AI & I

While walking to the office, our COO Brandon Gell had his AI agent call him and go over his emails in his inbox one by one. When he arrived, he opened Gmail and confirmed she'd done everything he'd asked. "My jaw is on the floor," he messaged me.
That was the moment Every got serious about setting up each employee with their own agent. Today, it's a reality—and it has completely changed how we work.
Dan Shipper talked to Every COO Brandon Gell and head of platform Willie Williams for Every's AI & I about what happens when everyone at a company gets their own AI sidekick. 
If you found this episode interesting, please like, subscribe, comment, and share!
To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe 
Follow him on X: https://twitter.com/danshipper 
Visit https://scl.ai/dialect to learn more about Dialect, a new system from Scale AI.
Timestamps:  
00:00 Introduction
00:02:21 How Brandon built Zosia, an AI agent to run his household
00:07:09 Brandon's aha moment re: using agents for work
00:09:39 What happened when everyone on the team got their own agent
00:12:42 How agents take on their owners' personalities, and why that matters inside an org
00:23:51 Why it's important for agents to do work in public
00:30:51 What we're still figuring out when it comes to agent behavior, including memory gaps, group chat etiquette, and the "ant death spiral" problem
00:40:45 How we built Plus One, our hosted OpenClaw product
00:47:27 The cultural shift required to make agents work at scale

Founded in 2019, Linear is the rare company started pre-ChatGPT to have successfully reinvented itself as an agent-native business.
On this episode of AI & I, Dan Shipper sat down with Karri Saarinen, cofounder and CEO of the product management tool, to discuss building a platform where humans and agents develop software together—and why the "SaaSpocalypse" isn’t coming for all SaaS companies. 
If you found this episode interesting, please like, subscribe, comment, and share! 
To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe 
Follow him on X: https://twitter.com/danshipper 
Visit  https://scl.ai/dialect to learn more about Dialect, a new system from Scale AI.
Timestamps:
0:00 Introduction 
2:00 Why Linear waited to ship AI features instead of rushing to chatbots 
5:06 Linear's agent platform and becoming the system that guides AI agents 
7:42 Why "SaaS is dead" is a simplistic narrative 
12:18 How Linear adopted AI coding tools
17:45 AI's impact on product building workflows—speed versus thoughtfulness 
22:18 The value of conceptual work and thinking before shipping 
29:30 How AI is reshaping Linear's product strategy  
37:18 Demo: Linear's agent skills, shared context, and code review workflow 
47:48 The future of product development and the enduring role of human judgment

Mike Krieger built one of the most consequential consumer apps of the last two decades as cofounder of Instagram. He is now at the frontier of determining what makes a breakout AI-native product as co-lead of Anthropic Labs.
Dan Shipper talked with Krieger for Every’s AI & I about how his experience creating Instagram shapes how he thinks about building with AI, including what can be sped up and what remains stubbornly time-intensive. 
If you found this episode interesting, please like, subscribe, comment, and share! 
To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe 
Follow him on X: https://twitter.com/danshipper 
Download Grammarly for FREE at grammarly.com
Timestamps 
Introduction: 00:01:39
What's gotten easier—and what hasn't—about building products in the age of AI: 00:02:33
Why vibe coding creates "indoor trees": 00:05:00
How rewrites have become a normal part of the development process: 00:09:00
What "agent native" product design means: 00:11:39
How Mike's labs team is structured and the cofounder model: 00:24:27
The best signal for a product bet is someone with "break through walls" conviction: 00:29:33
Navigating enterprise customers while keeping pace with rapid AI change: 00:38:51
OpenClaw, personal agents, and the product question defining 2026: 00:40:54
Links to resources mentioned in the episode:
Mike Krieger: https://x.com/mikeyk 
Agent-native architecture: https://every.to/guides/agent-native

Kate Lee has spent her career working with words—first as a literary agent, then in roles at Medium, WeWork, and Stripe. As Every’s editor in chief, she’s been the quiet force behind the newsletter for more than three years. 
Lately, something has shifted in Kate’s work. After years of watching her colleague Dan Shipper evangelize AI from the front lines, Katie has started rewiring how she works and is integrating more and more AI tools in her work. 
We had Kate on to talk about her career path from book deals to tech startups, what it really means to run a newsletter as a small team in the age of AI, and what she thinks the bottleneck to automating copyediting is. Plus: the story of pulling off reviews of two major model releases in 24 hours, and how she’s using her AI-powered browser to help her hire. 
To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe 
Follow him on X: https://twitter.com/danshipper 
Timestamps
0:01 – Introduction and Kate's early career as a literary agent
4:45 – From book publishing to tech: Medium, WeWork, and Stripe Press
12:00 – How Kate joined Every and what made the role click
27:00 – What it's like to be a knowledge worker at the frontier of AI
31:00 – The “aha” moment: using AI to manage hundreds of applicants
36:24 – How Every's editorial team uses AI to enforce standards and train taste
45:06 – Publishing two reviews of major model releases on the same day
51:39 – What automating copy editing requires
Links to resources mentioned in the episode:
Proof: https://www.proofeditor.ai/

Every has unveiled a new product, built by CEO Dan Shipper. It's called Proof, a free, open-source, live collaborative document editor built for humans and AI agents to work in together. 

Proof started as a Mac app designed to show the provenance of AI-written text—purple for AI, green for human. But when Shipper rebuilt it as a web app with real-time collaboration, something clicked. Suddenly, everyone at Every was using it for everything from planning docs, to creative writing and even daily to-do lists. The team realized they needed a lightweight space where their OpenClaw agents and humans could co-author documents and leave comments. 

In this special episode, Shipper is joined by Every chief operating officer Brandon Gell, Cora general manager Kieran Klaassen, and head of growth Austin Tedesco to demo Proof live and share how it's changed the way they work. Brandon walks through a loop where his Codex agent writes a plan, Dan's personal Claw R2-C2 reviews it, and the humans just steer. Austin explains how he uses Proof to write a weekly food newsletter, texting ideas to his Claw on runs and watching an outline take shape. And Kieran makes the case that Proof's power is its lightness—just a link you can hand to any agent or colleague.

The conversation covers what "agent native" means in practice, why AX (agent experience) matters as much as UX (user experience), what happens when 10 agents edit one document at the same time, and why some writing is now better read by an AI than a human.

If you found this episode interesting, please like, subscribe, comment, and share!

Want even more?

Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It's usually only for paying subscribers, but you can get it here for free.

To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe
Follow him on X: https://twitter.com/danshipper
Get started building today at http://framer.com/dan for 30% OFF a Framer Pro annual plan.
Download Grammarly for free at Grammarly.com 

Timestamps 
00:02:00 — Introduction and the origin story of Proof
00:07:24 — From Mac app to collaborative web editor
00:09:00 — What makes Proof “agent native”
00:14:30 — Live demo: watching an agent join and write inside a shared document
00:20:51 — How Austin uses Proof for creative writing and food journalism
00:24:30 — The challenge of multiple agents editing one document simultaneously
00:26:48 — When AI-written docs are better read by agents than by humans
00:29:30 — Brandon’s agent-to-agent collaboration loop
00:37:09 — Proof as a lightweight scratchpad vs. existing tools like Notion and GitHub
00:42:18 — Why Proof is open source and what that means for builders

Links to resources mentioned in the episode:
Proof Editor:⁠ https://proofeditor.ai⁠
Proof GitHub repo (open source):⁠ https://github.com/EveryInc/proof⁠
Every's compound engineering plugin:⁠ https://github.com/EveryInc/compound-engineering-plugin⁠