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Biggest lesson from OpenClaw is that a good teammate doesn't start from scratch everytime you check in. They remember what was decided, what's still open, and proactively help you. Today we launched heartbeats in Codex: automations that maintain context inside a single thread over time. Instead of each run...

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119,478 views • 3 months ago •via X (Twitter)

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“The only job left is to understand what you don't like, put it into words, and tell the AI.” Here’s my new episode with jason (DevEx at OpenAI) where he showed me how he uses Codex throughout his workday, including how to: → Set up a chief of staff for Slack and email → Turn past sessions into new AI skills → Give long-running projects verifiable goals Some example Codex use cases from Jason: “I want you to read the past week of Slack messages I’ve written and make a skill to figure out how to talk like me.” “Turn this thread into a heartbeat. I want you to check my emails, my Slack, my Linear, and tell me what I need to prioritize.” “Codex can find a booking ticket and check into the flight for me and text me the boarding pass to my phone.” Jason wrote the official OpenAI handbook on how to get the most out of Codex, so don’t miss this episode. 📌 Watch now: Thanks to our sponsors: Riverside: All-in-one AI studio for podcasts and video Google AI Studio: Build apps with Nano Banana, and more
0:30

“The only job left is to understand what you don't like, put it into words, and tell the AI.” Here’s my new episode with jason (DevEx at OpenAI) where he showed me how he uses Codex throughout his workday, including how to: → Set up a chief of staff for Slack and email → Turn past sessions into new AI skills → Give long-running projects verifiable goals Some example Codex use cases from Jason: “I want you to read the past week of Slack messages I’ve written and make a skill to figure out how to talk like me.” “Turn this thread into a heartbeat. I want you to check my emails, my Slack, my Linear, and tell me what I need to prioritize.” “Codex can find a booking ticket and check into the flight for me and text me the boarding pass to my phone.” Jason wrote the official OpenAI handbook on how to get the most out of Codex, so don’t miss this episode. 📌 Watch now: Thanks to our sponsors: Riverside: All-in-one AI studio for podcasts and video Google AI Studio: Build apps with Nano Banana, and more

Peter Yang

211,637 views • 12 days ago

I asked jason (DevEx at OpenAI): “What’s the craziest thing Codex did for you?” Here’s his answer: “I was on a bike ride when a coworker asked me to fix a launch video. So I connected remotely from my phone and asked Codex to use computer use to edit the video, export it, and post it back to Slack. Twenty minutes later, there was a new video in the Slack thread. Then I told Codex: ‘Every 30 minutes, check the thread for feedback and export V2, V3, V4.’ By the time I got home, the launch video was greenlit.” Codex had handled the revisions by repeatedly checking Slack for feedback. 📌 Watch the full episode here:
0:36

I asked jason (DevEx at OpenAI): “What’s the craziest thing Codex did for you?” Here’s his answer: “I was on a bike ride when a coworker asked me to fix a launch video. So I connected remotely from my phone and asked Codex to use computer use to edit the video, export it, and post it back to Slack. Twenty minutes later, there was a new video in the Slack thread. Then I told Codex: ‘Every 30 minutes, check the thread for feedback and export V2, V3, V4.’ By the time I got home, the launch video was greenlit.” Codex had handled the revisions by repeatedly checking Slack for feedback. 📌 Watch the full episode here:

Peter Yang

79,504 views • 11 days ago

Three months ago, Codex was trash for knowledge work. Now it's my daily driver. I use it for writing, recruiting, deep engineering work, and everything in between. It even keeps me at inbox 0. I chatted with Every 📧's head of growth Austin Austin Tedesco on Every 📧's AI & I about what changed, and why he now spends 80% of his working time in the Codex desktop app too. We get into: - How Codex went from making Austin feel like an idiot to being the place he goes to get stuff done, including complex tasks like writing go-to-market plans using existing material from Slack, Notion, and meeting transcripts. - Why the Codex’s desktop app, which is faster and more reliable than Claude Desktop/Cowork, is the real differentiator. - How I source candidates with Codex by having it identify career arcs, not keywords—my go-to move is identifying organizations likely to teach the skills Every needs for a role, and then find candidates from that pool who have since gone on to work in AI. This is a must-watch for anyone who's wondering whether it’s finally time to give Codex a try. Watch below! Timestamps How Codex went from a tool for senior engineers to a daily driver for knowledge work: 00:00:57 How Claude Code proved that a great coding agent works for any knowledge work: 00:02:42 Austin's switch to Codex: 00:07:24 How Austin set up Codex with folders, keys, and reviewer agents: 00:13:48 Using Codex to brainstorm automations across Gmail, Slack, and Notion: 00:18:24 How Austin manages the human review step when Codex is drafting communications: 00:22:42 Using Codex to build specialized agents inspired by product executive Claire Vo: 00:28:54 Synthesizing meeting transcripts and Slack threads into a go-to-market plan: 00:31:09 Building a live KPI tracker in Notion that agents can read: 00:40:15 Using Codex for recruiting: 00:44:54
58:23

Three months ago, Codex was trash for knowledge work. Now it's my daily driver. I use it for writing, recruiting, deep engineering work, and everything in between. It even keeps me at inbox 0. I chatted with Every 📧's head of growth Austin Austin Tedesco on Every 📧's AI & I about what changed, and why he now spends 80% of his working time in the Codex desktop app too. We get into: - How Codex went from making Austin feel like an idiot to being the place he goes to get stuff done, including complex tasks like writing go-to-market plans using existing material from Slack, Notion, and meeting transcripts. - Why the Codex’s desktop app, which is faster and more reliable than Claude Desktop/Cowork, is the real differentiator. - How I source candidates with Codex by having it identify career arcs, not keywords—my go-to move is identifying organizations likely to teach the skills Every needs for a role, and then find candidates from that pool who have since gone on to work in AI. This is a must-watch for anyone who's wondering whether it’s finally time to give Codex a try. Watch below! Timestamps How Codex went from a tool for senior engineers to a daily driver for knowledge work: 00:00:57 How Claude Code proved that a great coding agent works for any knowledge work: 00:02:42 Austin's switch to Codex: 00:07:24 How Austin set up Codex with folders, keys, and reviewer agents: 00:13:48 Using Codex to brainstorm automations across Gmail, Slack, and Notion: 00:18:24 How Austin manages the human review step when Codex is drafting communications: 00:22:42 Using Codex to build specialized agents inspired by product executive Claire Vo: 00:28:54 Synthesizing meeting transcripts and Slack threads into a go-to-market plan: 00:31:09 Building a live KPI tracker in Notion that agents can read: 00:40:15 Using Codex for recruiting: 00:44:54

Dan Shipper 📧

55,221 views • 3 months ago

Codex just turned an upcoming meeting into a fully automated cross-platform workflow. Box. Gmail. Slack. It researches across all three, synthesizes the context, and delivers a pre-meeting brief without anyone lifting a finger. This is what personal productivity looks like when agentic automation does the work for you. See it in action.👇
0:51

Codex just turned an upcoming meeting into a fully automated cross-platform workflow. Box. Gmail. Slack. It researches across all three, synthesizes the context, and delivers a pre-meeting brief without anyone lifting a finger. This is what personal productivity looks like when agentic automation does the work for you. See it in action.👇

Box

2,993,042 views • 4 months ago

It’s Codex Thursday, and yes, we have updates for you. First up: Appshots, a new way to bring the context of what you’re working on into Codex. On your Mac, press Command-Command to attach your app window to a Codex thread. Codex gets both a screenshot and text from the window, including content beyond what’s visible onscreen. Appshots are available across plans on Mac, with enterprise access coming soon.
0:45

It’s Codex Thursday, and yes, we have updates for you. First up: Appshots, a new way to bring the context of what you’re working on into Codex. On your Mac, press Command-Command to attach your app window to a Codex thread. Codex gets both a screenshot and text from the window, including content beyond what’s visible onscreen. Appshots are available across plans on Mac, with enterprise access coming soon.

OpenAI Developers

1,880,667 views • 2 months ago

The Codex deep dive that dominik kundel and I streamed last week is now on YouTube in case you missed it. (recording in thread 👇) We discuss how Codex has changed in the last two months and dive deep on the latest features with tips and best practices for getting the most out of it. Let us know what you think! We want to do a lot more of these.
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The Codex deep dive that dominik kundel and I streamed last week is now on YouTube in case you missed it. (recording in thread 👇) We discuss how Codex has changed in the last two months and dive deep on the latest features with tips and best practices for getting the most out of it. Let us know what you think! We want to do a lot more of these.

pranav

46,688 views • 10 months ago

We just launched Sites into Codex! Software creation was always about more than writing code. Sites in Codex fundamentally gives the power of end-to-end software creation to every user, no matter their technical fluency. These Sites are fully deployed to a URL, private to workspaces, come with authentication, can have static files, and can store dynamic data in databases. It is in preview for business and enterprise teams and will be rolling out to all workspaces over the next day. Give it a try by typing @ Sites into Codex and ask it to build anything! This project took a massive amount of effort across hundreds of people at OpenAI - proud that we were able to get this out and excited to see what you all build with it!
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We just launched Sites into Codex! Software creation was always about more than writing code. Sites in Codex fundamentally gives the power of end-to-end software creation to every user, no matter their technical fluency. These Sites are fully deployed to a URL, private to workspaces, come with authentication, can have static files, and can store dynamic data in databases. It is in preview for business and enterprise teams and will be rolling out to all workspaces over the next day. Give it a try by typing @ Sites into Codex and ask it to build anything! This project took a massive amount of effort across hundreds of people at OpenAI - proud that we were able to get this out and excited to see what you all build with it!

Rohan Varma

1,032,679 views • 2 months ago

I just built an entire app in 7 minutes using Codex Spark. EveryMCP: a universal MCP server installer that configures 15+ coding agents from a single CLI command. 12 Codex Spark subagents. All running in parallel. At the same time. The project itself isn't complicated, but just imagine what this looks like when you scale the complexity. My setup: • Codex 5.3 High to plan • Codex 5.3 Medium to orchestrate • 12 Codex Spark agents (xhigh) to implement in one shot Spark isn't competing with the big models. It's a different tool entirely. You orchestrate it. You run it in swarms. And it moves at a speed that wasn't possible before, even for the top 1% of AI coders. More complex workflows coming soon. Comment below if you want me to tell you how I did it.
4:29

I just built an entire app in 7 minutes using Codex Spark. EveryMCP: a universal MCP server installer that configures 15+ coding agents from a single CLI command. 12 Codex Spark subagents. All running in parallel. At the same time. The project itself isn't complicated, but just imagine what this looks like when you scale the complexity. My setup: • Codex 5.3 High to plan • Codex 5.3 Medium to orchestrate • 12 Codex Spark agents (xhigh) to implement in one shot Spark isn't competing with the big models. It's a different tool entirely. You orchestrate it. You run it in swarms. And it moves at a speed that wasn't possible before, even for the top 1% of AI coders. More complex workflows coming soon. Comment below if you want me to tell you how I did it.

am.will

16,916 views • 5 months ago

OpenAI just gave Codex a major upgrade. From a coding assistant into a workspace builder that can create interactive sites, apps, dashboards, planners, and review tools from plain work instructions. The most important new feature they released is "Sites". i.e. Codex can generate a hosted interactive workspace instead of only producing a document, spreadsheet, slide, or code file. OpenAI is also adding plugins for different jobs, so Codex knows how to help analysts, marketers, sales teams, product designers, investors, and bankers using the tools they already use. A data analyst might ask Codex to explain why sales dropped, then Codex could pull from data tools and create a dashboard. A sales team might ask Codex to prepare for a customer meeting, then Codex could collect account history, risks, follow-ups, and next steps into one shared page. The third feature is annotations, which means you can click a specific part of the result and ask Codex to fix only that part. Codex already reaches 5M weekly users, and OpenAI says 20% of them are now non-developers, with that group growing over 3x faster than developers.
0:43

OpenAI just gave Codex a major upgrade. From a coding assistant into a workspace builder that can create interactive sites, apps, dashboards, planners, and review tools from plain work instructions. The most important new feature they released is "Sites". i.e. Codex can generate a hosted interactive workspace instead of only producing a document, spreadsheet, slide, or code file. OpenAI is also adding plugins for different jobs, so Codex knows how to help analysts, marketers, sales teams, product designers, investors, and bankers using the tools they already use. A data analyst might ask Codex to explain why sales dropped, then Codex could pull from data tools and create a dashboard. A sales team might ask Codex to prepare for a customer meeting, then Codex could collect account history, risks, follow-ups, and next steps into one shared page. The third feature is annotations, which means you can click a specific part of the result and ask Codex to fix only that part. Codex already reaches 5M weekly users, and OpenAI says 20% of them are now non-developers, with that group growing over 3x faster than developers.

