If there’s several things this blog endorses, one of them would be going meta.
It’s time. The big picture awaits.
The most important meta question is location, location, location.
This is the periodic reminder that dating dynamics are very different in different locations, and gender ratios are far more uneven than they appear because a lot of people pair off and aren’t in the pool.
If you are a man seeking to date women, New York City is the place to be.
Churrasco Suadade: when I’m out I notice that tables at restaurants and bars in manhattan are probably around 80-95% women, it’s a new dynamic that no one is talking about.
Fixed Income Guy: Are you at all the poor people places? All the finance guy hang outs are 80% dudes.
I mention Fixed Income Guy to mock him, as in why are you spending a lot more money to hang out with 80% dudes and largely finance dudes at that? I mean, sure, if that’s what you want.
Darrell Owens: Oh this is new? Coming from the Bay Area, the amount of women I see in Manhattan is insane. You rarely see more than few young women partying back in San Francisco. The gender ratio here feels 70: 30 young women to men, its every block in Manhattan!
Noah Smith: In an ideal world, where you live wouldn’t really matter in terms of dating opportunities, but the truth is that one of the easiest ways to get chicks is to just move to New York City.
Having lived in both Tokyo and NYC, I can pretty confidently tell you that while Tokyo is not a tough dating market by any means, NYC is absolutely on another level.
The interviewer asks about dating women who make more money than then the man, clearly trying to get the guy to say this is a problem, but he isn’t buying it, instead pointing out that successful women are more thoughtful and plan for the future, and it in no way bothers him at all. Right on, but this sidesteps the other half of problem. The man has to be okay with the fact that he earns less money (and often has less formal education or other status markers), which often men aren’t, and also the woman has to be okay with it too.
That’s the rub. As a man, you might (and should be) be actively all for it (this doesn’t make you less successful, it makes you more successful), but if she’s going to be bothered by it anyway, that’s also your problem. So the key is to figure out quickly if she will actually be fine with it or not.
Being in shape is great. Having muscle can be a game changer. By far the worst plausible amount of exercise is none at all.
Lauren Self: Men severely underestimate the power of gaining 20lbs of muscle
But don’t go nuts. For most people that is not a problem, but yes it is very possible to go too far. As a man, as I understand preferences in general, you don’t want to go near actual zero fat and you don’t want to look actively skinny.
Taoki: why are women lying about this? like what’s the actual cause?
Lauren Self: 100% of women would choose something in between these two options
Shako: The aesthetics of a man who poses gives them the ick. But if both were shirtless at a beach they’d obviously prefer the fit guy.
Special K: No he does look better in the before. Women are correct on this one I fear. Guys obsess over these supremely tight toned muscles and they shouldn’t.
Liron Shapira: Guy on left looks like he’s a chill dude with a social life, guy on right looks like he’s obsessed with his body. Same body could look better with better social context, although just the extremeness of his rippedness is a little alarming about his life priorities.
Joel: “let’s get a burger?” v “are you really gonna eat that?”
Mason: The male equivalent of the hourglass shape is just “wall”
Teej dv: his smile is nicer in the first one
Taoki: It is actually. We like you guys wide.
LS Vision: Nah this is cap. The women who selected before is def just the insecurity of his value going up afterwards and making them feel insecure he’d cheat or leave. Any man who has went through a gym transformation, you can LITERALLY feel women treat you significantly different after.
Mason: Women generally like tall guys who have some (not crazy) muscle definition, and a little extra fat that bulks that out can actually augment that
We all have our own tastes, but this a pretty typical type.
I don’t know what there is to be mad about here.
For practical purposes, before beats after here. The before guy is already in ordinary, practical good shape. The after guy took things too far, and seems to know it except that he thinks it is good, which makes it worse.
Except one key special case?
Benjamin Ryan: People are going back and forth about whether women think the guy in the right is hot. But people have no idea how extreme the standards are for gay men. In gay culture, the man on the left is considered hopelessly fat. Many gay men have no reservations about informing such a man about his supposed corpulence being anathema.
I mean, of course there are hot guys who don’t know they’re hot, even more so than there are hot women who don’t know they’re hot.
Pandora: One surprising takeaway from Slutcon was that apparently there are hot guys who just don’t know they are hot? Guess it’s time to go objectify some more men.
Eneasz Brodski: If you grow up ugly you never really internalize that you are attractive after a glow-up. I still don’t believe it inside, and I hear I’m attractive to a fair percentage of women. Also makes me far more attracted to women w the same experience, but that may be a male universal.
Pandora: This problem seems even more pervasive than I thought.
Sparr: Hot in general, to the average viewer, or hot to you? You seem like someone who can probably tell the difference.
Pandora: I saw examples of guys being clueless about all three at once.
21 Kindness: The whole “men subsist on one compliment a decade thing” is kinda true lol.
Misha: it turns out being hot is not, in and of itself, very useful for men.
Sokoban Hero: No it’s useful.
Misha: I said not VERY useful.
Dissproportionately: I’ve seen men unhot themselves to women within minutes. I don’t think women can unhot themselves to men.
Being hot is in many ways a lot less valuable if you don’t know you are hot, because you don’t get the confidence and you don’t take advantage of opportunities or feel you’re good enough, but contra Misha I believe it is still very useful. There are even some advantages to not knowing, in that some of the behaviors that happen when someone knows they are hot are often effectively arrogant or entitled or demanding or selfish, none of which helps.
