Part One - Bryan McCann, CTO of You.com, on AI, Engineering, Art, and Everything In Between

You're tired of hearing that you need to pick up AI, so today I'm not going to add to that pile. Instead, we'll look back at two moments in history that look a lot like this one: the arrival of Fortran in the 1950s, and the spread of autopilot in commercial aviation. Both show how new abstractions change the shape of our work without being purely good or purely bad.

Fundamentals get talked about constantly, but rarely defined. In this episode I dig into what a fundamental actually is — the building blocks, heuristics, and core characteristics that don't change — and why they matter more than ever in a profession where abstraction moves faster than almost anywhere else. If you feel like you can't keep up with every new framework, model, or tool release, the answer isn't to read faster. It's to step up a level.

A 1967 study gave us the concept of learned helplessness — but the same researchers later reversed it. Passivity is our default state; control is what we learn. In this episode, I unpack what that neuroscience means for how you face hard things in your career, and why the action you take doesn't have to match the size of your problem.

As you grow as an engineer, something counterintuitive happens: the systems you build get simpler, not more complex. In this episode, I explore why senior engineers tend to collapse abstractions, accept certain risks, and reduce the surface area they're responsible for — and what drives that shift underneath the surface. Understanding the reasons behind the trend is what lets you get there on purpose instead of waiting a decade to arrive there accidentally.

Accountability is one of the most important concepts in your career—and one of the most frequently weaponized. In this episode, I unpack why so many of us have a visceral reaction to the word, and offer a pragmatic, functional definition that reframes accountability as something a good engineer actually invites. Drawing a parallel to software bug reports and root-cause analysis, I explain how healthy accountability creates clarity of expectation rather than surprise punishment.