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We all have digital lives scattered across random folders, external drives, cloud accounts, and endless years of photos and videos. ♥️ Download for Free: (Sign up before Sep 30 to receive 1,000 bonus MUZIM Credits.) The real issue isn’t storage anymore. It’s understanding what you already have—and actually putting...

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Eliana Skye 📊🚀

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20,650 görüntüleme • 10 gün önce •via X (Twitter)

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Your entire media library, searchable by memory instead of filename, running right on your own machine. It’s a local-first AI file agent called MUZIM. Instead of managing folders, you work with what's actually inside your photos, videos, and documents. Here's how it comes together in a real workflow: You get back from a two-week trip with 2,000 photos and clips on your camera. You point MUZIM at the folder, and it builds Collections on its own, by place, by people, by day. Nothing gets moved from where it already lives. A week later you want "the sunset shot where everyone's laughing." You don't remember the filename. So you just describe it. Vibe Search understands what's inside your media and takes you straight to that moment, even the exact second inside a video. Once the local model is downloaded, this part runs fully offline, connected or not. Then you turn it into something. Connect your own Claude or GPT key, and the online AI Agent pulls the best shots from that trip and drafts a highlight video, an X thread, or a recap. Through MCP, compatible tools work with authorized context without re-uploading gigabytes of raw video - saving massive input tokens while keeping raw files strictly local. The whole idea: search and organization run locally, on your device the AI workflows run when you want them, on your own key your raw files never leave your machine Cold storage becomes a private workspace you actually control.
1:04

Your entire media library, searchable by memory instead of filename, running right on your own machine. It’s a local-first AI file agent called MUZIM. Instead of managing folders, you work with what's actually inside your photos, videos, and documents. Here's how it comes together in a real workflow: You get back from a two-week trip with 2,000 photos and clips on your camera. You point MUZIM at the folder, and it builds Collections on its own, by place, by people, by day. Nothing gets moved from where it already lives. A week later you want "the sunset shot where everyone's laughing." You don't remember the filename. So you just describe it. Vibe Search understands what's inside your media and takes you straight to that moment, even the exact second inside a video. Once the local model is downloaded, this part runs fully offline, connected or not. Then you turn it into something. Connect your own Claude or GPT key, and the online AI Agent pulls the best shots from that trip and drafts a highlight video, an X thread, or a recap. Through MCP, compatible tools work with authorized context without re-uploading gigabytes of raw video - saving massive input tokens while keeping raw files strictly local. The whole idea: search and organization run locally, on your device the AI workflows run when you want them, on your own key your raw files never leave your machine Cold storage becomes a private workspace you actually control.

Alvaro Cintas

80,375 görüntüleme • 14 gün önce

I tried MUZIM by OpenSoul on my Mac this week. Most “AI for your files” tools want you to upload everything into someone else’s cloud. MUZIM is different. It is a local AI for your photo and video library. Not another chatbot. Your raw files stay on your machine. I imported a messy media dump and searched the way I actually remember things. Not filenames. Vibes. I typed “that rainy cafe by the window.” It found the shot. It can even land on a moment inside a video. And after the model downloads, that kind of search keeps working offline. Then the Smart Organization kicked in. I did not rebuild folders. MUZIM built Collections on its own from the dump. Nature, outfits, travel vibes. The library went from chaos to something I could browse. The part that surprised me most is what happens next. Once the library is organized, the AI Agent helps turn it into something I can actually ship. Captions. An X thread. A short highlight concept with hooks. Cold storage becomes a private workspace. You can also plug in your own Claude or GPT key if you want cloud AI on top of local files. Still your library. Still your control. This is the kind of AI I want. More understanding. Less uploading everything to the cloud. Try it:
0:59

I tried MUZIM by OpenSoul on my Mac this week. Most “AI for your files” tools want you to upload everything into someone else’s cloud. MUZIM is different. It is a local AI for your photo and video library. Not another chatbot. Your raw files stay on your machine. I imported a messy media dump and searched the way I actually remember things. Not filenames. Vibes. I typed “that rainy cafe by the window.” It found the shot. It can even land on a moment inside a video. And after the model downloads, that kind of search keeps working offline. Then the Smart Organization kicked in. I did not rebuild folders. MUZIM built Collections on its own from the dump. Nature, outfits, travel vibes. The library went from chaos to something I could browse. The part that surprised me most is what happens next. Once the library is organized, the AI Agent helps turn it into something I can actually ship. Captions. An X thread. A short highlight concept with hooks. Cold storage becomes a private workspace. You can also plug in your own Claude or GPT key if you want cloud AI on top of local files. Still your library. Still your control. This is the kind of AI I want. More understanding. Less uploading everything to the cloud. Try it:

