Our Vibe Check of a model that answers in probabilities, the computer chores our agents do for us now, and a workflow for making a solid deck with AI.
Today, head of evals Mike Taylor：https://every.to/@mike_2114 published a Vibe Check of TypeSafe’s Jev：https://every.to/also-true-for-humans/mini-vibe-check-typesafe-s-jev-judged-everything-i-ve-written-in-0-7-seconds , a new kind of model that responds to a fuzzy question with a probability rather than prose, letting your code act on the result directly. It can’t compete with a frontier model on capability but is fast and cheap enough to check work while it’s being done.
Mike is also the reason today’s issue is focused on computer use: Astra ’s ability to operate apps by clicking, typing, and scrolling changed his mind about the model. Later, we explain why that happened, how the rest of the team harnesses computer use to check off tedious items on our to-do lists, and how to use AI to create a slide deck that looks the way you want it to.
When we published our Astra Vibe Check：https://every.to/vibe-check/gpt-6-astra-vibe-check on September 3, Mike rated the model a yellow, which means “It’s okay, but I wouldn’t use it every day.”
“I’ve been using it for a few days and haven’t run into a single problem, but I also haven’t run into anything I couldn’t get from Fable 5.1：https://every.to/vibe-check/fable-5-1-vibe-check so far,” Mike wrote in his review. “The computer use seems much faster, but I feel like I’ll need to change the way I work to fully take advantage of that.”
Less than two weeks later, Mike had changed his mind and was “starting to believe that Astra is AGI.”
What caused the about-face? Two words: computer use.
The model handles tasks on his computer so quickly and capably that “I finally reach for it for every single task,” he says. He started small with one assignment, filling in forms for his daughter’s school, and watched it to see how it performed. That gave him confidence to try more ambitious tasks like making Google Slides deck updates and video edits. It nailed every job he fed it, and he now defaults to Astra in Codex for work he previously didn’t delegate to AI. Mike still prefers Fable 5.1 for writing and certain design choices, but day to day, the benefits pale beside Astra’s usefulness.
Recently, Mike handed Astra six presentations for his prompt engineering course. Astra added new screenshots and assets directly in Google Slides and made hundreds of tiny edits. Mike barely had to intervene.
Then he gave Astra a more tedious assignment: Check every link in the PDF proofs of his new book. Astra opened each destination, checked that the page loaded and matched the surrounding text, and compiled a spreadsheet of problems.
Before Astra, Mike steered agents away from computer use because it was too slow and clunky. Now, he’s handing work over to it. “Astra reminds me that AI can do a lot more of my work than I expected.”
None of these tasks are especially difficult. They’re just annoying enough that humans routinely put them off. Computer use turns “I should probably do that” into “I’ll ask the agent to do that.”
Every’s head of marketing Douglas Brundage wants every presentation, even internal ones, to look good.
“I’ve been a slide jockey my whole career,” he says. That used to mean spending hours formatting a single slide deck.
Now when he needs to create a presentation, he’ll design a few slides himself and ask Codex to build the rest of the deck directly in Google Slides, relying on computer use to click, type, and format each slide to match his templates.
Step 1. Give Codex a design to emulate. Douglas usually makes a few example slides himself: an opening slide, a section break, and layouts for text, images, or graphics. This gives Codex concrete references.
Step 2. Determine what you want each slide to say. He works with Codex on the copy and usually supplies images. For a recent presentation, he pointed Codex to illustrations he’d collected in Figma and asked it to insert one on each section break.
Step 3. Have AI do the heavy lifting. Once the text for each slide is ready, he asks Codex to open Google Slides and build the presentation, using his example slides as templates. The agent clicks and types in the app to add the text, place images, and format the deck. Douglas reviews the first pass. Codex makes mistakes: In one deck, it crammed 30 examples onto a single slide. Still, the mistakes are easy to fix. Douglas either makes small formatting updates himself or tells Codex what to change.
Step 4. Show it your edits. Douglas reviews and edits the finished deck in his browser, then sends it back to Codex. He asks it to turn the changes into rules and add them to his writing skills, or the saved instructions he’s building to help Codex write more like him.
Try it this week: Design two or three reference slides for an upcoming presentation, generate slide copy with Codex, and have it build the entire deck in Google Slides using your examples. Review the results, make changes, and have Codex save those instructions to avoid the same issues next time.
Four weeks ago, we launched Thesis Statements：https://every.to/thesis-statements?utm_cta_source=post_POSTID_post_body_thesis_statements_1, a collection of specific, contestable claims from builders and thinkers about the future of great human work with AI.
This week, we have six more predictions from people at the frontier:
If you want to help decide what matters in the future of AI and human work, think creatively, and build what comes next, join us at our inaugural Thesis: 2027 conference：https://every.to/thesis-2027?utm_cta_source=post_POSTID_post_body_thesis_2027_conference_1 on November 5, 2026.
Everyone’s a builder now. Every All Access：https://every.to/builder-pack gets you the full membership plus the Builder Pack—$9,000+ in credits for the tools we build with.
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Aioga 编辑摘要
Aioga 编辑摘要：对一款以概率形式作答的模型进行 Vibe Check，并实测 AI 智能体目前能替用户完成哪些电脑杂活，同时给出一套用 AI 做出靠谱演示文稿的工作流。 Aioga 将其归入「行业动态」方向，重点关注它对真实使用和行业竞争的影响。
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