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Your AI is average. Mathematically If you're using the same ChatGPT as 100M other people with zero context about your actual work, you're getting average intelligence. Generic answers to specific problems. I watched my team copy-paste the same project context between Claude, ChatGPT, and Gemini all day. Re-uploading the... same docs every session. Re-explaining the same projects on repeat. That's not an AI problem. That's a context problem. ClickUp just shipped Brain² and it flips the whole thing: one AI that already knows every task, doc, chat, and decision in your company — and how they all connect. No briefing. No re-explaining. It just knows. Pick any model (GPT, Claude Opus, Gemini), it routes to the best one for the job, runs with full context of your work, and actually does the work alongside your team. Multiplayer AI that gets smarter every time anyone on your team uses it. The wild part: the more your team uses it, the more it becomes your company's collective brain. 150 years of team expertise on tap instead of one person's memory. Average is a choice now.show more

Suryansh Tiwari

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244,203 Aufrufe • vor 1 Monat •via X (Twitter)

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We launched our Company Brain!! 🧠 onboarding is a context problem: your first weeks you're not working, you're reconstructing what the team already knows. company brain is that context, queryable and able to act. shared memory for your team, in slack: → answers from the company's own knowledge, grounded and cited → acts in your tools as you, files the ticket and assigns it, with your approval → runs on a permissions graph, so it only reads with your access → chimes in only when it can help → same brain and permissions follow you into cursor and claude code when i joined supermemory, i braced for the onboarding tax. it never came. i just asked the company brain

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Muskan Jain

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ClickUp has launched Brain², which automatically wires in your company's projects, org setup, and decisions as context for any frontier model you choose. It allows you to pick models like Claude 4.7, GPT 5.5, or Gemini 3.1, and Brain compresses everything your team knows before the model ever sees a prompt. > Preferences Memory - Brain retains your role in the org, team, and format preferences across every session > MCP live - connects Gmail, GitHub, Figma, and Slack natively, no middleware needed > Brain Slides - polished decks from one prompt, built on designer-authored templates

ClickUp has launched Brain², which automatically wires in your company's projects, org setup, and decisions as context for any frontier model you choose. It allows you to pick models like Claude 4.7, GPT 5.5, or Gemini 3.1, and Brain compresses everything your team knows before the model ever sees a prompt. > Preferences Memory - Brain retains your role in the org, team, and format preferences across every session > MCP live - connects Gmail, GitHub, Figma, and Slack natively, no middleware needed > Brain Slides - polished decks from one prompt, built on designer-authored templates

🚨 AI News | TestingCatalog

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clickup just mass-obsoleted every AI agent platform here's the thing nobody's talking about: AI doesn't fail because the models are bad. it fails because it has no context. you paste in a prompt. it hallucinates. you blame the tool. but the tool was never the problem. the CONTEXT was. clickup just solved this. their new "super agents" live INSIDE your workspace. they see everything: - your tasks - your docs - your meetings - your conversations - your decisions 100% context. always on. always scraping. this isn't bolted-on AI calling APIs. this is AI that already knows your business. i've been running an AI backend for my agency. the architecture works - but you have to BUILD the context layer. clickup just made that automatic. i already use it. have tons of data there. this is about to be unbelievable. if you're building automations and you're not paying attention to this— you're about to get lapped. playing with it hard over the next 2 days. full deep dive coming. drop "SUPER" and i'll send you the breakdown when it's ready.

clickup just mass-obsoleted every AI agent platform here's the thing nobody's talking about: AI doesn't fail because the models are bad. it fails because it has no context. you paste in a prompt. it hallucinates. you blame the tool. but the tool was never the problem. the CONTEXT was. clickup just solved this. their new "super agents" live INSIDE your workspace. they see everything: - your tasks - your docs - your meetings - your conversations - your decisions 100% context. always on. always scraping. this isn't bolted-on AI calling APIs. this is AI that already knows your business. i've been running an AI backend for my agency. the architecture works - but you have to BUILD the context layer. clickup just made that automatic. i already use it. have tons of data there. this is about to be unbelievable. if you're building automations and you're not paying attention to this— you're about to get lapped. playing with it hard over the next 2 days. full deep dive coming. drop "SUPER" and i'll send you the breakdown when it's ready.

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The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.

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You don't need a 30 step AI workflow to manifest your brand campaign. With Agent One by Invideo, you just need to chat with it and watch your vision flourish. You give it context once and it remembers it forever, across every generation. Just like that. No re-explaining the same lighting condition 500 times. No re-feeding it the same character sheet a millions times. It does the heavy-lifting so you can make real progress.