Robert Scoble

63,716 görüntüleme • 15 gün önce

This is how you build the next generation of AI applications. You need an idea, a good model architecture, and a great harness. That's what MUZIM did. It's an app that runs local multimodal and vision models offline to parse and index your images, videos, and documents frame by frame. • Super fast on-device processing • On-device video & image understanding • You can also bring your API keys for heavy reasoning • Your data stays where it is / nothing goes to the cloud You can do a couple of things with this: 1. Vibe searching for whatever you remember in photos or raw video clips. The app will jump straight to the exact frame and timestamp of the video. This is search as it should be. 2. Use local-running agents to perform tasks on your files. I show a couple of examples in my video. You can check it out here: Thanks to the MUZIM by OpenSoul team for showing me the tool and partnering with me on this post.
6:30

This is how you build the next generation of AI applications. You need an idea, a good model architecture, and a great harness. That's what MUZIM did. It's an app that runs local multimodal and vision models offline to parse and index your images, videos, and documents frame by frame. • Super fast on-device processing • On-device video & image understanding • You can also bring your API keys for heavy reasoning • Your data stays where it is / nothing goes to the cloud You can do a couple of things with this: 1. Vibe searching for whatever you remember in photos or raw video clips. The app will jump straight to the exact frame and timestamp of the video. This is search as it should be. 2. Use local-running agents to perform tasks on your files. I show a couple of examples in my video. You can check it out here: Thanks to the MUZIM by OpenSoul team for showing me the tool and partnering with me on this post.

Santiago

65,858 görüntüleme • 17 gün önce

For 40 years the file browser hasn’t changed. Today, we’re launching with $8 million in seed funding to rebuild the file browser into something more intelligent, searchable, and delightful. The world is in the middle of a data explosion. We’re generating and using more files than ever, but the apps we’re using to manage our files don’t even understand them. It’s time for file browsers to become useful. When you search for “dog”, it should show you content with dogs in it, not just files with “dog” in the name! When you want to edit, convert, summarize, or organize a file, your browser should do that, too. Your files tell the story of your life, but when you need a specific one, you usually can’t even find it anymore. Why can’t your file browser find it for you, or cross-reference it when you have a question? Prompting can give an LLM a million tokens of context. With Poly, you can give it the next trillion. As long as we can afford it, all new users receive 100GB of free cloud storage. We can’t wait for you to try it out!
1:25

For 40 years the file browser hasn’t changed. Today, we’re launching with $8 million in seed funding to rebuild the file browser into something more intelligent, searchable, and delightful. The world is in the middle of a data explosion. We’re generating and using more files than ever, but the apps we’re using to manage our files don’t even understand them. It’s time for file browsers to become useful. When you search for “dog”, it should show you content with dogs in it, not just files with “dog” in the name! When you want to edit, convert, summarize, or organize a file, your browser should do that, too. Your files tell the story of your life, but when you need a specific one, you usually can’t even find it anymore. Why can’t your file browser find it for you, or cross-reference it when you have a question? Prompting can give an LLM a million tokens of context. With Poly, you can give it the next trillion. As long as we can afford it, all new users receive 100GB of free cloud storage. We can’t wait for you to try it out!

Abhay Agarwal

1,777,717 görüntüleme • 9 ay önce

Obsidian CEO actually released the skill that lets your AI agent run your entire vault for you. It's called obsidian-skills. Install it into Claude Code, Codex, or OpenCode, and your agent can read, create, search, and organize notes directly, plus handle Markdown, Bases, and Canvas files without you touching a thing. This is the missing piece for an AI second brain. Your notes live in Obsidian, and now the agent actually knows how to work them. Want the full picture? We broke down how to build a complete AI second brain from scratch in the article below.
0:23

Obsidian CEO actually released the skill that lets your AI agent run your entire vault for you. It's called obsidian-skills. Install it into Claude Code, Codex, or OpenCode, and your agent can read, create, search, and organize notes directly, plus handle Markdown, Bases, and Canvas files without you touching a thing. This is the missing piece for an AI second brain. Your notes live in Obsidian, and now the agent actually knows how to work them. Want the full picture? We broke down how to build a complete AI second brain from scratch in the article below.

Simplifying AI

68,025 görüntüleme • 29 gün önce

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:
2:50

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:

Andrew Ng

125,385 görüntüleme • 7 ay önce

In the next few years, every digital action will be mediated by AI. Moving money. Business communications. Researching decisions. Booking meetings. Paying bills. Running workflows. Choosing what to do next. If you want to stay effective, you will need your own architecture around your personal AI agent. Not just a subscription. A personal system that helps your AI understand your world: your goals, context, rules, obligations, decisions, and outcomes. That is ODEI. Built to help you get more from the AI you already use: ChatGPT. Claude. Gemini. Grok (soon). Not by replacing them. By giving them your memory, rules, context, receipts, and local control. The model is not enough. The real leverage comes when your AI understands your world, works inside your rules, and compounds with you over time. (Footage captured live in a local staging environment)
0:33

In the next few years, every digital action will be mediated by AI. Moving money. Business communications. Researching decisions. Booking meetings. Paying bills. Running workflows. Choosing what to do next. If you want to stay effective, you will need your own architecture around your personal AI agent. Not just a subscription. A personal system that helps your AI understand your world: your goals, context, rules, obligations, decisions, and outcomes. That is ODEI. Built to help you get more from the AI you already use: ChatGPT. Claude. Gemini. Grok (soon). Not by replacing them. By giving them your memory, rules, context, receipts, and local control. The model is not enough. The real leverage comes when your AI understands your world, works inside your rules, and compounds with you over time. (Footage captured live in a local staging environment)

Anton Illarionov

1,118,705 görüntüleme • 3 ay önce

File systems are quickly becoming a core abstraction for AI agents for knowledge work. By having access to a file system, agents can effectively manage context, process any amount of information, and create new files and data. The challenge is that local file systems are inherently limited in size, lack governance capabilities, and are inherently personal -not collaborative- in nature. Now, with the Box API and LangChain's deepagent SDK, you can bring the full power of a secure, collaborative cloud file system to your AI agents. Repo ↓
0:37

File systems are quickly becoming a core abstraction for AI agents for knowledge work. By having access to a file system, agents can effectively manage context, process any amount of information, and create new files and data. The challenge is that local file systems are inherently limited in size, lack governance capabilities, and are inherently personal -not collaborative- in nature. Now, with the Box API and LangChain's deepagent SDK, you can bring the full power of a secure, collaborative cloud file system to your AI agents. Repo ↓

Box

227,348 görüntüleme • 6 ay önce

🚨BREAKING: Someone just built the open source Loom killer that turns your screen recordings into AI agents. It's called Bloom and it does something Loom never could. Your recordings don't just sit as files. They become queryable, searchable, agent-ready data the moment you stop recording. Here's what actually happens: You hit record. Bloom captures your screen, mic, and system audio locally. While you're still recording, it uploads chunks to the cloud in real time. The second you stop, it auto-generates a full transcript, creates visual embeddings, and indexes every spoken word. Then the wild part kicks in. You can query your recordings through APIs. You can hook Claude Code directly into your video library and ask it questions. Your screen recording just became a knowledge base. → Local-first, your files never get locked in → Cmd+Shift+R starts and stops from anywhere on your system → One-click shareable link for any recording → Chat directly with your video content through VideoDB Chat → Works with Claude Code and other agent frameworks out of the box Recordings are no longer files. They're inputs for AI. MIT License. 100% Opensource. Link in comments.
1:13

🚨BREAKING: Someone just built the open source Loom killer that turns your screen recordings into AI agents. It's called Bloom and it does something Loom never could. Your recordings don't just sit as files. They become queryable, searchable, agent-ready data the moment you stop recording. Here's what actually happens: You hit record. Bloom captures your screen, mic, and system audio locally. While you're still recording, it uploads chunks to the cloud in real time. The second you stop, it auto-generates a full transcript, creates visual embeddings, and indexes every spoken word. Then the wild part kicks in. You can query your recordings through APIs. You can hook Claude Code directly into your video library and ask it questions. Your screen recording just became a knowledge base. → Local-first, your files never get locked in → Cmd+Shift+R starts and stops from anywhere on your system → One-click shareable link for any recording → Chat directly with your video content through VideoDB Chat → Works with Claude Code and other agent frameworks out of the box Recordings are no longer files. They're inputs for AI. MIT License. 100% Opensource. Link in comments.

