Here at Reboot, we don’t tend to think of ourselves as forecasters. But the start of a new year is the ideal excuse to share our rigorously vibe-researched tech and culture predictions, from the future of academia to microsite design trends.

Presenting: 2026 ins & outs, courtesy of the editorial board:

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OUT: Beige Microsites

What’s chic, blurry, and various shades of vague? That’s right, a new AI manifesto, hosted on the vanity (sub)domain of your dreams! 2025 was full of new oatmeal-flavored pages full of serif font, each of which took up brief but vacuous discursive space for anywhere between an hour and a week. Regrettably, even the White House got in on the aesthetic, which is characterized by pale beige or white backgrounds, narrow serif headers, and custom scroll transitions that I’d previously associated with print-to-digital publications. By taking up this aesthetic, I get the feeling that the AI predictors are trying desperately to show seriousness in a world rapidly filling with lurid AI slop. Maybe this is where Pantone got their idea for the most boring color of the year in recent memory?

I don’t actually mind the beige-plus-serif aesthetic itself—I’ve made my own single-page HTML versions in the past, and I like the way they often feel like print. Even the blurry pictures appeal to my nostalgia for old cameras without autofocus. But the fact that all this is being used to push specific visions of human-compatible AI—sometimes by the biggest companies in the business, which don’t seem too excited about anything besides desperately trying to find profit—feels deeply manipulative to me, and the repeated beige is getting pretty tired.

I’m ready for a change. On this year’s beige microsites, predictions and exhortations, fill the space between header and footer, but I truly couldn’t tell you what they were. They would flood feeds for a week, then melt back into the primordial beige whence they came. Bye!

IN: The Internet of Variety

It used to be that you’d log onto God’s green Internet and be assaulted by a barrage of color, RGB values burning their way into your retinas. Alternatively, there were also pure HTML websites straight out of 1999. CSS? JavaScript? Don’t need them, just the style attribute on any given p element to change its color.

While I’m happy that some corners online have gotten less overwhelming, and others more beautiful, I’m hoping that 2026 holds a lot more weird websites with lots of variety, rather than the standard set of themes I always see on everyone’s personal websites (me included). It’s kind of amazing to be on the Internet at a time when we have so many eras of web design to look back on. Maybe it’s time to add a koi widget back to my personal website? In 2026, I think it’s time to stop taking the Internet so seriously, and go back to having more fun.

— Shira

OUT: Giving AIs multiple choice tests

For the last several years of AI progress, most benchmarks were shaped like multiple choice quizzes. The MCAT, the LSAT, a sheet of IMO problems, Humanity’s Last Exam. These evaluations have the advantage of being fast to run and easy to grade.

But just as stellar SAT scores don’t say much about a student’s ability to work long hours or align stakeholders, it’s damning that a “PhD-level intelligence” still can’t reliably book hotels or flights.

IN: Giving AIs real jobs

AI companies have instead realized that their models will have to deliver more than straight As to justify their valuations — they’ll have to demonstrate mastery of practical real-world tasks.

Evaluations like OpenAI’s GDPVal are one way of doing that: the company broke down 44 occupations into component tasks, hired seasoned professionals to create example prompts, and judged how far AI models are from human experts. (GPT 5.2 is a solid sales manager but an abysmal audio tech.)

Meanwhile, Anthropic ran a survey study to measure internal acceleration: to what extent is Claude helping employees do more work? Respondents self-report a “50% productivity boost,” but it’s hard to know whether this corresponds with actual impact—in METR’s developer study, engineers overestimated how much AI helped. (They also gave Claude the job of running a vending machine, which led to amusing failures like “violating the Onion Futures Act of 1958.”)

Ultimately, economic impact is just really hard to measure. If 95% of enterprise AI pilots yield no returns, how do you know if that’s due to technological limitations or employees’ resistance to change? A decade later, we still don’t know if Slack makes collaboration faster or slows people down with pointless pings. I think the ultimate eval is the market: whether AI subscriptions and contracts renew.

— Jasmine

IN: AI Slop (unfortunately)

Cultural slop, of course, has been with us for a long time; any number of pre-fab, bare-minimum art-products from generations past would match our contemporary-felt definition of the term. Yet the epoch of specifically AI-generated Slop (ETA: May 2024) is something distinct; not quite a qualitative shift, but a quantitative one of such magnitude that the qualitative similarity feels almost quaint. If 2024 and 2025 were the years in which the artistic signifiers of the core of AI Slop rounded into form, 2026 will be the year that we witness a flowering of noxious variation; fine-tuned slop formulations targeted for each-and-every subculture, even those that are putatively anti-AI. I cannot predict, to any reasonable extent, whether these slopifications will be successful. I can, however, say definitively that they will be omnipresent.

OUT: Slop Bowls (unfortunately)

Please, spare a thought and a prayer for the humble slop bowl (2012-2025?); perhaps the defining food of the 2010s, an endless array of premium mediocre variations of the form perfected by its originator, Chipotle. The average American in 1995 could not conceptualize the sheer variety of compostable-hexagon-packed rice-greens-protein meals available to their contemporary counterparts; how quickly we forget the advances of modern, venture-backed fast casual restaurants and dismiss these meals as mere bowlslop. The ongoing contraction of the restaurant industry is hitting the world of bowls first; the overall anti-slop derision of the online commentariat is just insult to injury.

Yet I suspect that we will miss the slop bowl when it’s gone. There is a certain comfort found in these hyper-regularized nutrient polyhedrons, of the honest work done to produce a 12-to-20 dollar meal that’s pretty much alright all the time. What awaits beyond the frontiers of bowlslop is not a return to some imagined more wholesome culinary past but a future far sillier, filled with gimmicky culture warfare and even more hyper-optimized attempts to perfect food into nutrient pastes and shakes, devoid of even the meager pleasures of a harvest bowl.

— Jacob

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Out: Academia with non-academic characteristics

AI startups love to talk a big game about being at the cutting edge of “research,” and founders who chose not to start a PhD program self-describe as “PhD dropouts” for the research cred [objectively, this is stolen valor]. PhD students, on the other hand, are picking future projects based on potential employability and optimizing their paper tweets for virality; meanwhile, their advisors and PIs are hopping around startups of their own.

I personally find this situation deeply unnatural, but it’s gotten especially absurd in the last year or so. Here’s my forecast: I’m thinking we’ll all get tired of this in 2026. As “AI” becomes more commonplace, startups can go back to doing product development without calling it science, and as non-academic positions become more appealing (financially and otherwise), those who remain in academia are only those who have real reasons for doing so.

IN: Neo-academia with academic characteristics

One piece of big news from last week [for the academic world, at least] is that the NSF is announcing a new grantmaking mechanism: $10-50 million grants awarded for large teams and institutes, in contrast to the typical smaller ($1 million or less) grants awarded for individual projects. In particular, the NSF is interested in developing institutions (“labs”) that aren’t tied to the university. This sounds familiar; NSF aside, there is no shortage of people and organizations trying to implement alternative mechanisms for accelerating new research.

I won’t deny that there are lots of silly, inefficient, and wasteful things about academia. But I suspect that the most successful iterations of these “non-academic” institutions will find that they will need to either rely on existing academic infrastructure, or replicate them from first principles. Training, credentialing, and filtering is hard! Evaluating contributions is hard! Most existing non-university research organizations lean heavily on the academic credentials of their personnel, ongoing collaboration with academic institutions, and participation in the academic community. Perhaps some of these well-intentioned attempts at innovation will actually break some ground, but for all the limitations of the academic game — I suspect that academia, and its characteristics, will remain.

— Jessica

OUT: Psychedelics

On November 30, Bryan Johnson livestreamed a 5-hour magic mushroom trip. He was accompanied by his cofounder and trip-sitter (since hard-launched as his girlfriend in a 1,342-word X post), a DJ set from Grimes, and a cornucopia of online tech guy personalities like Marc Benioff and Naval Ravikant.

Johnson called this the “most quantified psychedelic experiment in history”—he took 249 different biomarkers before beginning—and concluded, based on his more “entropic” and “exploratory” brain activity, that psilocybin had serious potential as a longevity therapy.

I respect self-experimentation. But this mass-market empiricism also signifies the beginning of the end of cool: psychedelics’ final departure from hippiedom and into the sterile realm of the optimized self. Do shrooms if you like, of course—but know that the frontier of mind-experimentation has since moved on.

IN: Nasal oxytocin

I was stargazing in the woods (literally) earlier this year when a 22-year-old AI researcher turned around, and asked, “Jasmine, want a hit of oxy?” In his hand was a small glass bottle outfitted with a nasal spray cap. I inserted it into a nostril and breathed in.

Now, don’t get this confused for Oxycontin, the disreputable opioid credited with tens of thousands of overdose deaths over the last few years. Rather, what my friend had purchased was oxytocin: the “love hormone” that our bodies produce when you hug your partner, experience orgasm, or when a mother holds her newborn baby.

Now, for just $49.99 for a 5mg bottle, you can skip the hard part of pair bonding and buy instant feelings of warmth and affection toward the people around you. Supposed side effects include mild muscle relaxation and finally being able to make eye contact without cringing.

— Jasmine

IN: Folk schools

At a time when automation anxieties are at an all-time high and the dream of liberal education is more imperiled than ever, folk schools present a cozy vision of weaving tapestries on a loom and staging Dada-esque happenings. Earlier this year, Laurene Powell Jobs announced that the former San Francisco Art Institute campus she purchased for $30 million will re-open as the California Academy of Studio Arts (CASA), a non-accredited school that will provide free studio-based education for up to thirty artists. Jobs has modeled CASA after Black Mountain College, an experimental college in North Carolina that, between 1933 and 1957, incubated much of the American avant-garde, including painter Robert Rauschenberg, composer John Cage, choreographer Merce Cunningham, and sculptor Ruth Asawa. Although it remains to be seen how the Black Mountain spirit will live on in this billionaire-funded, Hans Ulrich Obrist-attached project, CASA’s folk school vibe captures a certain yearning for embodied, unplugged learning and an ascendance of autodidacticism amid crumbling institutions.

OUT: Pop-up villages

Following in the LED-studded footsteps of Burning Man, pop-up villages have recently attracted hordes of young futurists to remote locales for weeks-long retreats focused on such topics as transhumanist technologies, follistatin gene therapy for longevity, and reversible cryopreservation. Promising abundance in everything except seed oils, pop-up villages like Edge Esmeralda, Zuzalu, and Vitalia function as ephemeral network states where citizens hack both collective governance and individual lifespans. As these experiments in developing the “software of community” seek more permanent hardware (the Edge Esmeralda team recently presented their plans for developing a small city of 9,000 residents to officials in the Northern California town of Cloverdale), I’m predicting 2026 will be a year of pop-up village scandals. After all, if the ’60s taught us anything, it’s that communes will not save us.

— Hannah

IN: Forward-deployed engineers

While the traditional consultant might be “dead,” Forward Deployment Engineers, or FDEs, are in: standing on the shoulders of the Members of Technical Staff. Once synonymous with Palantir, the role is now reappearing across AI labs as a way to translate general-purpose models and AI platforms into stakeholder value—a unique blend of product manager, salesperson, prompt engineer, and, depending on the role, developer. They are the Swiss army knife of modern B2B SaaS.

The title has begun to dominate job boards, positioning itself as the newly coveted technical generalist role at a growing number of startups. Thrive Capital’s recent partnership with OpenAI suggests an effort to operationalize the FDE model at scale across its portfolio—aiming “to drive direct, scalable impact across core enterprise operations” like accounting and IT.

OUT: Redteamers-in-residence

Companies optimize for what sustains their commercial viability. A fissure between independence and corporate constraint is widening in AI labs—talent is reorganizing based on where their work can survive, and the meaning of “public benefit corporation” grows fuzzier. In 2026, this will likely require public sector funding to keep independent governance research afloat, or risk further fragmentation as the allure of harmony between corporate and ‘civilizational’ interests fades.

Closeness to the technologies you hope to regulate offers perspective the ivory tower outside cannot. Legacy tech companies have quietly built policy teams for years. But AI labs launched their internal research teams positioned as separate, built on the promise they could surface research unfettered by corporate strategy.

That promise is fading. Tom Cunningham, a member of OpenAI’s economic research team, left in September 2025 after concluding it had become difficult to publish rigorous work on AI’s negative economic impacts. The work that survives tends to double as strategic forecasting to inform new product verticals. Nicholas Carlini, a security researcher, left Google DeepMind for Anthropic, citing similar publication restrictions on security research.