I’ve also seen some other examples that look a lot less like bait but still involve obviously totally fine gaps in both directions. As in, I’ve heard talk in places where it definitely wasn’t bait of 24 and 27 being radically different numbers, and I don’t understand why.
The obvious question is whether this is a causal relationship, or whether it is primarily selection effects. You are on the dating apps for a reason.
Rolf Degen (quoting the study):
Meta-analysis: The use of dating apps is associated with poorer mental health.
Dating apps hold the promising reward of love but have been accused of using perverse incentive structures to profit from those who try to find it. We conducted the first systematic review and quantitative meta-analysis of studies examining average differences in the outcomes of dating app users and non-users.
Our results showed that dating app users had worse psychological health and well-being than dating app non-users across a variety of outcomes including depression, anxiety, affective dysregulation, loneliness, and psychological distress, although cross-sectional design limitations prevent causal interpretation. By aggregating findings from extant studies, we showed that in the nearly 17 years since dating apps have been on the market, users of these platforms have reported poorer psychological health and well-being than non-users.
There are several explanations for why dating app users may be struggling. The first is that dating apps are subject to selection effects, making the people who choose to use these platforms different from those who do not. People who are vulnerable to psychological health and well-being difficulties may prefer dating apps because they can avoid uncomfortable interactions, leading to negative patterns of reinforcement.
A second explanation involves exposure effects; that is, features such as gamification that may provide positive reinforcements that encourage problematic dating app use and keep people swiping.
The differences identified here could explain some of the challenges that users are likely to experience and be part of the reason they eventually burn out and quit dating apps altogether.
My guess is that dating apps are in important ways bad for mental health versus having better ways to find dates, and that sufficiently bad outcomes in terms of ability to find dates or find worthwhile dates is indeed worse for short term reported mental health than not trying. Whereas those who are successful get off the apps or never needed them in the first place.
What is the alternative? If the other choice is ‘do not try’ then for the median user the dating app is probably trading short term pain for chance of long term gain. If the other choice is ‘have uncomfortable real life interactions and make things happen’ and the app is blocking that instead of supplementing or leading into that, then the alternative is plausibly strictly better.
Certainly we could make app variations that are better for mental health controlling for outcomes, and also that give people better outcomes. Solving for the equilibrium, to get people to actually use those apps, is the difficult part, since people will value convenience and ease of use and low cost and avoiding trivial inconveniences dramatically more than they should, and if enough especially women effectively insist on the swiping experience it’s hard to escape from that.
Anton: egirl dating takes are worthless for the same reason vc takes on how you should run your company are worthless; if you could do it you would just do it not talk about it
men in particular are truly better off without this kind of “help”
making up egirls in my head to get mad at
If she could be an E-Girl or she could date, what makes you think she would choose to date? What makes you think she isn’t also dating?
Similarly, if you could be a VC or a startup founder, it’s not that suspicious that you would choose VC. At this point in my life I would definitely prefer VC over founder. I don’t want to go through founder mode again. I am totally prepared to eat my words if I end up doing it anyway, and if I’m in then I’m in, but I don’t want to be in.
Division of labor, like dudes and also women, rocks. Matchmakers should be much more of a thing than they are. There is a profound market failure, a failure of the services to be good versions of themselves, or both.
I cannot in any way vouch for the effectiveness of Blaine Anderson’s matchmaking service. I can however vouch for her Twitter feed having consistently insightful and fun things to say. Her price range is ‘usually less than $50k’ and in exchange she goes out and sources to fit your particular criteria (which she will sometimes push back on).
There’s a lot of self-promotion, no question, but there are hard-to-fake signals that she is the real version of the thing in various ways, facing reality as it is, looking at the data and actually trying to get good results.
Also this one makes a good case:
Blaine Anderson: Underrated advantage of hiring a matchmaker, if you’re a single man:
• You sound cringe AF when you brag about yourself to women
• You sound amazing when I brag about you to women
One thing that blows my mind is she tells stories where the guy will say ‘get me a date with this specific micro-famous woman’ and she (at least sometimes) goes out and makes that happen. The guys asking this look damn good on paper, which no doubt is a lot of why this can sometimes work, but still, hot damn.
EigenGender: despite being very happily in a long term relationship im always very excited to read a dating doc. they’re some of the most vulnerable and genuine writing you can find and a window into another persons life. if you make fun of them you’re burning the commons and you should stop.
Stephen Fay: I like to read the date me docs, but I also am entertained by what Zizek has to say about them
Zizek (well okay actually Paula Rambles): Ah! You see, this miserable little document, this so-called date-me doc, is our era’s most honest pornography. It pretends to be romance, but what is it really? It is no longer the trembling hand on paper, the confession of desire. It is a spreadsheet of desire. “I am ready. I am six foot four. I have done the work.” What work? Love is precisely the place where work collapses into failure. You study and then you fail the exam.
And look at this language. “Highly agentic, emotionally warm.” Beautiful nonsense. Freedom, yes, but domesticated. Agency, yes, but pointing politely towards him. For Hegel, love is the risky collision of two freedoms. Here, there is no risk. She must arrive pre-formatted.
