Month: March 2026

Sedate Sunday: AI Impacts On Software Developers and that Pesky Recession

Millions of Americans marched in yesterday’s No Kings rallies, although you wouldn’t know it from the controlled state press. Heck, i’ve had to go to places like reddit to get a feel for what’s going on with ordinary citizens. The US is at war, but nobody wants to call it a war, except perhaps the unfortunate young people in the military sent on a benighted mission to take some waterway we really don’t need with weapons that are inadequate to the task. And as the stock market wobbles now that the Strait of Hormuz is closed by Iran in retaliation for the US/Israel strikes on the country, the price of a gallon of gas, along with some spring travel, has gone straight up the flue. 

But it’s a lovely Sunday in Silicon Valley, balmy and sunny. A perfect time to reflect on how jobs will be impacted by AI.

AI is not a “new thing”, and it’s not always a “bad thing”. AI is an excellent tool to analyze and respond to complicated contradictory datasets. 

William and I had planned to use AI for 386BSD. An operating system and written works supported by a couple of enthusiastic people is a difficult prospect to say the least. We not only had extensive source code repositories — we also had extensive often unpublished writings on those very code bases. And it was impossible to respond to inquiries timely about this project. It vexed us.

William’s untimely death prevented us from taking action in this area. But that doesn’t mean it is yet impossible. New and accessible AI tools to mine, collate, analyze, and respond are now available. Open source documentation, support, and updates would benefit from these tools.

While the constant refrain that “AI will take all the jobs” is frightening, it’s also not correct. But it grabs attention from dazed and scared people worried about their next paycheck. It sells papers, so to speak.

The most frequent press focus on AI is software development. This is because the people working on AI are software developers. We eat our own dog food, as the Microslop folk love to chant. We know about software development, so we think “Hey, let’s make it do software development”. 

Silicon Valley also loves to sell out their own. They always have. Our love of our own meritocracy results in a flawed reductionist nostalgia. Beginnings are difficult things, and we often start and stop before we achieve any success. We usually fail, but even the failures can have meaning. These lessons are forgotten once a startup becomes a success, sadly.

So the developers and inventors and folks who did the hard work are forgotten. Resentment of those “costly” developers festers. And then the Silicon Valley C-suite says “Hey, let’s use [pick a tool] to get rid of them. There’s a whole lot of code on the web. There’s stack overflow. Let’s raid it. Who needs those guys!”. Hence, the current fad. 

Many Silicon Valley companies overhired in the last decade, mostly to fill offices in their corporate real estate kingdoms. So reductions were expected. In addition, we’re in a late stage economic cycle before a recession. Holding on to lots of people developing products that can’t be sold in a recession is scary. Yes, the C-suite gets scared just like ordinary people. So they’re getting ahead of that event before it happens — often to excess.

This is not our first recession rodeo, folks. Been through it many times here in Silicon Valley. We got startup funding several times during the darkest recession times. Why? Because trying new approaches is a time-honored way of getting to the stage after the recession, which is growth. That’s where the good engineers and inventors and software developers will be. You can’t automate innovation.

So now, who is actually at risk? The answer is anyplace where costs dominate or innovation stagnates.

Companies and even individuals first reduce costs by looking at non-critical areas. Marketing, PR, and social media. HR. Travel. Creatives. They’re on the cutting board, as always. AI is already chatting with customers, and sometimes even solving the problem. Sometimes.

Stagnating innovation is a bigger issue. Product development at companies will be in a free fall. People will be fired. AI will be blamed. But it’s just the same old cost-cutting in a new coat. Gotta blame something, and blaming AI is easier than admitting your company is not going to do anything new for a good while. So batten down the hatches, folks. AI isn’t necessarily coming for your jobs. It’s just the convenient excuse. 

The dark and looming monster coming for your jobs is the anticipation of a recession. Will it actually occur? I don’t know. I don’t know when or how or why. Nobody does.

But the fear-of-losing-out culture is now the fear-of-moving-too-late culture. AI is the excuse, not the cause. Look behind the corporate curtain. Think critically. Read. And plan for your future. Because no one else cares about you like you do.

Thoughtful Thursday: Data Center Marauders and SV Villains


Today as our country spins further into self-induced insanity, I thought I’d talk a bit about (drumroll) data centers! This is ordinarily a rather dull topic to most, consisting of equipment and deployments and connectivity, hardware and software and systems, processors and networks, and of course, operating systems. 

Since it is a dull but necessary topic that keeps things running, I could not resist writing about them back in the day. I even put together a book for Wiley entitled Inside the Internet Data Center in the early 2000s which predicted many Internet issues from the perspective of the data center administrator and how to deal with them. It was an enjoyable exercise. Unfortunately, the publisher decided it was an uninteresting field of study and canceled the book. I got to keep the advance and soon moved on to other projects. But data centers will always hold a fond place in my technology heart.

Now, everyone is talking about data centers.  But not fondly. Not as an intellectual exercise. Nope, they are talking about them as technological marauders, stealing power and water and land from ordinary citizens in small towns. These entities are placed without any consultation or approval of the citizens in their communities. And the deals for taking the land and power and water are too often under nondisclosure, meaning nobody knows until it’s too late.

The big players in AI – Nvidia, Meta, Google, Amazon, OpenAI, and Microsoft – are now seen as the faces of villains. It’s a PR disaster for Silicon Valley. And yet, this is the endgame move. There are lots of pieces and players – and billions of dollars involved.

At the core, a data center is simply a processor receiving a request, accessing a database entry, and sending a result back. The devil is in the details. And there are a lot of devils, ranging from the actual hardware management and maintenance, to connectivity requirements, to database management, update and integrity — not to mention the software and operating systems that superintend these functions. 

These operations require power. Lots of power. And they produce heat. Lots of heat. Hence the massive power and water requirements. And the increased demands of AI mean even more power and water for those AI chatterboxes telling folks that they can do no wrong, even though the actual interactivity to the end user is essentially meaningless. 

According to McKinsey, almost $7 trillion will be invested in data center acquisition and development by 2030, $3 trillion in real estate and power infrastructure and $4 trillion in “computing hardware infrastructure” ($3.5T in servers and $.8T in storage). This is a mind-boggling number of processors.

Nvidia as the leading vendor of GPUs is beyond excited. At GTC this week, Nvida CEO Jensen Huang hailed these numbers, claiming he sees “at least $1 trillion” in revenue from Nvidia products through 2027. “I am certain computing demand will be much higher than that.” As Motley Fool noted, “This is startling — in a positive way — as it comes only five months after his earlier forecast, suggesting enormous momentum in orders in recent months. Also, Huang’s words imply that, from what he’s seen so far, he thinks revenue could surpass the level of $1 trillion.”  If so, McKinsey’s predicted spend is underestimated.“

The real estate side of the equation is equally compelling. Data center REITs are all the rage. While partners in these ventures are often carefully shielded from local scrutiny, huge funds are usually involved in the acquisition of land and construction of essentially a bunch of big concrete shells. Rural locations are targeted. Land is cheaper in rural locations. Political resistance is diluted. And oftentimes water available for agriculture can be recaptured for equipment cooling. In addition, it is easy to buy a few local officials (and relatively cheap) and obtain through strong-arm tactics power easements to the datacenter. 

When large corporations come into a community, they usually attempt to co-opt it by selling folks on jobs. However, once the datacenter shells are put together, there really isn’t much of a need for unskilled or semi-skilled labor. A large data center requires very few on-site personnel. Most software and systems administration is done remotely by engineers. Hardware failover means that a lot of CPUs and GPUs can burn out without having to swap out the damaged equipment. 

The modern data center isn’t a factory with people working in shifts and products trucked to customers. It’s a factory for analyzing your most personal secrets, foibles, and thoughts, circumscribing every purchase you make and every comment you write, and monetizing it.

If fund managers believe that $4T in real estate is worthwhile, think of what value they place on your personal data. To get a 10-fold investment return, youre looking at the data value of literally hundreds of trillions of dollars estimated. These numbers rival the GDPs of major countries and blocks, with the US, China and the European Union in the $20 trillion economy group. That’s two countries and one economic block.

Now, these numbers are incredible, but also quite ephemeral. The same value of data of citizens incorporated implicitly in GDP as a complex factor is often claimed as a pure monetary value by AI enthusiasts. Nope, this isn’t the ROI. It’s about controlling the mindspace of investors and securing current investments. 

What is real and tangible is the resistance of data center construction in communities throughout the US. And that antipathy has gone hand-in-hand with increased public fear of AI used for government surveillance. And most certainly some of the biggest advocates for its use have been companies like Palantir. People don’t like being reminded they’re being watched, even though that’s what the “free Internet” has been all about.

AI advocates have touted AI as the means for companies to find and fire people because they’re no longer needed. Lots of people. Huge numbers of people. This doesn’t make folks worried about their next paycheck feel real good about it. Especially when they open up their power bill and find it’s gone way up because a datacenter in their area has raised costs for everyone. 

And finally, the debacles of AI misinformation from overeager AI advisors have become a joke, and a mean one at that. AI for the masses is not a trusted source.

This is how the standing of Silicon Valley companies has plummeted — not in terms of the stock market, but in terms of their trustworthiness. 

William and I discussed the benefits of AI and data centers many years ago. Those benefits haven’t changed. But the mishandling, greed, and sheer contempt of major players in Silicon Valley and large investment funds have frittered away the goodwill and obscured the benefits.

It’s too bad. I really do like data center design. I like the software. I like the systems. I like the hardware. I like the benefits of AI.

But I don’t like the companies and pundits. Nobody does.