Rather, I feel that Apple has forgotten its roots. The Mac was “the computer for the rest of us,” and there were usability guidelines backed by research. What made the Mac stand out against Windows during a time when Windows had 95%+ marketshare was the Mac’s ease of use. The Mac really stood out in the 2000s, with Panther and Tiger being compelling alternatives to Windows XP.

I think Apple is less perfectionistic about its software than it was 15-20 years ago. I don’t know what caused this change, but I have a few hunches:

0. There’s no Steve Jobs.

1. When the competition is Windows and Android, and where there’s no other commercial competitors, there’s a temptation to just be marginally better than Windows/Android than to be the absolute best. Windows’ shooting itself in the foot doesn’t help matters.

2. The amazing performance and energy efficiency of Apple Silicon is carrying the Mac.

3. Many of the people who shaped the culture of Apple’s software from the 1980s to the 2000s are retired or have even passed away. Additionally, there are not a lot of young software developers who have heard of people like Larry Tesler, Bill Atkinson, Bruce Tognazzini, Don Norman, and other people who shaped Apple’s UI/UX principles.

4. Speaking of Bruce Tognazzini and Don Norman, I am reminded of this 2015 article (https://www.fastcompany.com/3053406/how-apple-is-giving-desi...) where they criticized Apple’s design as being focused on form over function. It’s only gotten worse since 2015. The saving grace for Apple is that the rest of the industry has gone even further in reducing usability.

I think what it will take for Apple to readopt its perfectionism is if competition forced it to.

Additionally, today’s sky-high RAM and SSD prices have caused an unexpected situation: Apple’s inflated prices for RAM and SSD upgrades don’t look that bad in comparison to paying market prices for DIMMs and NVMe SSDs. Yes, the Framework has the advantage of being upgradable, meaning that if RAM and SSD prices decrease, then upgrades will be cheaper in the future, whereas with a Mac you can’t (easily) upgrade the RAM and storage once purchased. However, for someone who needs a computer right now and is willing to purchase another one in a few years, then a new Mac looks appealing, especially when considering the benefits of Apple Silicon.

In my opinion, Clinton’s and Harris’ losses had less to do with their gender and more to do with the candidates themselves:

1. Clinton was facing strong anti-establishment headwinds, and Clinton is a very establishment politician. Many people in 2016 were piping mad at establishment politicians. Trump was able to win the GOP nomination on a platform of “draining the swamp” and pursuing an aggressively right-wing agenda compared to more moderate Republicans, and Sanders, who also had an anti-establishment platform, proved to be a formidable opponent to Clinton. Despite Clinton’s loss, she was still able to win the popular vote. Perhaps had there been less anti-establishment sentiment, it would have been a Clinton vs Jeb Bush election, and I believe Clinton would have won that race.

2. Harris never won a presidential primary election. The only reason she ended up becoming the nominee is because Biden dropped out of the race after his disastrous debate performance against Trump, which occurred after the primaries. Since it was too late to have the voters decide on a replacement for Biden, the Democratic Party selected a replacement: Harris. She only had a few months to campaign, whereas Trump had virtually campaigned his entire time out of office.

3. Let’s not forget the Trump factor in 2024. During Biden’s entire presidency, Trump was able to consolidate his hold on the GOP and his voting base, and in some ways he even expanded his base. The conservative media was filled with defenses of January 6, and Trump was able to convince enough Americans that he and his supporters were persecuted in the aftermath of the 2020 election and January 6.

A big reason for Trump's success despite his polarizing nature is the polarizing effects of the platforms of our two parties, which distinguish themselves on "culture war" issues such as abortion, gun rights, immigration, LGBT+ rights, and race relations. There are many Americans who love the MAGA agenda, and there are also many Americans who are not in 100% agreement with MAGA but who'd never vote for a Democrat since they feel that a candidate with the opposite cultural views is anathema. If third parties were more viable in America, the latter group of voters could vote for a candidate that is more to their temperament instead of voting for whomever the GOP nominee is.

Even so, the ARM Mac Pro felt more like a halo car rather than a workhorse. The ARM Mac Pro may have been more compelling had it supported GPUs. Without this support, the price premium of the Mac Pro over the Mac Studio was too great to justify purchasing the Pro for many people, unless they absolutely needed internal expansion.

I’d love a user-upgradable Mac like my 2013 Mac Pro, but it’s clear that Apple has long moved on with its ARM Macs. I’ve moved on to the PC ecosystem. On one hand ARM Macs are quite powerful and energy-efficient, but on the other hand they’re very expensive for non-base RAM and storage configurations, though with today’s crazy prices for DDR5 RAM and NVMe SSDs, Apple’s prices for upgrades don’t look that bad by comparison.

I have mixed feelings about this. On one hand I miss being able to upgrade RAM at a later date without having to pay up-front for all of the RAM I'm expected to use for the lifetime of the machine. This is especially painful in 2026 with today's sky-high RAM prices caused by intense demand. On the other hand, the memory bandwidth in Apple's ARM Macs is tremendous, especially in higher-end Macs, due to the tight integration of the design. This matters greatly in memory-intensive applications such as generative AI. I feel less bad about non-expandable RAM given the tradeoffs, though it still makes for quite expensive computing, especially at 2026 RAM prices.

I guess Apple has finally achieved Steve Jobs' original Macintosh vision of closed-off appliances, though (thankfully) the NeXT Cube and the NeXTstation were not like that. RIP to Jean Louis-Gassée's vision of expandable, upgradeable Macs, starting with the Macintosh II in 1987 and leading to other fine Macs such as the Macintosh IIfx, the Quadra lineup, high-end Power Macs (8100, 8500, 9500, 8600, 9600, G3, G4, G5), and the Mac Pro.

Times have changed. The field has become much more serious about making money; fantasies about volunteering at Apple have been replaced with fantasies about very large salaries and RSU grants. Simultaneously (and I don't think coincidentally), the field has become less fun. I recognized how privileged this sounds talking about "fun", given how for most of humanity, work isn't about having fun and personal fulfillment, but about making the money required to house, feed, and clothe themselves and their loved ones. Even with the drudgery of corporate life, it beats the work conditions and the abuse that many other occupations get.

Still, let's pour one out for a time when the interests and passions of computing enthusiasts did line up with the interests of the corporate world.

The “hacker-friendliness” of software industry employment has been eroding in the past decade or so, and generative AI is another factor that strengthens the position of business owners and managers. Perhaps this is the maturing of the software development field. Back when computers were new and when there were few people skilled in computing, employment was more favorable for hobbyists. Over time the frontiers of computing have been settled, which reduced the need for explorers, and thus explorers have been sidelined in favor of different types of workers. LLMs are another step; while I’m not sure that LLMs could do academic research in computer science, they are already capable of doing software engineering tasks that undergraduates and interns could do.

I think what some of us are mourning is the closing of a frontier, of our figurative pastures being turned into suburban subdivisions. It’s bigger than generative AI; it’s a field that is less dependent on hobbyists for its future.

There will always be other frontiers, and even in computing there are still interesting areas of research and areas where hobbyists can contribute. But I think much of the software industry has moved in a direction where its ethos is different from the ethos of enthusiasts.

I am now a tenure-track community college professor. I’m evaluated entirely by my teaching and service. While teaching a full course load is intense, and while my salary is nowhere near what a FAANG engineer makes, I get three months of summer break and one month of winter break every year to rejuvenate and to work on personal projects, with nobody telling me what research projects to work on, how frequently I should publish, and how fast I ship code.

This quote from J. J. Thomson resonates with me, and it’s more than 100 years old:

"Granting the importance of this pioneering research, how can it best be promoted? The method of direct endowment will not work, for if you pay a man a salary for doing research, he and you will want to have something to point to at the end of the year to show that the money has not been wasted. In promising work of the highest class, however, results do not come in this regular fashion, in fact years may pass without any tangible results being obtained, and the position of the paid worker would be very embarrassing and he would naturally take to work on a lower, or at any rate a different plane where he could be sure of getting year by year tangible results which would justify his salary. The position is this: You want this kind of research, but, if you pay a man to do it, it will drive him to research of a different kind. The only thing to do is to pay him for doing something else and give him enough leisure to do research for the love of it." (from https://archive.org/details/b29932208/page/198/mode/2up).

With that said, the dream is not dead. There's a project named Gershwin (https://github.com/gershwin-desktop/gershwin-desktop), which is a Mac-like desktop environment built on top of GNUstep. Gershwin appears to be heavily inspired by Apple Rhapsody (https://en.wikipedia.org/wiki/Rhapsody_(operating_system)) with some modern touches.

Our core computer science curriculum consists of five courses: (1) an introductory programming course taught in a procedural subset of C++, (2) an object-oriented programming course taught in C++, (3) a data structures and algorithms course taught in C++, (4) a discrete mathematics course, and (5) an assembly language course that also covers basic computer architecture. Students who pass all five courses are prepared to transfer to a four-year university to complete their undergraduate computer science programs. The majority of our students transfer to either San Jose State University or California State University East Bay, though many of our students transfer to University of California campuses, typically UC Davis, UC Santa Cruz, UC Merced, and UC Irvine.

Because I teach introductory freshman- and sophomore-level courses, I feel it is vital for students to have a strong foundation with basic programming and basic computer science before using generative AI tools, and thus I do not accept programming assignments that were completed using generative AI tools. I admit that I'd have a different, more nuanced stance if I were teaching upper-division or graduate-level computer science courses. I have found that students who rely on generative AI for programming tend to struggle more on exams, and they also tend to lack an understanding of the programming language constructs the generated program used.

With that said, I recognize that generative AI tools are likely to become more powerful and cheaper over time. As much as I don't like this brave new world where students can cheat with even less friction today, we professors need to stay on top of things, and so I will be spending the entire month of June (1/3rd of my summer break) getting up to speed with large language models, both from a users' point of view and also from an AI research point of view.

Whenever my students are wondering whether it's worth studying computer science in light of the current job market and anxieties about AI replacing programmers, I tell them two things. The first thing I tell them is that computers and computation are very interesting things to study in their own right. Even if AI dramatically reduces software engineering jobs, there will still be a need for people to understand how computers and computation work.

The second thing I tell them is that economic conditions are not always permanent. I was a freshman at Cal Poly San Luis Obispo in 2005, when computer science enrollment bottomed out in the United States. In high school, well-meaning counselors and teachers warned me about the post-dot com bust job market and about outsourcing to India and other countries. I was an avid Slashdot reader, and the piece of advice I kept reading was to forego studying computer science and earn a business degree. However, I was a nerd who loved computers, who started programming at nine years old. I even wrote an essay in high school saying that I'd move to India if that's where all of the jobs are going to end up. The only other things I could imagine majoring in at the time were mathematics and linguistics, and neither major was known for excellent job prospects. Thus, I decided to major in computer science.

A funny thing happened while I was at Cal Poly. Web 2.0, smartphones, cloud computing, and big data took off during my undergraduate years. My classmates and I were able to get internships at prestigious companies, even during the economic crisis of 2008-09. Upon graduation, I ended up doing an internship in Japan at a major Japanese tech company and then started a PhD program at UC Santa Cruz, but many of my classmates ended up at companies like Microsoft, Apple, and Google, just in time for tech industry to enter an extended gold rush from roughly 2012 when Facebook went public until 2022 when interest rates started to go up. Many of my classmates made out like bandits financially. Me? I made different choices going down a research/academic path; I still live in an apartment and I have no stock to my name. I have no regrets, except maybe for not getting into Bitcoin in 2011 when I first heard about it.... Though I'm not "Silicon Valley successful", I'm living a much better life today than I was in high school, qualifying for Pell Grants and subsidized student loans to help pay for my Cal Poly education due to my parents' low income.

I still believe in the beauty of an undergraduate curriculum that encourages critical thinking and developing problem-solving skills, as opposed to merely learning industry topics du jour. Specific tools often come and go; my 2005 Linux system administration knowledge didn't cover systemd and Wayland since they didn't exist at the time, but my copies of Introduction to Algorithms by Cormen et al. and my Knuth volumes remain relevant.

With that said, with the decline of commercial Unix and the dominance of Linux, POSIX, in my opinion, has become less important, and in its place Linux seems to be the standard. I prefer the BSDs to Linux due to its design and documentation, but Linux has better hardware support, and the FOSS ecosystem, especially the desktop, is increasingly embracing Linuxisms such as Wayland and systemd. The FOSS BSD ecosystems are too small to counter the Linuxization of the Unix ecosystem, and I feel that Apple does not pay much attention to the BSD side of macOS these days.

I don’t expect the BSDs to die, but I do believe they’ll need to find ways to adapt to an increasingly Linux-dominated FOSS ecosystem.

It was my first Apple laptop and I have fond memories of using it during my college years.

I think there are two typical paths to widespread visibility across CS subfields: (1) publishing a widely-adopted textbook, and (2) writing commonly-used software. For example, many computer scientists know about Patterson and Hennessy due to their famous computer architecture textbooks, and many computer scientists know about people like Jeff Dean due to their software.

Reading more academically-oriented literature such as the ACM’s monthly periodical “Communications of the ACM” is also a good way to get acquainted with the latest developments of computer science.

I don't know what it's like using modern Microsoft Office with no experience using toolbars and menus and then switching to LibreOffice, which still uses traditional toolbars and menus.

I prefer traditional toolbars and menus, but I remember Microsoft doing user studies when developing the original Office 2007 ribbon. It showed that the ribbon was more productive for beginners and casual users. Given that many office suite users are casual users who use word processors, spreadsheets, and presentation tools, Microsoft Office may be more productive for them than LibreOffice. It would be good if LibreOffice did user studies.

Things started going downhill, in my opinion, with the Windows XP "Fisher-Price" Luna interface and the Microsoft Office 2007 ribbon.