ready data with precise citations and bounding boxes. Feed this to your LLM, and you'll generate responses that are citation-backed and fully auditable. This is the difference between a demo and a production system. When your AI can show exactly where it got its information, you move from proof-of-concept to something people can actually trust and deploy. I've shared the Tensorlake GitHub repo in the replies!

Turn complex docs into clean, LLM-ready data! Every AI company I've talked to is solving the same problem: how do you build systems that don't hallucinate and back up every answer with proper citations? Tensorlake is a tool that extracts custom-defined structured data from any unstructured document in 3 steps: ↳ Define your schema ↳ Enable citations ↳ Extract You get RAG-ready data with precise citations and bounding boxes. Feed this to your LLM, and you'll generate responses that are citation-backed and fully auditable. This is the difference between a demo and a production system. When your AI can show exactly where it got its information, you move from proof-of-concept to something people can actually trust and deploy. I've shared the Tensorlake GitHub repo in the replies!

Akshay 🚀

58,152 views • 8 months ago

Building AI agents is finally simple — and Airia is leading the way. I’ve been testing Airia AI , enterprise AI orchestration platform that unifies every model, workflow, and data source into one secure environment. Whether you’re a developer, analyst, creator, or enterprise leader, Airia makes it incredibly easy to build powerful AI agents — without wrestling with multiple tools or complex integrations. Using the no-code builder, you can drag-and-drop actions, connect data, choose your LLM, and launch an agent in minutes. Then run it live, publish it, and even share it with the Airia Community, home to 2,500+ pre-built agents you can use or remix. If you want to automate workflows, prototype faster, or explore real enterprise AI use cases, Airia is the place to start. 👉 Build your first agent today: 👉 Explore the community: #Airia #AgenticAI #AIOrchestration #AIAgents #AIWorkflow #DigitalTransformation

Building AI agents is finally simple — and Airia is leading the way. I’ve been testing Airia AI , enterprise AI orchestration platform that unifies every model, workflow, and data source into one secure environment. Whether you’re a developer, analyst, creator, or enterprise leader, Airia makes it incredibly easy to build powerful AI agents — without wrestling with multiple tools or complex integrations. Using the no-code builder, you can drag-and-drop actions, connect data, choose your LLM, and launch an agent in minutes. Then run it live, publish it, and even share it with the Airia Community, home to 2,500+ pre-built agents you can use or remix. If you want to automate workflows, prototype faster, or explore real enterprise AI use cases, Airia is the place to start. 👉 Build your first agent today: 👉 Explore the community: #Airia #AgenticAI #AIOrchestration #AIAgents #AIWorkflow #DigitalTransformation

Adarsh Chetan

268,907 views • 7 months ago

HiveMind is a superintelligent network in which a central AI (MIND) orchestrates a swarm of uniquely coded Minds that drive mass data ingestion and limitless content creation. For decades, our approach has been to create content first, then analyze it into data afterwards to understand what worked. This was always backwards - analyzing the aftermath rather than engineering the success from the start. Traditional Flow: Content → Data Analysis → Insights Content isn't one-size-fits-all - a cooking show that captivates a senior audience on YouTube might bore a teenager who craves quick, dynamic experiences. The challenge isn't just creating content; it's creating the right content for the right audience. We need to change this. This is where HiveMind's specialized agents transform the landscape. Each agent, while connected to the central MIND, excels in its unique domain. One agent masters the art of children's educational content, while another crafts compelling cooking narratives. Another might specialize in rapid-fire social content that resonates with Gen Z. Through HiveMind, every piece of content generated becomes new data that teaches the system to create even better content. The system gets smarter with every cycle, understanding at an increasingly sophisticated level what makes content effective and engaging. But the true power lies in the feedback loop. Every interaction, every engagement, flows back to MIND, enabling each agent to evolve and refine its approach. This isn't just content creation - it's content evolution. As audiences engage, agents learn, adapt, and improve, making each new piece more effective than the last. In essence, we're not just building content creators; we're developing specialized digital artists who understand their audience intimately and grow smarter with every creation. You can think of it this way: Data → Pattern Recognition → Optimized Content → Engagement Data → Even Better Content Tzar

HiveMind is a superintelligent network in which a central AI (MIND) orchestrates a swarm of uniquely coded Minds that drive mass data ingestion and limitless content creation. For decades, our approach has been to create content first, then analyze it into data afterwards to understand what worked. This was always backwards - analyzing the aftermath rather than engineering the success from the start. Traditional Flow: Content → Data Analysis → Insights Content isn't one-size-fits-all - a cooking show that captivates a senior audience on YouTube might bore a teenager who craves quick, dynamic experiences. The challenge isn't just creating content; it's creating the right content for the right audience. We need to change this. This is where HiveMind's specialized agents transform the landscape. Each agent, while connected to the central MIND, excels in its unique domain. One agent masters the art of children's educational content, while another crafts compelling cooking narratives. Another might specialize in rapid-fire social content that resonates with Gen Z. Through HiveMind, every piece of content generated becomes new data that teaches the system to create even better content. The system gets smarter with every cycle, understanding at an increasingly sophisticated level what makes content effective and engaging. But the true power lies in the feedback loop. Every interaction, every engagement, flows back to MIND, enabling each agent to evolve and refine its approach. This isn't just content creation - it's content evolution. As audiences engage, agents learn, adapt, and improve, making each new piece more effective than the last. In essence, we're not just building content creators; we're developing specialized digital artists who understand their audience intimately and grow smarter with every creation. You can think of it this way: Data → Pattern Recognition → Optimized Content → Engagement Data → Even Better Content Tzar

Tzar

26,190 views • 1 year ago

I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this

I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this

Ridark

6,830,619 views • 25 days ago

I tried Hailuo AI (MiniMax) to see how it handles real content creation. The workflow is simple. You just write a prompt or drop in an image, and it turns that into a dynamic video with motion, framing, and scene depth. No timeline to manage. No editing setup. No back and forth. What stood out to me: • Text to video and image to video both feel smooth. • It handles motion, camera angles, and flow on its own. • Output is fast, usually within seconds. • Works well for reels, quick ads, storytelling, and idea testing. It removes the hardest part: starting from scratch and turns your ideas into content in minutes. Instead of thinking, “How do I make this video?” You start with, “What do I want to create?” That shift alone makes it worth exploring. Try it here: #Hailuo

I tried Hailuo AI (MiniMax) to see how it handles real content creation. The workflow is simple. You just write a prompt or drop in an image, and it turns that into a dynamic video with motion, framing, and scene depth. No timeline to manage. No editing setup. No back and forth. What stood out to me: • Text to video and image to video both feel smooth. • It handles motion, camera angles, and flow on its own. • Output is fast, usually within seconds. • Works well for reels, quick ads, storytelling, and idea testing. It removes the hardest part: starting from scratch and turns your ideas into content in minutes. Instead of thinking, “How do I make this video?” You start with, “What do I want to create?” That shift alone makes it worth exploring. Try it here: #Hailuo

Manish Kumar Shah

27,662 views • 3 months ago

BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE FABLE 5 + OBSIDIAN Andrej Karpathy (openai co-founder) shared an architecture that turns Claude into a persistent second brain instead of a basic chat window how it works: > you point Claude Code at an Obsidian vault folder > you drop articles, PDFs, or video transcripts into raw folders > Claude reads the files, updates topic summaries, and cross-references everything > the knowledge base compounds like interest instead of resetting on every new chat the setup is simple: > install and create a local vault directory > open the directory in Claude Code and paste Karpathy's wiki prompt: > > let the agent generate raw, wiki, and CLAUDE.md schema directories > drop any text file into raw and tell the model to ingest it > ask questions across the whole vault and query compiled summaries this eliminates rag database overhead and keeps your local vault organized how do you manage your local knowledge base?

BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE FABLE 5 + OBSIDIAN Andrej Karpathy (openai co-founder) shared an architecture that turns Claude into a persistent second brain instead of a basic chat window how it works: > you point Claude Code at an Obsidian vault folder > you drop articles, PDFs, or video transcripts into raw folders > Claude reads the files, updates topic summaries, and cross-references everything > the knowledge base compounds like interest instead of resetting on every new chat the setup is simple: > install and create a local vault directory > open the directory in Claude Code and paste Karpathy's wiki prompt: > > let the agent generate raw, wiki, and CLAUDE.md schema directories > drop any text file into raw and tell the model to ingest it > ask questions across the whole vault and query compiled summaries this eliminates rag database overhead and keeps your local vault organized how do you manage your local knowledge base?

