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Paul and Rich are ready to answer your questions about AI—and beyond. On the inaugural episode of “Ask Aboard,” they tackle a trio of queries from some familiar faces. First, NYU’s Vice Provost for AI and Technology in Education, Clay Shirky, asks how we can personally protect ourselves in the wake of the Hugging Face incident. Next, an anonymous letter-writer wants to know how to deal with clients who can’t stop generating bad AI artifacts. And finally, journalist and editor Josh Tyrangiel gets to the heart of it all, asking: What’s the software equivalent of yacht rock?

How can we get politicians and Silicon Valley on the same AI page? On this week’s episode, Paul and Rich welcome on Jason Goldman, whose long career in tech has taken him from Blogger to Twitter to the Obama administration to his current endeavor, the Center for Shared AI Prosperity. “AI capabilities are advancing faster than the political system is responding,” CSAIP’s website reads; Jason explains the challenges around and different approaches to redressing this gap. Plus: as the host of the movie podcast Escape Hatch, Jason ranks his expectations for the fall tech industry films, and makes a big prediction about Dune: Part Three.

How is AI reshaping internet culture? On this week’s episode, Paul is joined by a journalist who has truly looked into the digital abyss: Business Insider’s Katie Notopoulos. Using a few recent AI-related stories Katie reported as a lens, they discuss the increasingly blurry boundaries between the real and the artificial on our social feeds. Katie is known for, among other things, her lists of the worst things on the internet; with AI, Paul asks, has “worst” somehow gotten “even worser”? Plus: In a classic reporter move, Katie flips the script and quizzes Paul about his 2014 essay on YouTube, “The American Room.”

LLMs are often far too powerful for the small tasks they’re asked to complete. Is the more-contained Jev the alternative? On this week’s episode, Paul and Rich read a question from tech writer John Pavlus about Jev, a new model from Typesafe AI that’s been a major topic of discussion in programming circles recently. LLMs, Rich suggests, are often like using a power riding mower to cut the grass of your tiny lawn. As Paul breaks down Jev and others like it into layman’s terms, they debate whether this kind of technology is the future—or if it’ll just be one more thing absorbed by the AI giants?

How is observability being redefined in the AI era? On this week’s episode, Paul and Rich sit down with Charity Majors, the co-founder and CTO of Honeycomb. After a crash course on observability, the conversation pivots to AI and its cascading effects—both on this subfield, and on the tech community overall. Some engineers try to plan for every eventuality, but Charity stresses that the best thinking comes when you accept that anything could go wrong at any time: “There’s liberty in chaos.”

Tech execs are sounding alarms about the dangerously fast pace of LLM development. Will any regulators stop them? On this week’s episode, Paul and Rich discuss a heady few days in the world of Big AI, as Dario Amodei called for a slowdown on AI development that was soon echoed by other leaders like Sam Altman and Elon Musk. Do their stated concerns actually match up to reality? In our current political climate, how realistic is the idea of government intervention? Plus: Paul does a pretty convincing imitation of a data center.

Problems with your boss? Why not fire up Claude and hit HR with a lengthy legalistic complaint? On this week’s episode, Paul and Rich look at the erosion of human-to-human communication in the AI era, springboarding off a friend’s anecdote about employees sending official-sounding LLM-generated documents to HR rather than starting with simple conversations. AI tools allow us to flood each others’ inboxes. Is that making it impossible to truly communicate?

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!)

It might sound like he’s ranting, but the Palantir chief is zeroing in on the truth of our AI moment. On this week’s episode, Paul and Rich break down Alex Karp’s recent appearance on CNBC, in which he discussed Palantir’s position within the ever-expanding world of the AI giants. Orgs might be using OpenAI and Anthropic’s tokens, but Palantir’s position exposes, in Rich’s words, “the gap between transactions and relationships.” Finally, Paul asks Rich to run the new, imaginary consulting practice at Anthropic and obliterate Palantir. Can he do it? Does he have what it takes?

How is Silicon Valley engaging with ethics and religion today—and how is the Catholic Church responding to AI? On this week’s episode, Paul and Rich welcome on Father Brendan McGuire, a former engineer and current Catholic priest who serves at St. Simon Parish in Los Altos, California, aka the heart of Silicon Valley. He discusses his long work speaking between the tech industry and the Church, as an advisor to Anthropic as well as an early commenter on Pope Leo’s recent encyclical on AI, “Magnifica Humanitas.” (Don’t worry, Paul asks the question on everyone’s lips: In what file format does a pope distribute early copies of an encyclical?)

Silicon Valley “disruption” is at odds with the way software creation actually works—and that’s a problem. On this week’s podcast, Paul and Rich discuss Rich’s recent Aboard newsletter installment, “Maybe the Valley Could Listen a Little.” about how the dream of an “AI unicorn” who can use these tools to build a product all by themselves is a total fantasy. AI companies are promising revolutionary transformation across industries, but are they mostly just plastering over fundamental issues in processes and systems?