🤖 AI Summary
Overview
Kate Lee, Editor-in-Chief at Every, shares her journey from literary agent to tech startups, detailing her experiences at Medium, WeWork, and Stripe Press. She discusses how AI has transformed her workflow, the challenges of running a newsletter in the age of AI, and the evolving role of taste and editorial standards in a tech-driven environment.
Notable Quotes
- It's not about accepting what AI says blindly at all. It's trained on our stuff and what's worked. Your job as a writer or editor is to consider it.
– Kate Lee, on integrating AI into editorial workflows.
- I can either do the job or hire the person to do the job—there’s a very similar AI thing here where I can either do it the way I know how or potentially waste time figuring out how to get something else to do it.
– Dan Shipper, on the parallels between hiring and leveraging AI tools.
- For the first time, I felt like, 'Oh my God, I don’t have to wrestle with software anymore. I can just tell an agent to do it.'
– Kate Lee, on her breakthrough moment using AI for operational tasks.
📚 From Literary Agent to Tech Innovator
- Kate began her career as a literary agent, representing Pulitzer and Nobel Prize winners, before transitioning to tech roles at Medium, WeWork, and Stripe Press.
- At Medium, she found a seamless fit working with writers in a faster-paced, tech-driven environment.
- Her time at Stripe Press highlighted the importance of aligning publishing initiatives with a company’s broader mission, such as Stripe’s focus on global entrepreneurship.
🤖 AI’s Role in Editorial Standards
- Kate implemented AI tools to enforce editorial consistency across Every’s newsletter, using a style guide with 400 rules.
- AI projects were developed to lift the editorial “floor,” ensuring drafts met baseline standards before reaching her desk.
- She emphasized the importance of training AI on specific company standards and using it as a tool to enhance—not replace—editorial judgment.
🛠️ Practical Applications of AI in Workflow
- Kate described a pivotal moment using OpenAI’s browser tool to streamline hiring processes, including posting jobs and filtering hundreds of applications.
- AI saved her hours of manual work, allowing her to focus on higher-value tasks while maintaining control over hiring decisions.
- She highlighted the importance of trial and error in integrating AI tools effectively into operational workflows.
🚀 Publishing in the Age of AI
- Every’s editorial team leveraged AI to produce two major model reviews in 24 hours, showcasing the speed and efficiency AI enables in publishing.
- The team uses AI to generate headlines, test subject lines, and refine introductions, ensuring content resonates with readers.
- Kate stressed the importance of balancing AI-driven efficiency with maintaining high editorial standards and taste.
✍️ The Future of Copyediting and Taste
- Kate discussed the bottlenecks to automating copyediting, citing consistency and judgment as key challenges.
- She noted that while AI can handle repetitive edits, it struggles with nuanced decisions that require human taste.
- Dan predicted that AI might fully automate copyediting by mid-2026, reflecting the rapid advancements in AI capabilities.
AI-generated content may not be accurate or complete and should not be relied upon as a sole source of truth.
📋 Episode Description
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 into her workflow.
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/