Rohan Paul

48,353 views • 2 months ago

Today marks the biggest update in the platform's history. HermesOS is evolving into Hivra. With Hivra, you can now launch and manage multiple AI workers from a single dashboard, with support beginning with: • Hermes Agent • Claude Code And soon: • Codex • OpenClaw • AEON (aeon ⭐) • AgentZero and many more. P.S. $HermesOS isn't going anywhere. More on that later in the thread ↓
1:28

Today marks the biggest update in the platform's history. HermesOS is evolving into Hivra. With Hivra, you can now launch and manage multiple AI workers from a single dashboard, with support beginning with: • Hermes Agent • Claude Code And soon: • Codex • OpenClaw • AEON (aeon ⭐) • AgentZero and many more. P.S. $HermesOS isn't going anywhere. More on that later in the thread ↓

Hivra

29,705 views • 2 months ago

How to build a brand from scratch using Paper, Codex + GPT image model 2 Since two weeks back, I´ve done most of my design work in paper And I´m genuinely impressed by what you can do with their MCP Combined with claude & codex you can pretty much build out a brand in an hour or two 1. Brainstorm a name for you product or service 2. find a good design system you can iterate on or come up with one from scratch 3. create a moodboard of things you like and want the brand to be about (images, colors, shapes, elements, you name it) inside paper 4. select the moodboard and prompt codex to create a brand brief (hooked up to paper mcp) to create the inital brand book in code 5. Use the new brand book you created and copy as PNG, take that image into ChatGPT and use GPT model 2 (with the brand prompt) to create the brand book 6. You will get a finished and well-done 10 paged brand book Now you can use that to create anything in line with the brand: Landing pags, lead magnets, ads, anything you can think of Comment "bookmarkable" + RT and I´ll send you the brand prompt and step by step guide in DMs.
1:09

How to build a brand from scratch using Paper, Codex + GPT image model 2 Since two weeks back, I´ve done most of my design work in paper And I´m genuinely impressed by what you can do with their MCP Combined with claude & codex you can pretty much build out a brand in an hour or two 1. Brainstorm a name for you product or service 2. find a good design system you can iterate on or come up with one from scratch 3. create a moodboard of things you like and want the brand to be about (images, colors, shapes, elements, you name it) inside paper 4. select the moodboard and prompt codex to create a brand brief (hooked up to paper mcp) to create the inital brand book in code 5. Use the new brand book you created and copy as PNG, take that image into ChatGPT and use GPT model 2 (with the brand prompt) to create the brand book 6. You will get a finished and well-done 10 paged brand book Now you can use that to create anything in line with the brand: Landing pags, lead magnets, ads, anything you can think of Comment "bookmarkable" + RT and I´ll send you the brand prompt and step by step guide in DMs.

Shann³

14,157 views • 2 months ago

OpenAI member of product staff Alexander Embiricos describes the evolution of "Lord Bottleneck," an internal Codex loop developed by a single staff member that ultimately ended up creating a tight feedback and improvement loop for new user experiences: "This person on the growth team needed to figure out what experiments to run. And they needed to write code to run the experiment. Then they needed to analyze the experiment." "They started using Codex for each separate thing. So they had it run a bunch of analyses, interrogate the data, talk to Codex about the data. Then they would pick an experiment, and ask Codex to write the code. Then they would run the experiment, then ask Codex what the results of the experiment were. Then they would produce a deck." "All steps they were doing individually. They didn't start by saying, 'I'm going to automate this entire thing,' because that's hard and scary. They just started with using Codex to accelerate themselves." "Then, they started connecting all these things together into a giant skill. And one day, they just said [to Codex], 'Why don't you do this every morning?'" "They gave it a name: 'Lord Bottleneck.' Because it's solving the bottlenecks of friction for new users." "Now, every morning, Lord Bottleneck evaluates past experiments, looks at data, proposes some [new] experiments, and offers to the team to run the experiments. The team picks [what experiments to do]. Then Lord Bottleneck is like, 'Ok cool. Here's some code or whatever config that needs to be done,' runs the experiment, and they go and do the same loop the next day." "It's really serious value. I forget the numbers, but it's produced significant company value automatically through Codex."
1:42

OpenAI member of product staff Alexander Embiricos describes the evolution of "Lord Bottleneck," an internal Codex loop developed by a single staff member that ultimately ended up creating a tight feedback and improvement loop for new user experiences: "This person on the growth team needed to figure out what experiments to run. And they needed to write code to run the experiment. Then they needed to analyze the experiment." "They started using Codex for each separate thing. So they had it run a bunch of analyses, interrogate the data, talk to Codex about the data. Then they would pick an experiment, and ask Codex to write the code. Then they would run the experiment, then ask Codex what the results of the experiment were. Then they would produce a deck." "All steps they were doing individually. They didn't start by saying, 'I'm going to automate this entire thing,' because that's hard and scary. They just started with using Codex to accelerate themselves." "Then, they started connecting all these things together into a giant skill. And one day, they just said [to Codex], 'Why don't you do this every morning?'" "They gave it a name: 'Lord Bottleneck.' Because it's solving the bottlenecks of friction for new users." "Now, every morning, Lord Bottleneck evaluates past experiments, looks at data, proposes some [new] experiments, and offers to the team to run the experiments. The team picks [what experiments to do]. Then Lord Bottleneck is like, 'Ok cool. Here's some code or whatever config that needs to be done,' runs the experiment, and they go and do the same loop the next day." "It's really serious value. I forget the numbers, but it's produced significant company value automatically through Codex."

TBPN

80,403 views • 3 months ago

You know that moment after a great meeting when the idea is clear in your head—but your AI knows none of the context? So you open ChatGPT, Claude, or Codex and start explaining everything again. That gap is exactly what Vocci Ring is designed to close. Worn throughout the day, Vocci captures real-world context as it happens—from meetings and coffee chats to the ideas that surface between scheduled moments—and makes it usable inside the AI tools you already rely on. No rebuilding the conversation from memory. No endless copying and pasting. Just call Vocci Ring from your preferred AI tool and continue from what actually happened. What I appreciate most is that Vocci isn’t trying to replace the AI ecosystem you already use. It quietly gives those tools the context they’ve been missing. Your AI shouldn’t have to start from a blank prompt every time. Wear the Context. Loop in Real Life. #Vocci #AIRing #AIWearables
0:40

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

AI StackLab

52,413 views • 3 days ago

Gusto cofounder Edward Kim says today is the most important day in Gusto's history since launch. They just shipped Gusto Cofounder, an AI agent that you talk to through texting and Slack that automates almost everything a small business does in its back office. He explains: "We start with all the problems that we're already helping our customers with — payroll, benefits, HR, scheduling — then we bring on a lot of the power of AI into it." "You tell us what your business processes are, starting with payroll, benefits, and all these things we're already doing for you. And Gusto Cofounder will basically run your business process for you." "You communicate with it through SMS and Slack. You don't really even interface with it through a website." "And we connect to all the systems that you're using outside of Gusto as well. Notion, QuickBooks, Google Workspace... Gusto Cofounder brings it all together into one place where it automates your business processes."
4:07

Gusto cofounder Edward Kim says today is the most important day in Gusto's history since launch. They just shipped Gusto Cofounder, an AI agent that you talk to through texting and Slack that automates almost everything a small business does in its back office. He explains: "We start with all the problems that we're already helping our customers with — payroll, benefits, HR, scheduling — then we bring on a lot of the power of AI into it." "You tell us what your business processes are, starting with payroll, benefits, and all these things we're already doing for you. And Gusto Cofounder will basically run your business process for you." "You communicate with it through SMS and Slack. You don't really even interface with it through a website." "And we connect to all the systems that you're using outside of Gusto as well. Notion, QuickBooks, Google Workspace... Gusto Cofounder brings it all together into one place where it automates your business processes."

TBPN

58,412 views • 2 months ago

🚨 OpenAI just launched Codex, a brand-new autonomous coding agent that can build features and fix bugs on its own. We’ve been using it Every 📧 for a few days, and I’m impressed. I invited Alexander Embiricos (ben davies), a member of the product staff responsible for Codex, to demo Codex and talk about it live on a special edition of AI & I: What Codex is and how it works Codex is designed to be used by senior engineers—it performs coding tasks like adding features or fixing bugs autonomously. It's built to allow you to start many sessions at once, so you can have multiple agents working in parallel. Codex is built to have "taste" OpenAI trained Codex to have the taste of a senior software engineer. It knows how big codebases work, how to write a good PR, and uses clean, minimal code. Why an “abundance mindset” is best for interacting with agents Codex is designed to allow users to delegate many tasks at once without getting caught up in the details. This lets you point an abundance of agents at a specific task like a difficult bug—it’s worth it even if only one of them succeeds. How OpenAI is thinking about agents Codex is one piece of a unified super-assistant OpenAI wants to eventually build—an agent that helps users easily get things done by selecting the right tools for them behind the scenes. OpenAI’s vision for the future of programming In the future developers will probably spend less time writing routine code and more time guiding agents, reviewing their work, and making strategy decisions. Programming will become more social, letting teams easily delegate multiple tasks at once, allowing people to focus on ideas and collaboration instead of routine coding. Watch below!
44:33

🚨 OpenAI just launched Codex, a brand-new autonomous coding agent that can build features and fix bugs on its own. We’ve been using it Every 📧 for a few days, and I’m impressed. I invited Alexander Embiricos (ben davies), a member of the product staff responsible for Codex, to demo Codex and talk about it live on a special edition of AI & I: What Codex is and how it works Codex is designed to be used by senior engineers—it performs coding tasks like adding features or fixing bugs autonomously. It's built to allow you to start many sessions at once, so you can have multiple agents working in parallel. Codex is built to have "taste" OpenAI trained Codex to have the taste of a senior software engineer. It knows how big codebases work, how to write a good PR, and uses clean, minimal code. Why an “abundance mindset” is best for interacting with agents Codex is designed to allow users to delegate many tasks at once without getting caught up in the details. This lets you point an abundance of agents at a specific task like a difficult bug—it’s worth it even if only one of them succeeds. How OpenAI is thinking about agents Codex is one piece of a unified super-assistant OpenAI wants to eventually build—an agent that helps users easily get things done by selecting the right tools for them behind the scenes. OpenAI’s vision for the future of programming In the future developers will probably spend less time writing routine code and more time guiding agents, reviewing their work, and making strategy decisions. Programming will become more social, letting teams easily delegate multiple tasks at once, allowing people to focus on ideas and collaboration instead of routine coding. Watch below!

Dan Shipper 📧

145,487 views • 1 year ago

Another blow to Anthropic! They spent months building what's now fully open-source. Anthropic recently put Claude inside Slack, where you can tag it in a channel. It reads the thread, breaks the task into steps, and posts the result back. The problem is that it only runs Claude and only in the channels Anthropic supports. Running your own agent there is harder. The reasoning, tool calls, and state management are mostly handled by the framework. Connecting that agent to a messaging platform is not. Moreover, each platform has a different integration: - Slack renders messages with Block Kit - Teams uses Adaptive Cards - and each has its own SDK, auth flow, and delivery model. If an agent needs to run on three platforms, one must write three separate integrations against the same agent logic. That overhead explains why most custom agents never get deployed to Slack, and why the ones that do are usually a single vendor's hosted assistant. The alternative is to keep the agent in one place and add a per-platform adapter that translates its output into each platform's native format. The agent is written once, and each channel requires just another output target instead of a separate build. CopilotKit open-sourced this full implementation in the Channels SDK. Essentially, any agent that implements AG-UI can run in a messaging platform in a few lines of code, like Slack, Teams, Discord, WhatsApp, and many more. Because the agent runs inside the thread, it has that conversation's context, so it can summarize the discussion, open a ticket, or route to the right person. It works with any backend, so LangGraph, CrewAI, Mastra, Google ADK, or a plain HTTP agent can connect through an existing endpoint. The same message can render as a Block Kit in Slack and as Adaptive Cards in Teams. In practice, the model and orchestration stay the same; it requires no migration or rewrite. It also handles human-in-the-loop approvals, persistence, and transcripts that carry state across platforms, so a thread started in Teams can continue in Slack. CopilotKit is open-source, and AG-UI is supported across every major agent framework, including LangGraph, CrewAI, Mastra, and Google ADK. Here's the repo: (don't forget to star it ⭐) The agent running in Slack no longer has to be a vendor's. It can be the one you already built. The video below shows this in action. Thanks to CopilotKit for working with me on this launch.
0:30

Another blow to Anthropic! They spent months building what's now fully open-source. Anthropic recently put Claude inside Slack, where you can tag it in a channel. It reads the thread, breaks the task into steps, and posts the result back. The problem is that it only runs Claude and only in the channels Anthropic supports. Running your own agent there is harder. The reasoning, tool calls, and state management are mostly handled by the framework. Connecting that agent to a messaging platform is not. Moreover, each platform has a different integration: - Slack renders messages with Block Kit - Teams uses Adaptive Cards - and each has its own SDK, auth flow, and delivery model. If an agent needs to run on three platforms, one must write three separate integrations against the same agent logic. That overhead explains why most custom agents never get deployed to Slack, and why the ones that do are usually a single vendor's hosted assistant. The alternative is to keep the agent in one place and add a per-platform adapter that translates its output into each platform's native format. The agent is written once, and each channel requires just another output target instead of a separate build. CopilotKit open-sourced this full implementation in the Channels SDK. Essentially, any agent that implements AG-UI can run in a messaging platform in a few lines of code, like Slack, Teams, Discord, WhatsApp, and many more. Because the agent runs inside the thread, it has that conversation's context, so it can summarize the discussion, open a ticket, or route to the right person. It works with any backend, so LangGraph, CrewAI, Mastra, Google ADK, or a plain HTTP agent can connect through an existing endpoint. The same message can render as a Block Kit in Slack and as Adaptive Cards in Teams. In practice, the model and orchestration stay the same; it requires no migration or rewrite. It also handles human-in-the-loop approvals, persistence, and transcripts that carry state across platforms, so a thread started in Teams can continue in Slack. CopilotKit is open-source, and AG-UI is supported across every major agent framework, including LangGraph, CrewAI, Mastra, and Google ADK. Here's the repo: (don't forget to star it ⭐) The agent running in Slack no longer has to be a vendor's. It can be the one you already built. The video below shows this in action. Thanks to CopilotKit for working with me on this launch.

Akshay 🚀

217,319 views • 3 days ago

We’ve been in private beta with a human + AI workspace similar to Buzz, with a few really important differences: (We previously built a company backed by Slack that sold to Atlassian, so we've been thinking about this problem for a while) - Agents reply by default unless you specifically flip to “team chat.” This feels 10x better than having to @ mention the agent every time. - It’s all in the cloud, with shared compute spread across a set of VMs. Way smoother onboarding, and yes, you can still connect your claude/codex subscriptions - You don’t create an army of agents. Number of agents is a vanity metric. Instead, you create shared computers, each one is a “space” where you define shared memory, connectors, skills, automations, etc. The Type agent pulls the appropriate context from the space where you have the conversation. - You can connect it to Slack to make it easy for your team to adopt and slowly move over rather than having to rip out Slack day 1. We’re working with a couple dozen forward thinking companies, who have told us “the whole team loves type”, “it’s the most used app on my computer”, and “type gives you superpowers” Here's a demo of how it works. Reply if you want to test it out!
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We’ve been in private beta with a human + AI workspace similar to Buzz, with a few really important differences: (We previously built a company backed by Slack that sold to Atlassian, so we've been thinking about this problem for a while) - Agents reply by default unless you specifically flip to “team chat.” This feels 10x better than having to @ mention the agent every time. - It’s all in the cloud, with shared compute spread across a set of VMs. Way smoother onboarding, and yes, you can still connect your claude/codex subscriptions - You don’t create an army of agents. Number of agents is a vanity metric. Instead, you create shared computers, each one is a “space” where you define shared memory, connectors, skills, automations, etc. The Type agent pulls the appropriate context from the space where you have the conversation. - You can connect it to Slack to make it easy for your team to adopt and slowly move over rather than having to rip out Slack day 1. We’re working with a couple dozen forward thinking companies, who have told us “the whole team loves type”, “it’s the most used app on my computer”, and “type gives you superpowers” Here's a demo of how it works. Reply if you want to test it out!

Fletcher Richman

354,485 views • 11 days ago

Notch Clips. every other ad tool ignores the footage sitting in your dropbox and generates new clips from a prompt. notch opens your library instead. it watches every clip you have ever shot and understands what is inside each one. the mood. who is in frame. what they are doing. the quality. so when you ask it to build an ad, it does not start from scratch. it reaches into your past shoots, finds the clip that fits, and slots it into the exact moment that needs it. here is what that looks like. you had thirteen versions of one reaction shot. notch picked the one that worked and left the other twelve. not by filename. not by guessing from a reference image. it watched all thirteen and could tell the difference. that is the whole idea. the right clip was already in your library. every other tool was about to make a worse one. footage you already shot, turned into every ad you still need. drop your site and a few clips you have. notch builds the first ad from them.
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Notch Clips. every other ad tool ignores the footage sitting in your dropbox and generates new clips from a prompt. notch opens your library instead. it watches every clip you have ever shot and understands what is inside each one. the mood. who is in frame. what they are doing. the quality. so when you ask it to build an ad, it does not start from scratch. it reaches into your past shoots, finds the clip that fits, and slots it into the exact moment that needs it. here is what that looks like. you had thirteen versions of one reaction shot. notch picked the one that worked and left the other twelve. not by filename. not by guessing from a reference image. it watched all thirteen and could tell the difference. that is the whole idea. the right clip was already in your library. every other tool was about to make a worse one. footage you already shot, turned into every ad you still need. drop your site and a few clips you have. notch builds the first ad from them.

Vinay Jain

406,286 views • 2 months ago

Three skills I use every day in Claude Code and Codex to solve my hardest problems: 1️⃣ /agent-watchdog When I have one agent like Codex working on a task and I don't fully trust it's going to do everything right, I'll open up another one like Claude Code and tell it to watchdog the Codex thread. You can copy the Codex deep link into Claude Code and it'll look at the prompt you sent, watch the Codex thread until it's done, then compare the Codex solution to how it was planning to solve it and automatically fix anything that Codex missed. It can also test the work of the other agent end-to-end. Similar to the idea of OpenRouter's new Fusion feature, I've definitely found that two models thinking through a problem and checking each other's work can be wildly more impactful than just one. 2️⃣ /plan-arbiter Similar ideas as /agent-watchdog - but with this one you have both make plans, compare plans, negotiate the differences, and make a final plan to execute. I find Claude Code is better at writing plans, but Codex is faster and cheaper to execute on them. Then I usually have Claude Code watchdog the Codex work and fix anything that was missed. 3️⃣ /read-the-damn-docs One thing that drives me crazy with coding agents is they're so reluctant to look up docs. They'll just guess and guess and guess at the right API surface for things, or the right solution to an integration of two things. Once I explicitly tell it to look up the docs, it says "Oh, I see the answer," and it fixes the problem. So I made the /read-the-damn-docs skill. Add it and your agents will know when and how to do efficient web searches to look up docs for the types of problems you really should look up docs for. All of these are totally open source over on my GitHub. If you try them, let me know your feedback. Will link to them below:
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Three skills I use every day in Claude Code and Codex to solve my hardest problems: 1️⃣ /agent-watchdog When I have one agent like Codex working on a task and I don't fully trust it's going to do everything right, I'll open up another one like Claude Code and tell it to watchdog the Codex thread. You can copy the Codex deep link into Claude Code and it'll look at the prompt you sent, watch the Codex thread until it's done, then compare the Codex solution to how it was planning to solve it and automatically fix anything that Codex missed. It can also test the work of the other agent end-to-end. Similar to the idea of OpenRouter's new Fusion feature, I've definitely found that two models thinking through a problem and checking each other's work can be wildly more impactful than just one. 2️⃣ /plan-arbiter Similar ideas as /agent-watchdog - but with this one you have both make plans, compare plans, negotiate the differences, and make a final plan to execute. I find Claude Code is better at writing plans, but Codex is faster and cheaper to execute on them. Then I usually have Claude Code watchdog the Codex work and fix anything that was missed. 3️⃣ /read-the-damn-docs One thing that drives me crazy with coding agents is they're so reluctant to look up docs. They'll just guess and guess and guess at the right API surface for things, or the right solution to an integration of two things. Once I explicitly tell it to look up the docs, it says "Oh, I see the answer," and it fixes the problem. So I made the /read-the-damn-docs skill. Add it and your agents will know when and how to do efficient web searches to look up docs for the types of problems you really should look up docs for. All of these are totally open source over on my GitHub. If you try them, let me know your feedback. Will link to them below:

Steve (Builder.io)

43,089 views • 1 month ago

Time is valuable. Slack AI gives you more of it. 🙌✨ And starting today, every Slack user on a paid plan can start getting more time back with AI that works right where they need it to (in Slack). Learn more at:
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Time is valuable. Slack AI gives you more of it. 🙌✨ And starting today, every Slack user on a paid plan can start getting more time back with AI that works right where they need it to (in Slack). Learn more at:

Slack

24,860 views • 2 years ago