Kate traces her career path from representing authors to shaping editorial strategy at Medium, Stripe Press, and finally Every—where she helped define a distribution-first, taste-driven newsletter business. As AI accelerated, she moved from skepticism to deep integration: using AI-powered tools like Atlas for hiring, custom models for enforcing style guide consistency, and collaborative workflows to publish two major AI model reviews in under 24 hours. Rather than replacing human judgment, AI serves as a 'stand-in editor'—trained on Every’s voice and standards, then refined through debate and iteration. She emphasizes that automating copyediting isn’t just about better models, but embedding human feedback loops, institutional memory, and shared editorial taste into the tools themselves. The bottleneck isn’t technical capability alone—it’s aligning AI with nuanced, evolving standards of quality, clarity, and voice. Her experience reflects a broader shift: small teams leveraging AI not to cut corners, but to scale rigor, deepen collaboration, and sustain high-caliber output amid accelerating technological change.