He Built an AI Audience Simulator. It’s the Future of Customer Research.

TL;DR: Today we’re releasing a new episode of our podcast AI & I. I go in depth with Michael Taylor, a freelance prompt engineer and the author of our column Also True for Humans. We get into how good AI can be at simulating an audience—and how we can use that to test our ideas and assumptions. Watch on X or YouTube, or listen on Spotify. Here’s a link to the episode transcript.

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Michael Taylor has perfected the art of getting AI to speak in tongues. He’s taught it to mimic the voices of your customers—so you can see how they would respond before you ship.

Michael is the creator of Rally, a market research tool that lets you simulate an audience of AI personas. He built a simulator that lets us A/B test Every’s headlines on an audience that mimics the real Hacker News audience. It’s become a part of my writing workflow, and I love it because you test your assumptions quickly, cheaply, and without any of the risks of putting something out into the world.

Besides Rally, Michael co-authored a book on prompt engineering for O’Reilly, and he writes a column for Every about managing AI tools like you would people. In a past life, he founded a growth marketing agency which he grew to 50 people and sold in 2020. One of the reasons I’m drawn to Michael’s work is because he has a tinkerer’s mindset. He’s always exploring the limits of what a new technology can do, and what he’s into today, everyone else will likely discover six months later. We spent an hour talking about using language models to judge your work, best practices for assessing an AI’s performance, and Michael’s flow inside Cursor. He also demos Rally live on the show, testing three different potential headlines for an Every article.

You can check out our conversation here:

If you want a quick summary, here are some of the themes we touched on:

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Become a paid subscriber to Every to unlock this piece and learn about:

• Using AI personas as risk-free focus groups
• Making language models better judges through binary criteria
• The competitive advantage of risk tolerance in AI adoption