Dr. Philip Maymin and Dr. Jie Tao close out a two-part conversation with Margarida Sacouto and Sheila Green, graduates of Fairfield Dolan's MS in Business Analytics and AI, who spent a semester consulting for Synchrony Financial. This time: what they built, and why it took so long to start.

Sixty to seventy percent of the client work was spec-driven development, not code — a constitution, then a spec, then plans and tasks, in plain English, before anything ran. Green's group logged seven versions. Sacouto's pitch to executives: three days of every five-day week lost to data prep, cut to hours, and models scored better on her team's engineered features.

Maymin presses: isn't that just vibe spec-ing? Tao won't have it. Vibe coding, he says, is prompt and pray; auditing, red teaming, and persona challenges are the opposite. He abandoned test-driven development as models gained autonomy — the model becomes both judge and player, writing weak tests and gaming them. Maymin floats checkpoint-driven development as the successor; Tao counters with a living deliverable, not a living document.

The classroom rule follows from the practice: "I don't think it's responsible to teach students something that I don't use every day." The tool changes every semester — n8n on the original syllabus, Claude Skills by the end — and the philosophy doesn't. "We teach you the philosophy through the tool."

At the Institute's one-year showcase, senior Synchrony executives fill the room, the projector fails, a teammate away at an NCAA lacrosse tournament appears on video, and Green jokes about it. Synchrony asked for the students back.

"I'm becoming the bottleneck. I realize that. But I'm still slowing it down." Synchrony's side lands next episode.

Dr. Philip Maymin and Dr. Jie Tao — analytics professors at Fairfield Dolan, where Tao directs the AI and Tech Institute — host the first graduates of the MS in Business Analytics and AI to appear on the show: Margarida Sacouto and Sheila Green. Tao's course ran on one stubborn premise: you shouldn't have to change how you work because of AI. AI is here to help, not the other way around.

Then Tao rewrote the course mid-semester — the first time in his career — because a real client materialized. Synchrony Financial's regulated core business was off-limits by design, so students who signed up to automate their own cover letters were suddenly consulting for a Fortune 100 analytics function. Green's group, the youngest in the room and the most AI-native, decided they were the least technical and shipped anyway.

Cleaning data eats 50 to 80% of any analytics project, so Sacouto's team deliberately corrupted a credit-card dataset and built an agentic skill that cleaned it while logging every decision with a confidence score. Green's team piped it into compliance documentation. The two projects chained end to end by accident — vindicating Tao's insistence that spec-driven development was never spec-driven coding.

"Hallucination is a feature, not a bug." Results and the spec-driven deep dive land in the next episode.

Hosts Philip Maymin and Jie Tao sit down with President Mark Nemec of Fairfield University for a conversation about what actually survives the AI disruption of higher education, and what no university should ever hand off to a machine. This time the U stands for University. The argument starts with time horizons. Students think in weeks, faculty in semesters, deans in years, presidents in decades. Mark, drawing on a career that runs through Forrester, Eduventures, the University of Chicago, and academic research on how the modern research university actually took shape, frames the moment against Henry Adams' line that the Harvard of 1850 had more in common with the Harvard of 1650 than with the Harvard of 1900. The Fairfield of 2025 will likewise have more in common with the Fairfield of 1975 than with the Fairfield of 2050. But it will still be Fairfield. MOOCs were going to end residential education. The metaverse was going to end the campus. Sora was going to end film studios. COVID was going to end the residential experience entirely. None of those endings arrived. The group works through the toughest questions for higher ed. Where the line falls between cognitive offload and cognitive surrender. Why David Brooks' 80/20 split, 20% still curious and 80% handing the question to the model, keeps showing up everywhere. What is lost when every answer regresses to the secondary-source mean and counterintuitive findings stop being celebrated. Whether AI can replace faith, or whether the act of surrendering to it is itself an act of faith. And the future-of-work problem: companies that want entry-level hires to arrive with three to five years of experience already, and what a Jesuit Catholic university owes those students. The episode closes somewhere more personal. Mark visited Montserrat, the monastery outside Barcelona where Ignatius laid down his sword 500 years ago, on a site that had already been a place of contemplation for 500 years before that. Fairfield itself was founded less than four months after Pearl Harbor. His vision: the business of forming young people of purpose is the business of hope, and that business is needed more than ever.