Episode 4 welcomes Andy Masley, the independent writer and researcher behind one of the most widely read Substacks applying careful, numbers-first thinking to AI. A former high school Physics teacher with a background in philosophy, Masley has built a following by taking the claims everyone repeats and checking if they hold up.

Dr. Samuel Jay and Larry Sampler begin with language itself. Masley argues that the two dominant framings of AI like "it is just a tool" and "it cannot really think because it is not human," are both broken, and that the metaphors we reach for quietly shape policy, teaching, and who gets held accountable. From there the conversation moves into harder territory: what interpretability research can and cannot tell us about what is happening inside a model, why visible chain-of-thought reasoning may be fading, and why "it just predicts the next word" badly misleads people about what these systems do.

The back half turns to Masley's signature beat: AI and the environment. He walks through why the viral "a bottle of water per prompt" figure is wrong by roughly two orders of magnitude, where the real concerns actually sit (the green-energy transition, local gas turbines, electricity prices), and why contextless big numbers tell you nothing about any industry. Along the way: the higher-education cheating crisis, the geopolitics of whose values get trained into frontier models, the unglamorous work of fixing broken business practices before automating them, and a closing tour through effective altruism.

A wide-ranging, occasionally unnerving hour about thinking more clearly.

Check out Andy's Substack. It's a must-read, especially if you're playing a part in AI-related decision-making.

In this episode of Thinking Out Loud, recorded on-site at the Ai4 Conference in Las Vegas, Sam and Larry sit down with Kevin Taylor, Chief Information Officer, and Mike Hart, Chief Information Security Officer, at MSU Denver. Together, we explore what it means to lead institutional IT and cybersecurity at a moment when advanced AI has moved out of the labs and into daily campus life. Kevin and Mike share how their thinking has shifted, where the real tensions sit between innovation and governance, and what it takes to balance faculty, staff, and student demand for AI access with the realities of maintaining a complex enterprise environment.

Links mentioned during the interview:

• Colorado Higher Ed Computing Organization (CHECO)
• Terms of Service, Didn't Read

In episode three of Thinking Out Loud, Sam Jay and Larry Sampler recap their presentation to the MSU Denver Board of Trustees, subsequent discussion, and the work to be done over the summer as faculty, staff, and students prepare for a new academic year.

Have any question, comments, ideas, or feedback? Email us at ai@msudenver.edu.

In episode two of Thinking Out Loud, Sam Jay and Larry Sampler work through how they are preparing to brief the MSU Denver Board of Trustees on the university's AI readiness work.

They open with a round of fact or fiction, testing each other on a set of recent AI stories that range from useful to alarming to flat-out strange. The point is not the trivia. It is the reality that President Davidson and every senior leader now has to make decisions inside an environment this noisy and this fast-moving.

From there the conversation turns to the work itself. How do you build a governance structure that is flexible enough to keep up with AI without smothering the curiosity of a university full of smart people? Sam and Larry make the case for a task force model over a standing committee, walk through the four areas of emphasis shaping their plan (student readiness, faculty readiness and curriculum, operational innovation, and special projects), and get honest about the unglamorous truth that most of this work starts with documentation, not deployment.

Along the way: why they are not flipping every switch in Workday yet, what the controller's office taught them about where AI agents actually add value, the difference between training and education, and why keeping a human in the loop is the whole game.

Recorded as the team heads into board preparation and the summer planning stretch.

Have a question you are stuck on? Email us at ai@msudenver.edu.

Links and sources mentioned in this episode:

• The autonomous database deletion story
• Emergence World multi-agent simulation

In the inaugural episode of Thinking Out Loud, Sam Jay, Executive Director of Digital Learning and AI Strategy, and Larry Sampler, former COO and now Special Advisor to the President, sit down to introduce the show and the work behind it.

Sam and Larry trace the backstory that brought each of them to leading AI at Metropolitan State University of Denver, a public, open-access university serving 18,000 students in downtown Denver. They talk about what got them into this work, what they have learned so far, and why they decided a podcast was the right way to think about it in public.

The conversation then turns to the areas of emphasis that will shape their work in the months ahead. Faculty readiness and pedagogical excellence. Student readiness and curriculum development. Operational innovation across the university. The shared thread is a commitment to using AI in a way that enriches the university's mission rather than competes with it.

This episode sets the foundation for everything that follows. Future episodes will go deep on the specific decisions, pilots, and unresolved questions that come with building AI capacity at a public university.

If you work in higher education, lead an AI initiative, or are trying to make sense of where this is all going, this is the place to start.

Subscribe and send us the questions you are stuck on.

Music: Space Cadet Training Montage by Zane Little (CC0 1.0 Universal).