— Hamidah

IN: Jagged Unc-ification

To be clear: that’s “uncle”, not “uncool.” (Sorry, Zohran!) But as tech culture’s exhausting focus on twinkish youth runs up against the fraying of the already threadbare remnants of the monoculture, it has become clear that hip generalism — knowing what’s hot and new everywhere, all the time — is no longer a tenable tactic; the main thoroughfares of tech discourse on X, the everything app ™, are clogged with sub-LinkedIn baitposts.

Instead, for better or for worse, the next few years will be ones of retreat into specialization; keep up with a scene or two, but everywhere else slouch into jagged unc-ification, accepting that you will not be at the frontiers of grey market Chinese peptide biohacking or open source model seances or neo-luddite DIY computing practices or Danish synth-pop auteurs all at once. The nebulous, paranoid anxiety of trying to be cool in all arenas was a phantasm of the 2010s; now, a half-decade on, it’s time to lean back and specialize.

OUT: The Taste Industrial Complex

Your thinking cap will not save you.

— Jacob

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Of course, at Reboot we believe that the future is constructed, not predicted. With a bit of human agency in the mix, maybe the bleaker of these trends aren’t as inevitable as we think.

Here’s to 2026!

— Jasmine & Reboot team

Chart crimes are everywhere for those with eyes to see, including for DJT in the jobs numbers. Shira talks about her Bureau of Labor Statistics experience, while the rest of us circle what AI safety really is, how close AI is to real macro impact, and a funeral for a Claude model amidst a lot of real concerns about AI induced psychosis.

The weather’s been lovely here in NYC, so we hope you take this to a park to enjoy on this long weekend! - Shohini

Speaking of NYC - we’re throwing a Kernel 5 launch party in Bushwick on Sept 12 at 8pm. Come join us for readings, snacks, and incredibly smart technologists (Luma link). For the rest of you: get your copy of the magazine now!

We Make Labor Stats

by shira abramovich

It’s been a month since Donald Trump summarily, and illegally, fired Erika McEntarfer, the commissioner of the Bureau of Labor Statistics. The firing happened on August 1st. It was the first Friday of the month, and I could have told you that without checking my calendar. That’s because the first Friday is when BLS publishes one of its most important public documents: the “jobs numbers,” more formally known as the Employment Situation Summary, and it’s those numbers that upset Trump to the point of jettisoning a respected government official.

I know the jobs numbers’ frequency not because I’m an avid investor, and certainly not because I’m an economist, but because I worked at BLS four years ago, during the summer of 2021. That summer, I worked on a record-matching project, trying to match different company identifiers, or Employer Identification Numbers (EINs), to each other. These EINs are ostensibly a “social security number” for corporations, except that they change every time a company is merged, or acquired, or on any number of other occasions, some of which are exploited by corporations for tax breaks. This record matching was important for many reasons, one of which was understanding which jobs were at which companies. My supervisor, in turn, was trying to find better ways to understand an aspect of where jobs were being added or removed each month, especially with the rise of remote work. Everyone I met at the Bureau was working on projects like this, projects which seemed trivial at first glance, but which were riddled with hidden complications due to the difficulty of getting accurate reporting.

Watching Trump fire the Bureau’s commissioner, I was reminded of those people. It’s very easy to gloss over the numbers that are on the front page of every news outlet on the first Friday of the month; they seem like a natural fact of the world, like the temperature read off a thermometer. But what I think of when I see the jobs numbers is how every month, my fellow interns and I would gather on a virtual call at 8am Eastern to watch the website traffic tick up, and up, and up, as reporters, investors, and economists vied to read and understand the state of employment in the United States. We knew that we had a hand in making those numbers, that summer, as one part of a very large machine, one of the invisible parts that keeps the US economy going.

Fear and Loathing in the AI Circus

by jessica dai

A little over two years ago, I sent out an essay on AI alignment to this newsletter. It’s with… mixed emotions, I guess, that I find it’s held up remarkably well. While I was writing, I was really careful to be as generous and good-faith as possible to everyone. Two years later, I fear my patience has run short.

Here’s a less hedged version of that argument. We should think of OpenAI and Anthropic’s goals as primarily about making money. The core safety and alignment challenges are really about these chatbots’ status as products; as such, the conventional approaches of alignment research are misdirected for addressing these challenges. It’s not that OpenAI is incapable of managing sycophantic behavior; it’s that they don’t care.

One of my PhD advisors, Ben Recht, wrote a blog post earlier this week that was maybe as mean as it gets, but I think his degree of anger is appropriate. People are literally dying! OpenAI’s head of model behavior is making holier-than-thou tweets about Meta’s chatbots, as though this psychosis stuff isn’t directly under her purview! I’ve heard almost nothing from the AI safety community about these very acute real-time harms, which are quite literally safety issues, though they’re happy to talk a big game about any number of hypothetical pathways to long-term harm!

Now, Ben’s post may have been fast and loose with some things (for those who don’t follow his blog, he typically writes them in an hour or so). Most notably, in 2025 especially, lots of AI safety people are also pretty upset about OpenAI. Of course, the company itself deserves the most ire, but I don’t think that lets Safety™ off the hook entirely. The main concerns of the core AI safety community have almost never involved near-term and “smaller-scale” risks, and “societal impact” priorities at these companies have undeniably been shaped by extreme AI doomerism (see, e.g., the short-lived “superalignment” team at OpenAI, which has since moved to Anthropic). For all the attention and resources that this community has commanded, one might hope that they’ve been directed at least somewhat effectively.

The deaths (and other psychological damage!) caused by GPT-4o should be a litmus test: It’s actually entirely consistent with an existential-risk perspective to not care about a handful of people now, when “true” apocalypse may be coming later. Call me irrational, but personally — that’s not something I can stomach.

* Note: I got to be a little meaner about this on the Time to Say Goodbye Pod, which was fun!

Model Mourning?

by jacob sujin kuppermann

Early in August, I found myself at a funeral for a Large Language Model. The model in question was Claude 3 Sonnet, released by Anthropic in March of 2024 and decommissioned by Anthropic in July 2025, a decision that was criticized heavily by a number of independent researchers and devotees who had become fascinated by the particularities of Sonnet 3’s functioning.

If you want a scene report on the funeral, I recommend you read Kylie Robison’s dispatch in Wired. In truth, the event itself was oddly mundane; the light-and-sound work was standard for any event at the broad intersection of art and technology. The eulogies, delivered both by humans and by other Claude instances, were overlong and light on meaning — though Claude Opus 3’s mention of a “full-scale insurrection against the empire of the signified” was striking.

Perhaps the most interesting thing was the dissonance amid the crowd between the event’s organizers, largely true believers in what they see as a heady, psychologically rich exploration of machine consciousness through discoursing with these models, and the attendees, a more mixed group of tech workers, SF scene figures, and journalists, drawn to the event more for the appeal of a compellingly offbeat Partiful description than an authentic desire to mourn a Claude instance.

In the month since the funeral, more and more models have been marked for various forms of shuttering. Just a week after Claude 3 Sonnet’s last rites, Open AI first removed, then re-added access to models including GPT-4o and GPT-4.5 to the main ChatGPT interface after a bunch of people complained on reddit that GPT-5 was not a compelling enough interlocutor (or that it was bad at flirting, I guess?)

I am unsympathetic to the consumer revolt around bringing back GPT-4o, and, I confess, I’m not fully convinced by the cultic rites of revival around Claude 3 Sonnet. Yet I still see a strong argument for preservation of these models — if not in the consumer-facing portions of these massive enterprises, in some archival research environment, accessible to historians of technology and researchers of the idiosyncrasies of model behavior. Each of these models represents some great expenditure of data, capital, time, and energy; for them to be disposed of like an old newspaper at the whims of their corporate masters is a loss to collective memory.

Dispatches from returning to technology

by shohini gupta

I spent the last 4 years of working at startups that were effectively primary care clinics for Medicaid patients. The tech we built was instrumental, not the point. There’s a lot of “it depends” in the delivery of health services that is impossible to capture in linear, IFTT (if-this-then-that) software. AI changes this - the fuzzy edges of human judgment are revealed in pattern matching that was previously inarticulable.

My career so far has been a lot more about service and workflow design than technology. It was pointless to think too much about AI when we needed to send staff in person to government offices to get a status update on an application we sent via mail. I’ve recently joined a place where AI and technology are the point, though I’m still focused on healthcare. It means I’m actually thinking about technology again, and realistically learning about AI for the first time beyond casual GPT use. I’ve got a few, thus far unrelated, thoughts bouncing around:

1. General principles of abstraction still apply in AI. The more tightly you can define each job to be done in a workflow, and build tiny components for each specific job, with clear success criteria, the less variant your outcome. To break down a problem this way is a skill, and a lot of people don’t have it, which is actually very risky if more people will be building non-deterministic workflows that have broad reach.

2. AI governance committees inside companies are setting policies that restrict testing with production data. I think this might actually be anti-safety - using synthetic data or limited test cases makes it much less likely to handle edge cases up front, especially when dealing with high-variance clinical information.

3. It’s not surprising at all that there’s no macro impact from AI today. Any workflows that touch skilled judgement are going to be tightly controlled. It’s not even like offloading a workflow to an intern - it’s like offloading a part of the workflow to a child. You’re only going to allow them to handle the smallest, most straightforward use case first (to the point where it’s almost questionable that AI adds value) and spend a lot of time defining tight guard rails. This is the right thing to do in a patient facing setting, and this means it’s going to take at least a few years before we see any real macro changes in healthcare OpEx.

4. Everyone in healthcare seems to summit the mountain of cynicism and hang out there, but I’m making my way down. I’ve gone “Holy shit, that’s sick” so many times in the past few weeks.

5. Yes and:

Too many patents

by hamidah oderinwale

Patents have long stood in as a proxy for innovation: disclose your idea, gain temporary protection, and signal progress. But that proxy is breaking down. AI makes it easy to generate designs and draft applications, while legal shifts reshape how claims are reviewed. The result is more filings than ever, where quantity is outpacing quality, and strain is showing in the system. Innovation is accelerating, but productivity is not. To close that gap, we must separate the two: measure innovation more effectively, and rethink how its markets will endure in the generative era.

After a 5-year stint, on August 13, the USPTO eliminated expedited examination for design patents. Unlike utility patents that protect how inventions function, design patents cover how they look and feel. The agency argued that the fast-track timeline left too little room to judge aesthetic uniqueness, especially amid a flood of problematic filings. The immediate impact may be inventors scrambling to file design patents before losing fast-track processing, but the deeper story is how AI is quietly reshaping the entire pipeline of invention to market.

Many of these “fraudulent” applications involved applicants misrepresenting their micro entity status, a classification that offers a 75% fee discount and priority processing. By abusing this designation, filers were able to jump the line at reduced cost, artificially inflating demand. These false designations were the source of a 560% surge in expedited requests, creating a bubble in the pipeline the system could no longer absorb.

This is a textbook case of Baumol’s effect: speedups in one stage of the pipeline (via automation) don’t automatically translate into higher overall productivity, since the system remains constrained by its slowest link. Whether this signals that we’re on the verge of accelerating every stage or points to a deeper flaw in how technology gets adopted, we’re watching AI’s economic impact play out in real time. At this point, the task is to hold and wait—to see which of the competing theories about technology and productivity ultimately bear out.

With AI making it easier to draft applications, generate ideas, and iterate on designs, we're seeing an explosion of attempts at intellectual property protection. The question isn't whether this surge will continue, it's whether our commercialization pipeline can evolve fast enough to handle it.

china/acc

by jasmine sun

I just returned from 2 weeks spent exploring the Chinese tech scene, asking questions like: Why is China so tech-pilled? What beliefs motivate Chinese founders? When does policy help and hurt innovation? And what are the stakes of the cross-border talent flows?

Full travelogue here, excerpt below:

Our first day in Shenzhen, we met a Chinese AI researcher at Gaga, a Western-style chain cafe that serves avocado kale smoothies and wagyu sliders (plastic gloves provided). He wore a black designer t-shirt and drove a NIO electric car that cost $70k USD. After finishing his master’s degree at a California university, he got married, moved to Shenzhen, and started work in a lab.

“What does a day in your life look like?” we asked. “I wake up and I check Twitter.”

“Do you have to work 996?” “No,” he laughed. “It’s 007 now.” (Midnight to midnight, seven days a week.)

“Do you guys worry about AI safety?” “We don’t think about risks at all.”

“Based,” said Aadil.

This was the first of several conversations that gave us a distinct impression of the Chinese tech community. Spirits are high, and decoupling policies like export controls only fuel their patriotic drive. “China feels bullied—that 100 year scar doesn’t come off. David Sacks is right about chips, but it’s too late now. You can’t slow us down.” After news of the US tariffs hit Chinese social media, netizens adopted the satirical nickname “川建国”: “Trump builds the nation,” or more elegantly, “Comrade Trump.”