Rimsha Bhardwaj

128,775 görüntüleme • 4 ay önce

Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!
3:50

Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!

Workshop AI

29,124 görüntüleme • 5 ay önce

I vibe-coded an AI agent for making presentations 🤖🖼️ - accessible to everyone and open-source! You can upload both your context files, as well as a style template (a file that captures the style of the presentation you want to create). Then you launch a prompt and watch the agent one-shot your presentation. After the presentation is generated, you can edit the text inline, chat with the agent to add/modify/delete slides, and export to Powerpoint or PDF. Built with Claude Code, powered by Claude Agent SDK + LlamaParse. Hosted on Vercel/Render. To use it, you do need to specify your LlamaCloud API key and Anthropic API key (see below). App: Repo: Sign up to LlamaCloud:
0:54

I vibe-coded an AI agent for making presentations 🤖🖼️ - accessible to everyone and open-source! You can upload both your context files, as well as a style template (a file that captures the style of the presentation you want to create). Then you launch a prompt and watch the agent one-shot your presentation. After the presentation is generated, you can edit the text inline, chat with the agent to add/modify/delete slides, and export to Powerpoint or PDF. Built with Claude Code, powered by Claude Agent SDK + LlamaParse. Hosted on Vercel/Render. To use it, you do need to specify your LlamaCloud API key and Anthropic API key (see below). App: Repo: Sign up to LlamaCloud:

Jerry Liu

21,073 görüntüleme • 7 ay önce

If you use Cursor for coding, Claude Code for debugging, and local agents for automation, you almost certainly have a context problem. Every tool acts like an isolated employee. One assistant forgets what the other just learned. The biggest bottleneck in multi-agent workflows right now isn’t reasoning. It’s collective amnesia, combined with zero communication between agents. Memmy just launched a smart fix for this: a local, cross-agent memory layer. Instead of re-pasting your context everywhere, Memmy gives your stack a shared memory hub: → accumulate knowledge once, then use it across Cursor, Codex, and OpenClaw → automatically scan and import your existing agent history, so you don’t have to start from zero → keep your memory local, while model usage depends on your chosen provider or BYOK setup And it isn’t just a memory plugin. It’s a complete personal AI runtime with both MCP and a CLI. Memmy officially launched on Product Hunt, and the team is giving early users experiencing context fragmentation a free trial with 2M GPT tokens. Check it out and support the team with an upvote: → Best part? It’s also open-source for devs who want to build their own agents 🔥 Repo in 🧵↓
3:29

If you use Cursor for coding, Claude Code for debugging, and local agents for automation, you almost certainly have a context problem. Every tool acts like an isolated employee. One assistant forgets what the other just learned. The biggest bottleneck in multi-agent workflows right now isn’t reasoning. It’s collective amnesia, combined with zero communication between agents. Memmy just launched a smart fix for this: a local, cross-agent memory layer. Instead of re-pasting your context everywhere, Memmy gives your stack a shared memory hub: → accumulate knowledge once, then use it across Cursor, Codex, and OpenClaw → automatically scan and import your existing agent history, so you don’t have to start from zero → keep your memory local, while model usage depends on your chosen provider or BYOK setup And it isn’t just a memory plugin. It’s a complete personal AI runtime with both MCP and a CLI. Memmy officially launched on Product Hunt, and the team is giving early users experiencing context fragmentation a free trial with 2M GPT tokens. Check it out and support the team with an upvote: → Best part? It’s also open-source for devs who want to build their own agents 🔥 Repo in 🧵↓

Charly Wargnier

203,456 görüntüleme • 1 ay önce

Introducing the new Box Agent. The Box Agent works across your entire Box file system, maintaining all your security and access controls, and is hyper tuned for working with enterprise content. This means you can now ask questions from all your enterprise content, search for files that were impossible to find before, deploy an agent on specific tasks on subsets of documents, analyze complex data sets, and generate or edit documents and spreadsheets via the agent. You can have the Box Agent search across your Box account to prepare for a sales meeting, analyze customer sentiment reports, process a large set of contracts for legal risk, provide insights into product development, leverage existing knowledge to answer RFPs, and thousands of other use-cases. 90% of enterprise data is unstructured data. This means most enterprise knowledge is sitting in inside of research reports, marketing assets, presentations, roadmap files, contracts, HR documents, and more. This is the critical context that agents need to be able to answer questions about a business, automate workflows, or serve up to other agents. We’ve been grinding on this for a quite a bit, and due to recent AI model advancements we’re now ready to release it to customers. Previous model generations had a difficult time knowing when to give up or keep going on a search, when to browse for files vs. use queries, how to rank files appropriately to know which version of content to use, how to handle large amounts of context to comb through, and more. Due to recent breakthroughs from models like GPT-5.4, Opus 4.6, and Gemini 3, we’ve seen major gains in tool calling, code execution, advanced reasoning, and more. Combined with an agent harness tuned to Box context, now it’s finally possible to have an agent that can work across your file system on long running tasks and actually deliver high quality results. Best of all, because the Box Agent works with any leading AI model, you’ll quickly get the gains coming out of the major labs as major new models are released. Further, openness at Box is key, so you’ll be able to call up the Box Agent from Box’s APIs and MCP server, so you can interact with Box intelligently from any other AI system. We know work happens everywhere, and we want to ensure you can access to the content you need from those places. The new Box Agent is available starting today, rolling out now for Enterprise Plus and Enterprise Advanced customers.
0:58

Introducing the new Box Agent. The Box Agent works across your entire Box file system, maintaining all your security and access controls, and is hyper tuned for working with enterprise content. This means you can now ask questions from all your enterprise content, search for files that were impossible to find before, deploy an agent on specific tasks on subsets of documents, analyze complex data sets, and generate or edit documents and spreadsheets via the agent. You can have the Box Agent search across your Box account to prepare for a sales meeting, analyze customer sentiment reports, process a large set of contracts for legal risk, provide insights into product development, leverage existing knowledge to answer RFPs, and thousands of other use-cases. 90% of enterprise data is unstructured data. This means most enterprise knowledge is sitting in inside of research reports, marketing assets, presentations, roadmap files, contracts, HR documents, and more. This is the critical context that agents need to be able to answer questions about a business, automate workflows, or serve up to other agents. We’ve been grinding on this for a quite a bit, and due to recent AI model advancements we’re now ready to release it to customers. Previous model generations had a difficult time knowing when to give up or keep going on a search, when to browse for files vs. use queries, how to rank files appropriately to know which version of content to use, how to handle large amounts of context to comb through, and more. Due to recent breakthroughs from models like GPT-5.4, Opus 4.6, and Gemini 3, we’ve seen major gains in tool calling, code execution, advanced reasoning, and more. Combined with an agent harness tuned to Box context, now it’s finally possible to have an agent that can work across your file system on long running tasks and actually deliver high quality results. Best of all, because the Box Agent works with any leading AI model, you’ll quickly get the gains coming out of the major labs as major new models are released. Further, openness at Box is key, so you’ll be able to call up the Box Agent from Box’s APIs and MCP server, so you can interact with Box intelligently from any other AI system. We know work happens everywhere, and we want to ensure you can access to the content you need from those places. The new Box Agent is available starting today, rolling out now for Enterprise Plus and Enterprise Advanced customers.

Aaron Levie

44,624 görüntüleme • 5 ay önce

If you're evaluating AI IDEs this week, here's what getting started with Windsurf (retired) looks like (links below): • Download and install from Import any existing IDE settings during onboarding, or start fresh. • Cascade is the agent panel on the right. Chat, generate, edit, run code. @-mention files, symbols, or docs to scope context. • Choose your model - Opus, Codex, SWE, Kimi, GLM and more (Kimi K2.6 is free for the next 2 weeks 👀) • DeepWiki: Cmd+Shift+Click any symbol for an in-depth explanation of what it does. Send it to Cascade with one click. • Codemaps: hierarchical view of how files and functions execute together. Click a node to jump to code. Shareable as links. • Devin in Windsurf: start and manage cloud sessions without leaving the editor. • Agent Command Center: Kanban board of every running agent, local (Cascade) and cloud (Devin). See what's in flight, blocked, or ready for review. • Spaces: group sessions, PRs, files, and context for one task or project into a single view. • Centralized review: handle diffs, PRs, and agent output in one place. • MCP servers, Memories, and Workflows extend Cascade. Set them up once; reuse across projects.
0:41

If you're evaluating AI IDEs this week, here's what getting started with Windsurf (retired) looks like (links below): • Download and install from Import any existing IDE settings during onboarding, or start fresh. • Cascade is the agent panel on the right. Chat, generate, edit, run code. @-mention files, symbols, or docs to scope context. • Choose your model - Opus, Codex, SWE, Kimi, GLM and more (Kimi K2.6 is free for the next 2 weeks 👀) • DeepWiki: Cmd+Shift+Click any symbol for an in-depth explanation of what it does. Send it to Cascade with one click. • Codemaps: hierarchical view of how files and functions execute together. Click a node to jump to code. Shareable as links. • Devin in Windsurf: start and manage cloud sessions without leaving the editor. • Agent Command Center: Kanban board of every running agent, local (Cascade) and cloud (Devin). See what's in flight, blocked, or ready for review. • Spaces: group sessions, PRs, files, and context for one task or project into a single view. • Centralized review: handle diffs, PRs, and agent output in one place. • MCP servers, Memories, and Workflows extend Cascade. Set them up once; reuse across projects.

nader dabit

17,167 görüntüleme • 4 ay önce

This guy put an AI data center into a box that fits on a desk It doesn't look like a serious machine It looks like a mini PC you could hide behind a monitor But with enough unified memory it can run local models, answer over your own files, power agents and keep private work off someone else's servers That sounds like a hobby setup until you look at what people are actually renting every month Claude subscription ChatGPT subscription API credits cloud GPU time usage limits private files uploaded into third-party tools For years the deal was simple: if you wanted intelligence, you rented it Now a Mac Mini M4 Pro or a 128GB AMD mini PC can handle a big part of everyday AI work locally Ollama runs the models Open WebUI gives you the chat interface Tailscale lets you reach it from your phone or laptop without exposing it to the open internet The cloud still wins for the hardest tasks But most daily AI work is not frontier research It is reading documents, summarizing files, drafting, coding helpers, search, notes and private workflows Most people will keep paying rent because it is convenient Others are realizing the assistant they rent every month can become hardware they own save this
0:27

This guy put an AI data center into a box that fits on a desk It doesn't look like a serious machine It looks like a mini PC you could hide behind a monitor But with enough unified memory it can run local models, answer over your own files, power agents and keep private work off someone else's servers That sounds like a hobby setup until you look at what people are actually renting every month Claude subscription ChatGPT subscription API credits cloud GPU time usage limits private files uploaded into third-party tools For years the deal was simple: if you wanted intelligence, you rented it Now a Mac Mini M4 Pro or a 128GB AMD mini PC can handle a big part of everyday AI work locally Ollama runs the models Open WebUI gives you the chat interface Tailscale lets you reach it from your phone or laptop without exposing it to the open internet The cloud still wins for the hardest tasks But most daily AI work is not frontier research It is reading documents, summarizing files, drafting, coding helpers, search, notes and private workflows Most people will keep paying rent because it is convenient Others are realizing the assistant they rent every month can become hardware they own save this

Asteri

12,171 görüntüleme • 2 ay önce

Obsidian + Claude Code turned a 4,300-note vault into a second brain that answers back. Most people use Obsidian as a graveyard. You save 40 highlights a week, link nothing, and reread maybe 2% of it. The knowledge is there the retrieval is dead. Claude Code fixes the retrieval, because your vault is just a folder of markdown files and Claude Code lives in folders. The whole setup takes 20 minutes: Open a terminal inside your Obsidian folder and run Claude Code no plugins, no API glue, no export step. It reads all 4,300 files natively. Then drop a CLAUDE.md at the vault root explaining your structure: where daily notes live, how you tag, what your MOCs are. Now every session starts with context instead of chaos. From there you just talk to your vault: > "find every note where I mentioned churn and write a summary with backlinks" > "read my last 30 daily notes and list the 5 ideas I keep circling but never ship" > "build a MOC for everything tagged startup-ideas and link the orphan notes into it" It writes new notes straight into the vault with proper [[wikilinks]], and they show up in your graph view 10 seconds later. The boring layer automates too one command cleans broken links, one merges duplicates, one turns 6 months of meeting notes into a single decisions log. Work that used to eat a Sunday now runs while you make coffee. Before: 4,300 notes, 900 orphans, search by keyword and prayer. After: an agent that read everything you ever wrote and drafts in your own voice, from your own sources, with receipts. People pay $30/month for AI note apps with 10% of this. You already own the other 90%. Your notes stopped being storage. They started being staff.
0:55

Obsidian + Claude Code turned a 4,300-note vault into a second brain that answers back. Most people use Obsidian as a graveyard. You save 40 highlights a week, link nothing, and reread maybe 2% of it. The knowledge is there the retrieval is dead. Claude Code fixes the retrieval, because your vault is just a folder of markdown files and Claude Code lives in folders. The whole setup takes 20 minutes: Open a terminal inside your Obsidian folder and run Claude Code no plugins, no API glue, no export step. It reads all 4,300 files natively. Then drop a CLAUDE.md at the vault root explaining your structure: where daily notes live, how you tag, what your MOCs are. Now every session starts with context instead of chaos. From there you just talk to your vault: > "find every note where I mentioned churn and write a summary with backlinks" > "read my last 30 daily notes and list the 5 ideas I keep circling but never ship" > "build a MOC for everything tagged startup-ideas and link the orphan notes into it" It writes new notes straight into the vault with proper [[wikilinks]], and they show up in your graph view 10 seconds later. The boring layer automates too one command cleans broken links, one merges duplicates, one turns 6 months of meeting notes into a single decisions log. Work that used to eat a Sunday now runs while you make coffee. Before: 4,300 notes, 900 orphans, search by keyword and prayer. After: an agent that read everything you ever wrote and drafts in your own voice, from your own sources, with receipts. People pay $30/month for AI note apps with 10% of this. You already own the other 90%. Your notes stopped being storage. They started being staff.

Spike 1%

18,223 görüntüleme • 1 ay önce

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.
1:51

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.

Base44

1,582,732 görüntüleme • 5 ay önce

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:
1:48

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

Andrew Ng

81,696 görüntüleme • 11 ay önce

I just built an AI-powered creative search engine with Gemini Embedding 2 + Claude Code 🤯 Drop in your UGC clips, product shots, and ad variations — then search through everything in plain English. "Show me all the unboxing clips." "Find product shots with natural lighting." "Which creator talked about sensitive skin?" All inside Claude Code. Perfect for DTC brands and agencies sitting on hundreds of creative files they can never find when they actually need them. If you're digging through a folder of random file names, scrubbing through raw footage to find that one clip, and relying on memory to track down what's already been shot... This system eliminates the entire loop: → Drop your videos, images, and docs into a project folder → One prompt to Claude Code — it builds the entire search app for you → Google's new Gemini Embedding 2 model actually watches your videos and looks at your images → It understands what's inside each file — not just the file name → Search in plain English and get back the actual assets with confidence scores No scrolling through folders. No relying on file names to find anything. No re-shooting footage you already have. What you get: → A searchable library of every creative asset your brand has ever produced → Natural language search across video, images, and documents at the same time → Results that show the actual files inline — play videos, view images, read docs → A system that gets smarter every time you add richer descriptions to your assets One free API key. No monthly subscriptions. Runs on your machine. I put together a full playbook with the exact build prompt, the setup process, and DTC/agency use cases to get this running in under 30 minutes. Want the full playbook? > Like this post > Comment "SEARCH" And I'll send it over (must be following so I can DM)
0:22

I just built an AI-powered creative search engine with Gemini Embedding 2 + Claude Code 🤯 Drop in your UGC clips, product shots, and ad variations — then search through everything in plain English. "Show me all the unboxing clips." "Find product shots with natural lighting." "Which creator talked about sensitive skin?" All inside Claude Code. Perfect for DTC brands and agencies sitting on hundreds of creative files they can never find when they actually need them. If you're digging through a folder of random file names, scrubbing through raw footage to find that one clip, and relying on memory to track down what's already been shot... This system eliminates the entire loop: → Drop your videos, images, and docs into a project folder → One prompt to Claude Code — it builds the entire search app for you → Google's new Gemini Embedding 2 model actually watches your videos and looks at your images → It understands what's inside each file — not just the file name → Search in plain English and get back the actual assets with confidence scores No scrolling through folders. No relying on file names to find anything. No re-shooting footage you already have. What you get: → A searchable library of every creative asset your brand has ever produced → Natural language search across video, images, and documents at the same time → Results that show the actual files inline — play videos, view images, read docs → A system that gets smarter every time you add richer descriptions to your assets One free API key. No monthly subscriptions. Runs on your machine. I put together a full playbook with the exact build prompt, the setup process, and DTC/agency use cases to get this running in under 30 minutes. Want the full playbook? > Like this post > Comment "SEARCH" And I'll send it over (must be following so I can DM)

Mike Futia

12,279 görüntüleme • 5 ay önce