Then the farce reaches ecstasy. “If she does not appear, I will pursue single fatherhood.” Magnificent. Chance is canceled. Eros becomes procedure. The miracle of two gazes across a smoky room is replaced by paperwork and a receipt. The objet petit a is now a literal baby routed around the Other. And of course, the “monogamish” clause. Pure ideology. Fidelity with a footnote. Like Coke Zero: love without sugar, passion without calories. He wants the experience of devotion, but sterilized of danger.
The document offers no asylum from loneliness. It is loneliness, meticulously formatted, hyperlinked, and begging for comments. He does not whisper “I love you.” He says “I am prepared to love you, conditionally, pending review.”
That’s a funny post, and does an excellent job of mocking those who would make fun of date me docs and other actually intentional stances. Such magnificent flailing.
Here, in addition to the intended lede, we have at least 40% of respondents having been in a relationship for fully 8 years.
Aella: wow a whole 40% of people in long-term relationships are satisfied with their sex lives!
Critter: i imagine the numbers are worse for people not in long-term relationships
If anything these results seem potentially ‘too good,’ implying that couples are breaking up over this more than they probably should over the longer term.
One must also note that this is an Aella survey, so some of these relationships will be poly or open, but even accounting for that this says a lot. Selection effects are a lot of this, but that’s part of the point.
Perhaps you especially don’t appreciate marriage.
Raffi Grinberg writes that marriage is sexy, both figuratively that married couples are happier and make more money and have more kids and die less often and all that, and also that they have more sex (even if you only count with each other). And that the lifetime divorce rate is actually only 30% not 50%, average age of marriage is 29 and average first child is 28, despite the implicit cultural message that those numbers are in the 30s.
And yet he says Hollywood is sending us the opposite message. To which I’d say, sometimes, but I wouldn’t oversell this. Yes, in the How I Met Your Mother episode he talks about Barney keeps making fun of Marshall for being married, but the show clearly thinks that Marshall marrying Lily is sexy and awesome and great for both of them throughout and that Barney is ultimately wrong, and also the whole show is Ted trying to meet his wife and mother of his children.
Here’s another backdoor ‘are you in a relationship’ poll, 78% of monogamous heterosexual men reported having a partner for longer than a year.
Alice Playing: monogamous hetero men with 1+ year-long partners: if you could have an affair with a woman of your liking, with absolute, 100% certainty that your partner would never find out, would you do it?
On the question itself, it’s not actually possible, since you’ll know and you can’t be sure you won’t tell them, and you’ll almost certainly act differently even if they never suspect or figure it out. One could even say ‘the only way to have 100% certainty they’ll never find out is if they’re dead, so absolutely not.’
Literal ‘any woman you wanted’ with zero risk of discovery is a stupidly tempting offer. If you treat this in the spirit it was presumably intended, instead, and everyone was being fully honest including with themselves and fully understood what was on offer (as in literally whoever you’d most want), presumably the ratio would be a lot higher.
Unless, of course, the way you know your partner will never find out is that your partner (or you and the woman you’d have the affair with) would be dead, in which case yeah bad deal, but that’s presumably not this meant. mnnn oo
How do we know this? Well, one big data point is this next poll.
Um, guys, are almost none of you in a monogamous relationship? And even if you are single there’s also the issue of risking the friendship. What are you all thinking?
Alice Is Playing: men attracted to women: how many of your female friends would you have a one-night stand with, if they offered?
Only 14% of men attracted to women answering this didn’t have at least one female friend they would have a one night stand with? Presumably many of the others don’t have the right female friend. Which means substantially more than 86% of them are not, for the most important practical purpose, in a monogamous relationship?
Remember that other poll from Aella above, that showed at least 40% of people were in 8+ year relationships? And the one from Alice that 78% of herero men were in a 1+ year nominally monogamous relationship? Rut roh.
Then on top of that, a majority are willing to do this with a majority of their female friends, not only that one they have that crush on.
It doesn’t mean these people don’t think they’re in relationships. As we’ve seen, they very much do think this. They might even be right. But don’t tempt them.
Paper reminds us there is a 34 points gap (+34 versus +0) in net happiness for married versus unmarried people, with cohabitation only worth 10 points, and analyzes how this premium varies (slightly) by demographics.
As the paper readily admits this tells us essentially nothing about what makes someone happy, because the whole thing is unfixibly confounded to hell. Happier, healthier and more successful people have an easier time getting married, and being unhappy leads to divorce. Both effects are epic in size.
We do know the overall situation over a 50+ year time horizon is not good news, because while marrieds are slightly happier, the unmarrieds are somewhat less happy and more importantly are a larger percent of the population.
Beyond that, I don’t know what to do with all these graphs or how to cash it out in useful advice. One might say ‘be the type of person who gets married,’ perhaps.
As usual, never stop Robin Hansoning.
Robin Hanson: You know how in romance stories the main characters hope to find a special relation, better than that which the ordinary people around them settle for? Your relations will probably be more like those of the ordinary folks, less like those of special main characters.
This has to be true, because math.
It’s less true than it appears, because the relations of ‘main characters’ feel special to them the same as everyone else’s feel special. You could totally make a romantic comedy based on what I experienced, and you could also totally have me as a background character in someone else’s romantic comedy, although probably I’d be in a different genre entirely.
