Both arts and athletics involve a lot of deft physical movement, and I could see why professionals in those fields would benefit from learning to resist overthinking so they can “just do it.”  Almost every profession involves some need for focus, however, so you can see why, over time, the idea of a flow state breached its original limits. Now, “flow state” has all sorts of associations—some scientific, some folk, and some a mix of both. For many, the term has just become a dressed-up version of focusing.

A 2023 study found, for example, that there is a huge range of barriers to flow—many of which aren’t just interruptions from coworkers. They categorized these as situational barriers, such as interruptions and distractions; personal barriers, such as the work being too challenging or not challenging enough; and interpersonal barriers, such as poor management and poor team dynamics.

A 2018 study found, in addition, that the most disruptive interruptions aren’t external—they’re internal. 81% of the participants predicted internal interruptions would be worse, but they were wrong. “Self-interruptions,” the researchers wrote, “make task switching and interruptions more disruptive by negatively impacting the length of the suspension period and the number of nested interruptions.”

But because no one literally interrupted your work, you might be unaware of the costs of that rote, mundane work. You might even castigate yourself over the day for not getting the work done: You fought for a distraction-free day, got it, and you have nothing to show for it. It can feel bad.

a seemingly individual problem, staying focused, is often downstream from an organizational problem.

XML tags are used to wrap around content, like this: <tag>content</tag>. Opening and closing XML tags should share exactly the same name. The tag name can be anything you like, as long as it's wrapped in angle brackets, although we recommend naming your tags something contextually relevant to the content it's wrapped around.

To get the most out of XML tags, keep these tips in mind: Use descriptive tag names that reflect the content they contain (e.g., <instructions>, <example>, <input>). Be consistent with your tag names throughout your prompts. Always include both the opening (<tag>) and closing (</tag>) tags, including when you reference them, such as Using the document in <doc></doc> tags, answer this question. You can and should nest XML tags, although more than five layers of nesting may decrease performance depending on the complexity of the use case.

For situations with long documents or a lot of additional background content, Claude generally performs noticeably better if the documents and additive material are placed up top, above the detailed instructions or user query

When working with long documents (particularly 30K+ tokens), it's essential to structure your prompts in a way that clearly separates the input data from the instructions. We recommend using XML tags to encapsulate each document. This structure is how Claude was trained to take long documents, and is thus the structure that Claude is most familiar with

Given the often-classified nature of large defense and intelligence contracts, a lack of transparency makes it difficult to discern the true amount of U.S. spending diverted to Big Tech. Yet, research reveals that the amount is substantial, and growing. According to the nonprofit research organization Tech Inquiry, three of the world’s biggest tech corporations were awarded approximately $28 billion from 2018 to 2022, including Microsoft ($13.5 billion), Amazon ($10.2 billion), and Alphabet

From 2021 through 2023, venture capital firms reportedly pumped nearly $100 billion into defense tech startup companies — an amount 40 percent higher than the previous seven years combined.

The intransigent Zoomer modernity of Zendaya’s screen image — a face that, because of “Euphoria,” will probably always seem to me as if it’s “seen an iPhone” — is the perfect foil for a role so rooted in pre-Code comedies like “Design for Living,” and she harnesses that disconnect in a way that allows Tashi to have this entire movie by the balls without ever foot-faulting into invulnerability.

There isn’t an inch of nudity apart from some extras in the locker room showers, and yet Guadagnino shoots the climactic match with a stylistic vulgarity that suggests what sports might look like if Brazzers suddenly took over for ESPN. Slo-mo, Wong Kar-wai-esque step-printing, floor-angle shots from underneath the court, racket POV shots, ball POV shots … every point is defined by a different technique, each rally existing within its own self-contained universe in which sex doesn’t exist and tennis is the only form of human expression.

if you had showed VisiCalc to a lawyer or a graphic designer, their response might well have been ‘that’s amazing, and maybe my book-keeper should see this, but I don’t do that’. Lawyers needed a word processor, and graphic designers needed (say) Postscript, Pagemaker and Photoshop, and that took longer.

I’ve been thinking about this problem a lot in the last 18 months, as I’ve experimented with ChatGPT, Gemini, Claude and all the other chatbots that have sprouted up: ‘this is amazing, but I don’t have that use-case’.

A spreadsheet can’t do word processing or graphic design, and a PC can do all of those but someone needs to write those applications for you first, one use-case at a time.

no matter how good the tech is, you have to think of the use-case. You have to see it. You have to notice something you spend a lot of time doing and realise that it could be automated with a tool like this.

Some of this is about imagination, and familiarity. It reminds me a little of the early days of Google, when we were so used to hand-crafting our solutions to problems that it took time to realise that you could ‘just Google that’.

This is also, perhaps, matching a classic pattern for the adoption of new technology: you start by making it fit the things you already do, where it’s easy and obvious to see that this is a use-case, if you have one, and then later, over time, you change the way you work to fit the new tool.

The concept of product-market fit is that normally you have to iterate your idea of the product and your idea of the use-case and customer towards each other - and then you need sales.

Meanwhile, spreadsheets were both a use-case for a PC and a general-purpose substrate in their own right, just as email or SQL might be, and yet all of those have been unbundled. The typical big company today uses hundreds of different SaaS apps, all them, so to speak, unbundling something out of Excel, Oracle or Outlook. All of them, at their core, are an idea for a problem and an idea for a workflow to solve that problem, that is easier to grasp and deploy than saying ‘you could do that in Excel!’ Rather, you instantiate the problem and the solution in software - ‘wrap it’, indeed - and sell that to a CIO. You sell them a problem.

there’s a ‘Cambrian Explosion’ of startups using OpenAI or Anthropic APIs to build single-purpose dedicated apps that aim at one problem and wrap it in hand-built UI, tooling and enterprise sales, much as a previous generation did with SQL.

Back in 1982, my father had one (1) electric drill, but since then tool companies have turned that into a whole constellation of battery-powered electric hole-makers. One upon a time every startup had SQL inside, but that wasn’t the product, and now every startup will have LLMs inside.

people are still creating companies based on realising that X or Y is a problem, realising that it can be turned into pattern recognition, and then going out and selling that problem.

A GUI tells the users what they can do, but it also tells the computer everything we already know about the problem, and with a general-purpose, open-ended prompt, the user has to think of all of that themselves, every single time, or hope it’s already in the training data. So, can the GUI itself be generative? Or do we need another whole generation of Dan Bricklins to see the problem, and then turn it into apps, thousands of them, one at a time, each of them with some LLM somewhere under the hood?

The change would be that these new use-cases would be things that are still automated one-at-a-time, but that could not have been automated before, or that would have needed far more software (and capital) to automate. That would make LLMs the new SQL, not the new HAL9000.

Living in an immigrant, multilingual family will open your eyes to all the ways humans can misunderstand each other. My story isn’t unique, but I grew up unable to communicate in my family’s “default language.” I was forbidden from speaking Korean as a child. My parents were fluent in spoken and written English, but their accents often left them feeling unwelcome in America. They didn’t want that for me, and so I grew up with perfect, unaccented English. I could understand Korean and, as a small child, could speak some. But eventually, I lost that ability.

I became the family Chewbacca. Family would speak to me in Korean, I’d reply back in English — and vice versa. Later, I started learning Japanese because that’s what public school offered and my grandparents were fluent. Eventually, my family became adept at speaking a pidgin of English, Korean, and Japanese.

This arrangement was less than ideal but workable. That is until both of my parents were diagnosed with incurable, degenerative neurological diseases. My father had Parkinson’s disease and Alzheimer’s disease. My mom had bulbar amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Their English, a language they studied for decades, evaporated.

It made everything twice as complicated. I shared caretaking duties with non-English speaking relatives. Doctor visits — both here and in Korea — had to be bilingual, which often meant appointments were longer, more stressful, expensive, and full of misunderstandings. Oftentimes, I’d want to connect with my stepmom or aunt, both to coordinate care and vent about things only we could understand. None of us could go beyond “I’m sad,” “I come Monday, you go Tuesday,” or “I’m sorry.” We struggled alone, together.

You need much less to “survive” in another language. That’s where Google Translate excels. It’s handy when you’re traveling and need basic help, like directions or ordering food. But life is lived in moments more complicated than simple transactions with strangers. When I decided to pull off my mom’s oxygen mask — the only machine keeping her alive — I used my crappy pidgin to tell my family it was time to say goodbye. I could’ve never pulled out Google Translate for that. We all grieved once my mom passed, peacefully, in her living room. My limited Korean just meant I couldn’t partake in much of the communal comfort. Would I have really tapped a pin in such a heavy moment to understand what my aunt was wailing when I knew the why?

For high-context languages like Japanese and Korean, you also have to be able to translate what isn’t said — like tone and relationships between speakers — to really understand what’s being conveyed. If a Korean person asks you your age, they’re not being rude. It literally determines how they should speak to you. In Japanese, the word daijoubu can mean “That’s okay,” “Are you okay?” “I’m fine,” “Yes,” “No, thank you,” “Everything’s going to be okay,” and “Don’t worry” depending on how it’s said.

often these days I find myself in the position of defending someone I think is annoying from someone I know is dangerous.

The last three jobs I've held in the last 5 years have all felt like someone just handing me the keys to a sinking boat before they jump off. Every job is sold as having at least some greenfield development where you can "own" the domain and "lead" the direction of the project, but once you accept the offer and get on-boarded, you realize that the system is so brittle that any change will completely break and cause incidents, and there is a year's worth of backlog issues to address with duck-tape and glue before you could even consider fixing the fundamental problems.

Often the teams that built these systems are long gone, so there is nobody to ask for help when you're learning the rough edges, you're just on your own. The technology decisions are all completely set in stone because we could never justify the risk of making changes. There is so much tech debt and maintenance work, we don't really have time to do any new development with the current staffing levels. The job then becomes dominated by on-call responsibilities and fire-fighting. It's 90% toil, and almost zero actual system design and development work.

Being responsible for a whole system that you didn't build, that you know is brittle and broken, but which you cannot fix, is incredibly stressful. It's almost a hopeless situation.

In their quest for social change, givers like Arnold are reluctant to support “causes”; they want to “solve problems—big ones,” as Callahan puts it. But, in Arnold’s case, lessons had to be learned along the way. His early forays into philanthropy, including an effort to reform public pensions, were scorned, with critics noting that Enron’s collapse had resulted in the loss of billions of dollars in pension funds.

Moskovitz and Tuna weren’t keen to embrace traditional development organizations, which they are inclined to view as lethargic and bureaucratic. For them, grant making is akin to venture-capital investing: they want to act decisively and disrupt traditional models and structures. They have contributed $32 million to a group called Give Directly, which is not interested in vaccinating children, digging wells, building toilets, and creating schools. Rather, it gives cash handouts to the poor, who are free to spend the money as they wish. Callahan is skeptical of the ideology guiding Moskovitz and Tuna—who favor Silicon Valley mantras such as “empower individuals over institutions”—but he knows they are too influential to ignore. The couple will give away hundreds of millions of dollars every year. They are not yet thirty-five years old.

There are growing concerns about the influence and reach of the superwealthy: “Philanthropy is becoming a much stronger power center,” Callahan says, “and, in some areas, is set to surpass government in its ability to shape society’s agenda.” The state has retreated; the givers have advanced.

in many U.S. cities, elected officials are overwhelmed by debt obligations, and as a result have precious little money to spend on parks, museums, and other public services. The givers have no such constraints. In Boston, the Barr Foundation has done much to shape the city’s arts, culture, and political milieu. In Houston, Richard Kinder is helping to forge a massive network of urban trails. In Detroit, the Kresge Foundation is contributing funds for a new light-rail system. In New York, the Leon Levy Foundation has helped to revitalize a pair of Brooklyn landmarks, the Brooklyn Public Library and the Brooklyn Botanic Garden. These are worthy endeavors, but Callahan is right to express concern about a fundamental shift of power from a “hollowed-out public sector” to elite private givers who are not fully accountable and operate in dark corners.

In 2008 Stephen A. Schwarzman, another cofounder of Blackstone, gave $100 million to the New York Public Library at a moment when the Library was secretly undertaking a dubious real estate and construction scheme. For nearly a decade, the NYPL refused to reveal how Schwarzman’s money was being utilized. Only in recent months did the Library account for the gift’s use: the $100 million formed part of the endowment and will soon be used for new renovation projects.

