Ftrain, by Paul Ford

All the investors are flocking to the Silicon Valley giants, but where is AI really making a difference on the ground? On this week’s episode, Paul and Rich welcome back writer and editor Josh Tyrangiel to talk about his new book, AI for Good: How Real People Are Using Artificial Intelligence to Fix Things That Matter. From hospitals to classrooms to the IRS, Josh has been chronicling the ways large and small that people are using AI to transform their fields. Plus: A discussion of the past, present, and future of the media industry, including that time Josh put airplanes having sex on a major magazine cover.

It’s unrestrained summer fun, Paul Ford-style: Using AI tools to actually ship some software. On this week’s podcast, Paul shows Rich his recent vibe-coded project, Stellate.app, which visualizes whimsical, made-up musical genres and plays the corresponding electronically generated music. (Don’t worry: You’ll get to hear some!) This might have been a fun summer project, but what did Paul learn building it—and, importantly, getting it out into the world?

What would you do if your boss said he wanted your help to automate away your job? On this week’s episode, Paul and Rich are joined by Kate Lee, the editor in chief of the AI-related publication Every. Kate’s boss, Dan Shipper, has proposed just that: For the past few years, they’ve been building software to try to reliably automate major parts of the editorial process. At Every, writers and editors alike regularly use AI tools. So what does it actually look like when AI is a fundamental part of an editorial workflow?

AI has radically changed the way software is built—so why aren’t we seeing a glut of cool new products as a result? On this week’s episode, Paul and Rich browse recent app-related headlines and product announcements, searching for anything that isn’t AI-infrastructure related: What are people actually building on top of LLMs these days? (Spoiler: Not much.) They then attempt to diagnose what’s going on here, invoking a variety of metaphors for building product with AI, from mirages in the desert to wearing a set of beer goggles.

“Verification cannot belong to the verified.” On this week’s episode, Paul is solo in the host chair as he sits down with longtime tech researcher Tricia Wang, the co-founder and CEO of the Advanced AI Society. Verifying AI, she explains, is far more complicated than simply dealing with hallucinations; in a world where AI is operating at a massive scale, how can we trust the outputs—or the people controlling the models? “Where does accountability lie?” she asks. “How do we agree to this thing?” Plus: A long exploration of the art of chicken sexing. (Yes, this relates to AI!)