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Laura Entis is a staff writer at Every.
Plus Claude joins Slack, and design gets its own AI tells.
Our team has customized workspaces to get the most out of Codex. Pick one and dive in.
Plus: Why intent beats volume, a new AI productivity status metric, and a tool for squeezing the most out of cheaper models
Plus: Granola’s founder on why starting a company is a 'knife fight,' AI enters the C-suite, and who we’re following on X
Use them intentionally, or they could make your AI worse
Plus: OpenAI’s Codex playbook, a trick to cut Fable’s token spend, and the models the team is using this week
An exclusive look at how OpenAI’s infrastructure team is adapting to a flood of AI-generated code
Plus: Buzz enters the chat, a tool for protecting against Sol 5.6’s tendency to delete stuff, and a deep pull from our podcast archive featuring Wired cofounder Kevin Kelly
Plus: Paper and Mobbin join Every’s Builder Pack—now with $9,000 in free credits
A practical guide for using voice to build tools, patch bugs, write articles and generally get more done
Plus a workflow for managing agents while doing the dishes, why AI needs to be more social, and who to follow on X for design inspiration
Plus: AI dictation etiquette, Microsoft’s vision for the agentic web, and the models we’re reaching for this week
Plus: How AI helped build the Thesis website, an alien companion bringing in $4 million a year, and why the future of harness engineering is doing less
Plus: We unpack LLM watermarks, a Codex editing workflow, and the week’s AI news
Plus: A star investor admits to using AI on his op-ed, a self-improving Codex skill, and the hedge fund where AI use is mandatory
Five professional writers share how they use AI, where it disappoints them, and what they still insist on doing themselves
Why we’re building personal benchmarks for every employee, and how to start testing AI against your standards
Plus: Mike's 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
When expensive experimentation is worth it and when to rein in your tokenmaxxing
Why the classification model is blowing up your timeline, how to turn subjective questions into Jev checks, and the dawn of intent-based software
Laura Entis
Naveen Naidu