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Mercury Agent is now available on Atomic Bot! Say it once and every session after already has your context. The longer you work together, the less you have to explain. One click and Mercury is live 24/7 in the cloud!

atomicbot.ai

6,270 subscribers

26,745 просмотров • 11 дней назад •via X (Twitter)

Anya Rossi• Live Now

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Mercury Command is live. AI built directly into your Mercury account that completes financial work. Natural language, real actions, and you approve everything. This is how banking* works now.

Mercury Command is live. AI built directly into your Mercury account that completes financial work. Natural language, real actions, and you approve everything. This is how banking* works now.

Mercury

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The wait is over – Mercury Invoicing is here. You can now create and send professional invoices, get paid the way you want, and keep track of who owes you what — all from your Mercury account. See the magic at

The wait is over – Mercury Invoicing is here. You can now create and send professional invoices, get paid the way you want, and keep track of who owes you what — all from your Mercury account. See the magic at

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Close your laptops. Codex is now available on Atomic Bot, allowing users to close their laptops and keep tasks running in the cloud. Users can hand over their repositories to the agent in order to improve them continuously, discover and fix bugs, and more!

Close your laptops. Codex is now available on Atomic Bot, allowing users to close their laptops and keep tasks running in the cloud. Users can hand over their repositories to the agent in order to improve them continuously, discover and fix bugs, and more!

🚨 AI News | TestingCatalog

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Introducing: SAFEs by Mercury for C-Corps. You can now customize, sign, & share Y Combinator-templated SAFE docs on Mercury — and have the funding routed to your account. Plus, you can track the status of your investor checks in real time. Watch how it works 👇

Introducing: SAFEs by Mercury for C-Corps. You can now customize, sign, & share Y Combinator-templated SAFE docs on Mercury — and have the funding routed to your account. Plus, you can track the status of your investor checks in real time. Watch how it works 👇

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430,311 просмотров • 3 лет назад

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.

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.

Aaliya

23,225 просмотров • 1 месяц назад

On the periodic table, nothing separates gold (Au) from mercury (Hg); they are direct neighbors in the sixth period. Gold has the atomic number 79 (Group 11), and mercury has the atomic number 80 (Group 12). When these two elements mix, an immediate physicochemical reaction occurs in which the mercury dissolves the gold, forming a metallic alloy called an amalgam. The process is fully reversible and the gold is not lost, though the jewelry requires chemical or thermal treatment to return to its original state. Mercury does not destroy gold; it merely mixes with it at the surface. Since mercury evaporates at a much lower temperature than the melting point of gold, it can be completely removed. There was once a "legend" that the ancients could turn mercury into gold, though "EXPERTS" deny this. Today, however, through the use of nuclear physics, such a transformation is possible by altering the heart of the atom itself. Since mercury has 80 protons in its nucleus and gold has 79, modern science can "pluck" a proton from mercury to transform it into genuine gold.

On the periodic table, nothing separates gold (Au) from mercury (Hg); they are direct neighbors in the sixth period. Gold has the atomic number 79 (Group 11), and mercury has the atomic number 80 (Group 12). When these two elements mix, an immediate physicochemical reaction occurs in which the mercury dissolves the gold, forming a metallic alloy called an amalgam. The process is fully reversible and the gold is not lost, though the jewelry requires chemical or thermal treatment to return to its original state. Mercury does not destroy gold; it merely mixes with it at the surface. Since mercury evaporates at a much lower temperature than the melting point of gold, it can be completely removed. There was once a "legend" that the ancients could turn mercury into gold, though "EXPERTS" deny this. Today, however, through the use of nuclear physics, such a transformation is possible by altering the heart of the atom itself. Since mercury has 80 protons in its nucleus and gold has 79, modern science can "pluck" a proton from mercury to transform it into genuine gold.

Bronze Giant

489,202 просмотров • 3 дней назад

Run Codex 24/7 in the cloud with Atomic Bot! Just hand it a repo and close the laptop. One click to start. We ran it on ours first and it found a bug nobody had answered. Codex fixed it before we got back.

Run Codex 24/7 in the cloud with Atomic Bot! Just hand it a repo and close the laptop. One click to start. We ran it on ours first and it found a bug nobody had answered. Codex fixed it before we got back.

atomicbot.ai

23,432 просмотров • 25 дней назад

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

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GREG ISENBERG

194,171 просмотров • 5 месяцев назад

1/ It's time for @Mercury to help you understand and talk to your financial data! We're launching Mercury Insights today which is something I have always wanted to build into Mercury and AI has finally got good enough to make it possible.

1/ It's time for @Mercury to help you understand and talk to your financial data! We're launching Mercury Insights today which is something I have always wanted to build into Mercury and AI has finally got good enough to make it possible.

immad

14,886 просмотров • 6 месяцев назад

What the f*ck is this GitHub repo, 33k+ stars in less than a month. It's called OpenHuman, and the newest feature is why it's exploding, Super Context. > The moment you open a new chat, it runs a context pass first > Gathers what's relevant about you, your screen, your work > Then answers turn one like it's turn ten, already grounded It lives at the OS level, speaks in your voice across your whole system, connects to 118 apps you already use. Runs locally, never leaves your machine, and keeps learning you the longer you use it. It was #31 trending on GitHub for ten days straight and now it's the #1 repo on GitHub. > Repo:

What the f*ck is this GitHub repo, 33k+ stars in less than a month. It's called OpenHuman, and the newest feature is why it's exploding, Super Context. > The moment you open a new chat, it runs a context pass first > Gathers what's relevant about you, your screen, your work > Then answers turn one like it's turn ten, already grounded It lives at the OS level, speaks in your voice across your whole system, connects to 118 apps you already use. Runs locally, never leaves your machine, and keeps learning you the longer you use it. It was #31 trending on GitHub for ten days straight and now it's the #1 repo on GitHub. > Repo:

Defileo🔮

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Over the weekend I finished the to-do list that does itself. Everytime you add a task, a GPT-4 agent is spawned to complete it. It already has the context it needs on you and your company, and has access to your apps. It’s called the Do Anything Machine (Link in thread)

Over the weekend I finished the to-do list that does itself. Everytime you add a task, a GPT-4 agent is spawned to complete it. It already has the context it needs on you and your company, and has access to your apps. It’s called the Do Anything Machine (Link in thread)

Garrett Scott 🕳

2,893,376 просмотров • 3 лет назад

This clip will shock you to your core US Congressional Subcommittee hearings on dental mercury asks the FDA that now knowing that mercury “gets into the bloodstream and it goes to the brain and other organs of the body” would they still approve it for use? The FDA “Yes” The FDA even says they recommend mercury when it “cumulates in the brain”

This clip will shock you to your core US Congressional Subcommittee hearings on dental mercury asks the FDA that now knowing that mercury “gets into the bloodstream and it goes to the brain and other organs of the body” would they still approve it for use? The FDA “Yes” The FDA even says they recommend mercury when it “cumulates in the brain”

Wall Street Apes

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Meet your Chief Agent Operator in LobeHub now. You don't manage agents. Your CAO does. LobeHub hires agents from a 273K-skill marketplace, runs them in the cloud 24/7, and reports through IM apps you already live in. You run the strategy. We run the agents.

Meet your Chief Agent Operator in LobeHub now. You don't manage agents. Your CAO does. LobeHub hires agents from a 273K-skill marketplace, runs them in the cloud 24/7, and reports through IM apps you already live in. You run the strategy. We run the agents.

LobeHub

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AI assistants usually stop at giving you an answer. warmwind takes it a step further. It can click, type, navigate software, and handle repetitive workflows like a human entirely in the cloud. Teach it once, then let your cloud worker keep running 24/7. Warmwind OS is live Now. Limited capacity for free trial available. Watch the official launch video: Try Now Warmwind:👇

AI assistants usually stop at giving you an answer. warmwind takes it a step further. It can click, type, navigate software, and handle repetitive workflows like a human entirely in the cloud. Teach it once, then let your cloud worker keep running 24/7. Warmwind OS is live Now. Limited capacity for free trial available. Watch the official launch video: Try Now Warmwind:👇

Leonardo

37,645 просмотров • 17 дней назад

Your ChatGPT Work agent can now use websites that require you to sign in. Take over the cloud browser to log in, then let your agent continue the task. Your login persists across sessions, so you only have to sign in once.

Your ChatGPT Work agent can now use websites that require you to sign in. Take over the cloud browser to log in, then let your agent continue the task. Your login persists across sessions, so you only have to sign in once.

OpenAI Developers

1,092,454 просмотров • 1 месяц назад

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

11,584 просмотров • 1 месяц назад

Browser Use is now available in SpaceXAI's Grok Build! Ask Grok to complete tasks for you, or have it test your websites and fix bugs. Grok Build can work in your own browser or one hosted in the cloud.

Browser Use is now available in SpaceXAI's Grok Build! Ask Grok to complete tasks for you, or have it test your websites and fix bugs. Grok Build can work in your own browser or one hosted in the cloud.

Browser Use

34,537 просмотров • 22 дней назад

You can spin up an AI workforce with one prompt. Here's why it works: it pulls the context the AI needs to lay the foundation. Give it: - your role - team size - the goals you want to hit. Then say "interview me." After that, build it out in four steps: 1) Start with 1 agent. - What does it feel like to work with one? 2) Make that agent proactive. - Now it's doing things on your behalf before you ask. 3) Expand to 2 agents. - One directs the other, or routes to it. - This is where you learn how context gets passed. 4) Scale the workforce. - A mission control where you watch it all move around. - Now you see what has to run in parallel, which agent never needed that tool, which one runs fine on a smaller model. - Not everything needs Opus. Sub-agents are haiku and sonnet. The catch: the prompt gets you agents with markdown files doing some stuff. Getting to the 90% plus level is iteration, and that part is specific to each person. Nobody can hand it to you. Start with one agent. Spin up one agent this week. The rest is discovery.

You can spin up an AI workforce with one prompt. Here's why it works: it pulls the context the AI needs to lay the foundation. Give it: - your role - team size - the goals you want to hit. Then say "interview me." After that, build it out in four steps: 1) Start with 1 agent. - What does it feel like to work with one? 2) Make that agent proactive. - Now it's doing things on your behalf before you ask. 3) Expand to 2 agents. - One directs the other, or routes to it. - This is where you learn how context gets passed. 4) Scale the workforce. - A mission control where you watch it all move around. - Now you see what has to run in parallel, which agent never needed that tool, which one runs fine on a smaller model. - Not everything needs Opus. Sub-agents are haiku and sonnet. The catch: the prompt gets you agents with markdown files doing some stuff. Getting to the 90% plus level is iteration, and that part is specific to each person. Nobody can hand it to you. Start with one agent. Spin up one agent this week. The rest is discovery.

The Startup Ideas Podcast (SIP) 🧃

18,006 просмотров • 1 месяц назад

Glen is building the organizational learning and context layer for agents. Every agent session your team runs produces reasoning worth keeping, and nearly all of it is discarded the moment the window closes. Glen is the layer that unifies every agent and model your company run. Glen pulls in agent sessions from Claude Code, Codex and Cursor, plus Slack messages, GitHub prs, tickets, docs and calls. When a new agent picks up a task, Glen finds relevant prior context and injects it in the agents context window to steer it, producing knowledge work that is significantly higher quality, faster and cheaper than ever before. 29% less context and 21% faster to be exact. And Glen does more... > query the original agent behind any line of code > search every session your org has ever run > dynamic skill distillation > multiplayer agents > unified transcripts you can hand between Claude Code, Codex, and Cursor mid-task, > a company brain in Slack. Glen is in early access, sign up for the waitlist below.

Glen is building the organizational learning and context layer for agents. Every agent session your team runs produces reasoning worth keeping, and nearly all of it is discarded the moment the window closes. Glen is the layer that unifies every agent and model your company run. Glen pulls in agent sessions from Claude Code, Codex and Cursor, plus Slack messages, GitHub prs, tickets, docs and calls. When a new agent picks up a task, Glen finds relevant prior context and injects it in the agents context window to steer it, producing knowledge work that is significantly higher quality, faster and cheaper than ever before. 29% less context and 21% faster to be exact. And Glen does more... > query the original agent behind any line of code > search every session your org has ever run > dynamic skill distillation > multiplayer agents > unified transcripts you can hand between Claude Code, Codex, and Cursor mid-task, > a company brain in Slack. Glen is in early access, sign up for the waitlist below.

Nikos

19,466 просмотров • 26 дней назад