I’ve been doing Office Hours and the topic of AI has been in almost every one of the conversations. Everyone is wondering what the right play is with AI. A number of people are concerned about it replacing them. I’ve been giving the following advice, “Treat AI as an awesome teammate”

I was telling someone recently that I studied Physics & Philosophy and that Philosophy taught me the art of asking great QUESTIONS, while Physics taught the art of creating great ANSWERS. So let’s start with a great question:  What is a Team?

We don’t build teams just to have more bodies in the room. We build teams because we are all flawed. Every single one of us has peaks of high capability and deep valleys of incompetence. The theory of a team is that it is a structure designed to amplify our strengths and compensate for our weaknesses. Putting my SRE hat on, you can view it as an architectural pattern for resilience and error correction.

If you stop looking at AI as a threat and start looking at it as a teammate, the dynamic changes. You figure out how to use it to compensate for your weaknesses. As I’ve said many times, I am a deeply flawed human (that is why you can use wildcards everywhere in PowerShell) so I need awesome teammates to function.

I am not a finance guy. I am an engineer. But I’ve been in this industry for forty+ years, and I’ve got enough scar tissue to look at a P&L sheet and ask some questions. And frankly, I don’t like what I’m seeing.

When I look at the current AI landscape, I see a trillion-dollar venture. As I wrote recently in AI Bubble? : AI Skeptics Hard Look at the Value Equation, the math of this investment requires scrutiny, not just optimism. You have reports like Leopold Aschenbrenner’s “Situational Awareness” paper arguing that AGI by 2027 is a certainty based on straight lines on a graph. You have accelerationists claiming that “winning AI” is a geostrategic categorical imperative—that the U.S. must secure “superintelligence” before China does to ensure national security. (If you want to lose some sleep, watch the AI 2027 video).  The narrative is that it is effectively a “winner take all” race.  But breathy narratives rarely hold up in the real world. We need to focus on Getting the AI Hype Cycle Right – distinguishing between inevitable progress and the economic reality.

I always like to look at the physics of a situation. And the physics suggest that this massive spending isn’t building a defensible fortress. It’s building a money pit.

Because here is the hard truth: AI ages like fresh fish.

I got a lot of feedback on my AI Bubble? : AI Skeptics Hard Look at the Value Equation, and the reactions were fascinating. A lot of you read my analysis of the economics and put me in the “AI Skeptic” box.

That’s a mistake. It misses the physics of what is actually happening.

While I agree with many of the skeptical points regarding the current financial bubble—because let’s be honest, the math on some of these valuations is ‘no bueno’—my long-term view aligns much more closely with Jim Keller.

There is an ongoing conversation happening right now between three camps: the AI Accelerationists, who want ‘all gas no brakes”; the AI Safetyists, who want to slam on the brakes; and the AI Skeptics.

The first two camps get all the press because they deal in extremes—utopia or apocalypse and extremes drive the attention economy. But we need to pay attention to the Skeptics. There is a taxonomy to the camp of skeptics; some don’t think AI is going to do what people say it will; others believe that it is a distraction from more pressing issues; and some are all about the economics and the math. The skeptics in this discussion aren’t arguing about the soul of the machine or killer bot swarms; they are arguing about the math. And from their perspective, the math is no bueno. MUY no bueno.