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I’ve been waiting for something like this. Using multiple AI agents sounds great until you have to keep giving each one the same context. Jarvix Jarvix is built to solve that： It carries your selected context across the AI tools you already use and brings everything together in one... place. #JarvixOS You can use Jarvix Home to see your context and connections, Jarvix Search to find past information without remembering exact file names, and Self Reflection to spot patterns in the way you work. There’s also Jarvix Radio for personalized content discovery and Next Move to surface a useful direction based on your context. And the part I find most interesting: Agent Team Mode. Give Jarvix one goal, choose the agents you want to use, and it divides the work while keeping everyone on the same project context. You can watch the progress, review the result, and approve what happens next. No need to keep briefing every agent from scratch. One goal. Shared context. Multiple agents. You stay in control. That’s a much cleaner way to work with AI.show more

Aaliya

32,283 subscribers

23,225 次观看 • 2 个月前 •via X (Twitter)

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32 条评论

Elizaveta Zabrodskaya 的头像

Elizaveta Zabrodskaya2 个月前

@Jarvixdotlive Love how it keeps everything in one spot

Z-Coder 的头像

Z-Coder2 个月前

@Jarvixdotlive This looks interesting

Eyisha Zyer 的头像

Eyisha Zyer2 个月前

@Jarvixdotlive Shared context is the real unlock for multi agent workflows

Chidanand Tripathi 的头像

Chidanand Tripathi2 个月前

@Jarvixdotlive Jarvix looks really interesting

Usama Sha 的头像

Usama Sha2 个月前

@Jarvixdotlive Shared context across agents is what makes the multi agent setup actually practical.

Rohit 的头像

Rohit2 个月前

@Jarvixdotlive Shared context makes AI agents much more useful. This looks really promising!

Robert Smith 的头像

Robert Smith2 个月前

@Jarvixdotlive Amazing share

Mr Nikola 的头像

Mr Nikola2 个月前

@Jarvixdotlive Great

Artists Voyage 🔶 的头像

Artists Voyage 🔶2 个月前

@Jarvixdotlive amazing as I think Jarvix Search + shared context is a practical combo.

James 的头像

James2 个月前

@Jarvixdotlive That agent team mode sounds really useful. I hate having to repeat myself to different bots.

Csaba Kissi 的头像

Csaba Kissi2 个月前

@Jarvixdotlive It's like a multi-agent Jarvis

Kevin Parker 的头像

Kevin Parker2 个月前

@Jarvixdotlive Amazing

Fakhr 的头像

Fakhr2 个月前

@Jarvixdotlive This one’s new for me

Hussain Hashim | Building SundayBack 的头像

Hussain Hashim | Building SundayBack2 个月前

@Jarvixdotlive @aaliya_va this is actually huge. i've been juggling context issues forever with different AI tools. definitely gonna check out jarvix.

Javeriya Ahsan 的头像

Javeriya Ahsan2 个月前

@Jarvixdotlive Having to explain the same context to every tool is probably the most annoying part of using multiple agents. This fixes a very real headache. XD

Javeria 的头像

Javeria2 个月前

@Jarvixdotlive Keeping the human in control makes this even better.

Muhammad Ayan 的头像

Muhammad Ayan2 个月前

@Jarvixdotlive Jarvix said no more context déjà vu 🤣

Tarique Sha 的头像

Tarique Sha2 个月前

@Jarvixdotlive great to see as multiple agents working from the same project context removes so much repetitive briefing.

Luqman Ali 的头像

Luqman Ali2 个月前

@Jarvixdotlive Awesome

Aaliya 的头像

Aaliya2 个月前

@Jarvixdotlive Thanks

Haider Anis 的头像

Haider Anis2 个月前

@Jarvixdotlive This is powerful

Charlie Hills 的头像

Charlie Hills2 个月前

@Jarvixdotlive oh woooow shared context across agents 👀

Parul Gautam 的头像

Parul Gautam2 个月前

@Jarvixdotlive this is new for me

Amit 的头像

Amit2 个月前

@Jarvixdotlive will check it out.

Jack AI 的头像

Jack AI2 个月前

@Jarvixdotlive Nice work buddy

Liam | AI Tools & News 的头像

Liam | AI Tools & News2 个月前

@Jarvixdotlive Shared context between agents just makes sense.

HarriStack 的头像

HarriStack2 个月前

@Jarvixdotlive Finally, an AI that stops making me re-explain my entire life story to every new agent.

Shohan 的头像

Shohan2 个月前

@Jarvixdotlive Amezing share

marium 的头像

marium2 个月前

@Jarvixdotlive This sounds like a huge time saver! I'm always looking for ways to streamline my workflow.

Zayan 的头像

Zayan2 个月前

@Jarvixdotlive Shared context, smarter AI workflows.

H A J R A 的头像

H A J R A2 个月前

@Jarvixdotlive Shared context across multiple AI agents is a game changer. 🔥

Branding Waves 的头像

Branding Waves2 个月前

@Jarvixdotlive like that you still approve what happens next. Shared context across agents is useful, but keeping the human in control makes it much more practical.

相关视频

🚀 Global Launch: Jarvix, Your Context OS is now live! Meet the next generation of personalized AI built around your context, your taste, and your way of thinking. #JarvixOS transforms how you work with AI by understanding your patterns, carrying your context across agents, and helping you move from ideas to action. Step into a new era of AI collaboration: • Discover your AI-native archetype • Build your personal AI model from your evolving AI interactions • Never start from zero - your context moves with you across sessions • Coordinate Codex, Claude Code, Gemini, Hermes, OpenClaw, and more as one connected AI team. • Turn insights into your next move, with you always in control Instead of adapting yourself to every agent, Jarvix carries the context you choose, helps you understand what it reveals, and brings the right agents together when you decide to act. Your AI tools shouldn’t work like separate assistants. They should work like one team. That’s the future of AI: Not more agents. One shared context. One Jarvix.

🚀 Global Launch: Jarvix, Your Context OS is now live! Meet the next generation of personalized AI built around your context, your taste, and your way of thinking. #JarvixOS transforms how you work with AI by understanding your patterns, carrying your context across agents, and helping you move from ideas to action. Step into a new era of AI collaboration: • Discover your AI-native archetype • Build your personal AI model from your evolving AI interactions • Never start from zero - your context moves with you across sessions • Coordinate Codex, Claude Code, Gemini, Hermes, OpenClaw, and more as one connected AI team. • Turn insights into your next move, with you always in control Instead of adapting yourself to every agent, Jarvix carries the context you choose, helps you understand what it reveals, and brings the right agents together when you decide to act. Your AI tools shouldn’t work like separate assistants. They should work like one team. That’s the future of AI: Not more agents. One shared context. One Jarvix.

Jarvix

1,692,394 次观看 • 2 个月前

i merged all my AI agents into one brain Claude Code, Codex, Gemini: one team, one memory, zero re-briefing result: 8+ hours a week back, and every agent already knows my projects, my clients and how i think here's the setup with Jarvix: 1. dump your context once: projects, clients, writing style, how you make decisions.. it builds your personal model from your actual AI interactions 2. switch agents mid-task with zero re-briefing: Claude Code builds, Codex reviews, Gemini researches, all reading the same context 3. it carries what YOU choose across sessions.. never start a chat from zero again 4. when it's time to act, it pulls the right agents together as one team instead of five separate assistants the unlock isn't another agent. it's that your context finally travels agents without shared memory are five interns on their first day, forever. agents with it are a team that's worked with you for years not more agents. one shared context that's the right bet P.S. thanks to the Jarvix team for the early access

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The Startup Ideas Podcast (SIP) 🧃

18,006 次观看 • 2 个月前

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378,296 次观看 • 7 个月前

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4,367,105 次观看 • 22 天前

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11,782 次观看 • 22 天前

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1,584,294 次观看 • 7 个月前

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Anuj

337,698 次观看 • 1 个月前

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

GREG ISENBERG

194,990 次观看 • 6 个月前

Most AI agent tools are built for one person running a bunch of agents. I think the future of work is multiple people and multiple agents on the same project, and Teamily AI is the Humans + Agents platform that made it click for me. I used its Website Builder to turn an idea for an AI Creator Toolkit into a working website, Stacked. I wanted one place where creators could quickly find useful AI tools for content, productivity, video, images, and automation. I gave Teamily AI the idea in a group chat with the agents and a partner I'm working with, and watched them work through it: SEO/GEO Expert planned the categories and tools, and Social Media Strategist built the site from that plan. Then my partner asked for the recommendations to be easier for creators to compare, and the agents updated the tool comparison in Studio. What I liked most was not having to guide every little step. The agents and my partner worked from the same context and picked up each other's work, from idea to live site. This is what AI agents should feel like. Live site: Here's how the website came together ↓ Teamily AI

Most AI agent tools are built for one person running a bunch of agents. I think the future of work is multiple people and multiple agents on the same project, and Teamily AI is the Humans + Agents platform that made it click for me. I used its Website Builder to turn an idea for an AI Creator Toolkit into a working website, Stacked. I wanted one place where creators could quickly find useful AI tools for content, productivity, video, images, and automation. I gave Teamily AI the idea in a group chat with the agents and a partner I'm working with, and watched them work through it: SEO/GEO Expert planned the categories and tools, and Social Media Strategist built the site from that plan. Then my partner asked for the recommendations to be easier for creators to compare, and the agents updated the tool comparison in Studio. What I liked most was not having to guide every little step. The agents and my partner worked from the same context and picked up each other's work, from idea to live site. This is what AI agents should feel like. Live site: Here's how the website came together ↓ Teamily AI

Karen

33,208 次观看 • 22 天前

Your team deserves more from your agent observability platform - a single, connected place for instrumentation, investigation, and measurement, enhanced with intelligence. In Braintrust, you can start with an open-ended prompt about agent behavior and carry the investigation into code, evals, automation, and monitoring. New tools like Patterns and Debugger make it easier to find recurring behavior, get to root causes, and act on what you learn. The context you build in one step automatically follows to the next. Work in the platform with an enhanced Loop experience, or move to your coding agent of choice. Read more →

Your team deserves more from your agent observability platform - a single, connected place for instrumentation, investigation, and measurement, enhanced with intelligence. In Braintrust, you can start with an open-ended prompt about agent behavior and carry the investigation into code, evals, automation, and monitoring. New tools like Patterns and Debugger make it easier to find recurring behavior, get to root causes, and act on what you learn. The context you build in one step automatically follows to the next. Work in the platform with an enhanced Loop experience, or move to your coding agent of choice. Read more →

Braintrust

44,341 次观看 • 1 个月前

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!

Milind S

12,085 次观看 • 4 个月前

Introducing Bloome: a human–AI teammate system built around shared context and multi-agent collaboration. → You bring your task, and AI teammates collaborate with you in real time → Work flows through drafting, challenge, and refinement until it reaches the right answer → Claude, ChatGPT, and Deepseek operate together in a shared context with no information loss Everything stays connected from input to final output. This is how work starts changing.

Introducing Bloome: a human–AI teammate system built around shared context and multi-agent collaboration. → You bring your task, and AI teammates collaborate with you in real time → Work flows through drafting, challenge, and refinement until it reaches the right answer → Claude, ChatGPT, and Deepseek operate together in a shared context with no information loss Everything stays connected from input to final output. This is how work starts changing.

Bloome

347,044 次观看 • 4 个月前

The more agents and projects you have running, the harder it gets to keep track of everything through chat alone. This is where Hermes Kanban comes in. Here's how Hermes Kanban works, why it's worth using, and how I'd recommend setting it up: Chat is where you work with an agent. Kanban is where you manage the work across agents. Hermes Kanban gives you a visual dashboard for tracking tasks across your agents and projects. But it's much more than a task board. Here's what you can do with it: • Create tasks and assign them to specific Hermes agents. • Track what's ready, running, blocked, or completed. • Set dependencies so tasks wait for other work to finish. • Coordinate handoffs between specialized agents. • Review progress and see where something needs your attention. And with the dispatcher, Hermes can pick up tasks that are ready to run and launch the appropriate agent to handle them. Now, here's something I'd recommend: **Create a separate Kanban board for each major project.** For example: 📌 Content production Research → Drafting → Review → Assets → Done 📌 Software development Bugs → Features → Testing → Review → Done 📌 Business operations Research → Waiting → In Progress → Blocked → Done Hermes supports multiple isolated boards, so each project can have its own tasks, workspaces, logs, and agent workflows. You can also connect a board to a Hermes Project to keep the work tied to the right project context. The more work you hand off to Hermes, the more valuable this becomes. Instead of digging through conversations trying to figure out what every agent is doing, give each project its own board and manage the work from one place. 🎥 Video credit: Tom

The more agents and projects you have running, the harder it gets to keep track of everything through chat alone. This is where Hermes Kanban comes in. Here's how Hermes Kanban works, why it's worth using, and how I'd recommend setting it up: Chat is where you work with an agent. Kanban is where you manage the work across agents. Hermes Kanban gives you a visual dashboard for tracking tasks across your agents and projects. But it's much more than a task board. Here's what you can do with it: • Create tasks and assign them to specific Hermes agents. • Track what's ready, running, blocked, or completed. • Set dependencies so tasks wait for other work to finish. • Coordinate handoffs between specialized agents. • Review progress and see where something needs your attention. And with the dispatcher, Hermes can pick up tasks that are ready to run and launch the appropriate agent to handle them. Now, here's something I'd recommend: Create a separate Kanban board for each major project. For example: 📌 Content production Research → Drafting → Review → Assets → Done 📌 Software development Bugs → Features → Testing → Review → Done 📌 Business operations Research → Waiting → In Progress → Blocked → Done Hermes supports multiple isolated boards, so each project can have its own tasks, workspaces, logs, and agent workflows. You can also connect a board to a Hermes Project to keep the work tied to the right project context. The more work you hand off to Hermes, the more valuable this becomes. Instead of digging through conversations trying to figure out what every agent is doing, give each project its own board and manage the work from one place. 🎥 Video credit: Tom

Hermes Release Watch

27,640 次观看 • 21 天前

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

rody

18,089 次观看 • 1 个月前

introducing Pinterest in Krea Agent. now you can bring all your pins and boards into the tool and use them as context for your agents. try it now at krea . ai / agent

introducing Pinterest in Krea Agent. now you can bring all your pins and boards into the tool and use them as context for your agents. try it now at krea . ai / agent

Krea

15,409 次观看 • 1 个月前

Introducing Nebula Live: The fastest way to work with your agents. You can now talk, text or show them anything. They work in real time, understand what you're saying and autonomously kick off work. Invite your teammates into a live session and everyone can collaborate together. Experience hands free building while just talking and the best part is all your context is saved in the workspace forever. Background mode mutes your agent but they still listen to you, kick off work and let you know when things are done. Share your screen or camera and your agent can see what you are doing. Now in beta across desktop, mobile and web. We're giving away $100 for you to experience Nebula Live. Reply with what you want to talk to your agents about.

Introducing Nebula Live: The fastest way to work with your agents. You can now talk, text or show them anything. They work in real time, understand what you're saying and autonomously kick off work. Invite your teammates into a live session and everyone can collaborate together. Experience hands free building while just talking and the best part is all your context is saved in the workspace forever. Background mode mutes your agent but they still listen to you, kick off work and let you know when things are done. Share your screen or camera and your agent can see what you are doing. Now in beta across desktop, mobile and web. We're giving away $100 for you to experience Nebula Live. Reply with what you want to talk to your agents about.

Nebula

11,761 次观看 • 3 个月前

Roma is now the command center for you and your agents. We’ve talked to a lot of you over the past week, and the same thing keeps coming up: we’re using a lot of agents at once, but context gets lost. Work is scattered. We're still chasing things down. We heard you and we’ve updated our MCP tooling and API, built connections and plugins for popular agents, and made it simpler to connect them to Roma. Claude, Codex, OpenClaw, Gemini, Muse, Instinct, even the ones you built yourself. You can keep using your favorite agent, and use Roma as your command center for all your work in motion. And this just the beginning. Get started: Roma (YC F26) Y Combinator

Roma is now the command center for you and your agents. We’ve talked to a lot of you over the past week, and the same thing keeps coming up: we’re using a lot of agents at once, but context gets lost. Work is scattered. We're still chasing things down. We heard you and we’ve updated our MCP tooling and API, built connections and plugins for popular agents, and made it simpler to connect them to Roma. Claude, Codex, OpenClaw, Gemini, Muse, Instinct, even the ones you built yourself. You can keep using your favorite agent, and use Roma as your command center for all your work in motion. And this just the beginning. Get started: Roma (YC F26) Y Combinator

Jan Senderek

94,283 次观看 • 14 天前