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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...

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Dan Shipper 📧

121,128 subscribers

55,561 Aufrufe • vor 5 Monaten •via X (Twitter)

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.Natalia rode so hard for Claude Code we devoted an episode to how she was using it to automate her job running Every 📧’s consulting practice. Fast forward to five months later, and she rides just as hard for Codex. I had her back on AI & I to talk about what caused her to make the switch, including how she ran a prompt in Codex before bed and woke up to a finished, custom CRM tool. We get into: - Why she finds Codex easier to use than Claude Code - How she’s using loops in Codex to create customized tools that work exactly how she needs them to - Why the consulting team still pays for SaaS products like Attio and Asana even though they could vibe code their own versions - How she built an app to manage her father’s medical care in Codex - How knowledge work is evolving from sculpting to gardening, in which you develop the context and logic you need for an agent to execute for you This is a must-watch for anyone trying to figure out whether to build their own tools or buy real software—and what it takes to get an AI agent to run unsupervised for hours and nail the output. Watch below! Timestamps 1. Introduction: 00:01:05 2. How Natalia manages Claudie, the consulting team’s AI project manager: 00:02:35 3. Why the consulting team still pays for SaaS products: 00:04:55 4. Codex as a game changer : 00:11:47 5. Building personalized learning guides and illustrated explainers with AI: 00:14:55 6. Inside Natalia's AI-powered email triage system: 00:21:40 7. The shift from knowledge work as sculpting to knowledge work as gardening: 00:26:44 8. Using Codex to on-shot a custom CRM: 00:28:57 9. Using Codex to build an app that coordinates her father’s medical care: 00:33:16
41:15

.Natalia rode so hard for Claude Code we devoted an episode to how she was using it to automate her job running Every 📧’s consulting practice. Fast forward to five months later, and she rides just as hard for Codex. I had her back on AI & I to talk about what caused her to make the switch, including how she ran a prompt in Codex before bed and woke up to a finished, custom CRM tool. We get into: - Why she finds Codex easier to use than Claude Code - How she’s using loops in Codex to create customized tools that work exactly how she needs them to - Why the consulting team still pays for SaaS products like Attio and Asana even though they could vibe code their own versions - How she built an app to manage her father’s medical care in Codex - How knowledge work is evolving from sculpting to gardening, in which you develop the context and logic you need for an agent to execute for you This is a must-watch for anyone trying to figure out whether to build their own tools or buy real software—and what it takes to get an AI agent to run unsupervised for hours and nail the output. Watch below! Timestamps 1. Introduction: 00:01:05 2. How Natalia manages Claudie, the consulting team’s AI project manager: 00:02:35 3. Why the consulting team still pays for SaaS products: 00:04:55 4. Codex as a game changer : 00:11:47 5. Building personalized learning guides and illustrated explainers with AI: 00:14:55 6. Inside Natalia's AI-powered email triage system: 00:21:40 7. The shift from knowledge work as sculpting to knowledge work as gardening: 00:26:44 8. Using Codex to on-shot a custom CRM: 00:28:57 9. Using Codex to build an app that coordinates her father’s medical care: 00:33:16

Dan Shipper 📧

25,701 Aufrufe • vor 3 Monaten

OpenAI’s hottest app isn’t ChatGPT—it’s Codex. In the last few weeks alone, the Codex team shipped a desktop app, GPT-5.3 Codex (a new flagship model), and Spark, the fastest coding model I’ve ever used. Usage has grown fivefold since January and over a million people now use Codex weekly. Codex was also the app that OpenAI chose to run an ad for in the Super Bowl. I talked to Thibault (Tibo), head of Codex, and Andrew (Andrew Ambrosino), a member of technical staff who built the Codex app, for Every 📧’s AI & I about what OpenAI is building and how they’re using it internally. We get into: - Why they built a GUI instead of a terminal. Terminals work for quick tasks, they say, but feel limiting when you’re running multiple agents in parallel. The IDE, meanwhile, overwhelms users—and the Codex team wants the AI to dynamically decide which tools to show you for a given task. - How they’re teaching the model to read between the lines. Codex is great at following instructions, but optimize too hard in that direction, and it starts taking you literally—like copying a typo directly into the code. The team obsesses over this tradeoff, and is also introducing “personalities,” modes users can toggle between that control how blunt or supportive the model feels. - How OpenAI uses its own coding agent. Codex lets you schedule prompts to run on a recurring basis, and the team has dozens of automations running at all times. For example, one scans for merge conflicts every couple of hours so code is always ready to ship, and another picks a random file from the codebase multiple times a day and hunts for bugs no one would've gone looking for. - Why speed is a dimension of intelligence. OpenAI’s newest model (Spark) is so fast that they actually slow it down so you can read the output. They see the speed enabling three things: staying super in the flow, replacing brittle developer tools with intelligent ones that can adapt on the fly, and redirecting the model mid-task— especially with voice—so coding starts to feel more and more like a conversation. - Code review is the next bottleneck. Models can generate code faster than ever, but someone still has to verify that it works. The team is exploring a future where the model proves its own fix works—retracing the click path a user would take, screenshotting the results, and attaching the evidence to a pull request. This is a must-watch for anyone who uses AI coding agents—and is curious about the future of programming. Watch below! Timestamps: Introduction: 00:01:27 OpenAI’s evolving bet on its coding agent: 00:05:27 The choice to invest in a GUI (over a terminal): 00:09:42 The AI workflows that the Codex team relies on to ship: 00:20:38 Teaching Codex how to read between the lines: 00:26:45 Building affordances for a lightening fast model: 00:28:45 Why speed is a dimension of intelligence: 00:33:15 Code review is the next bottleneck for coding agents: 00:36:30 How the Codex team positions against the competition: 00:41:24
46:40

OpenAI’s hottest app isn’t ChatGPT—it’s Codex. In the last few weeks alone, the Codex team shipped a desktop app, GPT-5.3 Codex (a new flagship model), and Spark, the fastest coding model I’ve ever used. Usage has grown fivefold since January and over a million people now use Codex weekly. Codex was also the app that OpenAI chose to run an ad for in the Super Bowl. I talked to Thibault (Tibo), head of Codex, and Andrew (Andrew Ambrosino), a member of technical staff who built the Codex app, for Every 📧’s AI & I about what OpenAI is building and how they’re using it internally. We get into: - Why they built a GUI instead of a terminal. Terminals work for quick tasks, they say, but feel limiting when you’re running multiple agents in parallel. The IDE, meanwhile, overwhelms users—and the Codex team wants the AI to dynamically decide which tools to show you for a given task. - How they’re teaching the model to read between the lines. Codex is great at following instructions, but optimize too hard in that direction, and it starts taking you literally—like copying a typo directly into the code. The team obsesses over this tradeoff, and is also introducing “personalities,” modes users can toggle between that control how blunt or supportive the model feels. - How OpenAI uses its own coding agent. Codex lets you schedule prompts to run on a recurring basis, and the team has dozens of automations running at all times. For example, one scans for merge conflicts every couple of hours so code is always ready to ship, and another picks a random file from the codebase multiple times a day and hunts for bugs no one would've gone looking for. - Why speed is a dimension of intelligence. OpenAI’s newest model (Spark) is so fast that they actually slow it down so you can read the output. They see the speed enabling three things: staying super in the flow, replacing brittle developer tools with intelligent ones that can adapt on the fly, and redirecting the model mid-task— especially with voice—so coding starts to feel more and more like a conversation. - Code review is the next bottleneck. Models can generate code faster than ever, but someone still has to verify that it works. The team is exploring a future where the model proves its own fix works—retracing the click path a user would take, screenshotting the results, and attaching the evidence to a pull request. This is a must-watch for anyone who uses AI coding agents—and is curious about the future of programming. Watch below! Timestamps: Introduction: 00:01:27 OpenAI’s evolving bet on its coding agent: 00:05:27 The choice to invest in a GUI (over a terminal): 00:09:42 The AI workflows that the Codex team relies on to ship: 00:20:38 Teaching Codex how to read between the lines: 00:26:45 Building affordances for a lightening fast model: 00:28:45 Why speed is a dimension of intelligence: 00:33:15 Code review is the next bottleneck for coding agents: 00:36:30 How the Codex team positions against the competition: 00:41:24

Dan Shipper 📧

15,588 Aufrufe • vor 7 Monaten

🚨 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 Aufrufe • vor 1 Jahr

People keep saying GPT-5.5 + Codex mogs Claude Code. So I got OpenAI PM Abhi Muchhal to show me exactly how to use Codex like a pro: 03:48 - What Codex unlocks for PM work 05:34 - How he built his growth dashboard 11:32 - How to build in Codex with Playwright 14:52 - Moving away from PRDs to Codex prototypes 21:23 - 3 automations running before his day starts 28:37 - WhatsApp computer use demo setup 33:05 - Codex takes action inside WhatsApp 37:00 - Building a 1040 tax filing app in Codex 43:42 - What drove ChatGPT to 1B WAU 47:18 - ImageGen 2, the biggest ELO jump of any model 59:26 - How to break into OpenAI as a PM
1:07:06

People keep saying GPT-5.5 + Codex mogs Claude Code. So I got OpenAI PM Abhi Muchhal to show me exactly how to use Codex like a pro: 03:48 - What Codex unlocks for PM work 05:34 - How he built his growth dashboard 11:32 - How to build in Codex with Playwright 14:52 - Moving away from PRDs to Codex prototypes 21:23 - 3 automations running before his day starts 28:37 - WhatsApp computer use demo setup 33:05 - Codex takes action inside WhatsApp 37:00 - Building a 1040 tax filing app in Codex 43:42 - What drove ChatGPT to 1B WAU 47:18 - ImageGen 2, the biggest ELO jump of any model 59:26 - How to break into OpenAI as a PM

Aakash Gupta

106,261 Aufrufe • vor 4 Monaten

Michael Bolin (Michael Bolin) is the tech lead of the Codex open source repository at OpenAI and formerly a distinguished eng (E9) at Meta. I asked him for all the details on his career story and how he uses Codex for max benefit. Timestamps: 00:00:00 - Intro 00:00:56 - Chickenfoot 00:02:45 - Working at Google 00:06:34 - Overhauling Facebook's build system 00:16:36 - Rewriting Facebook's IDE 00:26:01 - Struggles after Principal Eng (E8) promo 00:28:39 - Building a virtual filesystem for Facebook 00:35:47 - Delayed Distinguished promo (E9) and learnings 00:39:56 - Joining OpenAI 00:43:05 - Research-led vs engineering-led cultures 00:44:53 - The story behind Codex 00:51:00 - How he uses Codex 00:57:00 - Why Codex's harness is open source 00:59:50 - Top technical book recommendations 01:05:02 - Why deep technical skills are still valuable (for now) 01:11:07 - How to start projects well 01:14:27 - Advice on writing better and career planning 01:17:06 - Advice for his younger self 01:19:10 - Outro He was a dream guest of mine and I'm excited to share his story with you all! Other places to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:
1:20:03

Michael Bolin (Michael Bolin) is the tech lead of the Codex open source repository at OpenAI and formerly a distinguished eng (E9) at Meta. I asked him for all the details on his career story and how he uses Codex for max benefit. Timestamps: 00:00:00 - Intro 00:00:56 - Chickenfoot 00:02:45 - Working at Google 00:06:34 - Overhauling Facebook's build system 00:16:36 - Rewriting Facebook's IDE 00:26:01 - Struggles after Principal Eng (E8) promo 00:28:39 - Building a virtual filesystem for Facebook 00:35:47 - Delayed Distinguished promo (E9) and learnings 00:39:56 - Joining OpenAI 00:43:05 - Research-led vs engineering-led cultures 00:44:53 - The story behind Codex 00:51:00 - How he uses Codex 00:57:00 - Why Codex's harness is open source 00:59:50 - Top technical book recommendations 01:05:02 - Why deep technical skills are still valuable (for now) 01:11:07 - How to start projects well 01:14:27 - Advice on writing better and career planning 01:17:06 - Advice for his younger self 01:19:10 - Outro He was a dream guest of mine and I'm excited to share his story with you all! Other places to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:

Ryan Peterman

119,601 Aufrufe • vor 6 Monaten

If you use Codex, Tibo needs no introduction. We talked 100% about Codex (fun fact: he started building it!), and 0% about resets. Timestamps: 00:00 Intro 07:21 Working at Google 12:41 What drew Tibo to OpenAI 15:19 The early days of Codex 18:20 Why Codex was built in Rust 21:15 Why Codex is open source 25:50 Codex plays nice with other models: why? 32:09 How the harness works 36:44 Harness and model improvements 41:19 The SDLC behind Codex 46:39 Code reviews at Codex 52:09 Maintenance and architecture 56:43 How AI tools expand what engineers can do 1:02:30 The Merge: ChatGPT + Codex 1:07:16 How Tibo uses Codex and ChatGPT 1:10:44 Advice for engineers who want to work in AI Brought to you by: • turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable. • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • Entire – Git hosting, rebuilt for the agentic era. Entire hosts your code in-region, and is up to 89x faster than any other competitor. Oh, and to those still reading and wondering about resets: there was one yesterday already 😅
1:14:22

If you use Codex, Tibo needs no introduction. We talked 100% about Codex (fun fact: he started building it!), and 0% about resets. Timestamps: 00:00 Intro 07:21 Working at Google 12:41 What drew Tibo to OpenAI 15:19 The early days of Codex 18:20 Why Codex was built in Rust 21:15 Why Codex is open source 25:50 Codex plays nice with other models: why? 32:09 How the harness works 36:44 Harness and model improvements 41:19 The SDLC behind Codex 46:39 Code reviews at Codex 52:09 Maintenance and architecture 56:43 How AI tools expand what engineers can do 1:02:30 The Merge: ChatGPT + Codex 1:07:16 How Tibo uses Codex and ChatGPT 1:10:44 Advice for engineers who want to work in AI Brought to you by: • turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable. • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • Entire – Git hosting, rebuilt for the agentic era. Entire hosts your code in-region, and is up to 89x faster than any other competitor. Oh, and to those still reading and wondering about resets: there was one yesterday already 😅

Gergely Orosz

81,044 Aufrufe • vor 23 Tagen

GPT-6 Astra is by far the best inside Codex. & this is THE Complete Beginners Guide to Codex. The 28 things you need to know about Codex and GPT-6 to start using it for knowledge work and coding work. My goal with this video: give you one guide you can send to anyone on your team so they can get comfortable with Codex, understand what’s possible, and start finding ways to use AI in your business. 00:00 Intro 01:15 The Codex Platform 02:02 Downloading Codex (ChatGPT Desktop) 03:25 1. Codex Is the App, GPT-6 Is the Model 06:10 2. Build Any App 10:32 3. Host Sites with GPT Sites 18:12 4A. Building Desktop App 21:33 4B. Building an iOS app 24:09 5. Built-In Web Browser 32:27 6. Create Any Document 35:00 7. Annotation Mode 38:41 8. Production-Ready Apps 44:29 9. Chats & Projects 48:54 10. Multitasking 50:09 10B Side Chat 51:13 11. Sections 54:27 12. Connect Every App (Plugins) 01:03:17 13. Ask Codex What to Work On 01:05:39 14. Blender & 3D Assets 01:08:25 15. Video Games 01:09:24 16. Interactive Learning Websites 01:13:12 17. Scheduled Tasks 01:16:19 18. Email & iMessage 01:18:56 19. Skills 01:22:54 20. Record and Replay 01:26:45 21. External APIs in Skills 01:30:00 22. Video Understanding Skill 01:35:51 23. Inline Charts 01:38:03 24. Control Codex from Your Phone 01:42:49 25. Generate & Edit Images 01:45:17 26. Sub-Agents 01:48:09 27. Computer Use 01:49:35 28. Whatever You Want
1:54:46

GPT-6 Astra is by far the best inside Codex. & this is THE Complete Beginners Guide to Codex. The 28 things you need to know about Codex and GPT-6 to start using it for knowledge work and coding work. My goal with this video: give you one guide you can send to anyone on your team so they can get comfortable with Codex, understand what’s possible, and start finding ways to use AI in your business. 00:00 Intro 01:15 The Codex Platform 02:02 Downloading Codex (ChatGPT Desktop) 03:25 1. Codex Is the App, GPT-6 Is the Model 06:10 2. Build Any App 10:32 3. Host Sites with GPT Sites 18:12 4A. Building Desktop App 21:33 4B. Building an iOS app 24:09 5. Built-In Web Browser 32:27 6. Create Any Document 35:00 7. Annotation Mode 38:41 8. Production-Ready Apps 44:29 9. Chats & Projects 48:54 10. Multitasking 50:09 10B Side Chat 51:13 11. Sections 54:27 12. Connect Every App (Plugins) 01:03:17 13. Ask Codex What to Work On 01:05:39 14. Blender & 3D Assets 01:08:25 15. Video Games 01:09:24 16. Interactive Learning Websites 01:13:12 17. Scheduled Tasks 01:16:19 18. Email & iMessage 01:18:56 19. Skills 01:22:54 20. Record and Replay 01:26:45 21. External APIs in Skills 01:30:00 22. Video Understanding Skill 01:35:51 23. Inline Charts 01:38:03 24. Control Codex from Your Phone 01:42:49 25. Generate & Edit Images 01:45:17 26. Sub-Agents 01:48:09 27. Computer Use 01:49:35 28. Whatever You Want

Riley Brown

193,991 Aufrufe • vor 19 Tagen

Moving your Coding Agents to the Cloud (ft. Codex Desktop & GPT-6 Astra) 00:00 The limitations of running agents locally 01:13 Parallel development and Git worktrees 02:03 Moving your coding agent to a remote machine 02:25 Introducing Railway Cloud Agents 02:52 Installing the CLI and signing in 03:03 Configuring your project and default agent 03:42 Bringing your agent skills 04:24 Connecting the Codex desktop app 04:48 How SSH configuration works 05:10 Adding the SSH connection in Codex 05:39 Creating a remote project and starting a chat 06:09 Long-running tasks and remote execution 06:26 ChatGPT mobile access 07:03 Using Railway from your coding agent 07:15 Orchestrating multiple cloud agents
8:20

Moving your Coding Agents to the Cloud (ft. Codex Desktop & GPT-6 Astra) 00:00 The limitations of running agents locally 01:13 Parallel development and Git worktrees 02:03 Moving your coding agent to a remote machine 02:25 Introducing Railway Cloud Agents 02:52 Installing the CLI and signing in 03:03 Configuring your project and default agent 03:42 Bringing your agent skills 04:24 Connecting the Codex desktop app 04:48 How SSH configuration works 05:10 Adding the SSH connection in Codex 05:39 Creating a remote project and starting a chat 06:09 Long-running tasks and remote execution 06:26 ChatGPT mobile access 07:03 Using Railway from your coding agent 07:15 Orchestrating multiple cloud agents

Railway

82,044 Aufrufe • vor 26 Tagen

THE 64 MINUTE OPENAI CODEX MASTERCLASS IS HERE if you've been meaning to learn Codex, this is the episode for you, we cover: 1/ Claude vs Codex (what's better?) 2/How to run Claude Code inside Codex (really cool) 3/Why GPT 5.5 changed everything for browser agents 4/How to create skills (reusable agents you build once and call by name forever) 5/How to connect Notion with surgical permissions (one database, not the whole workspace) 6/How to use Remotion inside Codex to create videos 7/ How to one-shot full mobile apps in Swift 8/The 4 projects to run on day one to get up to speed fast shoutout to Riley Brown for coming onto The Startup Ideas Podcast (SIP) 🧃 for the 5th time. every episode he delivers. this one is the Codex masterclass. if you've been meaning to learn Codex, this is the episode. 100% free i just want to see you build your ideas. watch
1:04:40

THE 64 MINUTE OPENAI CODEX MASTERCLASS IS HERE if you've been meaning to learn Codex, this is the episode for you, we cover: 1/ Claude vs Codex (what's better?) 2/How to run Claude Code inside Codex (really cool) 3/Why GPT 5.5 changed everything for browser agents 4/How to create skills (reusable agents you build once and call by name forever) 5/How to connect Notion with surgical permissions (one database, not the whole workspace) 6/How to use Remotion inside Codex to create videos 7/ How to one-shot full mobile apps in Swift 8/The 4 projects to run on day one to get up to speed fast shoutout to Riley Brown for coming onto The Startup Ideas Podcast (SIP) 🧃 for the 5th time. every episode he delivers. this one is the Codex masterclass. if you've been meaning to learn Codex, this is the episode. 100% free i just want to see you build your ideas. watch

GREG ISENBERG

200,125 Aufrufe • vor 5 Monaten

I vibe coded a new product on the side while running Every 🪨—and today we're launching it for free. It's called Proof, and it’s a live collaborative document editor where humans and AI agents work together in the same doc. It’s built from the ground up for the kinds of documents agents are increasingly writing: bug reports, PRDs, implementation plans, research briefs, copy audits, strategy docs, memos, and proposals. It's fast, free, and open source—available now at Why Proof? When everyone on your team is working with agents, there's suddenly a ton of AI-generated text flying around—planning docs, strategy memos, session recaps. But the current process for collaborating and iterating on agent-generated writing is…weirdly primitive. It mostly takes place in Markdown files on your laptop, which makes it reminiscent of document editing in 1999. That’s why we built Proof. What makes Proof different? - Proof is agent-native. Anything you can do in Proof, your agent can do just as easily. - Proof tracks provenance: A colored rail on the left side of every document tracks who wrote what. Green means human, Purple means AI. - Proof is login-free and open source: This is because we want Proof to be your agent's favorite document editor. How we use Proof Every 🪨: - Brandon Gell had OpenAI's Codex write a feature plan in Proof, then tagged my personal Claw (R2-C2) in Slack to review it. R2-C2 left feedback, I added comments, Brandon's agent revised the plan, and then Codex executed on it. Brandon submitted a PR to production without writing a line of code. - Austin Tedesco texts his Claw ideas while he's out on a run, then has it maintain a running Proof doc for his weekly food newsletter. He dictates drafts using Naveen Naidu's Monologue, writes into the outline himself, and uses the provenance gutter to track what's his voice vs. the agent's. - Kieran Klaassen uses it as a lightweight scratchpad for his compound engineering workflow. He brainstorms with an agent in the terminal, shares to Proof with one click, then opens the doc to leave comments and tells the agent to go work on them. His take: Proof's job is to communicate about writing and ideas. Proof is free, open source, and requires no login. I built the whole thing by vibe coding between meetings. I sat down with Brandon, Kieran, and Austin on Every 🪨's AI & I to demo it live and talk about how it's changing the way we work. If you're building with agents and need a better way to collaborate on text, this one's for you. Watch below! Timestamps Introduction and the origin story of Proof: 00:02:00 From Mac app to collaborative web editor: 00:07:24 What makes Proof "agent native": 00:09:00 Live demo—watching an agent join and write inside a shared document: 00:14:30 How Austin uses Proof for creative writing and food journalism: 00:20:51 The challenge of multiple agents editing one document simultaneously: 00:24:30 When AI-written docs are better read by agents than by humans: 00:26:48 Brandon's agent-to-agent collaboration loop: 00:29:30 Proof as a lightweight scratchpad versus existing tools like Notion and GitHub: 00:37:09 Why Proof is open source and what that means for builders: 00:42:18
44:37

I vibe coded a new product on the side while running Every 🪨—and today we're launching it for free. It's called Proof, and it’s a live collaborative document editor where humans and AI agents work together in the same doc. It’s built from the ground up for the kinds of documents agents are increasingly writing: bug reports, PRDs, implementation plans, research briefs, copy audits, strategy docs, memos, and proposals. It's fast, free, and open source—available now at Why Proof? When everyone on your team is working with agents, there's suddenly a ton of AI-generated text flying around—planning docs, strategy memos, session recaps. But the current process for collaborating and iterating on agent-generated writing is…weirdly primitive. It mostly takes place in Markdown files on your laptop, which makes it reminiscent of document editing in 1999. That’s why we built Proof. What makes Proof different? - Proof is agent-native. Anything you can do in Proof, your agent can do just as easily. - Proof tracks provenance: A colored rail on the left side of every document tracks who wrote what. Green means human, Purple means AI. - Proof is login-free and open source: This is because we want Proof to be your agent's favorite document editor. How we use Proof Every 🪨: - Brandon Gell had OpenAI's Codex write a feature plan in Proof, then tagged my personal Claw (R2-C2) in Slack to review it. R2-C2 left feedback, I added comments, Brandon's agent revised the plan, and then Codex executed on it. Brandon submitted a PR to production without writing a line of code. - Austin Tedesco texts his Claw ideas while he's out on a run, then has it maintain a running Proof doc for his weekly food newsletter. He dictates drafts using Naveen Naidu's Monologue, writes into the outline himself, and uses the provenance gutter to track what's his voice vs. the agent's. - Kieran Klaassen uses it as a lightweight scratchpad for his compound engineering workflow. He brainstorms with an agent in the terminal, shares to Proof with one click, then opens the doc to leave comments and tells the agent to go work on them. His take: Proof's job is to communicate about writing and ideas. Proof is free, open source, and requires no login. I built the whole thing by vibe coding between meetings. I sat down with Brandon, Kieran, and Austin on Every 🪨's AI & I to demo it live and talk about how it's changing the way we work. If you're building with agents and need a better way to collaborate on text, this one's for you. Watch below! Timestamps Introduction and the origin story of Proof: 00:02:00 From Mac app to collaborative web editor: 00:07:24 What makes Proof "agent native": 00:09:00 Live demo—watching an agent join and write inside a shared document: 00:14:30 How Austin uses Proof for creative writing and food journalism: 00:20:51 The challenge of multiple agents editing one document simultaneously: 00:24:30 When AI-written docs are better read by agents than by humans: 00:26:48 Brandon's agent-to-agent collaboration loop: 00:29:30 Proof as a lightweight scratchpad versus existing tools like Notion and GitHub: 00:37:09 Why Proof is open source and what that means for builders: 00:42:18

Dan Shipper 📧

33,092 Aufrufe • vor 6 Monaten

"You cannot walk from point A to B inside OpenAI without hearing Codex get mentioned." Here's my new episode with Rohan Varma (Codex PM) on how he uses Codex as his everything app to: → Prototype designs with Image Gen → Turn repeated work into automations → Turn project context into live Codex Sites → Use one Codex thread to manage others Some quotes from Rohan: "[Ask Codex] for something that seems 10x more ridiculous than you ever think it could do. And it probably can do 90% of it." "Over the course of the day, I'm probably doing 3-4x more than I would have without Codex." "For me, every time I do anything I basically think, could Codex have done this?" 📌 Watch now: Thanks to our sponsors: Wispr Flow: 4x faster than typing with your voice Riverside: All-in-one AI studio for podcasts and video
0:29

"You cannot walk from point A to B inside OpenAI without hearing Codex get mentioned." Here's my new episode with Rohan Varma (Codex PM) on how he uses Codex as his everything app to: → Prototype designs with Image Gen → Turn repeated work into automations → Turn project context into live Codex Sites → Use one Codex thread to manage others Some quotes from Rohan: "[Ask Codex] for something that seems 10x more ridiculous than you ever think it could do. And it probably can do 90% of it." "Over the course of the day, I'm probably doing 3-4x more than I would have without Codex." "For me, every time I do anything I basically think, could Codex have done this?" 📌 Watch now: Thanks to our sponsors: Wispr Flow: 4x faster than typing with your voice Riverside: All-in-one AI studio for podcasts and video

Peter Yang

141,629 Aufrufe • vor 3 Monaten

This is crazy, I can talk to OpenAI's realtime API, and it'll respond back with voice, and then help call Codex to help me code! Got curious about Codex and its realtime integration, and found codex's feature flag `realtime_conversation` integrated for the codex app-server. How it works: - launch codex app-server with realtime - connect a client to realtime through WebRTC voice connection - Codex app-server is also attached on the side - talk to realtime - realtime decides whether coding is needed, and responds back with events - Codex app-server takes these events and runs codex agent turns - codex writes code like your codex cli exp Keep in mind OpenAI hasn't released this officially, they're still actively working on it, I just created a fork. This is a completely new UX than the usual chat interface for agentic coding. For example, when the agent responds back in voice, it's actually faster for me to read the response, and I don't actually find voice response that useful unless it does so in the background. But image realtime working in the background, you can talk to it, realtime keeps track of the different agents working on your tasks and your status. More to come on demo side, i'll make a more polished version and include voice, but thought this was cool to share. You can see in the responses the distinction between my voice input, realtime response, and realtime calling Codex to do work!
0:28

This is crazy, I can talk to OpenAI's realtime API, and it'll respond back with voice, and then help call Codex to help me code! Got curious about Codex and its realtime integration, and found codex's feature flag `realtime_conversation` integrated for the codex app-server. How it works: - launch codex app-server with realtime - connect a client to realtime through WebRTC voice connection - Codex app-server is also attached on the side - talk to realtime - realtime decides whether coding is needed, and responds back with events - Codex app-server takes these events and runs codex agent turns - codex writes code like your codex cli exp Keep in mind OpenAI hasn't released this officially, they're still actively working on it, I just created a fork. This is a completely new UX than the usual chat interface for agentic coding. For example, when the agent responds back in voice, it's actually faster for me to read the response, and I don't actually find voice response that useful unless it does so in the background. But image realtime working in the background, you can talk to it, realtime keeps track of the different agents working on your tasks and your status. More to come on demo side, i'll make a more polished version and include voice, but thought this was cool to share. You can see in the responses the distinction between my voice input, realtime response, and realtime calling Codex to do work!

Matthew Lam

17,674 Aufrufe • vor 4 Monaten

Vibe Coding with Codex - Complete Guide Build a Web App, Desktop App & iOS App with Codex + GPT‑5.5 (No Coding Needed, Beginner Friendly) In this video you will learn: > Vibe Coding Basics + Vocab > How to build a web app using Codex > Add db, auth + storage with Firebase > Github Basics > Add AI Features (API's) > Deploy to internet (Vercel) > Convert Web App into Desktop app & iOS App Chapters 00:00 Intro 01:12 Setting up Codex 01:57 The basics of Vibe Coding and Codex 02:20 Projects, Files, App 03:45 Example App - Microsoft Paint 04:25 Running app locally 06:39 Save My Code - Use Github 10:37 Quick Review before building app 12:24 Building a web app - The Prompt 15:32 Creating Web App Project 16:34 Explaining Firebase (Database, Storage, Auth) 18:42 Setting up Firebase Project 22:54 Prompting Codex to build our app 24:49 Inspect Element - Console 26:24 Verify Data being Stored in Database 27:51 Making Changes to App 31:29 Fixing Storage Permissions with Codex 32:20 GPT API - Adding AI to our app 36:20 Making more changes using screenshots 39:02 Queuing vs Steering 40:23 Deploying our app to Vercel (App on Internet) 43:09 Convert web app to desktop app and iOS app 47:15 Web App and Desktop App work Now 48:36 Now let's run the iOS app 50:27 All three apps work! 51:11 Making Changes to iOS app 52:51 Testing agent skill feature of our app 53:55 Summary of what we did
55:24

Vibe Coding with Codex - Complete Guide Build a Web App, Desktop App & iOS App with Codex + GPT‑5.5 (No Coding Needed, Beginner Friendly) In this video you will learn: > Vibe Coding Basics + Vocab > How to build a web app using Codex > Add db, auth + storage with Firebase > Github Basics > Add AI Features (API's) > Deploy to internet (Vercel) > Convert Web App into Desktop app & iOS App Chapters 00:00 Intro 01:12 Setting up Codex 01:57 The basics of Vibe Coding and Codex 02:20 Projects, Files, App 03:45 Example App - Microsoft Paint 04:25 Running app locally 06:39 Save My Code - Use Github 10:37 Quick Review before building app 12:24 Building a web app - The Prompt 15:32 Creating Web App Project 16:34 Explaining Firebase (Database, Storage, Auth) 18:42 Setting up Firebase Project 22:54 Prompting Codex to build our app 24:49 Inspect Element - Console 26:24 Verify Data being Stored in Database 27:51 Making Changes to App 31:29 Fixing Storage Permissions with Codex 32:20 GPT API - Adding AI to our app 36:20 Making more changes using screenshots 39:02 Queuing vs Steering 40:23 Deploying our app to Vercel (App on Internet) 43:09 Convert web app to desktop app and iOS app 47:15 Web App and Desktop App work Now 48:36 Now let's run the iOS app 50:27 All three apps work! 51:11 Making Changes to iOS app 52:51 Testing agent skill feature of our app 53:55 Summary of what we did

Riley Brown

147,902 Aufrufe • vor 4 Monaten

When I talk to serious software engineers, they tell me everyone is sleeping on Codex + GPT 5.2 from OpenAI Which is why I was hyped to get an insiders "how to" from Alexander Embiricos product lead for Codex, showing us how he and the team use Codex to ship almost everything at oai. He'll show us how to: - jump into a new repo and start contributing, even as a non-technical PM - run git worktrees to parallelize agent tasks across codex instances - use best practices and to spec out your work and let codex rip We also talk model vs. harness and how to spy on codex development (which is all OSS!) to understand how to optimize your own implementations. This episode is brought to you by our amazing sponsors 🧠🤑 Brex - The intelligent finance platform built for founders 🦎🐛 Greptile - Your AI code review platform Watch it here:
0:47

When I talk to serious software engineers, they tell me everyone is sleeping on Codex + GPT 5.2 from OpenAI Which is why I was hyped to get an insiders "how to" from Alexander Embiricos product lead for Codex, showing us how he and the team use Codex to ship almost everything at oai. He'll show us how to: - jump into a new repo and start contributing, even as a non-technical PM - run git worktrees to parallelize agent tasks across codex instances - use best practices and to spec out your work and let codex rip We also talk model vs. harness and how to spy on codex development (which is all OSS!) to understand how to optimize your own implementations. This episode is brought to you by our amazing sponsors 🧠🤑 Brex - The intelligent finance platform built for founders 🦎🐛 Greptile - Your AI code review platform Watch it here:

claire vo 🖤

48,134 Aufrufe • vor 8 Monaten

I use subagents for ~80% of my Codex tasks these days. If you're new to subagents, here's a quick primer: - Subagents = separate agents that work on a specific piece of work in a fresh isolated context window. - Your main thread can create subagents and delegate work to them. - Subagents report back when tasks are complete. - Codex subagents are especially useful for read-heavy tasks (e.g research, investigation, and review). - Also useful for testing and building parts of a project in parallel. Subagents are great for working on focused parts of a big task, like planning, implementation, testing, or review. My biggest pro tip for using subagents in Codex: You don’t have to design the entire delegation plan yourself. Just ask Codex to “Use subagents as needed,” and then Codex can then decide where subagents would help it in the task. Here's a demo of using subagents in Codex:
0:42

I use subagents for ~80% of my Codex tasks these days. If you're new to subagents, here's a quick primer: - Subagents = separate agents that work on a specific piece of work in a fresh isolated context window. - Your main thread can create subagents and delegate work to them. - Subagents report back when tasks are complete. - Codex subagents are especially useful for read-heavy tasks (e.g research, investigation, and review). - Also useful for testing and building parts of a project in parallel. Subagents are great for working on focused parts of a big task, like planning, implementation, testing, or review. My biggest pro tip for using subagents in Codex: You don’t have to design the entire delegation plan yourself. Just ask Codex to “Use subagents as needed,” and then Codex can then decide where subagents would help it in the task. Here's a demo of using subagents in Codex:

Avthar

18,444 Aufrufe • vor 1 Monat

Is Claude Code Better Than Cursor? This video is a crystal clear explanation on what makes Claude Code different than Cursor, Codex and Windsurf. A classic whiteboard conversation! Next time he's on the pod (soon) he's going to build an app from scratch that will blow your mind. TIMESTAMPS: 00:00 Intro to Claude Code 00:28 Why Claude Code Is Best 02:38 Comparing Cursor, Windsurf & Claude Code 07:41 Using Claude Code with Other IDEs 12:41 Future of AI Coding Tools & Claude’s SDK 19:58 Integrating Codex with Chat GPT 21:14 Best AI Code Review Tools (Devon, CodeRabbit 26:49 Building an App with Claude Code (Step-by-Step) 35:32 Future Plans
37:07

Is Claude Code Better Than Cursor? This video is a crystal clear explanation on what makes Claude Code different than Cursor, Codex and Windsurf. A classic whiteboard conversation! Next time he's on the pod (soon) he's going to build an app from scratch that will blow your mind. TIMESTAMPS: 00:00 Intro to Claude Code 00:28 Why Claude Code Is Best 02:38 Comparing Cursor, Windsurf & Claude Code 07:41 Using Claude Code with Other IDEs 12:41 Future of AI Coding Tools & Claude’s SDK 19:58 Integrating Codex with Chat GPT 21:14 Best AI Code Review Tools (Devon, CodeRabbit 26:49 Building an App with Claude Code (Step-by-Step) 35:32 Future Plans

Riley Brown

115,852 Aufrufe • vor 1 Jahr

After creating Remodex: Codex remote control for iOS I decided to chill a bit by building a browser sidebar inside Theo - t3.gg 's T3 Code You can open it with Cmd+Shift+B This software is so easy to "manipulate" and build upon Congrats to all the guys that put the work in it because it is great I certainly will be building more things with it For this one I decided to switch from the Codex App to the Codex CLI too just to see how it works And boy it was so good
0:20

After creating Remodex: Codex remote control for iOS I decided to chill a bit by building a browser sidebar inside Theo - t3.gg 's T3 Code You can open it with Cmd+Shift+B This software is so easy to "manipulate" and build upon Congrats to all the guys that put the work in it because it is great I certainly will be building more things with it For this one I decided to switch from the Codex App to the Codex CLI too just to see how it works And boy it was so good

Emanuele Di Pietro

38,905 Aufrufe • vor 6 Monaten

OPENAI 🔥: Key insights from upcoming DevDay sessions. * This agenda is not public yet First, OpenAI will build Platform capabilities inside Codex, enabling users to develop plugins, agents, and apps right from a dedicated DevDay page, which is quite cool! Highlights from the agenda 👀 > Claw Labs "Join Peter Steinberger for a look at how agents can change the way open-source teams build." > 🔥 Codex Game Studio "What makes a game easy for humans but hard for AI? Build one and put Codex to the test." > 🔥 What Will You Build With Coding Agents That Don’t Quit? What engineering work deserves your time and tokens? Learn from a Codex run that spent more than 1,000 hours keeping builds and tests passing in a large shared codebase. See how this internal OpenAI agent had goals, subagents, and persistent plans that helped it investigate failures and coordinate fixes. > Codex Has Left The Laptop "As we move from delegating individual tasks to letting Codex tackle entire problems and goals on its own, it’s possible to harness the power of Codex wherever and however you work. " > From Single Player to Multiplayer with Codex "Follow a 2am outage from the first Slack messages to a reviewed fix and an update for the team." > What Comes After Loops?: Deep Dive Into Agentic Architecture "As models become more capable, agent architectures are changing. We'll trace the evolution from simple loops to collaborating agents, examine the design choices and model advancements behind that shift, and take a deep dive into what comes next."
1:31

OPENAI 🔥: Key insights from upcoming DevDay sessions. * This agenda is not public yet First, OpenAI will build Platform capabilities inside Codex, enabling users to develop plugins, agents, and apps right from a dedicated DevDay page, which is quite cool! Highlights from the agenda 👀 > Claw Labs "Join Peter Steinberger for a look at how agents can change the way open-source teams build." > 🔥 Codex Game Studio "What makes a game easy for humans but hard for AI? Build one and put Codex to the test." > 🔥 What Will You Build With Coding Agents That Don’t Quit? What engineering work deserves your time and tokens? Learn from a Codex run that spent more than 1,000 hours keeping builds and tests passing in a large shared codebase. See how this internal OpenAI agent had goals, subagents, and persistent plans that helped it investigate failures and coordinate fixes. > Codex Has Left The Laptop "As we move from delegating individual tasks to letting Codex tackle entire problems and goals on its own, it’s possible to harness the power of Codex wherever and however you work. " > From Single Player to Multiplayer with Codex "Follow a 2am outage from the first Slack messages to a reviewed fix and an update for the team." > What Comes After Loops?: Deep Dive Into Agentic Architecture "As models become more capable, agent architectures are changing. We'll trace the evolution from simple loops to collaborating agents, examine the design choices and model advancements behind that shift, and take a deep dive into what comes next."

🚨 AI News | TestingCatalog

110,192 Aufrufe • vor 4 Tagen

Laptop closed. Agent still working. 103 legal contracts reviewed in 40 minutes. Most AI agents stop the moment you close your laptop. This one does not. See how DigitalOcean, @chatgptapp Codex, and Box work together to autonomously process a stack of contracts while you step away. The new DigitalOcean Codex plugin makes droplet provisioning a one-click affair. - DigitalOcean: always-on compute for long-running agents - Codex: the harness driving the workflow - Box: the governed content layer (contracts in, review packets out) Timestamps: 00:09 – Workflow setup 01:23 – Provision DigitalOcean droplet for long-running tasks 02:45 – Connect Codex to Box with Box MCP 03:01 – Start a remote session on Codex 03:26 – Implement the legal workflow 05:00 – Review the work 06:05 – Conclusion
6:49

Laptop closed. Agent still working. 103 legal contracts reviewed in 40 minutes. Most AI agents stop the moment you close your laptop. This one does not. See how DigitalOcean, @chatgptapp Codex, and Box work together to autonomously process a stack of contracts while you step away. The new DigitalOcean Codex plugin makes droplet provisioning a one-click affair. - DigitalOcean: always-on compute for long-running agents - Codex: the harness driving the workflow - Box: the governed content layer (contracts in, review packets out) Timestamps: 00:09 – Workflow setup 01:23 – Provision DigitalOcean droplet for long-running tasks 02:45 – Connect Codex to Box with Box MCP 03:01 – Start a remote session on Codex 03:26 – Implement the legal workflow 05:00 – Review the work 06:05 – Conclusion

Box

321,533 Aufrufe • vor 2 Monaten

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:
1:21

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 Aufrufe • vor 3 Monaten