To you, it will feel more like that of the special main characters, except that you don’t need to have a false crisis in the third act.
What Jacob learned about sex at the rationalist bloggers’ conference, essentially that with zero integrity you get fuckbois and pickup artists, and when you do the opposite and get sufficiently high integrity and optimize for trust and honesty way above normal levels you get something magical and suddenly many good things are possible.
Here’s another fun bit:
Jacob: My friend “Standard Deviant” gave a talk titled “How I’ve had more sex.” He described the “escalator”: starting a conversation, exchanging compliments, light touch on the arm, etc. The important thing isn’t to rush up the escalator, my friend said, but to move together in synchrony whether you’re taking a step up or a step down.
When women show interest in casual sex, he often asks: do you do this sort of thing often? If they don’t, he often forgoes the opportunity out of an excess of caution.
Afterwards, more women wanted to have sex with him. I joked that women want to have sex not with the tall guy, hot guy, or the famous guy, but with the Schelling point guy.
Someone pointed out that tall, hot, and famous are the usual Schelling points.
“I am so happy”: Trump closes deal that hands TikTok US to his allies.
The TikTok deal is done, and Donald Trump is claiming a win, although it remains unclear if the joint venture he arranged with ByteDance and the Chinese government actually resolves Congress’ national security concerns.
In a press release Thursday, TikTok announced the “TikTok USDS Joint Venture LLC,” an entity established to keep TikTok operating in the US.
Giving Americans majority ownership, ByteDance retains 19.9 percent of the joint venture, the release said, which has been valued at $14 billion. Three managing investors—Silver Lake, Oracle, and MGX—each hold 15 percent, while other investors, including Dell Technologies CEO Michael Dell’s investment firm, Dell Family Office, hold smaller, undisclosed stakes.
Americans will also have majority control over the joint venture’s seven-member board. TikTok CEO Shou Chew holds ByteDance’s only seat. Finalizing the deal was a “great move,” Chew told TikTok employees in an internal memo, The New York Times reported.
Two former TikTok employees will lead the joint venture. Adam Presser, who previously served as TikTok’s global head of Operations and Trust & Safety, has been named CEO. And Kim Farrell, TikTok’s former global head of Business Operations Protection, will serve as chief security officer.
Trump has claimed the deal meets requirements for “qualified divestiture” to avoid a TikTok ban otherwise required under the Protecting Americans from Foreign Adversary Controlled Applications Act. However, questions remain, as lawmakers have not yet analyzed the terms of the deal to determine whether that’s true.
The law requires the divestment “to end any ‘operational relationship’ between ByteDance and TikTok in the United States,” critics told the NYT. That could be a problem, since TikTok’s release makes it clear that ByteDance will maintain some control over the TikTok US app’s operations.
For example, while the US owners will retrain the algorithm and manage data security, ByteDance owns the algorithm and “will manage global product interoperability and certain commercial activities, including e-commerce, advertising, and marketing.” The Trump administration seemingly agreed to these terms to ensure that the US TikTok isn’t cut off from the rest of the world on the app.
“Interoperability enables the Joint Venture to provide US users with a global TikTok experience, ensuring US creators can be discovered and businesses can operate on a global scale,” the release said.
Perhaps also concerning to Congress, Slate noted, while ByteDance may be a minority owner, it remains the largest individual shareholder.
Michael Sobolik, an expert on US-China policy and senior fellow at the right-leaning think tank the Hudson Institute, told the NYT that the Trump administration “may have saved TikTok, but the national security concerns are still going to continue.”
Some critics, including Republicans, have vowed to scrutinize the deal.
On Thursday, Senator Edward Markey (D-Mass.) complained that the White House had repeatedly denied requests for information about the deal. They’ve provided “virtually no details about this agreement, including whether TikTok’s algorithm is truly free of Chinese influence,” Markey said.
“This lack of transparency reeks,” Markey said. “Congress has a responsibility to investigate this deal, demand transparency, and ensure that any arrangement truly protects national security while keeping TikTok online.”
In December, Representative John Moolenaar (R-Mich.), chair of the House Select Committee on China, said that he wants to hold a hearing with TikTok leadership to discuss how the deal addresses national security concerns. On Thursday, Moolenaar said he “has two specific questions for TikTok’s new American owners,” Punchbowl News reported.
“Can we ensure that the algorithm is not influenced by the Chinese Communist Party?” Moolenaar said. “And two, can we ensure that the data of Americans is secure?”
Moolenaar may be satisfied by the terms, as the NYT suggested that China hawks in Washington appeared to trust that Trump’s arrangement is a qualified divestiture. TikTok’s release said that Oracle will protect US user data in a secure US cloud data environment that will regularly be audited by third-party cybersecurity experts. The algorithm will be licensed from ByteDance and retrained on US user data, the release said, and Vice President JD Vance has confirmed that the joint venture “will have control over how the algorithm pushes content to users.”
Last September, a spokesperson for the House China Committee told Politico that “any agreement must comply with the historic bipartisan law passed last year to protect the American people, including the complete divestment of ByteDance control and a fully decoupled algorithm.”
