It’s an old trick, one that’s been pulled out of the hat by the powerful throughout history: keep folks fighting among themselves, and they won't notice who's really pulling the strings. We're talking about the manipulation of everyday citizens through fear and division, a strategy that feels eerily familiar whether you look back to the aftermath of the American Civil War or fast forward to our world in 2025. While the specific methods and the context change, the underlying tactics are strikingly similar, almost like a playbook passed down through the generations, perhaps even inspired by the grand old "divide and conquer" strategies of imperial powers like the British.

After the Civil War, during what is called the Reconstruction period, there was this real chance for a new, more equal America, especially for the newly freed enslaved people. But powerful interests quickly swooped in, eager to put the brakes on any real progress. They weaponized racial fear and stoked economic anxieties to perfection. As Black citizens started gaining ground, a nasty backlash emerged. White supremacist groups, often quietly (or not so quietly) backed by the rich and powerful, spread ugly stories about Black inferiority and criminality. They whipped up fears of "Black domination" and "racial mixing" to justify violence, strip voting rights, and enforce segregation. The rise of Jim Crow laws across the South, which basically cemented racial separation and systemic discrimination, was a direct result of this fear-mongering. It was a classic "divide and conquer" move, preventing poor Black and white citizens from uniting and potentially challenging the folks at the top. You can see this clearly in events like the Wilmington Insurrection of 1898, where a biracial government was violently overthrown, all fueled by intense racial paranoia and propaganda. It’s a stark reminder of how potent these tactics can be.

Then came the Gilded Age, a time of massive industrial boom and the rise of those legendary industrialists we often call "Robber Barons." As working people started to organize, forming unions and demanding better wages and conditions, the elite again went to their trusted playbook. They actively sowed divisions within the working class itself, often using existing prejudices against immigrant groups or pitting them against native-born workers. They also played on fears of radicalism, painting union organizers as dangerous anarchists or communists threatening the very fabric of society. Strikes were frequently met with brutal force, always justified by these fear-driven narratives. The Haymarket Affair in Chicago in 1886, for instance, became a potent symbol for industrialists and the media to demonize labor movements, associating them with violence and foreign ideologies. That fear was then leveraged to crush any efforts at worker solidarity.

Fast forward to 2025, and while we're not dealing with Jim Crow laws or 19th century factory strikes, the fundamental tactics of fear and division are still very much alive and kicking. Powerful entities continue to exploit our anxieties and even create new ones to keep their influence intact. The biggest game changer now? Social media and disinformation. These platforms have become incredibly effective at spreading divisive stories. Algorithms, it turns out, love content that stirs up strong emotions like fear and anger, leading to these digital echo chambers where misinformation just thrives.

Consider how this plays out with issues like immigration. We've seen a consistent effort to "manufacture the migrant threat," portraying new arrivals not as individuals seeking a better life, but as an existential danger to national security, economic stability, or cultural identity. This racialized and nativist narrative is a potent tool for manipulation, effectively turning citizens against each other and against newcomers. For instance, recent polls reveal a significant amount of misinformation about immigrants circulating, especially in the context of major elections, showing how these false narratives take root and influence public opinion. You can see how prevalent some of these misperceptions are when looking at polling data related to the 2024 presidential election.

These divisive campaigns aren't accidental; they're often well-funded and strategically deployed. Think about the influence of "dark money" in shaping political and social landscapes. Huge, opaque donations, like the staggering sums funneled through figures such as Leonard Leo to fund conservative judicial activism and other initiatives, demonstrate how vast wealth can be secretly deployed to push specific, often polarizing, agendas. This kind of hidden funding allows powerful interests to amplify "culture war" issues, creating a sense of urgency and conflict that distracts from systemic problems. By keeping our attention fixed on these emotionally charged cultural battles, they cleverly distract us from bigger, systemic problems that might actually challenge their own power or wealth, like growing economic inequality, unchecked corporate influence, or serious environmental degradation.

When you strip it all down, the core strategies are incredibly consistent. It's like an ancient blueprint for manipulation. First, you identify or create an "other" - whether that was formerly enslaved people, immigrants, labor organizers, or some contemporary "enemy" group. Then, you exaggerate the threats this "other" supposedly poses to our safety, jobs, culture, or values. Fear of loss is a powerful motivator, right? They’ll always exploit existing anxieties, whether it's economic downturns or social changes, because that's fertile ground for planting seeds of suspicion. Crucially, they control the narrative, using whatever media is dominant at the time — newspapers back then, social media and partisan news today — to reinforce divisions and justify the status quo. And the ultimate goal is always to distract us from the real, systemic issues. By getting us to fight among ourselves, the underlying problems of power imbalances and economic inequality stay conveniently hidden.

It began with a conversation between old friends at dinner—all of us engineers who've been building systems and applications since the late '90s and early 2000s. One friend who has been experimenting with AI tools in his highly regulated workplace, was excitedly brainstorming ways to deploy them safely without compromising compliance. Another, fresh from a hackathon where they’d leaned heavily on AI-assisted coding, voiced a darker concern: "At this rate, will there even be a need for human engineers in the near future?"

That tension - between unbridled optimism and existential doubt - feels familiar. I've navigated similar technological crossroads throughout my 25-year career, watching each revolution reshape our craft while preserving its essence.

There's a particular thrill that comes with working in technology across decades—the kind that only reveals itself in retrospect. My career began in 1999, at the dawn of what would become the open-source revolution, when installing Linux meant compiling kernels by hand and debugging hardware conflicts via serial console. Today, as I fine-tune LLMs with RAGs, investigate MCP servers, I'm struck by how much has changed—and how the underlying ethos of computing remains remarkably consistent.

The early days were tactile in a way that's almost foreign now. Building a production server meant physically racking hardware, carefully selecting SCSI controllers, and tuning ext2 filesystems by hand. Linux, then still rough around the edges, offered something radical: complete visibility and control. You could strip it down to exactly what you needed, patch the kernel yourself, and understand every process running on your machine. There was no abstraction layer between you and the metal—just you, the source code, and the blinking lights of the data center.

The cloud changed everything. Suddenly, infrastructure became software-defined. Where once I'd spend afternoons crawling under raised floors tracing network cables, I could now provision entire fleets of servers with Terraform configurations. AWS turned capital expenditures into operational ones, and tools like Ansible and Kubernetes transformed manual processes into declarative code. The magic wasn't just in the automation—it was in the reproducibility. Entire environments could be spun up, tested, and torn down with a few commands. The craft shifted from physical assembly to architectural design.

Now we're in the midst of another sea change. Modern AI, particularly the open-model ecosystem, feels like Linux did in those early years—raw, powerful, and full of possibility. The parallels are striking: just as Linux democratized operating systems, open weights and permissive licenses are democratizing AI. Need to fine-tune a model for your specific use case? The tools are there, just as the kernel source was twenty years ago. Startups today can prototype AI applications in days that would have required months of infrastructure work in the past.

What's most interesting is how each technological wave has preserved the hacker ethos while removing entire classes of drudgery. We've gone from manually allocating IRQs to systems that self-optimize based on workload patterns. The throughline is democratization: Linux put operating systems within reach of anyone willing to learn; the cloud did the same for infrastructure; now AI is doing it for capability - making what once required specialized expertise accessible through natural language interfaces and open models.

Yet some fundamentals remain unchanged. The best engineers still peel back abstractions when needed. Performance still demands understanding what happens underneath. And that essential joy of creation—of solving interesting problems with elegant systems—persists regardless of the technological substrate.

As I watch today's developers build with AI, I'm reminded of the early Linux community—that same spirit of experimentation and open knowledge sharing. Yet legitimate concerns remain: the environmental costs of training massive models, the black-box nature of some AI systems, and the real possibility that these tools could displace certain development jobs while creating new ones. The most thoughtful engineers I know aren't just adopting AI—they're interrogating it, understanding its limitations as deeply as its capabilities.

This is why history matters. The lessons from our Linux and cloud migrations teach us that technological upheavals tend to be neither as apocalyptic nor as utopian as we first imagine. The developers who thrived through past revolutions weren't those who resisted change or blindly embraced it—they were the ones who learned to harness new tools while maintaining their fundamental craft. Today's AI revolution demands that same balanced approach: enough optimism to explore its potential, enough skepticism to use it wisely, and enough historical perspective to know we've navigated similar transformations before.

The tools will keep evolving, but the best engineers will continue doing what they've always done—peeling back layers when needed, solving interesting problems, and remembering that technology ultimately serves human creativity, not the other way around.

When The Washington Post documented the $38 billion in government support behind Musk's empire, it should have settled the debate. Yet Semafor's recent piece reads like someone analyzing a magic show while refusing to acknowledge the trapdoors.

Turns out, Elon's empire runs on the kind of government assistance that would make a 1980s welfare queen blush. We're talking $38 billion in contracts, subsidies, and good old-fashioned corporate welfare. But sure, he's totally "self-made."

Tesla’s State-Sponsored Roadtrip

• $1.3 billion from Nevada just to show up (the Gigafactory "incentive package")
• $2.4 billion in EV tax credits - because nothing says "free market" like Uncle Sam paying your customers
• $6.8 billion from selling imaginary pollution credits to actual car companies

Fun fact: Tesla would've gone bankrupt in 2013 without those sweet, sweet government-mandated ZEV credits. But please, tell us more about "disrupting" the auto industry.

SpaceX: Welfare Checks With Rocket Engines

• $11.8 billion in NASA contracts (aka "please don't let Russia own space")
• $4.3 billion from the Pentagon (because nothing says "libertarian" like military contracts)
• $1.3 million/year rent on NASA's launch pad - that's cheaper than a Brooklyn studio apartment

The Semafor piece somehow forgot to mention that SpaceX's entire business model is "government pays us to deliver government stuff to government stations." But hey, details schmetails.

The Cult of Elon

What's most fascinating isn't the money - it's watching otherwise smart people twist themselves into pretzels to pretend:

1. Subsidies don't count when Elon gets them
2. NASA contracts are "private enterprise"
3. A guy who built his fortune on government programs is somehow anti-government

It's almost like... the author wants to believe. Like they've seen the holy spreadsheet of Starlink profits and achieved enlightenment.

The Bottom Line

Elon Musk didn't build that. We built that - through taxes, contracts, and policy. The real innovation wasn't the tech; it was convincing everyone that corporate welfare is "disruption" when your guy does it.

The WaPo exposed the receipts. Semafor chose to admire the emperor’s new clothes.

I had been feeling down and depressed the last few days. Perhaps it was the weather, or the cold and cough I still have or the unnecessary and unexpected drama at work. All part of the human condition, I’m pretty sure.

And so, we did nothing yesterday and had planned to go to the museum today.

So glad we went to the museum, specifically the MoMA PS1 in Queens. It was a short ride on the subway from our nest in Clinton Hill.

This was my first visit to the PS1. It is a beautiful location and space. There are huge open spaces as you enter, with tables and benches in graveled sections. There is interesting interplay of sunlight and shadows in these sections, accentuated by the high walls of the museum. The exterior of the building itself looks like a school or a prison from a period drama on BBC or PBS.

The building is three floors, with two levels of stairs that take to you the first level. Once you land on the first floor, there’s a café to your right. It was closed this cold wintry afternoon in January.

There are two large doors that take you into the building. We took the one on the right and walked through another set of doors and turned right.

The first exhibition on our left felt like a community space and the art there felt nascent. It seemed to reflect and resonate with my values and experiences. Nothing new for me there. Later, while reminiscing, I came to the conclusion that this was a good appetizer to what lay ahead.

We walked out and took one of a set of stairs that took us to the second floor. On this floor, we entered a door to our right into a room that had two entrances on either side. We entered the one to our left.

This exhibit had artwork that was a combination of embroidery and oil on canvas. There were themes of anti-capitalism and queer imagery. The art itself looked shoddily done. The word kitschy constantly popped up in my head and I wasn’t entirely sure if it was the right word.

The use of embroidery on canvas was intriguing. Artists do come up with some very creative ideas.

Next, we entered the exhibit to the right. The paintings, mostly acrylic on canvas were really bright and colorful. The scenes chaotic, irreverent and nonsensical.

After a bit of digesting, the paintings got the gears in my head going. It was like completing the process of stepping into a familiar yet unfamiliar world. The words and the individual visual elements felt familiar, but the combination did not. The artist was taunting me, challenging me to glean what they were saying.

This, to me, felt like the main course for this brunch. This is when I had the epiphany.

This is what I consider Art. Art that takes me in and through entirely new and different worlds, where I want to question my own reality and experiences, question my own place in this world etc.,

All art is art and worthy of our time. And as the audience or viewer, it is our responsibility to glean the essence of what the artist is saying. The more difficult and challenging that endeavor, the more interesting the art. Art then truly reveals who we are.

This artist was Umar Rashid.

After that exhibit, we took the stairs to the third floor and caught the remaining exhibits. One of them, artwork and exhibits by Jumana Manna - one movie in particular, I think, called the Foragers made me ask the question - has Israel been committing genocide all this while against the Palestinians?

We finished our tour of the third floor and walked down to the first floor. There were a few remaining exhibitions we hadn’t seen that had to be seen to complete a very eventful visit on a beautiful, sunny and crisp day.

We left the museum through the door on our right.