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I just built a self-improving second brain in Claude Code 🤯 A brain that runs your brand: every tool reads from it, it's wired to your live data, and it gets smarter every week. All running on the Claude Agent SDK. Perfect for DTC brands and agencies whose AI output sounds generic because every new chat starts from zero. If you're re-explaining your brand to AI every single time — re-pasting the voice guidelines, re-describing the customer you've described a hundred times, re-uploading the same positioning doc you uploaded yesterday, and still editing for an hour to strip out the generic phrasing... A brand second brain fixes the entire loop: → Build 3 foundation files once: brand DNA, voice, and customer → Every skill you create reads from them automatically → Wire in live data — your ad account, competitor ads, customer reviews → A weekly routine refreshes the brain with what's actually working → Every output comes back on-brand on the first pass No re-briefing AI on every chat. No hour of editing to undo generic phrasing. No brain that goes stale the week after you build it. What a second brain gives you: → The exact 3-file foundation that runs the whole system → The skill structure that makes every tool brand-aware by default → The live-data wiring that keeps it grounded in reality → The weekly self-improvement loop that keeps it sharp → The cold-start sequence to stand it all up from zero Built 100% in Claude Code. I put together the full playbook with the file structure, the wiring, and the exact setup. Want it for free? > Like this post > Comment "BRAIN" And I'll send it over (must be following so I can DM)

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Been wearing this titanium ring for a bit now and it quietly changed how I talk to my AI tools No more re explaining context every time I open Claude or ChatGPT Wear the Context. Loop in Real Life.

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Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!

Harjot Gill

4,775,106 Aufrufe • vor 3 Monaten

Claude Skills are a cheat code for DTC creative teams 🤯 One setup, reusable forever. Claude automatically follows your exact creative process — briefs, hooks, ad copy, research — without you explaining anything twice. Perfect for e-comm brands and agencies who are using Claude for creative work but wasting time re-explaining context every single conversation. Here's the problem: You open Claude: you paste in your brand guidelines, explain your brief format, write the copy, you close the chat. Next day, you do it all over again. Every conversation starts from zero. You're burning 20 minutes on setup before you even get to the actual work. Claude Skills fix this: → Write your creative process once as a Skill (a simple markdown file) → Claude reads it automatically whenever the task comes up → Skills compose — research triggers the research Skill, briefs trigger the brief Skill, copy triggers the copy Skill → All in one conversation, all building on each other → Share across your team so everyone gets the same quality output No re-explaining your brand voice. No pasting the same context every chat. No siloed projects that don't talk to each other. What's in the playbook: → The full architecture (how Skills trigger, chain, and compose) → 5 ready-to-use Skill templates built for DTC and agency creative teams → Step-by-step setup from zero to working Skills → How to write instructions that produce consistent output every time → The composability framework for running multi-step creative workflows in one conversation I put together the complete Claude Skills Playbook for DTC brands and creative agencies. Want it for free? >Like this post >Comment "SKILLS" And I'll send it over (must be following so I can DM)

Mike Futia

31,910 Aufrufe • vor 5 Monaten

If you're hitting Claude Code's context limit, check your terminal output before blaming your project size. Every command Claude runs dumps raw output into your context window. git status : 76% of it is noise. A failed cargo test : 155 lines becomes 3. A grep across your codebase : same story You're not running out of context because your code is too big. You're running out because the commands are bleeding you dry before you get anywhere. RTK intercepts that output, compresses it, and hands Claude a clean version instead. 60–90% fewer tokens. Same information. Runs in the background after a one-command setup. Real numbers from 2,900+ commands: average 89% compression across the board. MIT license. Free. 39k GitHub stars. rtk init -g That's it. Restart Claude Code and every command is compressed automatically.

If you're hitting Claude Code's context limit, check your terminal output before blaming your project size. Every command Claude runs dumps raw output into your context window. git status : 76% of it is noise. A failed cargo test : 155 lines becomes 3. A grep across your codebase : same story You're not running out of context because your code is too big. You're running out because the commands are bleeding you dry before you get anywhere. RTK intercepts that output, compresses it, and hands Claude a clean version instead. 60–90% fewer tokens. Same information. Runs in the background after a one-command setup. Real numbers from 2,900+ commands: average 89% compression across the board. MIT license. Free. 39k GitHub stars. rtk init -g That's it. Restart Claude Code and every command is compressed automatically.

Charlie Hills

16,666 Aufrufe • vor 3 Monaten

You know that moment after a great meeting when the idea is clear in your head—but your AI knows none of the context? So you open ChatGPT, Claude, or Codex and start explaining everything again. That gap is exactly what Vocci Ring is designed to close. Worn throughout the day, Vocci captures real-world context as it happens—from meetings and coffee chats to the ideas that surface between scheduled moments—and makes it usable inside the AI tools you already rely on. No rebuilding the conversation from memory. No endless copying and pasting. Just call Vocci Ring from your preferred AI tool and continue from what actually happened. What I appreciate most is that Vocci isn’t trying to replace the AI ecosystem you already use. It quietly gives those tools the context they’ve been missing. Your AI shouldn’t have to start from a blank prompt every time. Wear the Context. Loop in Real Life. #Vocci #AIRing #AIWearables

You know that moment after a great meeting when the idea is clear in your head—but your AI knows none of the context? So you open ChatGPT, Claude, or Codex and start explaining everything again. That gap is exactly what Vocci Ring is designed to close. Worn throughout the day, Vocci captures real-world context as it happens—from meetings and coffee chats to the ideas that surface between scheduled moments—and makes it usable inside the AI tools you already rely on. No rebuilding the conversation from memory. No endless copying and pasting. Just call Vocci Ring from your preferred AI tool and continue from what actually happened. What I appreciate most is that Vocci isn’t trying to replace the AI ecosystem you already use. It quietly gives those tools the context they’ve been missing. Your AI shouldn’t have to start from a blank prompt every time. Wear the Context. Loop in Real Life. #Vocci #AIRing #AIWearables

AI StackLab

52,413 Aufrufe • vor 3 Tagen

OpenClaw just got a plugin nobody is talking about. And it can replace a whole operations team. It is called Paperclip. It lets you build a full AI company on your own computer. You get an AI CEO. You get a marketing team. You get a tech team. They have real memory so they never forget a task. They wake up every day and do the work for you. You do not have to manage them or pay them a salary. Your data stays safe because it runs on your hardware. Here is how to start today. Go to GitHub and download OpenClaw. Install the Paperclip dashboard inside it. Pick one task and hire your first AI worker.

OpenClaw just got a plugin nobody is talking about. And it can replace a whole operations team. It is called Paperclip. It lets you build a full AI company on your own computer. You get an AI CEO. You get a marketing team. You get a tech team. They have real memory so they never forget a task. They wake up every day and do the work for you. You do not have to manage them or pay them a salary. Your data stays safe because it runs on your hardware. Here is how to start today. Go to GitHub and download OpenClaw. Install the Paperclip dashboard inside it. Pick one task and hire your first AI worker.

Julian Goldie SEO

33,889 Aufrufe • vor 4 Monaten

Your Claude has a tell, and almost nobody uses it. Make it start every reply with your name. One line in custom instructions, no code. The moment it stops saying your name, its context window is full. That is the exact point the output starts drifting, and you do not notice. Name stops? Start a fresh chat. It has killed about 90% of my “why has Claude gone weird” moments. Miners sent a canary down the pit to catch the gas they could not see. Same trick, for your context. Comment GUIDE and I’ll send you the exact canary setup.

Your Claude has a tell, and almost nobody uses it. Make it start every reply with your name. One line in custom instructions, no code. The moment it stops saying your name, its context window is full. That is the exact point the output starts drifting, and you do not notice. Name stops? Start a fresh chat. It has killed about 90% of my “why has Claude gone weird” moments. Miners sent a canary down the pit to catch the gas they could not see. Same trick, for your context. Comment GUIDE and I’ll send you the exact canary setup.

Charlie Hills

22,956 Aufrufe • vor 26 Tagen

Claude Code is terrible at UI design and everyone knows it so this guy fixed it by building an MCP that gives Claude its own AI design tool instead of going back and forth between a design platform and your code editor, Claude now creates the designs itself and drops them straight into your codebase the MCP has full context of your existing design system and project so everything it generates actually matches what you already have. one command to set up and it installs the MCP and skill files so Claude instantly knows how to use it if you're tired of the same Inter font, purple gradient, card grid layout on every project, this is definitely worth trying

Claude Code is terrible at UI design and everyone knows it so this guy fixed it by building an MCP that gives Claude its own AI design tool instead of going back and forth between a design platform and your code editor, Claude now creates the designs itself and drops them straight into your codebase the MCP has full context of your existing design system and project so everything it generates actually matches what you already have. one command to set up and it installs the MCP and skill files so Claude instantly knows how to use it if you're tired of the same Inter font, purple gradient, card grid layout on every project, this is definitely worth trying

Om Patel

400,187 Aufrufe • vor 4 Monaten

I've spent 2 months teaching my AI how I work again and again Claude Code knows one thing. Cursor knows another. Codex starts from scratch. OpenClaw has its own memory. None of them remember what the others learned. Memmy brings those histories into one local, user-controlled memory—so you can switch agents without re-explaining your projects, decisions, and preferences. Switch agents without rebuilding your context. Let every AI remember the same you. GitHub: ProductHunt:

I've spent 2 months teaching my AI how I work again and again Claude Code knows one thing. Cursor knows another. Codex starts from scratch. OpenClaw has its own memory. None of them remember what the others learned. Memmy brings those histories into one local, user-controlled memory—so you can switch agents without re-explaining your projects, decisions, and preferences. Switch agents without rebuilding your context. Let every AI remember the same you. GitHub: ProductHunt:

Priyank Ahuja

13,228 Aufrufe • vor 8 Tagen

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

GREG ISENBERG

84,381 Aufrufe • vor 2 Monaten

Claude Code + Obsidian + 1 free GitHub skill = unlimited memory. Almost nobody is running this yet. Here’s the problem nobody tells you. Claude forgets you. Every new chat starts at 0. You re explain your business, your projects, your style every single time. That tax is why most people never compound anything with AI. The fix is 1 skill. It’s called Obsidian Mind. It turns your Obsidian vault into Claude’s long term brain. 2,000 notes, 14 projects, every idea you’ve ever dumped Claude reads it live and writes back to it live. It stops being a chatbot. It becomes a second brain that builds. What it does: → Bridges Claude Code straight into your vault. → Pulls any note in real time no copy paste, no context limit. → Updates your vault as you work Claude writes its own memory. → Links everything into 1 graph Claude can navigate. Day 1: Claude knows your last 6 months. Week 2: it drafts off your own past notes. Week 4: it’s running plays you forgot you wrote down. The people making real money with AI right now aren’t smarter. They just stopped starting from 0 every morning. Setup takes 11 minutes. The skill is free. You’ll have a brain that never forgets.

Claude Code + Obsidian + 1 free GitHub skill = unlimited memory. Almost nobody is running this yet. Here’s the problem nobody tells you. Claude forgets you. Every new chat starts at 0. You re explain your business, your projects, your style every single time. That tax is why most people never compound anything with AI. The fix is 1 skill. It’s called Obsidian Mind. It turns your Obsidian vault into Claude’s long term brain. 2,000 notes, 14 projects, every idea you’ve ever dumped Claude reads it live and writes back to it live. It stops being a chatbot. It becomes a second brain that builds. What it does: → Bridges Claude Code straight into your vault. → Pulls any note in real time no copy paste, no context limit. → Updates your vault as you work Claude writes its own memory. → Links everything into 1 graph Claude can navigate. Day 1: Claude knows your last 6 months. Week 2: it drafts off your own past notes. Week 4: it’s running plays you forgot you wrote down. The people making real money with AI right now aren’t smarter. They just stopped starting from 0 every morning. Setup takes 11 minutes. The skill is free. You’ll have a brain that never forgets.

West Lord

107,959 Aufrufe • vor 1 Monat

If you don't know what a RAG system is, you're already behind. Plenty of people are still typing questions into ChatGPT and pasting answers back out. That's the beginner level. You're renting a smart stranger who forgets you the second you close the tab and makes things up, because it has never seen your actual work. A RAG system is a completely different level of using AI. You build an AI plugged into your own world. Your files, company's docs, notes. It's not pulling from the internet, it only knows what you fed it. Ask it anything and it digs through your data, finds the answer, and shows you which document it came from. That's the gap. One person is asking a chatbot for generic answers. The other has built a private expert that knows their business cold and answers with receipts. And that gap is worth real money: > At work, the person who can wire a company's knowledge into an AI that actually answers correctly is rare and paid like it. > As a business, companies pay serious money for a system that reads their internal docs and answers staff and customers accurately. You build it once, you sell it. > For yourself, you get a second brain that actually remembers. Same skill behind all three, and it's still rare enough to be worth learning. Full breakdown in the article below.

If you don't know what a RAG system is, you're already behind. Plenty of people are still typing questions into ChatGPT and pasting answers back out. That's the beginner level. You're renting a smart stranger who forgets you the second you close the tab and makes things up, because it has never seen your actual work. A RAG system is a completely different level of using AI. You build an AI plugged into your own world. Your files, company's docs, notes. It's not pulling from the internet, it only knows what you fed it. Ask it anything and it digs through your data, finds the answer, and shows you which document it came from. That's the gap. One person is asking a chatbot for generic answers. The other has built a private expert that knows their business cold and answers with receipts. And that gap is worth real money: > At work, the person who can wire a company's knowledge into an AI that actually answers correctly is rare and paid like it. > As a business, companies pay serious money for a system that reads their internal docs and answers staff and customers accurately. You build it once, you sell it. > For yourself, you get a second brain that actually remembers. Same skill behind all three, and it's still rare enough to be worth learning. Full breakdown in the article below.

Yarchi

32,840 Aufrufe • vor 27 Tagen