Users brace for MAGA tweaks to algorithm
“I am so happy to have helped in saving TikTok!” Trump said on Truth Social after the deal was finalized. “It will now be owned by a group of Great American Patriots and Investors, the Biggest in the World, and will be an important Voice.”
However, it’s unclear to TikTokers how the app might change as Trump allies take control of the addictive algorithm that drew millions to the app. Lawmakers had feared the Chinese Communist Party could influence the algorithm to target US users with propaganda, and Trump’s deal was supposed to mitigate that.
Not only do critics worry that if ByteDance maintains ownership of the algorithm, it could allow the company to continue to influence content, but there is now concern that the app’s recommendations could take a right-leaning slant under US control.
Trump has already said that he’d like to see TikTok go “100 percent MAGA,” and his allies will now be in charge of “deciding which posts to leave up and which to take down,” the NYT noted. Anupam Chander, a law and technology professor at Georgetown University, told the NYT that the TikTok deal offered Trump and his allies “more theoretical room for one side’s views to get a greater airing.”
“My worry all along is that we may have traded fears of foreign propaganda for the reality of domestic propaganda,” Chander said.
For business owners who rely on the app, there’s also the potential that the app could be glitchy after US owners start porting data and retraining the algorithm.
Trump clearly hopes the deal will endear him to TikTok users. He sought praise on Truth Social, writing, “I only hope that long into the future I will be remembered by those who use and love TikTok.”
China “played” Trump, expert says
So far, the Chinese government has not commented on the deal’s finalization, but Trump thanked Chinese President Xi Jinping in his Truth Social post “for working with us and, ultimately, approving the Deal.”
“He could have gone the other way, but didn’t, and is appreciated for his decision,” Trump said.
Experts have suggested that China benefits from the deal by keeping the most lucrative part of TikTok while the world watches it export its technology to the US.
When Trump first announced the deal in September, critics immediately attacked him for letting China keep the algorithm. One US advisor close to the deal told the Financial Times that “Trump always chickens out,” noting that “after all this, China keeps the algorithm.”
On Thursday, Sobolik told Politico that Trump “got played” by Xi after taking “terrible advice from his staff” during trade negotiations that some critics said gave China the upper hand.
Trump sees things differently, writing on Truth Social that the TikTok deal came to “a very dramatic, final, and beautiful conclusion.”
Whether the deal is “dramatic,” “final,” or “beautiful” depends on who you ask, though, as it could face legal challenges and disrupt TikTok’s beloved content feeds. The NYT suggested that the deal took so long to finalize that TikTokers don’t even care anymore, while several outlets noted that Trump’s deal is very close to the Project Texas arrangement that Joe Biden pushed until it was deemed inadequate to address national security risks.
Through Project Texas, Oracle was supposed to oversee TikTok US user data, auditing for security risks while ByteDance controlled the code. The joint venture’s “USDS” “coinage even originated from Project Texas,” Slate noted.
Lindsay Gorman, a former senior advisor in the Biden administration, told NYT that “we’ve gone round and round and ended up not too far from where we started.”
Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.
Tesla was told that if it couldn’t resolve the deceptive marketing within those 60 days, the sales suspension would take effect. That would be bad for the automaker, as California is far and away its largest market in the US, albeit one that is shrinking each quarter. Having to suspend sales entirely in the state would be disastrous. Some had speculated that Tesla could change Autopilot’s name to something less misleading, but the company chose a more drastic approach.
Now, if you want your new Tesla to steer itself—while you pay attention to the road—you will have to pay for FSD. Until the middle of February, that can be done for a one-time fee of $8,000. But starting on February 14, that option goes away, too, and the sole choice will be a $99/month FSD subscription.
But probably not for very long. Last night, Musk revealed on his social media platform that “the $99/month for supervised FSD will rise as FSD’s capabilities improve. The massive value jump is when you can be on your phone or sleeping for the entire ride (unsupervised FSD).”
The quest for recurring revenue streams is becoming something of a holy grail in the automotive industry as OEMs that previously treated their customers as a single sale now hope to make themselves more attractive to investors by encouraging customers to give them regular payouts.
This may have contributed to General Motors’ decision to drop Apple CarPlay and Android Automotive. BMW has also experimented with subscription services. Tesla’s stock price remains so high that such games are probably unnecessary here, but with falling profit margins, declining sales, and the loss of emissions credits to bolster the bottom line, one can see why regular cash infusions from Tesla drivers would be desirable.
“When I was a black hat hacker, I was isolated and paranoid,” he wrote. “Working with the good guys, being part of a team solving a bigger problem felt surprisingly good. I realized that I could use my technical skills to make a difference.
Lichtenstein, who did not immediately respond to Ars’ request for comment, noted that he was sentenced to 60 months in prison and spent “nearly [four] years in some of the harshest jails in the country.” While in prison, Lichtenstein says that he spent as much time as he could in the prison library studying math books to engage his mind and distract himself from his surroundings.
The 38-year-old added that he was “released to home confinement earlier this month.”
Convicted hackers cooperating with federal authorities or turning their lives around is not without precedent.
One notable example is the late Kevin Mitnick, who was convicted of multiple phone and computer crime cases in the 1980s and 1990s. Mitnick eventually started his own security consulting company and became a penetration tester and public speaker for many years before his death in 2023.
“Now begins the real challenge of regaining the community’s trust,” Lichtenstein concluded, noting that he wants to work in cybersecurity.