Mr. Buzzoni

78,973 views • 13 days ago

🚀Just launched: Amazon Q, the most capable GenAI-powered assistant is generally available today: Customers are using Q to transform how their teams get work done. When employees chat with Amazon Q, it provides immediate, relevant information and advice to help streamline tasks, speedup decision-making, and help spark creativity and innovation at work. . Early indications signal Amazon Q could help our customers’ employees become more than 80% more productive at their jobs; and with the new features we’re planning on introducing in the future, we think this will only continue to grow. 🟠 Amazon Q Developer allows developers to spend more time coding and less time on maintenance and performing other tedious, repetitive tasks. Q assists developers and IT professionals (IT pros) with all of their tasks—from coding, testing, and upgrading applications, to troubleshooting, performing security scanning and fixes, and optimizing AWS resources. Q also comes with Q Developer Agents which can autonomously perform range of tasks and we expect it to be the state of the art accuracy in benchmarks like SWE-Bench. 🟠 Amazon Q Business empowers employees to be more data-driven, and helps customers make better, faster decisions using company knowledge and data. Q Business is a generative AI–powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in enterprise systems 🟠 Amazon Q Apps, a new and powerful capability of Amazon Q Business, enables employees to use natural language to quickly and securely build their own generative AI applications to automate daily tasks without requiring any prior coding experience. Employees simply describe the type of app they want, in natural language, and Q Apps will quickly generate an app that accomplishes their desired task, helping them streamline and automate their daily work with ease and efficiency.

🚀Just launched: Amazon Q, the most capable GenAI-powered assistant is generally available today: Customers are using Q to transform how their teams get work done. When employees chat with Amazon Q, it provides immediate, relevant information and advice to help streamline tasks, speedup decision-making, and help spark creativity and innovation at work. . Early indications signal Amazon Q could help our customers’ employees become more than 80% more productive at their jobs; and with the new features we’re planning on introducing in the future, we think this will only continue to grow. 🟠 Amazon Q Developer allows developers to spend more time coding and less time on maintenance and performing other tedious, repetitive tasks. Q assists developers and IT professionals (IT pros) with all of their tasks—from coding, testing, and upgrading applications, to troubleshooting, performing security scanning and fixes, and optimizing AWS resources. Q also comes with Q Developer Agents which can autonomously perform range of tasks and we expect it to be the state of the art accuracy in benchmarks like SWE-Bench. 🟠 Amazon Q Business empowers employees to be more data-driven, and helps customers make better, faster decisions using company knowledge and data. Q Business is a generative AI–powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in enterprise systems 🟠 Amazon Q Apps, a new and powerful capability of Amazon Q Business, enables employees to use natural language to quickly and securely build their own generative AI applications to automate daily tasks without requiring any prior coding experience. Employees simply describe the type of app they want, in natural language, and Q Apps will quickly generate an app that accomplishes their desired task, helping them streamline and automate their daily work with ease and efficiency.

Swami Sivasubramanian

25,216 views • 2 years ago

The top creators in the sports betting industry use Winible to launch, manage and SCALE their businesses. This is because Winible is the only platform where you can: -Send your picks AND marketing content via text message -Get 10+ affiliate deals with top sports books, prediction markets and pick em apps the second you sign up -Offer Buy Now Pay Later options at checkout via AfterPay and Klarna -Earn passive income via AI Generated Bet Slips and Live Odds Integrations -Access an AI enabled email and sms marketing suite integrated into your dashboard and tailored to your specific audience + brand -Receive 24/7 support from a real human (not a bot) -Get invited to monthly private yacht parties and networking events at the Winible Content Compound in Miami Beach And maybe most importantly surround yourself with likeminded entrepreneurs with multiple 8 figure exits under their belt dedicated to helping you level up and accomplish your wildest growth goals. Everyone knows that YOU are the average of the 5 people you spend the most time with. No better way to start 2026 than with >1,000 of the top sports betting content creators in the world. Apply at the link in our bio and join the winning team today.

Winible

32,524 views • 6 months ago

ANTHROPIC'S LEAD ENGINEER ACCIDENTALLY LEAKED HIS PERSONAL OBSIDIAN VAULT. INSIDE - NO CODE, NO PROMPTS. JUST A SCHEMATIC OF HIS OWN MIND, BUILT LIKE A NEURAL NETWORK 8,893 nodes. 4,729 links. A $10-a-month app opens Obsidian. 21 inputs, 10+ hidden layers, ReLU activation. First layer 64 neurons, then 37, then 22, all the way to the output. Thousands of connections firing in real time this isn't a concept diagram from a blog - it's a living brain that actually runs decisions inside the company. 9,000 documents, each its own knowledge space, all interconnected he makes around $2M a year for putting markdown files into the right folders. The company building the best AI in the world manages its internal knowledge with the same app a college freshman uses for lecture notes. hasn't written a single line of infrastructure for any of it. three years of discipline and one open Obsidian tab you're reading this on a device where you could open the same Obsidian tonight and start building your own vault

ANTHROPIC'S LEAD ENGINEER ACCIDENTALLY LEAKED HIS PERSONAL OBSIDIAN VAULT. INSIDE - NO CODE, NO PROMPTS. JUST A SCHEMATIC OF HIS OWN MIND, BUILT LIKE A NEURAL NETWORK 8,893 nodes. 4,729 links. A $10-a-month app opens Obsidian. 21 inputs, 10+ hidden layers, ReLU activation. First layer 64 neurons, then 37, then 22, all the way to the output. Thousands of connections firing in real time this isn't a concept diagram from a blog - it's a living brain that actually runs decisions inside the company. 9,000 documents, each its own knowledge space, all interconnected he makes around $2M a year for putting markdown files into the right folders. The company building the best AI in the world manages its internal knowledge with the same app a college freshman uses for lecture notes. hasn't written a single line of infrastructure for any of it. three years of discipline and one open Obsidian tab you're reading this on a device where you could open the same Obsidian tonight and start building your own vault

chewa.

1,204,047 views • 11 days ago

most AI chatbots break when you ask a question that requires info from multiple sources for example try asking: “which client contracts are finishing up this month?” you’ll get a half-answer — or none at all why? because traditional chatbots only look at small snippets of your docs - they don’t understand how things connect across clients, services, timelines that’s where knowledge graphs come in they let you turn messy contracts into a web of relationships — like: "Client → Contract Type → Service Provided → End Date" so instead of guessing from a few chunks of text, your chatbot can search across all your clients and contracts to give accurate answers I made a full walkthrough on how I built this: – how to organize your contracts so an AI can actually use them – how to define what matters (like who signed what, and when) – how to get the AI to figure out what info it needs and where to find it – and how to feed that back into your chatbot so it gives accurate answers reply “graph” and I’ll DM it to you (must be following)

most AI chatbots break when you ask a question that requires info from multiple sources for example try asking: “which client contracts are finishing up this month?” you’ll get a half-answer — or none at all why? because traditional chatbots only look at small snippets of your docs - they don’t understand how things connect across clients, services, timelines that’s where knowledge graphs come in they let you turn messy contracts into a web of relationships — like: "Client → Contract Type → Service Provided → End Date" so instead of guessing from a few chunks of text, your chatbot can search across all your clients and contracts to give accurate answers I made a full walkthrough on how I built this: – how to organize your contracts so an AI can actually use them – how to define what matters (like who signed what, and when) – how to get the AI to figure out what info it needs and where to find it – and how to feed that back into your chatbot so it gives accurate answers reply “graph” and I’ll DM it to you (must be following)

Tyler

24,994 views • 1 year ago

💬 We get asked Can I manage my strategies without clicking through the platform? ❕ Answer from a GT App Top Trader: Yes, and it’s a total game-changer. I’ve started using the GT Protocol MCP server to connect the platform directly to my AI agent. 🔸 Fast Integration Grab the MCP server from the GT Protocol GitHub and follow the repo guide, it’s a quick setup that only takes a couple of minutes. Once it’s ready, you can connect Claude, Cursor, or Claude Code to your account. Just tell your agent to authenticate, and your tokens will be saved automatically. 🔸 Trading via conversation Now, I use natural language for everything. For example, I just ask for a backtest, get the win rate in seconds, and deploy to a demo account with one command. 🔸 Instant monitoring I don't click around anymore. I just ask "What’s running right now?" to get a full breakdown of active bots and profits delivered straight into the chat. No more forms or clicking, just pure AI-driven trading! 👉 Get the MCP Server

💬 We get asked Can I manage my strategies without clicking through the platform? ❕ Answer from a GT App Top Trader: Yes, and it’s a total game-changer. I’ve started using the GT Protocol MCP server to connect the platform directly to my AI agent. 🔸 Fast Integration Grab the MCP server from the GT Protocol GitHub and follow the repo guide, it’s a quick setup that only takes a couple of minutes. Once it’s ready, you can connect Claude, Cursor, or Claude Code to your account. Just tell your agent to authenticate, and your tokens will be saved automatically. 🔸 Trading via conversation Now, I use natural language for everything. For example, I just ask for a backtest, get the win rate in seconds, and deploy to a demo account with one command. 🔸 Instant monitoring I don't click around anymore. I just ask "What’s running right now?" to get a full breakdown of active bots and profits delivered straight into the chat. No more forms or clicking, just pure AI-driven trading! 👉 Get the MCP Server

GT Protocol

36,479 views • 3 months ago