How Two Engineers Ship Like a Team of 15 With AI Agents

Tl;dr: Today Dan Shipper and the Every team are hosting more than 200 subscribers for Claude Code for Beginners, so we’re republishing one of our favorite episodes from our podcast AI & I. Dan goes in depth with Kieran Klaassen, general manager of Cora, Every’s AI-powered email assistant, and engineer Nityesh Agarwal, about how AI-assisted coding tools like Claude Code have transformed how they build products. Watch on X or YouTube, or listen on Spotify or Apple Podcasts. Here’s a link to the episode transcript.

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Two engineers at Every shipped six features, five bug fixes, and three infrastructure updates in one week—and they did it by designing workflows with AI agents, where each task makes the next one easier, faster, and more reliable.

In this episode of AI & I, Dan Shipper interviewed the pair—Kieran Klaassen, general manager of Cora, our inbox management tool, and engineer Nityesh Agarwal—about how they’re compounding their engineering with AI. They walk Dan through their workflow in Anthropic’s agentic coding tool, Claude Code, and the mental models they’ve developed for making AI agents truly useful. Kieran, our resident AI-agent aficionado, also ranked all the AI coding assistants he’s used. You can check out their full conversation here:

If you want a quick summary, here are some of the themes they touch on:

The workflow you can use to 10x your engineering capabilities

At the heart of Kieran and Nityesh’s workflow with AI is a meta move: They built a prompt that writes prompts. With help from Anthropic’s Prompt Improver, they created a custom command in Claude Code that transforms a rough feature idea into a fleshed-out GitHub issue. Each issue includes a clear explanation of the problem, a proposed solution, the technical details needed to make it happen, and a step-by-step implementation plan. The agent pulls in relevant parts of the existing code and best practices from the web to help guide the approach.

Once the GitHub issue is created, they review it themselves and queue it up to be implemented. By planning the work, writing out the issue, and then reviewing it, they create space to think clearly about the problem before any code is written. Unlike AI code editor Cursor, which is “made to code,” Kieran says Claude Code reduces the friction to think things through before jumping into execution.