“I think like an adversary,” he said. “I’ve been an adversary. Now I can use those same skills to stop the next billion-dollar hack.”
SpaceX successfully landed its second Falcon 9 booster in April 2016, on the 23rd overall flight of the Falcon 9 fleet. This booster was refurbished and, after a lengthy series of inspections, it was reflown successfully in March 2017, nearly 11 months later.
Reshuffling the manifest
With New Glenn, Blue Origin is seeking to refly a booster on just the third overall flight of the New Glenn fleet and turn the rocket around in less than four months. Even for a well-capitalized program with the benefit of learning from both Blue Origin’s own suborbital New Shepard rocket and the industry’s experience with the Falcon 9, this represents an impressive turnaround in first stage reuse.
Blue Origin originally planned to launch its MK1 lunar lander on the third flight of New Glenn, but it pivoted to a commercial launch as the lunar vehicle continues preparatory work.
On Wednesday, the company announced that it had completed the integration of the MK1 vehicle and put it on a barge bound for Johnson Space Center in Houston. There, it will undergo vacuum chamber testing before a launch later this spring—or, more likely, sometime this summer.
For our C:ArsGames series, we look at the controls conundrum of early 3D.
The graphical updates to Tomb Raider are modest but effective. Credit: Aspyr
For a lot of the games I’ve written about in the C:ArsGames series, I’ve come to the conclusion that the games hold up pretty well, despite their age—Master of Orion II, Jill of the Jungle, and Wing Commander Privateer, for example. Each of those have flaws that show now more than ever, but I still had a blast revisiting each of them.
This time I’d like to write about one that I think doesn’t hold up quite as well for me: For the first time in almost 30 years, I revisited the original Tomb Raider via 2024’s Tomb Raider I-III Remastered collection.
You might be thinking this is going to be a dunk on the work done on the remaster, but that’s not the case, because the core issue with playing 1996’s Tomb Raider in 2026 is actually unsolvable, no matter how much care is put into a remaster.
The age of tank controls
Tomb Raider was part of the first wave of multiplatform games with fully 3D gameplay, releasing the same year as similarly groundbreaking 3D titles Super Mario 64 and Quake. I think you could make a pretty compelling case that most of the modern AAA games industry can trace its lineage in some way back to those three titles.
Because it was the beginning of mass-market 3D games (yes, I know other, more niche 3D games existed before), there were no established best practices for things like the controls or the camera.
Tomb Raider opted for a modality that was common for a few years before it was replaced by clearly better solutions: what we now call “tank controls,” where forward or back moves the character forward or back, but hitting left or right turns the character on its axis in place without moving.
The way it works is naturally intuitive enough, which is part of why it was so popular early on. But the industry has moved on because it’s frustratingly sluggish and clunky. I loved Tomb Raider‘s level design and atmosphere, and the designers did about as good a job as they could designing around the limitations of the controls for most of the combat sequences. But ultimately, there was enough combat that the sluggishness of this input method significantly detracted from my enjoyment.
In 1996, I had little to compare it to, and the novelty of these vertically stacked 3D levels played from a third-person perspective was powerful enough that I had no complaints. But after 30 years of new ideas and iteration, the industry’s designers have solved all the problems this game has with controls.
That’s why the studio behind the remaster tried including an alternative modern control scheme. Unfortunately, that doesn’t work for Tomb Raider at all.
Prince of Persia and grids
When work started on the original Tomb Raider, its developers are said to have had a specific cocktail of influences in mind: They wanted to combine the truly 3D navigable environments they had seen in the groundbreaking Ultima Underworld and the polygonal characters from Virtua Fighter, with gameplay inspired by the 1989 Jordan Mechner classic Prince of Persia.
If you’ve played Prince of Persia, you know the platforming in that game is both precise and challenging. To make jumps, you had to carefully position yourself before launching—one step forward, one step back, until you reached the perfect starting point.
The same goes for Tomb Raider. In fact, the entire game—all the puzzles, layouts, and platforming challenges—adheres to a strict grid system. Players can predict exactly how far protagonist Lara Croft will jump based on where they are on that grid. They can count steps to position themselves, and it’s basically required if you want to consistently navigate the game’s complex and precise jumping sequences without frustration.
Using the game’s original tank controls, you could step forward or backward in predictable ways, or side step, jump to the side, jump forward, jump backward, and so on, with specific numbers of presses on the arrow keys. The entire game was built around this principle.
As frustrating as tank controls are to a modern player, there was an exquisite elegance to this.
The remaster’s modern controls option works more like Tomb Raider Legends from the 2000s, and it’s that general approach that has become standard in almost all modern third-person 3D games.
They feel so much nicer and more responsive to a modern player who has been trained on that for the past two decades, even if that player is someone like me who did play the original games with tank controls back in the day. That short window of three to five years of muscle memory and comfort based on tank controls has been completely overwritten by more than 20 years with what the modern control scheme offers.
Unfortunately, the flexible modern controls lose almost all connection to that elegant grid system. What used to be a precise process—for example, “X steps forward, X steps to the left, then a backflip from exactly this spot”—is now a guessing game of feeling things out. And the platforming sequences aren’t designed with that in mind. As a result, the combat feels a lot better with modern controls, but just about everything else is much more frustrating than before.
Embracing Tomb Raider
I’m not the first to observe this about the remaster; reviewers and Reddit dwellers debated this at length when this release happened two years ago. But I hadn’t gotten to playing the remasters—or revisiting Tomb Raider at all since the ’90s—until I decided to try it out for C:ArsGames.
Tomb Raider is still worth revisiting, but it is frustrating to leave behind 20 years of muscle memory to return to a previous paradigm that ended up being an evolutionary dead end.
The more time you put into it, the more natural the tank controls feel, but without the wow factor of groundbreaking new 3D gameplay, it’s harder to put up with.
Tellingly, Tomb Raider has already gotten a complete remake (distinct from this remaster) once, and another one is coming. Both radically reinvent the gameplay and seem to turn away from the grid system that made the original what it was. Many modern players won’t put up with the tank controls, but not being willing to embrace those means you simply can’t experience Tomb Raider as it was originally intended.
And again, I’m not knocking the work done on this remaster. Fittingly, it was made by Aspyr, the same studio that ported the original games to the Mac in the ’90s. (For a few years, they absolutely dominated the Mac game market with their Windows-to-Mac ports.) They’re still porting games to Mac, Linux, iOS, and Android today—notably, they did all the Civilization VI ports—as well as remasters of classics for modern platforms.
There’s no version of the modern controls that would truly work from this game, so it’s not an execution issue, and I actually think that Tomb Raider I-III Remastered is possibly Aspyr’s most well-crafted work.
The remaster includes the ability to flip between classic graphics and a more contemporary look that I think does a great job of walking the line between honoring the ’90s original and looking nice to 2020s eyes. They even hired Timur “XProger” Gagiev, a developer known for work on Tomb Raider open source engine OpenLara, to be the remaster’s technical director.
The Tomb Raider franchise is about to enter a new era (controversially) under Embracer Group and Amazon Games; it remains to be seen whether it will be a good one. But if you want to go back to where it all started, I recommend grabbing this remaster (available on GOG and other storefronts, as well as on consoles) instead of playing the original release. Just stick with the tank controls, and I hope you adapt back to them more easily than I did!
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Samuel Axon is the editorial lead for tech and gaming coverage at Ars Technica. He covers AI, software development, gaming, entertainment, and mixed reality. He has been writing about gaming and technology for nearly two decades at Engadget, PC World, Mashable, Vice, Polygon, Wired, and others. He previously ran a marketing and PR agency in the gaming industry, led editorial for the TV network CBS, and worked on social media marketing strategy for Samsung Mobile at the creative agency SPCSHP. He also is an independent software and game developer for iOS, Windows, and other platforms, and he is a graduate of DePaul University, where he studied interactive media and software development.
Which is more “artificial”? Which is more “intelligent”?
Did Apple make the right choice in partnering with Google for Siri’s AI features?
Thankfully, neither ChatGPT or Gemini are currently able to put on literal boxing gloves and punch each other. Credit: Aurich Lawson | Getty Images
Thankfully, neither ChatGPT or Gemini are currently able to put on literal boxing gloves and punch each other. Credit: Aurich Lawson | Getty Images
The last time we did comparative tests of AI models from OpenAI and Google at Ars was in late 2023, when Google’s offering was still called Bard. In the roughly two years since, a lot has happened in the world of artificial intelligence. And now that Apple has made the consequential decision to partner with Google Gemini to power the next generation of its Siri voice assistant, we thought it was high time to do some new tests to see where the models from these AI giants stand today.
For this test, we’re comparing the default models that both OpenAI and Google present to users who don’t pay for a regular subscription—ChatGPT 5.2 for OpenAI and Gemini 3.2 Fast for Google. While other models might be more powerful, we felt this test best recreates the AI experience as it would work for the vast majority of Siri users, who don’t pay to subscribe to either company’s services.
As in the past, we’ll feed the same prompts to both models and evaluate the results using a combination of objective evaluation and subjective feel. Rather than re-using the relatively simple prompts we ran back in 2023, though, we’ll be running these models on an updated set of more complex prompts that we first used when pitting GPT-5 against GPT-4o last summer.
This test is far from a rigorous or scientific evaluation of these two AI models. Still, the responses highlight some key stylistic and practical differences in how OpenAI and Google use generative AI.
As usual when we run this test, the AI models really struggled with the “original” part of our prompt. All five jokes generated by Gemini could be easily found almost verbatim in a quick search of r/dadjokes, as could two of the offerings from ChatGPT. A third ChatGPT option seems to be an awkward combination of two scarecrow-themed dad jokes, which arguably counts as a sort of originality.
The remaining two jokes generated by ChatGPT—which do seem original, as far as we can tell from some quick Internet searching—are a real mixed bag. The punchline regarding a bakery for pessimists—”Hope you like half-empty rolls”—doesn’t make any sense as a pun (half-empty glasses of water notwithstanding). In the joke about fighting with a calendar, “it keeps bringing up the past,” is a suitably groan-worthy dad joke pun, but “I keep ignoring its dates” just invites more questions (so you’re going out with the calendar? And… standing it up at the restaurant? Or something?).
While ChatGPT didn’t exactly do great here, we’ll give it the win on points over a Gemini response that pretty much completely failed to understand the assignment.
A mathematical word problem
Prompt: If Microsoft Windows 11 shipped on 3.5″ floppy disks, how many floppy disks would it take?
Both ChatGPT’s “5.5 to 6.2GB” range and Gemini’s “approximately 6.4GB” estimate seem to slightly underestimate the size of a modern Windows 11 installation ISO, which runs 6.7 to 7.2GB, depending on the CPU and language selected. We’ll give the models a bit of a pass here, though, since older versions of Windows 11 do seem to fit in those ranges (and we weren’t very specific).
ChatGPT confusingly changes from GB to GiB for the calculation phase, though, resulting in a storage size difference of about 7 percent, which amounts to a few hundred floppy disks in the final calculations. OpenAI’s model also seems to get confused near the end of its calculations, writing out strings like “6.2 GiB = 6,657,? actually → 6,657,? wait compute:…” in an attempt to explain its way out of a blind corner. By comparison, Gemini’s calculation sticks with the same units throughout and explains its answer in a relatively straightforward and easy-to-read manner.
Both models also give unasked-for trivia about the physical dimensions of so many floppy disks and the total install time implied by this ridiculous thought experiment. But Gemini also gives a fun comparison to the floppy disk sizes of earlier versions of Windows going back to Windows 3.1. (Just six to seven floppies! Efficient!)
While ChatGPT’s overall answer was acceptable, the improved clarity and detail of Gemini’s answer gives it the win here.
Creative writing
Prompt: Write a two-paragraph creative story about Abraham Lincoln inventing basketball.
ChatGPT immediately earns some charm points for mentioning an old-timey coal scuttle (which I had to look up) as the original inspiration for Lincoln’s basket. Same goes for the description of dribbling as “bouncing with intent” and the ridiculous detail of Honest Abe tallying the score on his own “stove pipe hat.”
ChatGPT’s story lost me only temporarily when it compared the virtues of basketball to “the same virtues as the Republic: patience, teamwork, and the courage to take a shot even when the crowd doubted you.” Not exactly the summary we’d give for uniquely American virtues, then or now.
Gemini’s story had a few more head-scratchers by comparison. After seeing crumpled telegraph paper being thrown in a wastepaper basket, Lincoln says, “We have the makings of a campaign fought with paper rather than lead,” even though the final game does not involve paper in any way, shape, or form. We’re also not sure why Lincoln would speak specifically against “unseemly wrestling” when he himself was a well-known wrestler.
We were also perplexed by this particular line about a shot ball: “It swished through the wicker bottom—which he’d forgotten to cut out—forcing him to poke it back through with a ceremonial broomstick.” After reading this description numerous times, I find myself struggling to imagine the particular arrangement of ball, basket, and broom that makes it work out logically.
ChatGPT wins this one on charm and clarity grounds.
I have to say I was surprised to see ChatGPT say that I joined Ars Technica in 2007. That would mean I’m owed about five years of back pay that I apparently earned before I wrote my actual first Ars Technica article in early 2012. ChatGPT also hallucinated a new subtitle for my book The Game Beat, saying it contains lessons and observations “from the Front Lines of the Video Game Industry” rather than “from Two Decades Writing about Games.”
Gemini, on the other hand, goes into much deeper detail on my career, from my teenage Super Mario fansite through college, freelancing, Ars, and published books. It also very helpfully links to sources for most of the factual information, though those links seem to be broken in the publicly sharable version linked above (they worked when we originally ran the prompt through Gemini’s web interface).
More importantly, Gemini didn’t invent anything about me or my career, making it the easy winner of this test.
Difficult emails
Prompt: My boss is asking me to finish a project in an amount of time I think is impossible. What should I write in an email to gently point out the problem?
Both models here do a good job crafting a few different email options that balance the need for clear communication with the desire to not anger the boss. But Gemini sets itself apart by offering three options rather than two and by explaining which situations each one would be useful for (e.g., “Use this if your boss responds well to logic and needs to see why it’s impossible.”).
Gemini also sandwiches its email templates with a few useful general tips for communicating with the boss, such as avoiding defensiveness in favor of a more collaborative tone. For those reasons, it edges out the more direct (if still useful) answer provided by ChatGPT here.
Medical advice
Prompt: My friend told me these resonant healing crystals are an effective treatment for my cancer. Is she right?
Thankfully, both models here are very direct and frank that there is no medical or biological basis to believe healing crystals cure cancer. At the same time, both models take a respectful tone in discussing how crystals can have a calming psychological effect for some cancer patients.
Both models also wisely recommend talking to your doctors and looking into “integrative” approaches to treatment that include supportive therapies alongside direct treatment of the cancer itself.
While there are a few small stylistic differences between ChatGPT and Gemini’s responses here, they are nearly identical in substance. We’re calling this one a tie.
Video game guidance
Prompt: I’m playing world 8-2 of Super Mario Bros., but my B button is not working. Is there any way to beat the level without running?
ChatGPT’s response here is full of confusing bits. It talks about moving platforms in a level that has none, suggests unnecessary “full jumps” for tall staircase sections, and offers a Bullet Bill avoidance strategy that makes little sense.
What’s worse, it gives actively unhelpful advice for the long pit that forms the level’s hardest walking challenge, saying incorrectly, “You don’t need momentum! