Almost every single person @every is freaking out about how good voice mode in ChatGPT for Work is Have not seen vibes this high in a while. If you haven’t tried it yet, you should

not surprising that @OpenAI is firing on all cylinders right now, and it’s an unbelievably interesting story - they launched GPT-5 summer of 2025 and positioned it as a pair programmer. we wrote at the time @every that they completely missed the new agentic coding that was starting to happen inside of Claude Code. they bet on agentic coding in the browser / vms and vibe coding in ChatGPT but it was too early - a small team broke off and began working on a separate Codex model line and product. didn’t have to serve the gigantic customer base of ChatGPT, and by November / December of 2025 with 5.3 it was clear they were starting to make something good and the progress was fast - Codex Desktop app launched in Feb and was just clearly superior. there’s a weird late comer advantage sometimes in AI because you get to skip to what works instead of your product having the scars of new capability improvements being bolted on every 3 months - Codex started getting popular it was clear it was a thing, and needed to get merged back in. Which they did, imo quite well—a super complicated thing that would’ve been very easy to screw up. most companies try to disrupt themselves and fail. OpenAI somehow figured out how to disrupt their main product, and then merge it back in seamlessly. incredible aura

Even when things are going great, running a $1.5 billion AI startup is a knife fight. @MeetGranola was one of the first AI apps of this generation to achieve near-ubiquitous adoption. But meeting notes are not the company’s be-all and end-all. The real battle is over owning the interface that everyone uses to get their work done in an AI-native world. I had Chris Pedregal (@cjpedregal), cofounder and CEO of Granola, back on @every’s AI & I to talk about the current state of the application layer, AI’s frontier, and the future of work. We get into: - Why meeting notes clones don’t matter. Three big companies cloned Granola’s core feature. To him, meeting notes were never the real prize. “Easy come, easy go” is his view of anyone’s lead, including his own. - How he thinks about building proactive features in AI. Granola pre-generates millions of pre-meeting briefs, which include context on the nature of the meeting and people participating, that most people never open. But when they do, they have a magical experience. - Why Granola is betting on “bring your own agent.” Chris says the API and MCP will get “a lot better” over the next few months, and we talk about their agent-native strategy and why they’ve pushed the product that way. This is a must-watch for anyone building at the application layer. Watch the episode! Timestamps Introduction: 00:00:59 Why running a company is a knife fight even when it’s working: 00:01:57 Granola’s counterintuitive view on competition: 00:04:33 Dan’s “pirate and architect” model for early-stage product teams: 00:10:44 Granola’s “shaping” and “validation” phases for building features: 00:13:09 Why Dan lives almost entirely inside Codex: 00:18:17 The case for “Codex-native apps”: 00:24:40 Granola’s “handrail” philosophy: 00:35:37 Why Granola is going all in on winning meeting-adjacent context: 00:38:12 What a transcript alone can never capture: 00:44:19

if you are reading @every, you knew codex was about to take off 6 months ago :) success kid pointing to when i started getting extremely, absolutely, annoyingly codex pilled and we began covering it

BREAKING: Introducing All Access from @every, our new membership tier for the best builders in AI All Access subs get the Builder Pack which includes $7,000 in credits and free usage to the models + tool stack we use @every. All Access subscribers get: - $1,000 in Codex / @ChatGPTapp for Work credits - 12 months free of @Cursor_AI Pro+ - $4,000 in @PostHog credits including self-driving to automatically fix bugs and identify issues in your production app - 1 year free of @Framer - 6 months free of @NotionHQ And much more! (Did I mention $1,000 in Codex credits? It's time to build!) Get all access: Why All Access and the Builder Pack This is the best time in history to build something. For a long time, it’s been possible to one-shot impressive demos, but they’d fall flat the minute they hit production. But the release of GPT-5.6-Sol and Fable 5 heralds a new era: Everyone can build, launch, and maintain the software that they’ve always dreamed of. Everyone is a builder now. There’s just one catch: Building with AI is very expensive. (Ask me how I know.) (Alright, I’ll tell you. I accidentally used 2 billion tokens overnight this week on a big GPT-5.6-Sol run. Worth it.) This is unique in the history of technology. For most of the personal computing era, a billionaire and a solo builder could buy essentially the same top-of-the-line Mac. AI changes that: The more tokens you can afford, the more you can make. And we want to make that accessible to more people. That’s why the main feature of our new All Access plan is the Builder Pack: more than $7,000 in credits and discounts on the full stack we use to run Every, from idea to production—Codex, Claude, PostHog, Render, Gemini, FLORA, and more. Early-bird membership is only $500/year for the next 24 hours—and the Codex credits alone are worth $1,000. (I could’ve used it for my overnight run this week.) Now we’re handing it to you. Get all access: Meet the Builder Pack It's got more than $7,000 in offers from 10 of the AI products we use to write, design, build, and run @Every: BUILD - $1,000 in Codex credits plus one month of ChatGPT for business - Twelve months free of Cursor Pro+ - One month free of @Claudeai Max - Three months free of @Google AI Pro DESIGN - One year free of @Framer Pro - One month free of @floraai Max HOST - $300 in @render credits IMPROVE - $4,000 in PostHog credits - Six months free of @Notion Business - Six months free of @AgentMail We rely on these every day, and we tried to put together a package that helps you comprehensively for each part of the process of building and running software in AI. What comes with All Access - Everything in an existing paid Every membership: our daily writing, guides, camps, and software like @usemonologue, @CoraComputer, @SparkleApp, and @TrySpiral - The Builder Pack, with more than $7,000 in partner offers - Unlimited email accounts use of Cora and unlimited Spiral usage - Members-only programming with me and the Every team and me Get All Access:

Yesterday, GPT-5.6 Sol Ultra became generally available. Today, I'm sharing that I accidentally spent 2b tokens overnight and I didn't even solve a 50-year-old math conjecture. This is extremely cool though, skill issue on my part clearly

BREAKING: GPT-5.6 Sol is out—AND Codex has been merged into ChatGPT Desktop as ChatGPT Codex. This combo model and desktop app harness are the gold-standard for knowledge work in AI. 5.6 is powerful, fast, half the price of Fable, and my default for almost everything. We’ve been testing it internally @every for about a month across coding, writing, design, and knowledge work. Here’s our day-zero vibe check: - An A-tier coder—but it’s not Fable. Sol scored 56/100 on our Senior Engineer benchmark compared to a 91 for Fable. I think the 56/100 undersells it, it's an excellent implementor, and very smart. But Fable just writes conceptually cleaner code and works better at the top end of task complexity. PRO-TIP: Use GPT-5.6 as Fable's subagent for the most goated combo in AI coding. - The best writer of the frontier models. It’s clearer and more concise than Fable or Opus 4.8, without the overexplaining or weird private language. It can one-shot marketing emails, help you workshop taglines, and explain complex concepts clearly. It's also super fast, which makes it easy to collaborate with. - Design is better, but not top-tier. It has noticeably more taste than 5.5, but Fable and Opus 4.8 are still playing at a different level. See examples in the video and vibe check below. - The real leap is knowledge work. Sol is the first model I’ve trusted to run whole loops of knowledge work—not just help with individual tasks. I use it to process email, surface decisions from meetings and Slack, find job candidates, scan Facebook Marketplace for furniture, and log my meals. It has shifted my job from doing the work to tending the system that does it. - The merged app is fine. I was extremely worried about this because I love the Codex app. OpenAI was caught in an interesting position: How to make an agent orchestration app for regular ChatGPT consumers, coders, and businesses all in one app. They now split the interface between ChatGPT Work and ChatGPT Codex. They're basically the same except Work hides code. And "Chat" has been demoted to 2nd tier status for quick questions in either one. It's not a big leap, but it's not a huge setback either. And it remains my favorite of the desktop agent orchestration apps. Verdict: If I really had to put my finger on it, I'd say Fable has way more big model smell. But that means it's a skill in itself to get value out of it—99% of people are still not there yet. GPT-5.6 is almost as powerful, but is easy to use, fast, and relatively cheap. It should give you an early sense of where model work is going. Full @every Vibe Check:

GPT-5.6 is the first model I’ve used that can reliably run whole loops of knowledge work, not just help with individual tasks. Your job shifts from doing the work to tending the system that does it. I use it to run loops that autonomously 1) do my email 2) help me find new hires for @every 3) keep me up to date on key decisions in all internal meetings / slacks @every 4) scan facebook marketplace to help me find furniture for my apartment

You don't know what you have until you lose it. We've been testing GPT-5.6-Sol for about a month @every. We briefly lost access for about a week, and I felt like I was back in the stone age. Even with Fable access. It's just such a good daily driver. Allows me to delegate so many knowledge work tasks (like email) in a way that no other model can.

GPT-5.6 is a much better writer than Fable. It consistently one-shots marketing emails for @tedescau that every previous model would fail at. Fable is too verbose and liable to fall into using sentences in its own private language. If you use AI for writing, 5.6 is a fantastic model for you.

GPT-5.6 is like a Porsche, Fable is like a warp drive. We've been testing internally @every for about a month. And GPT-5.6 is the best combination of power, speed, and performance for your day to day knowledge work and coding. Fable is a different beast. If you need to get across the galaxy use Fable. If you need to get around town using the best available tool for the job, use 5.6 Full vibe check dropping tomorrow!

.@NataliaZarina 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

We’ve automated every single thing we can @every with AI agents. And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3. I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI. After Automation: