BREAKING: Introducing the @Every Agent—an agentic coworker in Slack built to help you AI-pill your company. It comes with: - Everything you'd expect from a premium company agent. You can delegate difficult, long-running—like opening PRs, writing reports from large datasets, and monitoring social or customer feedback—and get high-quality results all from Slack - Every's best workflows, pre-installed and always updated. Compound Engineering to Compound Writing. We add more all the time. - Personalized Frontier Alerts. to help you keep up with new models. When we drop a Vibe Check, the Every Agent will read it and let you know if the new model is relevant to your workflow. - Zero markup on tokens. What we pay is what you pay—as token prices go down, so does your bill. You can try it today with $15 in free credits per person, up to $500 per workspace. After that: it comes with your $30/month Every subscription, plus tokens at cost. Add the Every Agent to Slack: Why it's hard to AI-pill your coworkers If you’re the AI-pilled one at work, you know the problem: you discover something incredible in Claude or Codex, but getting your coworkers to try it is another matter. The problem is that most of your AI use is invisible. You do it alone, in a terminal or a chat window. Your coworkers see the finished report or the five new ads, but they never see the request that produced them, or the corrections you made along the way. When you describe it afterward, it sounds like magic, but nobody learns a magic trick without seeing how it’s done. Why a company agent, in Slack, solves this problem When you use a company agent like the @every agent you go from prompting in private, to prompting in public. In a Slack channel, a coworker who would never open a terminal scrolls past a thread with your agent interaction and thinks: I could do that too. This lets you show instead of tell your coworkers about your discoveries. New AI tools and workflows then spread naturally and virally across your organization. That's why we made the @every agent for ourselves—and why we're releasing it to you today. Add the Every Agent to Slack:

The new “Dot” in @usemonologue by @every might be the biggest quality-of-life upgrade to my workflow in a long time. It’s also, somehow, my favorite little piece of UI on the entire Mac. Tiny dot. Ridiculously good product design. I’m addicted.

my interview with @sama: • how he uses dots to manage @OpenAI and reduce his screentime • his default speed setting (ultrafast!) • how AI might bring about a new renaissance

Monologue for Mac v1.5.1 is out with lots of small quality of life improvements. Faster dictation, easier Notes search, more control over shortcuts, and fixes for note uploads, meeting detection, and the Dot. Update Monologue to try it.

.@usemonologue now runs on it's own model and it's really good. 100ms median API response time and ~7% word error rate. That's better than every provider's models. The software is amazing, especially if you're an AI pilled builder, and now the model is too.

We wanted dictation to be both fast and accurate. We couldn’t find a model that met that bar, so we trained and host our own. Nearly six months later, we’re proud to share it and open access through our enterprise API.

Introducing mono-1, our in-house dictation model, built to turn natural speech into text you can use. Against our previous API-based pipeline, mono-1 required about 55% fewer estimated edits and delivered finished dictation 3× faster by median API response time. Accurate speech recognition is the foundation of good dictation. But good dictation also needs to handle corrections, formatting, context, and writing preferences. mono-1 is the culmination of six months of development, production testing, and feedback from Monologue users—improving how Monologue recognizes your words, handles corrections, and formats your writing. More here:

BREAKING: Anthropic just dropped Opus 5.5—and it’s pulling some of our recent Codex converts back to Claude. We’ve been testing it at @every across coding, design, writing, and knowledge work. It sometimes beats Fable 5.1 in our testing and is up to 40% cheaper than Opus 5. It's a strong contender for new daily driver model: It’s excellent at end-to-end builds that match your taste. I’ve started reaching for Opus over Fable on big, end-to-end coding projects. And @kieranklaassen is replacing Fable 5.1 with Opus for his day-to-day product work. He calls it his new favorite model. It produces legible prose, but still trails Astra on writing tasks. Opus 5.5 scores a 68.42 on reading ease—the highest on any model we've tested. But in my writing benchmark tests it consistently buries the main point in intro paragraphs, and revisions. You'll be able to understand what this model is saying (yay!) but for day-to-day writing it's still behind. The economics are striking. Anthropic says Opus 5.5 will cost $5 per million input tokens and $20 per million output tokens. That’s the same input price and 20% less for output than Opus 5’s $5/$25. Altogether it should save roughly 40% on costs than Opus 5. It still has a “do the most” problem. @hammermt tested it on our standard knowledge work benchmarks, and it's results were great when thye came back. On at least one test it ran past the 10 minute time limit before delivering. Net Result: If you build apps and interfaces, try it. It’s become my go-to for ambitious coding projects. I’m still roughly 80/20 Codex versus Claude in day-to-day use, and I still prefer Sol and Astra for editing. But I’m spending far more of my tokens with Claude than I was a week ago. State of Play: Codex is still the better harness for me, but Anthropic is steadily gaining ground. They have a history of making their smaller models perform better than their bigger ones (Sonnet 3.7 for example) and they seem to have done the same with Opus 5.5. Full vibe check will be on @every soon!

Opus 5.5 is the model for people who do actual work: build products, write code. - It's good from low effort to max. Higher effort goes deeper, not wider. Lower effort leaves space for you to fill in, which I love. - It uses fewer tokens than the last Opus and doesn't run in circles like Opus 5 did. - It's easier to steer than Fable in some cases. - It can run for a long time, but in-the-loop work is where it feels special. I think this is the model that brings the next wave of people into AI, the way 4.5 did.

A year ago today, we launched monologue There’s so much we want to build, and I’m excited to keep working on it To everyone who’s used it, shared it, or told us how to make it better: thank you! Here’s to year two 🚀

Introducing OpenRouter for tools ⚒️ Old world: SaaS bundles priced for humans. $139/mo, and you don't even know what's in the box. New world: agents don't care about vendors. They want the best API for the task - and to pay for the result. - 2,600 agent-friendly tools: seo/geo, social, leads, ads... - search by task: see price/request/response, call it - pay per call, no subscriptions - 0% markup - Open-source Try it here: