Adam Gonnerman

Once when I was in a role supporting a multi-market digital release I was facilitating a meeting that had quickly become circular and unproductive. Engineering was discussing technical dependencies, product was focused on feature completeness, and regional stakeholders were raising compliance concerns. All of this was being discussed at the same time, with people occasionally talking over one another. Each group was using different terminology and optimizing for different risks, which made it difficult to determine what decision actually needed to be made. The conversation kept expanding instead of converging. What to do? I paused the discussion and reframed the session around three concrete questions: What decision are we making today? What constraints are non-negotiable? What options are truly on the table? I then captured each group’s concerns in plain language on a shared Google document, grouping them under timeline, compliance, and technical risk. This structure made overlaps a...

The following is the minimalist RPG system I discussed in my post yesterday. My teammate in creating this was named Maria, per her email address, but I don't have her last name. If that ever becomes available, I'll update it here. 

While pursuing my Master’s degree at Salve Regina University , I collaborated with a fellow student on a class project to design a minimalist tabletop role-playing game. Role-playing games (RPGs) are collaborative storytelling games in which players take on fictional characters in a shared world. One participant—often called the Game Master—describes the setting and challenges, while the other players declare what their characters attempt to do. Outcomes are typically determined by simple rules and dice rolls, blending imagination, strategy, and chance. Our goal was to create a system simple enough for beginners but structured enough to feel meaningful. I initially sketched a rules framework built around four core attributes—Strength, Agility, Intelligence, and Charisma—using a single six-sided die to resolve actions. Players would choose streamlined classes like Warrior, Mage, Rogue, or Healer, each interacting differently with combat and problem-solving. The system emphasized fast e...

When most people think about operating systems, they picture the old desktop rivalry between Windows and Mac. But this video looks beyond that familiar battle to tell a different story—one about a quiet contender that reshaped the digital world from behind the scenes. It begins with a hobby project in 1991 and traces how an open-source experiment, rooted in the Unix tradition, began spreading in unexpected places. Without dominating the desktop spotlight, it steadily found its way into the infrastructure that powers the internet, mobile devices, and far more than most people realize. Rather than focusing on who “won” the visible war, the video invites viewers to reconsider what winning actually means—and to discover how the software you rarely see may be running more of the world than you ever imagined.

When we think about modern finance, we picture sleek apps, real time payments, and cloud infrastructure humming in the background. What we rarely picture is the decades old code quietly processing trillions of dollars every day. This video pulls back the curtain on the surprising reality that much of global banking still runs on COBOL, a programming language built for precision and reliability long before most modern developers were born. It explores why banks continue to trust COBOL for mission critical systems, how an aging workforce has created what some call the Greybeard Crisis, and whether artificial intelligence can realistically step in to maintain or modernize the backbone of the financial system. Beneath the surface of innovation lies a fragile stability, and understanding that tension is essential to understanding the hidden risks inside global finance today.

Several years back I was in a program role supporting high-visibility digital platform launches. As usual for such a role, I was responsible for driving an on-time release tied to contractual distribution milestones. Meanwhile, a senior engineer was focused on refactoring part of the integration layer to improve long-term maintainability. We were seemingly at cross-purposes, because my goal was to schedule adherence and certification readiness, and the senior engineer was technical sustainability and reducing future defects. These priorities seemed to be in tension, as deeper refactoring risked delaying launch. How could we move forward? Thinking it through, I decided that instead of forcing a trade-off, I would facilitate a working session to break the work into phases. That is, we would identify what refactoring was critical for launch stability versus what could be sequenced into a fast-follow release. Through this process we aligned on a minimal, high impact improvement set that re...

The AI boom has sent tech stocks soaring, with Nvidia and the Magnificent 7 capturing the imagination of investors worldwide — but what if the entire rally rests on a foundation far more fragile than anyone is talking about? In this video, we pull back the curtain on a single, largely overlooked vulnerability hiding at the heart of the AI supply chain: a geographic and industrial bottleneck so concentrated that one geopolitical flashpoint could send shockwaves through every major tech company on the planet. Before you buy into the AI narrative, there's something you need to understand.

Behind the headlines celebrating the AI revolution lies a financial story that isn't nearly as clean as the press releases suggest. Trillions of dollars in debt, underwhelming adoption numbers, and a revenue loop that may be more circular than it first appears — this video takes a hard look at whether the AI boom is built on solid ground or something far more precarious. If you think the biggest risk to your portfolio is missing out on AI, you might want to watch this first.

The AI boom hasn't just captured investor imagination. It has quietly become one of the biggest concentrations of financial risk in modern history. In this video, we dig into the economic mechanics that most coverage glosses over: a business model that may actually lose more money as it scales, a web of capital flows that can look like growth while cycling through the same handful of players, and a market so top-heavy that a single crack could become a systemic fracture. The technology may be real, but the economics deserve a much harder look.

The AI story has moved well beyond Silicon Valley hype. It has become a question of market structure, systemic risk, and who actually holds power in the global economy. In this video, we look at why this boom may be unlike any speculative cycle before it, not because the technology isn't real, but because it has embedded itself so deeply into critical systems that a correction wouldn't stay contained. For executives and investors still treating AI purely as an opportunity, this one is worth your full attention.

The debate around AI and jobs tends to focus on robots taking over, but the more unsettling story is quieter and already underway. In this video, we examine what's actually happening to the workforce beneath the headlines: not mass layoffs, but something that may be harder to reverse. If you're early in your career, managing a team, or just trying to understand where the economy is actually headed, this one cuts closer to home than most AI coverage does.

The conversation around AI tends to treat it as a force of nature, something arriving whether we want it or not. This video pushes back on that framing. What if the way AI is actually being deployed has less to do with innovation and more to do with a very old corporate playbook? Behind the language of transformation and inevitability, there are specific choices being made by specific people, and those choices are worth naming clearly. If you've ever felt like the AI story doesn't quite add up, this might be why.

The AI hype cycle is loud, but the numbers behind it tell a quieter and more troubling story. In this video, we look at the growing gap between what the industry is promising and what it is actually delivering, from the economics that get worse as they scale to the valuations that depend on growth that may never arrive. It's not a reason to give up on technology, but it might be a reason to stop taking the headlines at face value.

Most of us have noticed it, that creeping sense that the internet just isn't as good as it used to be. But frustration doesn't explain why it happened or who's responsible. In this video, we get into the real mechanics behind the decline of platforms we once relied on, and why the answer isn't to find a better app. If you've ever wondered whether any of this can actually be fixed, the argument here might surprise you.

The deal that was made with an entire generation, work hard, get a degree, and a career will follow, is quietly falling apart. In this video, we look at what the data actually shows about young workers entering the labor market today, how AI is reshaping who gets hired and who gets left out, and why the old playbook no longer works the way anyone promised it would. If you're early in your career, raising someone who is, or trying to understand where the economy is actually headed, this one is worth watching.

AI is making organizations look more efficient than ever, but there is a cost that isn't showing up on any balance sheet yet. In this video, we examine what happens when companies optimize so aggressively for short-term output that they quietly eliminate the conditions that produce future expertise. The talent pipeline doesn't break all at once. It erodes, and by the time the problem becomes visible, rebuilding it is far harder than it would have been to protect it.

AI adoption in engineering is nearly universal, but the productivity story being told to investors and the one unfolding inside engineering teams are starting to diverge in some uncomfortable ways. In this video, we look at what the research actually shows about AI-generated code, where the hidden costs are accumulating, and why the organizations moving fastest may be building up a problem they won't fully feel until it's expensive to fix.