Under an initiative backed by Broad and like-minded funders, L.A. could add hundreds of new charter schools in a decade. Broad is quick to refute allegations that he is overreaching: “I think everyone is getting heard,” he informed Callahan. “We’re getting heard, the philanthropists. The unions and administrators are getting heard. Overall, we’re creating debate.”

That may be so, but increasingly the debate is among people who already agree. The Givers makes a persuasive case that the superwealthy are expanding their influence at a moment when many Americans are bolting from civic and political life. The author, drawing on the scholarship of Theda Skocpol, evokes an earlier era when mass-membership organizations such as trade unions flourished, giving ordinary citizens a certain degree of influence vis-à-vis elite power structures. These days, he writes, “We’re fast moving toward a future where private funders, not elected officials and the citizens they answer to, choreograph more of public life.”

Of the top eighty American foundations, only twenty-six post detailed information about their current grant making on public databases. The Susan Thompson Buffett Foundation, endowed by Warren’s wealth, “has no real website and the information available on its grant making through tax returns is always a few years out of date,” Callahan notes.

The Givers is alive to these and other contradictions in the philanthropic sector and poses thorny questions for elected officials and nonprofit leaders: why is a check to a right-wing think tank tax-deductible but a check to a conservative senator is not? Why are many large foundations spending a mere 5 percent of their assets each year when they can easily afford to spend more? Why do so many foundations exist in perpetuity, instead of “spending down” and closing their doors? Why is the sector so lightly regulated by government, particularly the IRS? Finally, what exactly is the public getting in exchange for colossal tax breaks granted for philanthropy, which mainly go to rich people?

The Givers, which went to press before Donald Trump was elected, concludes with a stark and prescient warning: the nonprofit sector should initiate its own reforms, before politicians do it with a heavier and more mischievous hand. “It’s not okay,” he warns, “to settle for a status quo in which the foundation world remains forever a black box.” His proposals for change—the creation of a new U.S. federal office of charitable affairs, a reevaluation of what should qualify for tax-exempt status, trustee boards that are more inclusive and transparent—are not likely to be embraced in Trump’s Washington, however.

Katz, writing after Trump’s victory, argued that Callahan has sidestepped the central issue: Our current dire political situation is the product of both traditional American anti-statism and a very different and deliberate assault on the state by plutocrats. We do not have so many billionaires, and thus mega-foundations, because we now have a larger and more adept entrepreneurial class, but because the structure of (mostly federal) economic policy has been captured by people of wealth, who have rewritten the laws to enable themselves to become extraordinarily rich…It seems to me that the new plutocrats are in fact the problem, and they are quite unlikely to be part of the solution, as Callahan contends.

My own wish is that Callahan had confronted, in a more pungent way, the structural features of the behemoth that looms before him: the grant-making model itself, upon which modern American philanthropy rests. Foundation leaders advocate transparency, inclusion, and equality, but they operate in a strikingly hierarchical manner. They are a cloistered elite.

Does this top-down model—in which grantees spend immense time and energy chasing cash—inhibit the growth of dues-paying organizations, which may be more vibrant and democratic than nonprofit organizations dominated by an aloof board of trustees and an executive director? Passages in The Givers suggest that Callahan has pondered these matters, but he stops short of a full critique.

There are now more than ninety thousand private foundations, whose assets total $700 billion. These foundations supply money to more than a million tax-exempt, nonprofit organizations. Some of these nonprofits are financially secure, but many chafe under immense anxiety as they await annual grants from their masters in the foundation suites.

what consequences has the rise of management consulting had for the organization of American business and the lives of American workers? The answers to these questions put management consultants at the epicenter of economic inequality and the destruction of the American middle class.

Managers do not produce goods or deliver services. Instead, they plan what goods and services a company will provide, and they coordinate the production workers who make the output. Because complex goods and services require much planning and coordination, management (even though it is only indirectly productive) adds a great deal of value. And managers as a class capture much of this value as pay. This makes the question of who gets to be a manager extremely consequential.

In the middle of the last century, management saturated American corporations. Every worker, from the CEO down to production personnel, served partly as a manager, participating in planning and coordination along an unbroken continuum in which each job closely resembled its nearest neighbor.

Even production workers became, on account of lifetime employment and workplace training, functionally the lowest-level managers. They were charged with planning and coordinating the development of their own skills to serve the long-run interests of their employers.

At McDonald’s, Ed Rensi worked his way up from flipping burgers in the 1960s to become CEO. More broadly, a 1952 report by Fortune magazine found that two-thirds of senior executives had more than 20 years’ service at their current companies.

Top executives enjoyed commensurately less control and captured lower incomes. This democratic approach to management compressed the distribution of income and status. In fact, a mid-century study of General Motors published in the Harvard Business Review—completed, in a portent of what was to come, by McKinsey’s Arch Patton—found that from 1939 to 1950, hourly workers’ wages rose roughly three times faster than elite executives’ pay. The management function’s wide diffusion throughout the workforce substantially built the mid-century middle class.

The earliest consultants were engineers who advised factory owners on measuring and improving efficiency at the complex factories required for industrial production. The then-leading firm, Booz Allen, did not achieve annual revenues of $2 million until after the Second World War. McKinsey, which didn’t hire its first Harvard M.B.A. until 1953, retained a diffident and traditional ethos

A new ideal of shareholder primacy, powerfully championed by Milton Friedman in a 1970 New York Times Magazine article entitled “The Social Responsibility of Business is to Increase its Profits,” gave the newly ambitious management consultants a guiding purpose. According to this ideal, in language eventually adopted by the Business Roundtable, “the paramount duty of management and of boards of directors is to the corporation’s stockholders.” During the 1970s, and accelerating into the ’80s and ’90s, the upgraded management consultants pursued this duty by expressly and relentlessly taking aim at the middle managers who had dominated mid-century firms, and whose wages weighed down the bottom line.

Management consultants thus implemented and rationalized a transformation in the American corporation. Companies that had long affirmed express “no layoff” policies now took aim at what the corporate raider Carl Icahn, writing in the The New York Times in the late 1980s, called “corporate bureaucracies” run by “incompetent” and “inbred” middle managers. They downsized in response not to particular business problems but rather to a new managerial ethos and methods; they downsized when profitable as well as when struggling, and during booms as well as busts.

Downsizing was indeed wrenching. When IBM abandoned lifetime employment in the 1990s, local officials asked gun-shop owners around its headquarters to close their stores while employees absorbed the shock.

In some cases, downsized employees have been hired back as subcontractors, with no long-term claim on the companies and no role in running them. When IBM laid off masses of workers in the 1990s, for example, it hired back one in five as consultants. Other corporations were built from scratch on a subcontracting model. The clothing brand United Colors of Benetton has only 1,500 employees but uses 25,000 workers through subcontractors.

The shift from permanent to precarious jobs continues apace. Buttigieg’s work at McKinsey included an engagement for Blue Cross Blue Shield of Michigan, during a period when it considered cutting up to 1,000 jobs (or 10 percent of its workforce). And the gig economy is just a high-tech generalization of the sub-contractor model. Uber is a more extreme Benetton; it deprives drivers of any role in planning and coordination, and it has literally no corporate hierarchy through which drivers can rise up to join management.

In effect, management consulting is a tool that allows corporations to replace lifetime employees with short-term, part-time, and even subcontracted workers, hired under ever more tightly controlled arrangements, who sell particular skills and even specified outputs, and who manage nothing at all.

the managerial control stripped from middle managers and production workers has been concentrated in a narrow cadre of executives who monopolize planning and coordination. Mid-century, democratic management empowered ordinary workers and disempowered elite executives, so that a bad CEO could do little to harm a company and a good one little to help it.

Whereas at mid-century a typical large-company CEO made 20 times a production worker’s income, today’s CEOs make nearly 300 times as much. In a recent year, the five highest-paid employees of the S&P 1500 (7,500 elite executives overall), obtained income equal to about 10 percent of the total profits of the entire S&P 1500.

as Kiechel put it dryly, “we are not all in this together; some pigs are smarter than other pigs and deserve more money.” Consultants seek, in this way, to legitimate both the job cuts and the explosion of elite pay. Properly understood, the corporate reorganizations were, then, not merely technocratic but ideological.

corporate reorganizations have deprived companies of an internal supply of managerial workers. When restructurings eradicated workplace training and purged the middle rungs of the corporate ladder, they also forced companies to look beyond their walls for managerial talent—to elite colleges, business schools, and (of course) to management-consulting firms. That is to say: The administrative techniques that management consultants invented created a huge demand for precisely the services that the consultants supply.

Consulting, like law school, is an all-purpose status giver—“low in risk and high in reward,” according to the Harvard Crimson. McKinsey also hopes that its meritocratic excellence will legitimate its activities in the eyes of the broader world. Management consulting, Kiechel observed, acquired its power and authority not from “silver-haired industry experience but rather from the brilliance of its ideas and the obvious candlepower of the people explaining them, even if those people were twenty-eight years old.”

A deeper objection to Buttigieg’s association with McKinsey concerns not whom the firm represents but the central role the consulting revolution has played in fueling the enormous economic inequalities that now threaten to turn the United States into a caste society.

Meritocrats like Buttigieg changed not just corporate strategies but also corporate values.

GM may aspire to build good cars; IBM, to make typewriters, computers, and other business machines; and AT&T, to improve communications. Executives who rose up through these companies, on the mid-century model, were embedded in their firms and embraced these values, so that they might even have come to view profits as a salutary side effect of running their businesses well.

When management consulting untethered executives from particular industries or firms and tied them instead to management in general, it also led them to embrace the one thing common to all corporations: making money for shareholders. Executives raised on the new, untethered model of management aim exclusively and directly at profit: their education, their career arc, and their professional role conspire to isolate them from other workers and train them single-mindedly on the bottom line.

American democracy, the left believes, cannot be rejuvenated by persuading elites to deploy their excessive power somehow more benevolently. Instead, it requires breaking the stranglehold that elites have on our economics and politics, and reempowering everyone else.

Under Raghavan, Google has become less reliable, less transparent, and is dominated by search engine optimized aggregators, advertising, and outright spam.

Google is the ultimate essential piece of online infrastructure, just like power lines and water mains are in the physical realm.

In April 2011, the Guardian ran an interview with Raghavan that called him “Yahoo’s secret weapon,” describing his plan to make “rigorous scientific research and practice… to inform Yahoo's business from email to advertising,” and how under then-CEO Carol Bartz, “the focus has shifted to the direct development of new products.” It speaks of Raghavan’s “scientific approach” and his “steady, process-based logic to innovation that is very different to the common perception that ideas and development are more about luck and spontaneity,” a sentence I am only sharing with you because I need you to see how stupid it is, and how specious the tech press’ accolades used to be. This entire article is ridiculous, so utterly vacuous that I’m actually astonished. What about Raghavan’s career made this feel right? How has nobody connected these dots before and said something? Am I insane?

Sundar Pichai, who previously worked at McKinsey — arguably the most morally abhorrent company that has ever existed, having played roles both in the 2008 financial crisis (where it encouraged banks to load up on debt and flawed mortgage-backed securities) and the ongoing opioid crisis, where it effectively advised Purdue Pharma on how to “growth hack” sales of Oxycontin. McKinsey has paid nearly $1bn over several settlements due to its work with Purdue. I’m getting sidetracked, but one last point. McKinsey is actively anti-labor.

Some pointed out that labeling nei ge or its pronunciation as offensive, as the USC ​administration seemed to do, following the letter, only makes sense within an Anglophone bubble – that doing so portrays the Chinese language as subject to English rules rather than independent and possessing its own contexts

The Black China Caucus, an American organization that describes itself as “amplifying Black voices in the China space,” also defended Patton on Twitter. “The BCC is shocked by how USC mishandled this situation,” the organization posted. “Not only would a quick Mandarin lesson reveal that “nèi ge” is a common pronoun, but USC’s reaction cheapens and degrades substantive conversations surrounding real (diversity, equity and inclusion) challenges on college campuses!”

Upon arriving at the facility, Bruce handed in his smartphone and passed through metal detectors. He was in awe of the semiconductor production line: Overhead rails carried wafers from one station to another while workers in white protective suits kept the machinery running. “It really just felt like I was touring some kind of living thing that was greater than humans; that was bigger than us,” Bruce recalled.

TSMC made attempts to bridge some of the cultural differences. After the American trainees asked to contact families and to listen to music at work, TSMC loosened the firewall on T phones to allow all staff access to Instagram, YouTube, and Spotify. Some Taiwanese workers attended a class on U.S. culture, where they learned that Americans responded better to encouragement rather than criticism, according to an engineer who attended the session.

Several former American employees said they were not against working longer hours, but only if the tasks were meaningful. “I’d ask my manager ‘What’s your top priority,’ he’d always say ‘Everything is a priority,’” said another ex-TSMC engineer. “So, so, so, many times I would work overtime getting stuff done only to find out it wasn’t needed.”

Training in Taiwan, which typically lasted one to two years, wasn’t all miserable, the Americans said. On the weekends, the trainees traveled across the island, marveling at the country’s highly efficient public transport network. Bruce spent his weekends hiking and frequenting nightclubs. He chatted with the families that run night-market food stalls, and entertained strangers who requested selfies with foreigners.

For the Taiwanese, many of whom planned for extended stays in Phoenix, that meant relocating entire families — toddlers and dogs included — to a foreign country. Many regarded it as a once-in-a-lifetime opportunity to explore the world, practice English, and send their children to American schools. Younger families planned pregnancies so they could give birth to American citizens. “If we are going to have children, of course we will have them here,” a Taiwanese engineer told Rest of World. “As an American citizen, they will have more options than others.”

Many experienced a culture shock. The bustling cities of Taiwan are densely packed and offer extensive public transport, ubiquitous street food, and 24-hour convenience stores every few blocks. In northern Phoenix, everyday life is impossible without a car, and East Asian faces are scarce

“Everything is so big in America,” said one engineer, recalling his first impression. He recounted his wife summarizing her impression of the U.S.: “Great mountains, great rivers, and great boredom.”

Having spent years under the company’s grueling management, they were used to long days, out-of-hours calls, and harsh treatment from their managers. In Taiwan, the pay and prestige were worth it, they told Rest of World — despite the challenges, many felt proud working for the island’s most prominent firm. It was the best job they could hope for.

Sometimes, the engineers said, staff would manipulate data from testing tools or wafers to please managers who had seemingly impossible expectations.

A former TSMC staffer who worked on the education program said managers were instructed not to yell at employees in public, or threaten to fire them without consulting human resources. “They would say, ‘Okay, okay, I get it. I’m not going to do that,’” the employee recalled to Rest of World. “But I think in the heat of the moment, they forgot, and they did do it.”

Chang-Tai Hsieh, an economics professor at the University of Chicago, told Rest of World that TSMC had found the U.S. a challenging environment to operate in because of the complicated regulatory process, strong construction unions, and a workforce less used to the long hours that are commonplace at TSMC in Taiwan.

Sitting in a room together, the engineers admitted that although they had made some progress in acclimating to life in the U.S., TSMC had yet to find a balance between the two work cultures. Some Taiwanese workers complained that management was being too accommodating in giving Americans less work, paying them high salaries, and letting them get off work early.

Handling the vast volume of AI-generated images still requires precise curation, adjustments, and post-production. The prompt is just a starting point. These images rarely manage to stand alone without context; layout, copywriting, and motion need to click in place, and the formula needs to be replicable to create a robust brand system. That’s the right moment to pull in multiple collaborators, bringing expertise and taste into play. It's good to have more time for that.

I use generative AI primarily for concepting and moodboarding. It helps clients imagine what their brand identity could look like. I save time browsing stock image libraries or trying to describe art direction concepts (“It would look like this illustration depicting a car, but it would actually show a jar of cream!”). AI-generated concepts then serve as a brief for skilled illustrators, photographers, and other creatives to build upon.

For early-stage companies, I often use AI-generated images because it's a cost-effective way of creating a library of differentiated visual assets that they otherwise wouldn't be able to afford to produce.

I mostly use Midjourney, TopazAI, Glif.app, Visual Electric, Krea, ChatGPT, Magnific, Adobe Firefly