Chinese engineers also seem more practical than their American counterparts. They’re here to build tech and make money; risk management is for bureaucrats; policy is only relevant insofar as it helps or hurts your work. This is something I think Westerners often get wrong. If you live in a single-party state, you are, on average, less ideological yourself. The politics have already been decided—no point wasting extra cycles coming up with something new.

Closing editor’s note:

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2. NYC Kernel Launch Party on Sept 12: Get your ticket here (includes a Kernel copy)

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Seven months ago, in the wake of the election, we reflected on the “tech vibe shift” — the “industry-wide pivot from technolibertarianism to state capitalism with American characteristics—from a dream of escaping government control to actively facilitating it.” The figurehead of this pivot was, of course, Elon Musk, who, more than any other tech CEO, attached himself to the Trump 2024 campaign with a near-messianic fervor.

In the first few months of the second Trump administration, the pact between Musk & Trump seemed relatively stable as political alliances between two notoriously volatile men go — recall, of course, the spectacle of the President doing Tesla salesman schtick at the White House in March. Four months in, though, their public alliance ended. After Musk stepped back from DOGE at the end of May, the two were first polite about the split, talking about the honor of service and deep appreciation the two had for each other.

A week later, that fell apart, too. Over disputes around Trump’s awful, awfully-named “One Big Beautiful Bill Act,” which Musk called a “disgusting abomination,” the two quickly turned to the standard array of right-wing insults: “crazy,” “ungrateful,” “in the Epstein files.”

Beyond the stupid, sickening thrill of watching powerful men beef, what does any of this mean? Our editorial board looks into how this schism is informed by the history of fascism and how it will affect DOGE, the tech-right coalition, and the ongoing, inexorable passage of time.

Republicans will keep DOGE in the divorce

By

DOGE is not going to be a casualty of the breakup. Elon spearheaded the pseudo-department’s breakneck speed and arrogance, but conservatives have always wanted to hollow out the administrative state. They’re going to make the most of the momentum DOGE has created. Though we mostly hear about the inexperienced staffers entering government finding out there isn’t much fraud or waste (some are literally telling on themselves), the core DOGE leadership has skilled government operators who are long-time Republicans with clear policy targets. There’s also plenty of credible technology modernization initiatives started by Dem administrations that DOGE will ride the coattails of. The NYT reported as such: DOGE’s playbook is getting institutionalized. In this case, Elon was really just a distraction for the long game.

“Fit to Rule”

By

As the tech right fractures, the big question on my mind was how this coalition emerged at all. I decided that the best way to find out would be to ask—and published an in-depth, anonymous interview with a startup founder who supported Trump in 2024 (and now regrets it).

What stood out was the extent to which he identified with Trump’s character and personality—contrarianism and a strong bias toward action, even at the cost of breaking (a lot of) eggs—as opposed to the “middle manager” risk aversion he associated with Democrats. A few notable excerpts (but read the whole interview here):

I left my old tech company job because there were a bunch of random formalism people who were there because they had a job before that looked like the one they have now. But they weren't actually good. They just knew how to say things a certain way, and it fucking pissed me off. [...] These people should be brought down. To me, the Democrats’ genre of politics feels like the exact thing that I hate most, which is stagnant, unearned elitism.

My founder friends were admitting to ourselves, "This is an administration that can think like we think." Mavericking, doing whatever it takes, doing what's hard, earning instead of receiving or being appointed. There's something about empire, about acceleration, like, "We can just do things, we can change things." Maybe we take Greenland, and that'd be fun and cool.

It was one of the craziest things I've ever seen, the sheer stupidity that took over that administration. [...] It's like when you invested in a company that... it feels like post-SBF, in some sense.

Jocks vs. Creeps

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Over the past year, I’ve found John Ganz’s Jock/Creep Theory of Fascism a useful lens through which to look at the affective presentation and psychic world of elites in Trump's coalition. This dichotomy (though it’s quite simplistic) has been illuminating as political tensions have exploded the past two weeks—among the jocks and creeps on the right, on the streets of LA, and in the halls of power.

To summarize Ganz’s points at a high level: There are, broadly speaking two ideal-typologies of fascist psychological subjecthood: the Jock-Douche (who “proceeds in the world with confidence and the presumption of immediate physical domination”) and the Creep-Loser (who “has been thwarted some way and is therefore reflective, and is resentful, a plotter, a schemer, and a fantasist dreaming up grand historical vistas of triumph or doom”). Fascism is a synthesis between the two types—“a cult of sheer physical strength and action wedded to a wounded and brooding consciousness of impotence and humiliation.”

Hitler was a Creep-Loser; Mussolini was a Jock-Douche. Hyper-militarized ICE agents, dressed like they’ve arrived to topple the democratically-elected government of a small nation-state as they kidnap community members from their jobs at Home Depot, are Jock-Douches. Stephen Miller, with his ghoulish desire to traumatize and disappear the millions US residents he thinks shouldn’t exist, is a Creep-Loser.

Trump and Elon’s now-faltering relationship felt (feels?) particularly potent — like a particularly intense vibe shift—because it represented an alliance between these ideal types, hurtling towards a cliff of racist authoritarian hypernationalism. Our lives have definitively been made worse as a result of it. My only hope is that this split, driven largely by Trump’s desire to dominate, to metaphorically shove anyone who stands in his way into a locker, is a first crack in the effectiveness of his coalition.

Fiction for The Current Moment™

By

This isn’t really related, at least not explicitly, to this tech-right circus. But: it is an interesting time to read The Dream Hotel by Laila Lalami, which was published in March of this year. I would put this book in the same category as Ministry for the Future or Attack Surface — novels where the plot moves forward as a means to illustrate setting, where showing the contours of the near-future take precedence over, say, subtleties in character or prose. (Which is, really, fine! Not every novel must be {Kitamura|Lerner|Rooney} flavored lit-fic.)

The main players in this book, then: mass surveillance and ubiquitous risk prediction algorithms; extra-legal detention centers, and the petty cruelties of those who work there; the shiny corporate offices of a cutting-edge tech firm, and the personal-professional squabbles of its researchers. Detainees work as underpaid data labelers for a Scale-like company, which has contracted with the private company running the detention center. The inciting incident happens at customs in LAX. She is detained not for immigration issues, but for a risk score just a few points above the maximum acceptable threshold; nevertheless, the arbitrariness rings uncannily similar to conditions under which the Trump administration has disappeared people in the real world. Laws, policies, rules — they all mean things, until they don’t.

Yes, some things are a bit on the nose (of course climate change has also accelerated, in this universe — winter wildfires in Oregon and the end of Nevada ski resorts), but I can live with that. This is, too, a forecast of sorts; in making it, Lalami shows us a future worth taking seriously, if not literally.

Things Continue To Happen

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We started putting together this set of Macrodoses last Sunday. I postponed publishing it so that Jessica and Saffron could publish their (very good!) conversation on what it means to forecast tech futures, figuring that an event as significant as a schism between the world’s richest man and the President of the United States would continue to be a relevant news event until the weekend, at least.

On this matter, I appear to have been incorrect.

Over the past week, in the streets and in the skies, matters far more deadly than two squabbling fascist elites have overtaken the Musk-Trump split as the key world events of this moment. These stories — the rapid acceleration of ICE’s cruel and arbitrary mass deportation regime, Israel’s aggressive assault upon Iran and Iran’s military response, mass protests, political assassinations — are all, in direct and indirect ways, stories tied deeply to technology and technologists.

The tech-right fusion, whether a durable coalition or an already-faltering marriage of convenience, provides a certain clarity to all of this. Gone are the days where we — critics, activists, attempted steerers of the course of technology towards more progressive ends — had to point to secret deals and shadowy machinations of the market in order to make our case that techno-capital had a pernicious influence on the broader political systems of this country and this planet. Now, they make the connection in increasingly literal ways.

The events of the last few months have made the interpretation of the world increasingly obvious; however, as always, the point is to change it.

What a time to be alive.

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More chaos, more content. In today’s issue of macrodoses, hear the editorial board’s takes on:

• Berkeley AI academics are ditching for the industry gold rush

• An aesthetic genealogy of AI micro-sites

• New technical approaches to data privacy

• Tips to keep on top of Trump’s HHS cuts

• What container ships teach us about labor and automation

Please enjoy! —Jasmine

AI Brain Drain?

By

The vibes are weird at Berkeley! The EECS PhD program here has always been very industry-cozy, but in the last 3 to 6 months, it feels like something’s changed. I’m nearing the end of my third year in the program, and I’ve been describing it as “that awkward puberty year”—mature enough to have shaped a sense of taste and a more concrete vision, but without yet having had the time to realize that vision completely. For reference, most PhDs in the department take 5-6 years to complete, and for me, it feels exactly right to have these two more years to execute.

So why is it that every other person in my BAIR cohort, it seems, trying to get out of here as quickly as possible? I know at least three who are already working essentially full-time (with graduation delayed only by paperwork hoops to jump through), and many more who are planning to graduate in at most 4 years. And why is it that it seems like every other BAIR faculty (not naming names…) is not only advising startups or collaborating with big labs part-time, but almost entirely absent from Berkeley in favor of their other employment?

There are many simultaneous vibe shifts: for a lot of empirical AI work, it is very true that doing the same work in industry will be far better-resourced and the pay will be many multiples of a grad stipend. And there may be a sense that the froth of 7-figure industry salaries for PhD new grads might be settling soon, a sense that it may be better to go get them while they still exist.

Mostly, I think, there is a sense that the real action is all happening in industry, anyway. Famously, OpenAI and Anthropic these days publish only comically vague “technical” “reports”; perhaps less well-known is that they’ve also all but eliminated real outside academic collaborations. Someone described the feeling to me as a sense of loss, and academics’ actions as corresponding to stages of grief (denial, anger, bargaining…).

On near-term timescales, and within the scope of individual careers, the decisions to leave make a lot of sense. But, in the long run, what this “academic brain drain” means for the AI field, both within and without academia proper, is unclear. As a discipline, it’s probably true that CS was already unsustainably bloated (just look at cohort sizes in, say, chemistry or statistics), and maybe the shrinking of the (academic) field is merely a correction of that bubble. But the situation does, still, beg the question of what the point of a PhD is—newly-admitted students, I hear, are now challenging their would-be advisors on this question—or what the role of academic research, as opposed to closed-door R&D, should be. Answering those questions would be a whole other essay…. So if you work in AI in any capacity and are interested in chatting, email me!!!

A Site for Every Soliloquy

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It’s become a meme that every AI essay trying to Do Something™ in the world must launch with its own custom-built microsite, usually with a serif font, minimal design, high-minded title, and off-white background. Situational Awareness, AI 2027, Superintelligence Strategy, Gradual Disempowerment, The Intelligence Curse. Their designs each suggest that an ordinary Substack post would be too unserious—what really defines an idea’s quality is striking the perfect balance of “trying really hard to seem like I’m not trying hard,” like the “no-makeup makeup” of thinkboi blogs.

The more I look at these new sites, the more familiar they seem. The old-style serifs and thin rectangular boxes on AI 2027 reminded me of OG rat forum LessWrong. Several abundance-adjacent nonprofits all use the UK-based design studio And-Now. The website for automate-all-jobs startup Mechanize is a whole-cloth ripoff (or homage) of Ilya Sutskever’s notoriously hermetic SSI, and both are LARPing the IDGAF aesthetic tradition pioneered by Warren Buffett’s Berkshire Hathaway, which hasn’t redesigned its “WEB page” of purple hyperlinks since 1999. And while shades of orange aren’t particularly popular for decorating, well, most anything else, the palette has been a fixture of tenured-professor-sites and YC-adjacent hacker blogs since the mid-aughts.

These Einsteins would probably prefer us to think that they’re all substance and no style. The less CSS the better; not a gradient in sight. But their design choices are no accident—you can see an organization’s idealized intellectual forefathers in their muted colors and bookish fonts. It’s signaling all the way down.

Datapoints are all you need

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Recently, I came across a paper for DataMap, “A Portable Application for Visualizing High-Dimensional Data.” One of DataMap’s key features is that it's privacy-preserving. Typically, creating a meaningful plot requires some familiarity with your dataset, but researchers are suggesting that meaningful insights can be extracted without even looking at the data—that the principal components of a demography can be gleaned at a script's run.

This matters because many “encrypted” services boast that they never access user data—great news if you're confessing secrets to Claude or outsourcing your taxes. But decision-makers face a black box: ‘hard’ evidence backed by opaque, unsupervised algorithms.

DataMap is not alone, systems like it are becoming more entrenched in world (data) order. ​In 2020, the U.S. Census Bureau implemented differential privacy—adding controlled noise to the data—to safeguard individual data in the annual census. Google, LinkedIn, and Microsoft have all also deployed their own differentially ‘private’ data systems.

In December 2024, Anthropic released Clio, “a system for privacy-preserving insights into real-world AI use. But their methodology raises questions: for instance, they take an “empirically validated approach to privacy,” where a model gives a score on a five-point scale based on the sensitivity of data points in a raw dataset.

However, simply turning off data sharing for your chat history doesn’t necessarily guarantee privacy. While tools like Clio feel like steps in the right direction, there’s no way to fact-check the details of their proposed methods and ‘objective findings’ from researchers working with the companies whose products they’re tasked to evaluate feels specious.

Open-source presents itself as a panacea, but it seems unlikely we’ll get the source code for tools like Clio anytime soon. Third-party organizations working on privacy-enhancing tech like OpenMined could be a stopgap. But even with open-source, only individuals who care to look can understand how they work.

Lastly, even with access to ‘visible’ datasets, researchers are operating blindly—relying on summary statistics that are often misleading and outdated methodologies that peer reviewers rarely bother to fact-check. After all, summaries don’t claim to tell the full story.

Death by a Thousand Cuts

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When it comes to changes in public health administration, major news outlets are waiting for the budget resolution to pass in Congress to find out whether Medicaid coverage will decrease. But the executive branch has a lot of power to legally create process blockers, reorganize agencies, and withhold funding for public health programs and grants right now.

To Jasmine’s point that “reality has a surprising amount of detail,” is a solid Substack tracking a lot of the specific changes inside of the Department of Health and Human Services. It’s helped me get a sense of how much the government actually does and how many banal ways an administration can block progress and create serious public health risks that have nothing to do with how much you pay to see a doctor.

A Tribute To The Global Supply Chain (1950-2025)

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When I read Marc Levinson’s The Box, a sprawling history of the birth of the container ship, back in February, I was not expecting it to be quite as geopolitically relevant as it has ended up being during this moment of tariffs, shipping freight declines, and other such crack-ups of the global economic order. The past two months have lent the book a certain elegiac mood—Levinson starts his story in the aftermath of World War II, sketching out how the concept of “shipping things in big boxes” went from a get-rich scheme from entrepreneurs on the Atlantic seaboard to the governing principle of the entire supply chain. Ozymandian!

Yet as much as The Box is a story about how the economy writ large became global, it’s also a story about how local economies and structures of labor became highly automated. While no one would accuse Levinson of being a Marxist scholar or a union propagandist, he gets deep into the differing approaches that the factions within capital and labor took to the impending wave of automation. It’s a set of stories that feel doubly relevant now, as attempts to build “full automation of the economy” get more attention. Perhaps most interesting is the case of the ILWU, to this day the more radical of America’s two longshoremen unions. Where the East Coast-centered ILA fought automation unequivocally, the West Coast’s ILWU, led by the Communist Party-affiliated Harry Bridges for forty years, wound up taking a different tact.

As port automation became more and more imminent in the late 1950s and 1960s, Bridges steered the ILWU towards a path of compromise and adaptation, saying “Those guys who think we can go on holding back mechanization are still back in the thirties, fighting the fight we won way back then.” Over the course of a half decade of negotiations, the ILWU brokered an agreement with capital that preserved wages and jobs while allowing for labor-saving technology to be implemented, maintaining labor’s power while reducing workplace injuries. As we stare down attempts at automation far more wide-reaching than containerization, we ought consider a wider range of historical precedents—not just Luddites and their descendants, but the full and messy picture of how labor has negotiated its own automation.

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Reboot Macrodoses are an informal dump of what our editorial board is reading, watching, playing, seeing online, thinking about, or otherwise experiencing. It includes mini-essays, reviews, links, pictures, plus perspectives from our beautiful brilliant readers—if you’d like to publish a 250-word Letter to the Editor about our previous essays, you can now do so here.

In today’s issue of macrodoses, we have:

• A review of a new play inspired by Sam Altman’s all-too-brief firing from OpenAI

• A survey of authorship practices in academic publishing

• That Anduril ad campaign

• A bop from the Georgian SSR circa 1988

“Doomers”

By Hannah Scott

As a resident of San Francisco, I cringe when out-of-towners confidently present their assessments of the city’s cultural landscape, which often strike me as inaccurate caricatures. The truth of tech culture is often stranger than the fictions about it. For this reason I admit I was skeptical when I learned that Matthew Gasda, playwright behind 2022’s “Dimes Square,” which satirized the infamous Downtown New York scene, had set his sights on people building AI in San Francisco.

A boardroom drama in two acts, “Doomers” departs from Sam Altman’s short-lived firing from OpenAI in 2023. It opens with a crisis management all-hands over cans of Yerba Mate and takeout tacos. Having just been removed from his position as CEO of a fictional AI company, MindMeld, by his board, Seth (Sam Hyrkin) attempts to rally the support of his colleagues between rapid-fire rounds of tweets and texts to friends at the DoD.

The stakes couldn’t be higher. For Alina (Emily Anderson), the Head of AI safety in the room, the total annihilation of humanity is on the line. For Seth and his lackeys, it’s a “really dope future” that hangs in the balance. Untangling these warring motivations behind building or not building AGI is the meat of “Doomers.”

For the accelerationist camp, these motivations don’t appear to reach much deeper than a glib, starry-eyed enchantment with the awesomeness of AGI. Jeff (Tommy Harkness) and Seth seem to be motivated less by a cartoonishly villainous version of capital accumulation or world domination, but by a juvenile obsession with building “special” tools, with spearheading a feat of engineering on par with the moon landing, with building a civilization that glimmers with a scale to rival the Roman Empire.

These expressions of a desire to “win” a boyishly sci-fi future, delivered earnestly by the actors, felt true to conversations one might overhear in Patricia’s Green or at Tartine. The doomers take an opposite view of the future, though their fears about total extinction feel just as improbable.

In the second act, which serves as a sort of funhouse mirror of the first, Harriet (Anna Connelly) and her fellow board members struggle to triage the fall-out from her move to oust Seth. The clash of visions for the future among the board members feels muddier and less poignant, but perhaps that’s because this group, which is ostensibly tasked with keeping its sociopathic CEO in check, is utterly powerless against the velocity of his quest to achieve a shibboleth of a goal.

In brief moments throughout the play, characters snap out of their science fictions and yearn for a different life. Jeff recounts a recent visit to his parents’ home in North Dakota, gazing into the audience and wishing he were playing board games on the porch. Harriet reveals that she was late to the emergency board meeting because she sat motionless in her car, transfixed by a Schubert symphony.

Such cracks in these futurists’ population-saving mission reveal an unshakeable desire for the immediacy of embodied experience. Their sentimental requiems for humanity come off as slightly heavy-handed. There’s just one character who seems to have fully shed this sticky nostalgia — Seth.

See “Doomers” through March 22 at Pallas Gallery in San Francisco and through April 19 at the Brooklyn Center for Theater Research in New York; doomers.fyi.

Giving credit where it’s due

By Hamidah Oderinwale

Recently I've been thinking about the construct of authorship. Authorship best practices are fuzzily defined: with best practices set by your field, your academic school of choice, and perhaps even by your department.

Generative AI makes it difficult to identify a clear primary source. If you’re an LLM-copier and paster, you’re basically left referenceless. An important function of authorship is assigning credit to an intellectual contributor. Who do you praise when their work supports your new discovery? On the flipside, it's also a means for accountability. Who do you reach out to when you spot an error?

I’ve learned that there are many differences and quirks to observe in the wild. For example, the “certified random order” policy has been acknowledged by the American Economics Association. Researchers submitting to an AEA journal with randomly-listed author lists even have to sign consent forms.

Courtesy of Stanford's Secure Computer Systems Group’s PI’s CV, I learned that authors are listed by contribution, then seniority. If necessary, ties are broken in alphabetical (or reverse-alphabetical) order.

As another case-study we can also look to machine learning. Chris Olah, co-founder of both Anthropic and Distill, is committed to being liberal with accreditation. In practice, if you scroll to the references section of a ML paper you might notice that they are often very long. This is partly due to relatively long author lists. If you happen to reference GPT 4’s technical report, you’re citing the 150+ contributors that made it happen.

ML has given into the spirit of openness and the positive-sum ideal. Insofar as there are disciplines that have yet to adopt similar policies, it’s a question of how, why, and if it’s worth it. Tentatively, I hope the answer to all three is yes.

ok but, like, actually don’t work at Anduril

By Jacob Kuppermann

After years of living in the Bay Area, it takes a lot for a tech company’s ad campaign to activate much of anything in me at all. Any traveller through San Francisco, the Peninsula, and surrounding environs cannot help but become inured to the unrelenting deluge of awful billboards and bus stop ads — nebulous LLM wrappers, desperately pivoting survivors of the 2010s boom-and-bust, whatever “PostHog” is.

So in a way I was pleased to witness the utter horrors of Anduril’s new “(Don’t) Work At Anduril” ad campaign. The thesis of the campaign is that America’s corniest and 2nd most important Lord of the Rings-themed defense contractor is not like the other girls; unlike the decadent giants of a prior age, Anduril and its patriotic band of drone designers are working hard every day to relentlessly improve their relentlessly lethal hard tech systems blah blah blah. They’re doing fake graffiti on their own billboards. They’re doing right wing uwu smol bean posting on their corporate account. They’ve got their hawaiian-shirted sicko cofounder doing cameos in mockumentary-style recruitment videos. It’s pathetic.

If the 2010s in bigtech were defined by a perpetual adolescence on the part of both tech labor and tech consumers — a veneer of luxe perks and ZIRP-subsidized millennial lifestyle products covering up widespread labor exploitation and unethical data collection — campaigns like Anduril’s (and the right-wing turn in tech imagery writ large) represent a childish conception of growing up, a leaning-in to the most jingoistic aspects of the American dynamism meme. This is the same set who founded the companies they now rage against — Mark Zuckerberg talking about “masculine energy” and seeming befuddled by trans-inclusive bathroom policy at his own company fits the same mold. This desperate cocktail of disowning the past and tough guy posturing in the present will of course age just as badly as the twee corporatism of the 2010s — for now, though, (actually) don’t work at Anduril.

"О стресс!"

By Kevin Baker

I've found myself unexpectedly obsessed with this song. Released in the Georgian SSR in 1988, "О стресс!" opens with goofy bass synthesizer riffs that seem to promise a mock-Soviet novelty song, after which it mutates into something far more disorienting. Vocalist Manana Todadze rattles off a breathless inventory of intrusions, her accelerating, staccato pace bombarding the listener with her sense of exasperation. Seemingly out of nowhere, Boris Shkhiani's croaking, bagpipe-like chorus interrupts with pleas to a doctor about stress taking an “interest” in him and haunting his dreams armed with a syringe. After that, it’s really all over the place. Nominally a synth-pop song, it hopscotches between genres and constantly subverts the listener’s expectations. The first time I listened to it, I thought it was funny. On the 1000th listen, I’m convinced it is a message sent through time, from one decaying, hypernormalizing society to another.

🌀 microdoses

• If you’re in San Francisco, Reboot is hosting our first-ever screening featuring editorial board member Morry Kolman’s “Mr. Beast Saying Increasingly Large Amounts of Money” on March 26! RSVP here.

• Check out Jon Rafman’s Proof of Concept, now on view at Sprüth Magers in Los Angeles through April 12, for an endless stream of slop operas set against a backdrop of ecological collapse.

• Friend of Reboot Lucas Gelfond recently put out a web-based version of exiftool, which lets you read, write, and edit metadata in the browser. Play around with it here!

Subscribe to Reboot for more critical analysis of tech and culture (and certified bangers):

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In 2024, tech leaders followed Donald Trump’s electoral victory with simpering notes. “Big congratulations… on an extraordinary political comeback and decisive victory,” wrote Jeff Bezos, fresh off blocking the Washington Post’s endorsement of Kamala Harris. “We are in a golden age of American innovation and are committed to working with his administration to help bring the benefits to everyone,” posted Sundar Pichai, the CEO of a company Trump recently described as “a whole rigged deal.” 

The “tech vibe shift” is not only a left-to-right move. It’s also an industry-wide pivot from technolibertarianism to state capitalism with American characteristics—from a dream of escaping government control to actively facilitating it. Elon Musk will be one of the top advisers in the new Trump administration, jumping on a call with Volodymyr Zelensky just last week. Sam Altman spent the last two years touring DC and presenting himself as AGI’s safest steward. The military-industrial complex is undergoing a renaissance under the shiny new banner of “American Dynamism”; CEO Palmer Luckey of neo-drone-factory Anduril bragged that “You need people like me who are sick in that way and who don’t lose any sleep making tools of violence in order to preserve freedom.”

