Opus 5.5 and Sol Split the Team

Hello, and happy Sunday. Three new models dropped this week, and we Vibe Checked each: Opus 5.5 pulled several of our team members back to Claude, GPT-6 Sol is Dan Shipper’s new daily driver, and Grok 4.7 won back one power user (but no one else). Later, Steal these gathers the week’s workflows: Mike Taylor on benchmarks and writing, Jack Cheng and Douglas Brundage on Jev, and Becky Isjwara on video. Some housekeeping: Micah Rich leads a prompting workshop on Friday, October 2, and Thesis: 2027 is down to its last tickets.—Kate Lee

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Vibe Checks

Two models came out on Tuesday and another on Monday. Here’s our verdict on each.

“Vibe Check: Opus 5.5 Is Pulling Our Codex Converts Back to Claude” by Katie Parrott/Vibe Check: Katie and the team found Opus 5.5 matched or beat Fable 5.1 on product and design work at 60 percent less per token—enough to become Kieran Klaassen’s new daily driver and to tempt a few Codex converts back to Claude. There are still two significant tradeoffs: Opus buries the point in prose and will run for hours unless you set a budget.

“Vibe Check: GPT-6 Sol vs. Opus 5.5” by Dan Shipper/Vibe Check: Dan’s verdict: Sol if you want a fast, cheaper daily driver in Codex that leads with the main idea. Opus 5.5 if you’re willing to pay more for ambitious coding and visual work, like the webcam heart rate monitor it built and Sol couldn’t finish.

“Mini-Vibe Check: Grok 4.7” by Laura Entis/Context Window: Mike, Kieran, and Tyler Nishida were already testing Grok 4.7 for a Vibe Check when it was released on Monday, so on Thursday we ran a short version. It won back Tyler, who finds it cheap and steerable enough to be his daily driver again, but no one else: Kieran won’t consider it next to Opus 5.5, and Katie found its writing had no rhythm or feel for the reader.

Steal these

Nine workflows to use from this week’s four how-tos:

Build a benchmark for your own job

From Mike Taylor’s “How to Create Your Own Personal AI Benchmark”

Start with the tasks AI got wrong. Mike has his coding agent search the past month’s sessions for 10 tasks that needed heavy back-and-forth or were abandoned, then runs them on several models and compares the outputs side by side. The prompt
Turn taste into tests. Mike dictates what he liked and disliked about each output and has the model turn that into yes-or-no checks on a reusable grading rubric. The method
Validate your benchmark. To get from a private test to a defensible benchmark, Mike saves every brief, output, and round of feedback into a skill per task, so each skill accumulates 20 or more cases alongside a gold star example and an eval script. The folder structure

Write with AI without losing your voice

From Mike Taylor’s “Good Writing With AI Starts Before the Prompt”

Think before you prompt, and judge after the draft. Mike’s 12-step process for writing with AI cuts a day of writing to less than two hours by having him come up with a title, gather sources, and spitball in Monologue before a model drafts; after picking what he likes most from each version, he writes the ending and debates the finer points with his editors himself. The process
Watch it happen. On Thursday, Mike, Katie Parrott, and Jack Cheng wrote and edited with AI on camera to close our How We Write Now series. The recording

Put Jev to work

From Laura Entis’s “How to Get the Most Out of Jev”

Hand Jev the snap judgments. Mike’s rule of thumb: If a person could make the call in less than 10 seconds—sort this email, flag this phrase—send the task to Jev, and save anything slower for a language model. Here’s why
Turn a fuzzy question into checks. Jev can’t answer a subjective question like “Is this urgent?” until you define the term, so the workflow has your agent interview you, turn the definition into yes-or-no checks Jev can score, and test them against items you’ve already judged. The steps
Copy a demo off X. Douglas Brundage gave a Jev demo to the Grok bot that writes his morning news scan and asked, “Can you just do this?” The bot now reviews more than 500 posts a morning, including ones he never saw on X. The prompt

Turn an article into a video

From Laura Entis’s “Why Evals Are So Hot Right Now”

Storyboard before you animate. Becky gives Claude an article URL, approves a still image storyboard in the cover’s colors, has Hyperframes turn it into an 18-second clip, and fixes it scene by scene in the preview. The steps

Knowledge base

“Why Evals Are So Hot Right Now” by Laura Entis/Context Window: Nearly half of the product management openings Lenny Rachitsky shared last week ask for experience writing evals, and Nityesh Agarwal explains why: Models are capable enough now that speed, price, and taste decide which one you use. A personal benchmark is how you know whether a release changes anything for you. Also inside: Willie Williams on why Slack agents are the new websites.

“Copilot Gets a Seat in the Org Chart” by Ryan Sloan: Ryan Sloan went to Microsoft’s launch in Redmond, Washington, and tried the new Copilot, which folds chat, code, Office, and a persistent agent called Autopilot into one app that has your documents, conversations, and permissions. When he asked Copilot to move a table from Word into Excel, it found both files and said it lacked permission to edit the workbook: The IT controls that make it trustworthy inside a company can also stop it from doing an ordinary task.

Thesis Statements

Read five more predictions from frontier builders and thinkers in Thesis Statements, a collection of specific, contestable claims about the future of great human work with AI.

AI will have rules, but those rules will constantly be shifting by Drew Breunig, CEO and cofounder of Cmpnd
We’ll be assessed on what we can defend, not what we can produce by Sean Campbell, director of AI integration for the MBA program at George Fox University
The time spent in the details is an investment in having the next good idea by Geoffrey Litt, design engineer at Notion
Intelligence will live in your pocket, not a data center by Daniela Rus, director of MIT’s Computer Science and Artificial Intelligence Laboratory
Every token will be connected to a budget, an owner, or an outcome by Arielle Shipper, head of operations at Every

Join us at our inaugural Thesis: 2027 conference on November 5, 2026. Fewer than 50 tickets are left.

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Get hands-on with how Every uses AI. At these live camps, workshops, and meetups, team members teach our workflows.

Upcoming workshop

AI Foundations: Prompting Is a Thinking Skill: Friday, October 2, 12–1 p.m. ET, virtual. Micah Rich leads a guided weekly planning exercise on what to tell AI, how to move the conversation forward, and how to judge whether the answer is any good. No coding experience required. Register.

That’s all for this week. Follow Every on X at @every and on LinkedIn.

Thanks to Eleanor Wikstrom for editorial support.

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