The Aboard Podcast

The big tech CEOs are openly embracing Trump—so what do we all do now? On this week’s Aboard Podcast, Paul and Rich dig into Steven Levy’s recent cover story for WIRED’s politics issue that breaks down the industry’s hard pivot towards Trumpism. What did these leaders think they were signing up, and what are they actually getting? Plus: By way of metaphor, Rich offers up the world’s worst bundt cake recipe (it’s full of gold!). 

The Aboard Podcast is about software in the age of AI—but what non-AI things are happening in the world of software? Not much, Paul and Rich are sorry to report. In the first half of this week’s episode, they discuss how AI is sucking up all the tech oxygen in the room. Then, they pivot to talking about AI and kids: What should parents be teaching their kids about these tools? (Or should they even let them use LLMs at all?) 

Will AI put an end to management consulting? Maybe hold off on writing that McKinsey obituary for now. On the podcast, Paul and Rich break down the different kinds of consulting on a practical level, and assess what AI might mean for that work going forward. Can these companies really get away with charging the same rates if AI lets them reduce headcount or dramatically speed up the work?

Millions of people are using AI tools to search—so what does that mean for search engines? On this week’s podcast, Paul and Rich dive into (the questionably named) “GEO,” or Generative Engine Optimization. After an overview of Google’s classic model, they explore the ways AI is currently upending the search world, and speculate about what might emerge in the years to come. If LLMs cannibalize all the content on the web, what will be left to search in the future?

How should the business leaders of the future think about AI? On this week’s podcast, Paul and Rich are joined by Matt Seitz, the Director of the AI Hub for Business at the University of Wisconsin’s School of Business. Matt discusses his journey from years at Google to his current role at UW, and he gives on-the-ground insight into the AI struggles of both leadership and employees in this moment of transition. Plus: They ponder whether AI can improve Wisconsin cheese. (Spoiler: No. It is perfect.)

Aboard uses AI to help build software, but in just a few years, AI will gain sentience and take over our work, personal lives, and even brains—just kidding! Yes, the fourth and final installment of “AI Summer School” is about AGI, or “Artificial Generalized Intelligence.” What does it mean? Can anyone agree on a definition? And if no one can define it or agree on those definitions, what’s the likelihood that all these Silicon Valley AGI predictions will come true?

So now that you’ve set up your AI agents, what can you build with them? In the third lesson of AI Summer School, Paul and Rich are joined by CTO Adam Pash to spin up a sample app in Aboard. How do agents work together to simulate the development process—and what’s the difference between Aboard’s structured approach and a vibe-coding tool? Plus: Introducing the Adam Pash Drinking Game, where you take a shot every time you say the word “guardrails.”

“Agents” are a big marketing term for AI companies right now—but how do they actually work? In the second installment of AI Summer School, Paul and Rich are joined by Aboard Director of Engineering Kevin Barrett, who breaks down what “agent” actually means, and how they function within the platform. Plus: In the process of demoing Aboard’s agent capabilities, Paul becomes transfixed by the breeding records of a fictional alpaca farm.

Feel a little lost when it comes to AI? It’s time to go back to school—Aboard’s AI Summer School! Over the month of August, Paul, Rich, and a few special guests will break down the basics of LLMs, agents, AGI, and a host of other AI-related topics. In the first installment, they discuss how LLMs think—or rather, don’t think—and compare the major players on the AI scene right now.

Mapping the history of the universe—and the limits of current AI programming tools. On this week’s podcast, Paul walks Rich through his recent experiments trying to build timeline software via vibe coding. Spoiler: There were issues. Halfway through 2025, where do the current tools excel, and where do they fall flat? And looking over the few years at where these tools might be headed, what should a young person interested in tech be learning right now?