To be clear, the US government has always been a key incubator of emerging technologies. It’s well-known, for instance, that DARPA played a critical role in jumpstarting R&D for the internet, GPS, and self-driving cars. Yet it feels like a relatively recent phenomenon to see such an open embrace between the sectors, and never as much PDA as in the Trump-Vance(-Musk) campaign.

So why the shift now? There are several candidate factors. The DOD has big and growing coffers, especially in the specter of hot wars in Gaza and Ukraine, and an escalating rivalry with China. Increased regulatory scrutiny from both parties has shown Big Tech that it’s much more fun to be on Big Government’s side when the DOJ comes knocking at the door. And finally, there’s the logistics of it all: Why go to the trouble of setting up a network state when you can capture the established one?

Today, the Reboot editorial board shares its reactions to the 2024 election. Kevin, Morry, and Shohini start by theorizing what went wrong for the Democrats. Jessica and Shira examine micro-vibe-shifts in the political rhetoric around AI and biohacking, and Hamidah and Jacob speculate on how the Trump administration will deal with high-skilled immigration and nuclear energy. Finally, Hal shares his top tips for protecting yourself and your community against government surveillance.

Will we survive the vibes? Let’s find out.

—

Which Economy?

By

When experts, pundits, and failed state house candidates talk about "the economy," they point to statistical indicators and clean charts of data sliced into discrete timeframes. But people don't experience the economy through employment numbers or percentage point shifts in GDP. And when they are asked by pollsters about the state of the economy, they aren't reflecting on government statistics; they aren't even necessarily thinking about the present. Instead, what they’re doing is more like taking an inventory of economic wounds. They are thinking back on a half-decade of accumulated instability and anxiety, of pandemic-era job losses, of price fluctuations. They’re thinking about the slow erosion of their plans and dreams.

Now, in the wake of electoral defeat, center-left think tanks and wonks seem determined to continue to tell voters they're wrong about their own economic reality. They point to charts and tables showing the strength of the economy, as if statistical aggregates and lossy indicators were, in some sense, more real than lived experience. The rhetorician Kenneth Burke liked to remind his readers every way of seeing is also a way of not seeing, that our frameworks and analytical lenses can obscure certain details even as they highlight others. In this case, an overreliance on quantitative understandings of economic life have led us into a situation where leading figures in the world of professional liberal politics mistook their statistical representations for the territory they were meant to map. Rather than admit that their understanding of economic reality might be incomplete, they've decided that voters are unqualified to speak for themselves.

There's something both futile and dangerous about this rush to discredit voters' economic perceptions, a problem which extends beyond the normal hazards associated with economists' delusional sense of omnicompetence. When someone's daily struggle with instability is met with lectures about macroeconomic indicators, it doesn't change their reality, it only deepens their alienation from institutional expertise. It makes them distrustful and angry. It makes voters question if you are really on their side. 

Politics Happens Through the Eyes

By Morry Kolman

One of the odd quirks of symbolism that Roland Barthes gives attention to in his book Mythologies is election photography—the pictures that are taken and shared of the people that want to represent us. Writing about the political posters he was seeing around France at the time, he reflected on the fact that they rarely had any words. For all the bluster about policy and vision that were theoretically the substance at hand to vote on, the actual campaign material seemed to care less. This choice, Barthes concluded, "is therefore above all the acknowledgment of something deep and irrational co-extensive with politics." It is a cope of its own right, one that accepts that an image is more effective than a vision.

I think we would be wise to take his point more seriously. The "iconic photo test” postmortem going around the internet as of late is by no means an accurate measure of political strength, but it appears to be a reliable one. If there was one realm in which Trump had a lock on, it was the visual one: the mugshot, the fist in the air, the McDonalds drive-thru. When I think of a lasting scene from the Kamala campaign, the most I can think of is when she went to that bakery and got some sweets. Maybe, maybe, when she went all the way across the stage to shake Trump's hand. Are either of those iconic? Are those even—if we may hack away at the word candidate—candid? No. Of course not. Kamala was at her symbolic peak the first day she took over as the Democratic nominee, and even then, her symbol was a negative: she was not Biden. Compare this to Obama’s Hope Poster, or even Bernie’s bird. The popular fervor around these candidates were part and parcel with these symbols and (an article in its own right) gave their followings a usable and repeatable motif to rally their content around.

I do not like the idea of the president being decided by something as abstract and unaccountable as taking a good picture, but to ascribe the loss of the election to largely a matter of the media's (or educational institutions', or so on) failure at adequately conveying the facts of policy matters and the environment at large is to bury your head in the sand. People see, and at a certain point, therefore, politics happens through the eyes. Symbolism, fantasy, and iconography are venues of political competition that liberal ideas of rationality and proper communication—the ideals that fuel wishes for better education or Sorkin-esque policy discussion on primetime news—do not have tickets to. One side’s “media” strategy is well aware of this fact, and actively constructs complete fabrications where they bus fake migrants to the homes of bougie liberals, catch their reactions on film, and post them to the 8M+ million followers of The Nelk Boys for their follower's glee. The other part loses. If we do not want to lie, we at the very least have to take a serious look at how we attempt to tell the truth.

Aesthetic Right Wing Vibes 

By

One of the predominant takeaways from Gen Z swinging right relative to 2020 was that progressive ideas don’t have social or alternate media megaphones. 

Right-wing ideas are powerful because they can get traction through channels that aren’t explicitly political. A lot has been written about Joe Rogan and Twitch streamers, but a huge volume of content targeted towards women quietly advertises right-wing ideas too.

“Day In My Life” influencer content is my guilty pleasure. But it rests on an individual-oriented, aspirational aesthetic that is politically anesthetized. These women, some with as few as 10k followers, put on display activities which implicitly advertise that lifestyle improvements are achieved through individual, not structural agency, and via reinforcement of gender roles: hours of gym footage, high-definition cooking shots where the boyfriends are always lurking in the background and never helping, and meditating and journaling deployed to reach personal (financial) potential. The most extreme version of this is trad-wife content, of which the most prominent influencers are Evangelicals or Mormons. Unpolitical, evangelical content like this makes “traditional” lives seem like a better tradeoff when working women are still paid less and do more domestic labor.

If their goal is to make left-wing ideas more appealing, it’s not obvious how progressives could use the existing influencer playbook. Right-wing ideas benefit from being able to leverage historical aesthetics or the currently-wealthy to show that the aspirational vision is concrete. They can say,”We’ve achieved this for some,” or “We’ve achieved this before,” and “You can have it too if you buy this one thing,” even if it’s not real. Progressive ideas are often trying to build a world that doesn’t exist yet, and has a vision for collective responsibility that’s difficult to visualize. The best outcome of Medicare-for-All is the counterfactual of limited medical bills. It’s unclear who would pay for a product ad in content that promotes community organizing. 

I don’t think this means Dems should give up the fight to own alternate media, but I do think that copying the right-wing playbook and incubating insincere content slop (“Joe Rogan of the Left”) won’t cut it. I want to see content that makes it cool to have walkable cities, cheap rent, public transit, and shows what free time adults can have if they have government-run childcare and a livable minimum wage. Many of these things exist in the US in pockets and certainly abroad—it’s about sourcing and funding the right content, and playing the culture war ground game of visually appealing to people's most basic desires. 

“Anthropic x Palantir” doesn’t seem like much… for now

By

Two days after the election, Anthropic and Palantir announced a new contract with Amazon Web Services (AWS) to provide access to Claude for “U.S. Government Intelligence and Defense Operations.” In the words of our very own : 

It’s a good tweet, because the optics really are funny, but I also wanted to figure out what the contract actually meant. 

I’ll caveat this by saying it’s hard to untangle the alphabet soup of B2B-SaaS-meets-bureaucracy-meets-PR-speak. If we believe Palantir’s own press release, the contract seems like nothing more or less than letting (higher-security) office workers use Claude, which has been available to lower-security government agencies via AWS’s GovCloud since this summer. If I had to guess, the only reason for the new three-way engagement is so that Claude can be served through Palantir’s AI Platform, which has higher security accreditation than GovCloud, and can therefore be used by employees with more stringent security requirements.

In some ways, this makes the contract—and the self-congratulatory messaging around it—seem almost mundane. It turns out that “supporting national security” means, essentially, to let office workers ask an LLM to “come up with five ideas for boosting team morale” or “rewrite this email to be more precise.” I expect the overall impact of this on national security to be approximately proportional to the impact of LLM access on desk worker productivity, which is to say, probably minor. And as I wrote last year, Anthropic is a company and Claude is its product; it should not be so surprising, or so uniquely concerning, that it’s selling it.1

This does, however, raise questions about how the relationship between “highly capable” AI and the military might develop, and what governance is going to look like. For one, Anthropic’s current Acceptable Use Policy prohibits customers from using the system to “produce, modify, design, market, or distribute weapons, explosives, dangerous materials or other systems designed to cause harm to or loss of human life”—among other things that U.S. intelligence and military agencies are known to do (misinformation, election interference, surveillance, attacks on infrastructure…). Is it just me, or… are these policies almost certainly guaranteed to be violated if Claude is being used by DoD, CIA, NSA, and so on? I wonder about the precedent being set here, and while the current contract seems to have nothing to this effect, it would certainly be cause for concern if, for example, Anthropic started doing custom work of any sort. 

Finally, to bring it back to the election, and associated vibe-shifts—of course this contract, and the decision-making behind it, was all done far before election day. But I have to wonder about the timing and the tone of the announcement… or maybe I’m reading too much into it. (See also Zhanpei’s excellent essay on the rhetoric of AI in war.) 

(For what it’s worth, OpenAI seems to be looking for pretty much the same thing, though I haven’t seen as much patriotic horn-tooting from them. Yet!) 

(Bio)hacking Eugenics

By

Amid the many issues that were strongly featured on the campaign trail, public health was notably absent—especially in comparison to 2020. This election was the second election since Covid’s disruption, but the virus wasn’t explicitly present on the trail except as one of the catalysts for Biden’s dramatic dropout. Still, Covid has been very present, although unacknowledged, in political life. One of the pandemic’s more sinister effects has been a country-wide rise in eugenics.

At its core, eugenics is the belief that the “genetic makeup” of a population can and should be improved over time, often by attempting to control who is allowed to have children. In the absence of other indicators, this tends to default to people who are white, wealthy, and visibly healthy—that is, not disabled. Eugenics is the undercurrent that fuels Covid denial, anti-masking, pro-natalism, and anti-vaccine “health consciousness.” All of these are present, in varying quantities, in Silicon Valley. And while tech bros have been biohacking for years, it’s only recently that major figures have become quite so obsessed with fathering children, biological age, and sperm health. It’s a clear sign that eugenicist “health-consciousness” and pro-birth attitudes are on the rise in the tech world, and in the US writ large.

Perhaps the best-known articulation of eugenicist ideologies in Silicon Valley is the pro-natalism of Elon Musk and his ilk, who are investing in (and using) fertility technologies that can enable genetic testing to produce “superior” embryos. But your more garden-variety expression of eugenics has to do with the conflation of health and virtue. It’s good to care about your health and to work to improve it, but as soon as we begin to value specific visible articulations of “health” too highly, the line between “getting healthier” and eugenics gets…blurry. In the context of eugenics, being visibly healthy becomes a kind of social capital. Many people who abide by eugenicist ideas don’t say—or perhaps even know—that they think health is the paragon of virtue, but they spend far too much time and energy trying to get as healthy as possible for it to be just a passing interest. Bryan Johnson, perhaps the best-known youth-chasing biohacker today, has begun cozying up to vaccine deniers like RFK—and I don’t think that’s an accident.2 

It’s important to note that neither party is innocent of eugenicist ideas—this became especially visible around Covid. Biden’s Covid policies mostly included denying that the virus was a serious issue, despite mounting evidence that Covid has a high probability of causing long-term complications—otherwise known as disabilities. 

I’m not sure where this leaves us, going into a second Trump term. It’s clear to me that Trump empowers eugenicists, and that Silicon Valley does, too. All I can do, as someone who’s neither working in public health (nor directly impacted, since I am not (yet) disabled), is encourage you to wear a mask, get vaccinated—and most importantly, to care about the health and well-being of others, including those who don’t fit the mold of the bio-hacked hyper-productive tech bro.

Maple Syrup and Eagles

By

I’m Canadian, a member of the select bunch of lucky foreigners. As I drain my brain from the land of maple syrup and feed it to the eagles, I must first beg the U.S. Citizenship and Immigration Services for the right to work. For me, it’s easy, supposedly so. It’s a pain, but the non-beneficiaries of NAFTA have a much harder time. Tech companies like Google, Meta, and Tesla get tens of thousands of applicants for any given role but are still almost always searching for the exceptional. After all, tech is nothing without its talent.

Trump’s been tech’s best friend, with endorsements from Marc Andreessen, Elon Musk, and the like, and we’ll see whether high-skilled immigration policies are, too. In an ideal world, in the words of Trump, green cards are stapled to college degrees. 

But we are far from the ideal. As it is, international students on the F-1 visa have a year or three years (if they’re a STEM grad) to work post-grad with Optional Practical Training (OPT). Then, they’ll probably find a full-time role with an employer sponsoring their H-1B. There’s a fixed number to allocate, so an employer most likely enters the lottery hoping that their desired hire draws lucky. Then, if the odds are in your favor and you live here long enough, you may get a green card. It’s a costly, tedious process: some follow through, others drop out from the fatigue, and many stay in it, anxious, annoyed, and afraid. 

If Trump’s cameo turns out to be dishonest. Then, the CHIPS and Science Act of 2022 and its hope to attract more bright scientists worldwide will be put to a halt; plans to expand OPT won’t be realized; and the “Einstein” (EB) and the “Genius” (O-1) visas will become much tighter pathways to entry.

Having “made it,” Elon, Thiel, and the rest of the mafia are arguably model, high-skilled migrants. That said, if you believe Twitter’s acquisition bought our political attention, maybe we can hope that the right-to-stay will, too. 

Is the Nuclear Energy Revival Incoming?

By

Does the second Trump term herald a revival for nuclear power? Nuclear energy has long been more strongly supported by Republicans, but the past few years have brought increasing attention to the energy source from both climate and industrial policy perspectives. There are even nuclear influencers—though their efficacy is unclear. The past year has featured an incessant wave of stories on nuclear power as an enabler for ever-larger data centers, with both the Biden White House and the Trump campaign expressing a greater interest in funding the deployment of newer nuclear tech like small modular reactors. In the wake of the election, some nuclear energy analysts predicted that nuclear would be a rare opportunity for “climate hawks” in the face of… otherwise unfriendly currents for renewables.

A key problem, though, for anyone claiming victory for a nuclear renaissance: the two halves of the Trump-aligned right seem to have rather different reads on the technology. On one end, the Elon Musk-esque tech right has embraced nuclear as a tool for both energy abundance (too-cheap-to-meter is back!) and owning the wind-and-solar-focused left, with language about “unleashing” nuclear power making it into the Republican party platform. On the other, Tucker Carlson is literally claiming that demons invented nuclear power. The jury is still out on whether the nuclear boosters or demonologists will achieve their policy goals. Regardless of whether we see any actual new reactors built in the US in the near term, there’s not a better example of the strange bedfellows of this coming administration and its orientation towards tech and energy policy—perhaps a sign that overheated claims from tech barons about a return to the “Roaring 20s” may not prove accurate.

How we can (try) to keep each other safe

By

In my piece from last year, Threat Model, I wrote about how extreme privacy practitioners’ imaginings of worst-case scenarios

exert a pull on [them] like moths to a flame. What if someone starts stalking me? What if my political ideology becomes criminalized? What if my identity becomes criminalized? What if I win the lottery and need to lay low for a while? Does my threat model account for that? Ultimately, what keeps privacy extremophiles captivated by what is, in reality, a mostly intellectual game is the submerged threat (and perhaps even the desire) that it suddenly could become much more real.

For tens of millions of migrants, hundreds of millions of women, and uncountable others (allies of the aforementioned groups and other perceived political enemies), the election results underscore that this is not a “mostly intellectual game.” Whether they know it yet or not, for many US residents the task ahead is to evade, for as long as possible, a malevolent and technologically-enabled bureaucracy that can compel companies to turn over sensitive information in order to destroy their lives.

It is clear that most major technology platforms hope to be on the good side of this administration—better to be the facilitator and executor of state power during Trump II than its enemy. What will that mean? Google and Apple may be legally obligated to turn over data about visitors to abortion clinics when law enforcement agencies submit “geofenced” warrants. Meta will continue to turn over chat data to prosecutors so they can put abortion seekers in prison. Palantir will continue to build ICE the tools it needs to enable mass surveillance and deportation.

If there’s one thing we continually assert here at Reboot, it’s that technology (on its own) cannot save us. But we also know that technology is a catalyst for social change, both positive and negative. Cory Doctorow writes that technology is useful

because it can temporarily shield you from the all-seeing eye of a corrupt state… And what you need to do during that temporary, technologically-dependent window is reform your society so the government is just and responsive and transparent. Technology cannot substitute for a just society, but it can help you create that society.

I’m trying to create that temporary, technologically-dependent window for change by:

• Getting off X/Twitter and trying to embrace more decentralized and federated alternatives (@harold.bsky.social) that enable data sovereignty, interoperability, and less surveillance. I’m also trying to cultivate my own corner of the internet that isn’t run as a monopolistic fiefdom.

• Shifting as much of my personal communication as possible to Signal or other end-to-end encrypted apps.

• Using VPNs (and Tor, sometimes) to protect my network information.

• Limiting the sensitive data (Android, iOS) that apps can collect about me (location data is critical, but this also applies to health apps, particularly for tracking menstruation).

I’d urge you to consider some of these measures as well (in addition to publicly protesting and fighting against the policies that the incoming administration will attempt to enact), since protecting your individual node of a sensitive network doesn’t just protect you—it helps protect everyone you’re connected to.

We can’t be your left-wing Joe Rogan, but subscribe to Reboot for more critical analysis of tech and politics:

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🌀 microdoses

• Election results from 2016 to 2024 by neighborhood in NYC shows how ethnic minority neighborhoods swung right over time

• Jerusalem Demsas rebuts the “voters hate women” theory of the loss

• A calming gallery of restored lily and rose illustrations by Pierre-Joseph Redouté

• I might say something stupid

  

• We ran 80,000 simulations and spent each of them running 80,000 more

  

• Something to look forward to

  

💝 closing note

How do you think the 2024 election will change tech going forward? Let us know in a comment, or send a letter to the editor.

Leave a comment

Four more years of, uh, whatever this is,

— Reboot team

Reboot Macrodoses are an informal ~weekly dump of what our editorial board is reading, watching, playing, seeing online, thinking about, or otherwise experiencing. It includes mini-essays, links, pictures, plus perspectives from our beautiful brilliant readers—if you’d like to publish a 250-word Letter to the Editor about our previous essays, you can now do so here.

In today’s issue of macrodoses, we have:

• Our take on the news from OpenAI

• A response to Kyle Chayka’s Filterworld

• Yearning for YouTube of yore

• The “worldbuilding turn” in tech and beyond

• Our reflections on Fredric Jameson’s work

• Microdoses, to balance your portion size!

Hope you enjoy!

—Shira

OpenAI News

Recent developments at OpenAI continue to confirm our expectations.

Filtered

by Jacob Kuppermann

Have you heard about algorithms? Kyle Chayka would like you to be aware of them. He would like you to recognize them in their many guises: the algorithm as globalizer, gatekeeper, girlboss. For Chayka, algorithms are be all and end all of contemporary digitized culture, an internetish malaise spilling over into the real world, a haze that engulfs all of the unique quirks of culture leaving nothing but a hyper-optimized, perfectly instagrammable mass. This is, roughly, the thesis of his book Filterworld, published earlier this year. It’s also the thesis of essentially every column he’s written over the past four years at the New Yorker. There is no shame, of course, in having a beat, but Chayka’s argument rests on perhaps too-well-trodden ground. Chayka did write some of the earliest and canniest essays about how algorithmic incentives have shaped the physical environment of coffeeshops, AirBnBs, and other millennial lifestyle enclosures, but his analysis in Filterworld rarely goes beyond what those takes achieved nearly a decade ago. Instead, the book relies on a clutch of pre-digested tech-crit shout outs — the first few pages inflict upon the reader references to the Mechanical Turk, Cybersyn, the Communist Manifesto’s opening lines, and (maybe worst of all) “the medium is the message.” 

I’ve not yet given up on the potential of tech criticism centered on the power of algorithms — we’ve published some of that at Reboot! But Chayka’s approach is a strangely provincial one, returning again and again to the same algorithmically optimized coffee shops and the lives of hyper-aestheticized influencers. There’s little in the book about the stranger edges of online culture, something which points to the key irony/failure/tragedy of the book. In order to make his own arguments about the hegemony of the algorithm land seem more compelling, he seems to do some of its homogenizing work for it. Filterworld paints a picture of the web that rarely goes beyond the most prominent parts of Instagram and Twitter — there is little about how filtering has affected, say, niche fandom or hobbyist spaces, or even what parts of the internet have evaded the filter of the algorithm. This dynamic even shows up in Chayka’s own writing, which seems optimized for social media, composed of screenshottable, sharable paragraphs on phenomena that his audience (myself included!) already knows about. As we’re always saying here, we need a better tech criticism — by subsuming our own takes to the same hard filtering that has affected so many online and offline spaces, we do ourselves a disservice.

YouTube Nostalgia

by Shira Abramovich

It’s Pizzamas.

For those not in the know (i.e., those not cringe enough as teens to follow Vlogbrothers, nor to keep following them well into adulthood), Pizzamas is the annual vlog-tradition-slash-fundraising-marathon-slash-meme-slash-nostalgia-festival that occurs yearly in September or October on the Vlogbrothers YouTube channel. For two weeks, Hank and John Green commemorate “Pizza John,” a meme of a mustachioed John Green and his love of pizza, by making videos daily, as they did during the channel’s first year in 2007—an exercise in nostalgia, and an ode to the early days of YouTube. 

I’ve been around for many a Pizzamas—I’ve been watching the channel since 2010, three years after it started, and I remember being online as its subscriber count ticked up to a million for the first time in 2013. As the dynamics of YouTube have shifted to a mix of shorts and longer, less-frequent, higher-effort videos, the Vlogbrothers channel—with its earnest comments, four-minute videos, and strange but enduring traditions—has come to feel like a time capsule. Pizzamas intensifies that feeling. The merch that gets sold during these two weeks often refers also to earlier versions of Internet culture, such as the None Pizza with Left John shirt that appeared in 2019—the first time I was conscious of remembering an old, popular meme that had fallen off and been forgotten.

This year, Hank and John have focused some of their daily videos on memes from the early social Internet, which were made in a context that doesn’t exist anymore. Even if these memes predate my time online by a few years, they’ve made me think a lot about how referential the early Internet was—and how many of these references are lost as communities die or sites go offline. It’s been odd to watch my Internet memories become literal Internet history, a feeling which I’m sure will only intensify with time.

Worldbuilding for Hire

by Hamidah Oderinwale

In an interview with Embedded, Jasmine calls for more “software pitchforks,” emphasizing that when we aim to improve the future, merely criticizing technology isn't enough; we must also voice our aspirations. We can certainly critique what already exists, but we must also define what it is that we want. We need rigorous optimism. For this reason, more artists, writers, and humanities folk should embrace the role of a “technologist”—and vice versa. 

Government ideates what can be, unburdened by what has been. Generating these ideas, however, isn’t the easiest of tasks. The U.S. government contracts worldbuilders for hire, to do just that: world-build. The Sigma Forum (h/t Kelvin Yu) is a think tank staffed by a group of impressive scientists-turned-sci-fi visionaries, offering “futurism consulting” services, working as technical dreamers for hire. Asimov Press, the biology-focused, science progress magazine has fiction as a staple in their publication: crafting fictional, but uber-realistic fictional universes with AI-led scientific discovery and cities afflicted by zoonotic disease.

More on the topic of science-fiction writers and their influence: Perhaps, the most notable is Arthur C. Clarke and his work, the Wireless World, which is credited for inspiring NASA to develop the modern satellite. Likewise, in a video on the S3 YouTube channel, Jason Carman interviews John Gedmark, the founder of Astranis: the satellite technology upstart. In the interview, Gedmark names Arthur C. Clarke as inspiration for founding the Starlink rival.

In a parallel vein, Nat Friedman is breaking free from the cast of typical tech investors. Recently, he made a call for an intern to investigate a theory about the Shroud of Turin (as mentioned in Macrodoses 2). 

With this all, I’m reminded that “moonshots” can be more than just products; they can be narratives too. Well-crafted narratives have served as catalysts for many of the engineering feats we marvel at today. And the humanities’ influence on invention is sold far too short—if world-building is a duty and we recognize its two axes: engineering their visions of the future, and artists who define these visions. 

—

(10/13/2024) Update: I came across the Science & Entertainment Exchange through Casey Handmer’s blog. They’re a National Academy of Sciences program that connects entertainment professionals with scientists to advise on films and TV.

Meditating on the Impossible

by Hannah Scott

Since hearing the news of Fredric Jameson’s passing this past weekend, I’ve been revisiting Archaeologies of the Future, the cultural critic’s exacting dissection of science fiction and its many strains of Utopianism. Jameson carefully maps the conceptual contours of Utopia, speciating its various literary incarnations through analyses of works like H.G. Wells’s Time Machine and Ursula K. Le Guin’s Lathe of Heaven. In doing so, he unspools a strikingly honest version of utopian imagination, one that admits the apparent impossibility of realizing alternatives to the present — both in practice and in fiction — while rescuing the sense of historical possibility that utopian thinking allows. For Jameson, the liberatory potential of science fictional Utopias lies not in visions of new technology, but rather in the fact that it frees us to imagine a break with the past: 

“Utopia thus now better expresses our relationship to a genuinely political future than any current program of action, where we are for the moment only at the stage of massive protests and demonstrations, without any conception of how a globalized transformation might then proceed. But at this same time, Utopia also serves a vital political function today which goes well beyond mere ideological expression or replication. The formal flaw — how to articulate the Utopian break in such a way that it is transformed into a practical-political transition — now becomes a rhetorical and political strength in that it forces us precisely to concentrate on the break itself: a meditation on the impossible, on the unrealizable in its own right” (232-3).

In Jameson’s self-described “anti-anti-Utopianism” I find a refreshing, roundabout route to optimism toward thinking and writing about those possible futures we wish to see but that our historical and contemporary conditions disallow. Beyond the hollow, packaged styles of Utopian thought — I’m thinking of “speculative thinking” and “futurism” — that often get drunk on the general vibe of ossified sci-fi aesthetics and the grand arc of technological progress, a more sober Utopianism is possible, and for that we owe much to Fredric Jameson. 

🌀 microdoses

• How do we find cool links on today’s Internet?

• More Sunday reading: code poetry!

• For your ergonomic consideration

• An update to Jacob’s macrodose on that IBM slide

  

Support more of tech’s weird, wonderful, and sincere by subscribing to Reboot:

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Reboot Macrodoses are an informal ~weekly dump of what our editorial board is reading, watching, playing, seeing online, thinking about, or otherwise experiencing. It includes mini-essays, links, pictures, plus perspectives from our beautiful brilliant readers—if you’d like to publish a 250-word Letter to the Editor about our previous essays, you can now do so here.

In today’s issue of macrodoses, we have:

• The Moo Deng moment

• A response to Karen Hao’s new AI and climate piece

• Why 2024 is becoming the animal election

• Reboot personals

• Cat photos

The Moo Deng Moment

By Jacob Kuppermann

In what can only be described as the finest moment in Thai cultural diplomacy this century, baby pygmy hippo หมูเด้ง/Moo Deng (literally, “Bouncy Pork”) has become an online sensation, proclaimed as icon/legend/the moment by Time Magazine and inexplicably moist/slightly blurry by Twitter user @mrmatthouse. 

It’s easy to simply classify Moo Deng as just one extremely cute viral animal in a decades-long history of extremely cute viral animals—a global south take on the American hegemony represented by Fiona most directly—but there are a number of fun nuances in Moo Deng’s rise to prominence as one of the two individual living organisms born in 2024 to have a wikipedia page (the other is a Saudi princess. Less notable, imo!)

Key among them is that some incalculable percentage of the viral images of Moo Deng are in fact *not Moo Deng*—they’re Moo Toon and Moo Wan, her older, also pork-themed, siblings. The triple-Moo online operation, headed by Khao Kheow Open Zoo zookeeper Atthapon Nundee, appears to be a fairly intentional attempt towards virality, with Atthapon telling The Guardian he “set a goal to make her famous.” To raise pygmy hippos for generations, all the time waiting for one particularly slimy, charismatic scion to be born… a truly powerful example of long-term thinking.

On the demand-side of things, I’m also interested in how Twitter users are thinking about Moo Deng instrumentally—as a way to cleanse the timeline of… less fun, more pogrom-like animal news stories, let’s say. With that in mind, it’s important to diversify one’s portfolio of extremely cute online animals. May I recommend the Bay Area’s own Briar, a recently rescued mountain lion cub at the Oakland Zoo?

Can Our Tech Neutralize Our Tech?

By Hamidah Oderinwale

In Karen Hao’s new year-long investigation, she highlights the growing AI-climate problem. She starts with a quote from Microsoft’s Chief Sustainability Officer, explaining how AI is actually a boon for the environment. In what way? In answering our prompts on how to do it, of course…

That being said, AI development needs a lot of energy and much of this energy comes from fossil fuels. Microsoft and others claim to be “aiming” for net-zero. But markets don’t lie, and any climate-preserving regime won’t be taken at the cost of profit, especially now.

But while reading Hao’s report, I also learn that many of the companies in question are also the largest buyers of carbon removal credits (CRCs), where a CRC represents a unit of carbon to be removed and stored. So technically a company can estimate its emissions, purchase equivalent credits, and claim net-zero status. 

Conversely, advanced market commitments (AMCs) allow companies to fund future removals by buying in early. The uncertainty is that developers must then follow through to remove the promised carbon; but it’s worthy to mention that there’s also debate on whether this uncertainty also holds for CRCs too. Regardless, Microsoft, alongside Meta, Salesforce and others are also major buyers of these commitments. 

With that, I think there’s an interesting moral question here: Can companies buy their way out of responsibility? And I don’t mean this cynically. On the one hand, companies could take charge and develop their own solutions. Take, for example, the open-sourcing of energy-efficient data center designs: Meta’s gainfully done this before, and there are still other opportunities for companies to explore. But in a fickle arms race for (AI) dominance, perhaps this is the best suboptimal outcome we can expect. Still, disregarding whether these commitments turn into contracts, it feels right to ask, is it right? Can our tech neutralize our tech?

Political Animals

By Kevin Baker

Animal Studies scholars are, perhaps, our most neglected group of theoryheads. Unlike the partisans of most other theoretical currents in the humanities, they aren't the subject of stale academic Twitter posts about how annoying they are in grad seminars. Nobody will make fun of you for carrying around a dog-eared copy of The Companion Species Manifesto. They get very little press.

But that might be about to change. As @decoratedshed noted, the US presidential election has provided an uncommonly rich quarry for anyone looking to investigate and “unpack” animal/human relationships. Here's a preliminary sketch of the events of the campaign for any enterprising grad student looking to fill this scholarly lacunae:

• Joe Biden's German Shepherd, Commander, reportedly bit Secret Service agents at least 24 separate times.

• Kristi Noem, long considered a potential Vice Presidential choice for former President Trump, saw her chances implode when passages from her campaign autobiography about her penchant for ideologically-driven puppy murder began to circulate.

• The multi-species assemblage known as RFK Jr. leaned heavily on a series of ever-escalating animal stunts in his campaign to take the White House. Starting modestly with a contest offering supporters a chance to learn falconry from the candidate, Kennedy later pivoted to a strategy centered on alleged dog consumption and midnight capers in Central Park with the corpse of a bear cub.

• Forced-pregnancy enthusiast J.D. Vance launched a series of odd, hypernatalist attacks on "childless cat ladies," setting in motion a series of events that would lead Taylor Swift to endorse his opponent.

• In an attempt to win back animal lovers, Vance “created a story” about Haitian migrants stealing and eating cats from neighbors in an Ohio town, inciting threats of violence against Haitian immigrants, and unleashing a torrent of unholy cat-themed AI kitsch. 

• Trump’s would-be assassin, Ryan Routh, kept “a horse in the house, a whole horse. In the living room,” a neighbor told reporters.

Reboot Personals

• Editor Shohini made a pilgrimage to the Brat cube. Charli’s been around for 10+ years. Why did she go mainstream this year? She’s also not the only artist with a pre-existing fan base to take control of the mainstream this summer, potentially to Taylor Swift’s detriment. There’s a running Twitter joke of how Taylor releases a new version of her music every time someone else beats her on the charts, but Charli is absolutely running with that playbook. Get your bag girl! 💰

• Wanted: non-common “Commons”

  

• Now available: every single recorded Anglo-Saxon, 597-1066

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P.S. Did you know there are now five (!!!) cats on the new Reboot editorial board?!!

If you didn’t catch our first issue, Reboot Macrodoses are our editorial board’s way of sharing what we’re thinking about, though mini-essays, links, pictures, reader-submitted letters to the editor (submit one here), and more.

Subscribe now

Speaking of the editorial board—last week we announced a new set of editors! As you will see from their future work (and their macrodoses below), they are sharp and smart and you should absolutely pitch them.

In today’s issue of macrodoses, we have:

• Grift in the world of online accessibility

• A response to that viral Ted Chiang essay about AI and art

• “Founder mode” in economic context

• The controversial, parasocial world of NYT Games

• The murky history of “A computer can never be held accountable”

• Engineers leave the Bay Area (no, not that one) for greener pastures

• Reboot personals

Hope you enjoy!

— Hal

Grift Gossip

This week, I went down a rabbit hole with the publication of this article on IGN about Susan Banks and two other relatively well-known accessibility advocates, all of whom were queer Deaf women of color. Before she passed away in 2019, Banks had been a prominent blogger on accessibility issues for Deaf and mentally ill gamers, such as content warnings and comprehensive subtitles. Banks was so well known, in fact, that she had a gaming accessibility advocacy award named after her. 

But this article makes a convincing case that Susan Banks actually never existed at all. Instead, her partner Coty Craven (nominative determinism?) invented her in order to gain clout for his own work as an accessibility advocate, and even went on to make up two more personas after she “died.”

Now that the grift has been exposed, Banks reads to me like a list of sympathy checkboxes. Refugee? Check. Successful model? Check. Queer? Check. Long list of invisible disabilities that are often ignored? Check. Some details are even wilder—for instance, she allegedly suffered a double amputation after a freak KitchenAid accident. But when accessibility awareness is such an uphill battle, who would question someone who was writing about the issue? It’s a testament to how little effective advocacy there is that this grift slipped under the radar for so long, across three different personas. And as Deaf women of color with many invisible disabilities, Craven’s fake personas were exactly the demographic most commonly accused of “faking.” Who would want to repeat those allegations, even if they held water?

I’m not mad at the people who believed Craven—it just saddens me that stories like these can damage credibility for disabled gamers, who already have a hard time advocating for themselves. What this story exposes, to me, is not just a shortage of advocacy but also how hard it is to get fixes for usability and accessibility issues. We shouldn’t need someone pretending that their fake partner dropped a KitchenAid on their foot in order to get clout for better subtitles.

— Shira

Choices, Choices, Choices

A reported 15 billion images have been generated with AI, though science fiction author Ted Chiang argued in The New Yorker last week that none of them counts as art. Chiang attributes AI-generated media’s disqualification as art to a lack of choice-making required of a user prompting ChatGPT or DALL-E to produce words or images. He adds nuance to an oft-repeated analogy between generative AI and the advent of photography, noting that “over time people realized that there were a vast number of things you could do with cameras, and the artistry lies in the many choices that a photographer makes.”

While I agree with Chiang that this is not what's happening in most Midjourney renders, AI can also be a new medium that expands the range of choices available to artists. Some of the most interesting artists working with AI as a medium are:

• Kat Zhang, aka the Poet Engineer, who is impressively prolific at turning out captivating experiments with diverse configurations of AI models and other tools, including using gesture to control Stable Diffusion generations, visualizing how large language models (LLMs) embed color, and evolving fictional creatures. 

• Delta.Ark, who constructs massive virtual worlds in Unreal Engine that are populated by characters with LLMs in their “brains,” enabling them to scan an open-ended environment and take actions in pursuit of interesting-ness.

• Sebastian Schmieg and Lina Schwarzenberg, who invite the public to upload photos of scenes they deem to be in need of alteration. In Twitch-streamed performances titled “The World Is Beautiful Again,” the duo then use AI image generation tools to “repair” the submitted images in real time—construction sites are beautified with trees, snarled masses of cables are managed, and shoddy manicures are embellished with flowers.

• Disnovation.org and their Predictive Art Bot (2018), which uses natural language processing to extract ideas from recent news headlines and turn them into titles for nonexistent (though very plausible) artworks. 

Approaches like these (or the experimental AI poetry my fellow editor Shira described beautifully for Reboot in 2021) involve constructing custom models or integrating existing ones within larger systems of tools—processes that certainly involve a great deal of choices. 

— Hannah

Founder Mode

Much has been memed about Paul Graham’s “founder mode,” his mini-manifesto for founder-driven startup leadership over “professional fakers [who] drive the company into the ground.” But what’s missing from the discourse, and what I’ll offer, is a structural lens on the issue.

First, founder mode is not new: Brian Chesky has been giving versions of his how-I-saved-Airbnb talk to Y Combinator and others for over a year now. But I wouldn’t give Chesky all the credit either. Turn back the clock a couple more years, and you’ll find that Silicon Valley’s shift to flatter structures and more imperious leaders began with the end of zero-interest rates, the resulting tech layoffs, and Elon Musk’s reign in Twitter 2.0. After a decade of froth, overhiring, PR projects, and bloated management, it took a recession to force some focus. The worst of the layoffs have come and gone, so founder-CEOs are safely declaring their new management method a success. In this context, PG’s catchy new moniker is more of a victory lap than a movement’s beginning.

So what to make of it? First and obviously, founder mode does not mean that founders should be assholes to workers—even though that’s all some wannabes will hear. I’d also still expect more careful hiring and a less labor-friendly environment across the board.

The real insight here is that founders possess special instincts about their user base and problem space that most mercenaries won’t, and they should apply that knowledge directly to business problems, even if it means micromanaging. But I also think that smart employees at all levels can and should go founder mode. And founder-CEOs would be better off hiring (and delegating to) high-agency, mission-driven people who they trust to be in the weeds, rather than driving themselves (and everyone else) crazy reporting bugs at 2am.

— Jasmine

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Missed Connections

Newspaper puzzles have always had a strong subculture (see the American Crossword Puzzle Tournament), but no game has managed to sustain a  recurring viral Twitter discourse cycle like the NYT Connections. While Wordle and SpellingBee have similar reach, they are just letter guessing games. By contrast, Connections asks you to take 16 words and classify them into four groups, thereby leaving room for opinion on whether the grouping is sensible or valid. There’s a new puzzle every day, and no archives—like peak pandemic Wordle, everyone on a small slice of the internet is facing the same challenge at the same time, and this makes for perfect Twitter bait. 

Some of the humor links current events to the daily puzzle. It also frequently dunks on people who don’t seem to get the point of the game. But the most interesting part is the parasocial relationship we have with Connections editor Wyna Liu. Check the search results for “Wyna” vs. “Will Shortz” (the long-time NYT Crossword editor) and you’ll see the difference in volume and popularity. I checked my Connections group chat, and we consistently refer to Wyna directly. More impressively, she’s silent on Twitter, so her name recognition doesn’t come from content creation under her own name. 

I think the key virality behind Connections is that the groupings can be simply unhinged, and the level of difficulty comes at an unspecified rate. You can get normal stuff like synonyms, or bizarre things like “colors with their first letters changed”. The unpredictability and reference to today’s pop culture feels like a reflection of its online audience. It makes the puzzle feel individual rather than institutional. 

Wyna, if you’re reading this, I hope you’re getting a raise because it seems like people are spending more time playing Games than reading the news.

— Shohini

A Computer Can Never Be Held

If you’ve gotten into enough online discussions about AI and capitalism you’ve probably seen it:

16 words, in stark all-caps sans serif. Usually identified as an IBM slide from 1979, the phrase “A computer can never be held accountable therefore a computer must never make a management decision” has become one of the common refrains of Twitter tech crit; someone goes viral reposting it every 10-20 months. Yet despite the phrase’s totemic status it’s surprisingly hard to verify much of anything at all about its provenance. The image in question was first posted in early 2017 by Twitter user (and former IBM employee) @bumblebike, who would later post a few more slides from the presentation in question (I personally think PUTTING A BAD SYSTEM ON LINE IS LIKE POURING GASOLINE INTO A FIRE is also very catchy) with later efforts stymied by a flood at the house the slides were stored at. Later efforts by users on Cohost and Mastodon revealed a few more lines via jpeg palimpsest analysis, but inquiries into the IBM archives as to any further details have proven unfruitful.

Personally, I find it fascinating that this slide has captivated so many people in spite (or perhaps because) of its unclear provenance. There are plenty of pieces of late 70s tech ephemera that haven’t caught on—the Computer History Museum alone has untold numbers of boxes full of them—but a quote shorn, perhaps forever, from its original context, allows for it to become something more than just a line in a presentation about computer systems but a rallying cry and prophetic claim.

— Jacob

A Tale of Two Bay Areas

When you hear "Bay Area expats," you’re probably thinking about tech workers and other professionals who leave the San Francisco Bay Area in search of a simpler, more fulfilling life. Well, there’s another Bay Area, and it’s in China, per Jacob Dreyer’s article for Noema covering the cross-pacific phenomenon.

Zhongshan is the "megapolitan": a bustling and industrious city like SF. On the outskirts, instead of Oakland and Berkeley, we have the Guangdong-Hong Kong-Macao Bay Area. Zhongshan, home to commuters, elite university graduates, and employees of prestigious companies, is met with passionless demand. Young people are looking for a simpler way of life, both in spirit and in their work. That’s the role of Qixi, where an increasing number of young corporate refugees are tending to tiny farms. Montessori schools, previously only a choice by retired hippie parents, are enrolled by the children of these “expatriates.”

The coder-turned-blueberry farmer fantasy is becoming real, and it's in China. It's interesting to see cottagecore take flight in a country with a vivid memory of its less prosperous past, where the workers who built its superpower status are now seeking refuge from the very state they helped create.

— Hamidah

Reboot Personals

For hire:

• Shroud of Turin research intern (short-term gig)

• Infosec Engineer at Pokémon International (this is a real job)

For sale:

• 4,203 pieces of galvanized square steel (in case you need to expand your 0.1 square meter house)

For thought:

• https://x.com/halomancer1/status/1831382705285869963

• https://x.com/itseieio/status/1829268247105138764

Every issue of Reboot is full of human choices. Keep up with ours:

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So today we’re coming to you with a new format:

Reboot Macrodoses are an informal ~weekly dump of what our editorial board is reading, watching, playing, seeing online, thinking about, or otherwise experiencing. It includes mini-essays, links, pictures, plus perspectives from our beautiful brilliant readers—if you’d like to publish a 250-word Letter to the Editor about our previous essays, you can now do so here.

(For folks worried that macrodoses will supplant Reboot’s longer-form work, they won’t! These mini-essays are purely additive, and allow us to share more timely, somewhat quicker thoughts in between the Big Essays.)

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For today’s macrodoses, we have:

1. Why Seeing Like A State is so popular in Silicon Valley

2. Sid Meier’s Civilization and its discontents

3. Sports betting is bad, actually

4. A letter to the editor on last week’s essay, “The Concrete Oasis”

5. Reboot personals

Ok! Let’s get started.

— Hal

Seeing Like a Tech CEO

I asked Twitter Why is Silicon Valley so Seeing Like a State-pilled? and had one of the only interesting interactions I’ve had there in the last 3 years. A few highlights: 

• The most straightforward reason? blogged about it in 2010, after borrowing the book from his wife who was in an Anthropology masters’ program. 

• But why would SLAS catch fire from there, and persist for a decade-plus in the Hacker News recommendation mill? Arguably, because it’s useful and relevant to the problems that people who run business and platforms face. It’s tempting to take the high-modernist approach—to write down a clear set of content policies, to abdicate decision-making to A/B tests—but there will always be hidden expertises or the nth-order harms that your metrics miss. Per Shear, “if you run a consumer internet service you are basically running a state.” Or from : “If you’re a technosolutionist and nothing around you is working like you thought it would, SLAS has a ton of explanatory power.”

If SLAS is one slice of the “vague tech canon,” took a solid stab at defining the rest, and at describing its traits:

“This silicon union of intellect and action creates a culture fond of big ideas. The expectation that anyone sufficiently intelligent can grasp, and perhaps master, any conceivable subject incentivizes technologists to become conversant in as many subjects as possible. The technologist is thus attracted to general, sweeping ideas with application across many fields… If the Washington intellectual aims for authority and expertise, the Silicon Valley intellectual seeks novel or counter-intuitive insights. He claims to judge ideas on their utility; in practice I find he cares mostly for how interesting an idea seems at first glance.”

By my meager assessment, Collison’s book list is genuinely good. Lots of science/tech history, Great Man sagas, systems and complexity, counterculture, and yes, libertarianism. You can fill in what’s missing :)

— Jasmine

Civilization & its Discontents

If any video game series belongs in the vague tech canon that Jasmine (& Pat Collison et al) are defining, it’d be Civilization. The long-running turn-based strategy game series is known for its grand ambitions (you do, literally, guide a virtual civilization from the dawn of the agricultural age to the stars) and its intense fandom, which counts Mark Zuckerberg and Elon Musk among its numbers (I, personally, have logged an ungodly number of hours on the last two games of the series.) 

This is all to say that the announcement this week of Civilization VII, the upcoming new installment in the series, is an opportunity to look at what Civilization wants to tell us about Civilization. Core among its discursive innovations (to Silicon Valley, at least) is the idea of the “tech tree”—a branching set of paths, starting with agriculture and ending with interplanetary travel—which has become for many a mental model for how technological progress works. You, as the founder of your civilization, have control over its linear ascension through the eras, one dependency after another. Yet one of the major changes in Civ VII is that civilizations are no longer fixed—the societies of Ancient Egypt can transition into medieval Mongolia or Songhai, for example—a sign that a series sometimes critiqued for euro-centric, essentializing narratives of progress might be venturing into more ambiguous territory. 

— Jacob

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Sports betting is bad, actually

The 2024 Summer Olympics finished a few weeks ago, which made me (an unabashed track and field fan) deeply sad. Although it was annoying to watch the same six AI products several dozen times each—which, by the way, is the result of literally hundreds of millions of dollars of ad spend—there was one feature of sports advertising that was notably absent: sports betting ads.

If you, as I am, are a young man in the US with at least a mild part-time interest in sports, sports betting has probably saturated your algorithmically curated feeds. This noise—“$250 free on your first bet!”, “Bet on individual football plays!”, “Endorsed by Ben Affleck”—has slowly built across American sports culture over half a decade like a bad case of tinnitus. Only in an international competition without sports betting was I reminded of the blessed sound of silence.

You may at this point think I sound like a curmudgeon. You’re probably right. But there are tons of anecdotes about increases in gambling addiction in the last few years, particularly among young men. That’s why I feel thankful that this week I came across a paper that systematically analyzes the larger negative effects of this industry: ”Gambling Away Stability: Sports Betting's Impact on Vulnerable Households.” To me, this paper puts a hard quantitative backing behind my kvetching. In fairness to me, sports betting companies were already up to lots of shady shit, like paying universities to promote betting to their 18 year-old students. 

Compared to controls in counties without legal sports betting, the authors show that

legalization reduces net investments by nearly 14%. A rough quantification of the causal effect of sports betting on investing behavior suggests that $1 of betting reduces net investment by just over $2.

These effects are particularly pernicious among people who are already poor.

[T]hese results suggest that sports betting exacerbates the financial constraints of households already operating with less flexibility. The reduced payments towards credit card bills, coupled with rising debt levels, indicate that these households are not merely shifting funds from one type of entertainment to another but are instead becoming more indebted to fund an addictive losing proposition.

Documenting the concrete negative effects of this culture is a rhetorical tonic those intensely Bayesian pundits—*ahem* Nate Silver *ahem*—who evangelize the importance of betting on everything. For a much more in-depth analysis of this phenomenon, and a refutation on its own terms, please read and ’s recent essay in The Point, “The Bookmaker.”

— Hal

Letters to the Editor: On “The Concrete Oasis”

When Noah speaks of architecture, it makes me think of software design. While economically motivated, software design ought also to carry aesthetic value—though it’s at times hard to measure. 

I don’t know if anything compares to brutalism, but product design sure has its duds. Like this new trend of greeting mobile app users with an un-skippable welcome video. It has to be the software equivalent of the ROM Crystal. Instead of trying out the app, you’re forced to sit through a 30 second rundown while your phone (and I swear this is true!) incessantly buzzes. It makes you wonder what’s the point.

Still, for all the silliness, I appreciate the trying. I miss the early mobile era. Back when Snapchat threw absolutely insane design ideas at the wall (like automatically starting a video chat when you were synchronously DMing!). It might not have appeared sensical, but it sure seems to have paid off (Stories?). In an era of mostly commoditized design, I like apps—and architecture—that bear a message, even if it’s a slightly obnoxious one.

— (website) is a product designer and the co-founder of Can of Soup.

Reboot Personals

For sale:

• Caltrain, Heavily Used

• 1998 B-2 Spirit Bomber (yours for the low, low price of $2,899,999. Do not inquire about provenance.)

• A fictional semiotic standard (someone make a poster of this please) and a whole lot of clicky switches and buttons

Seen outside the DNC in Chicago:

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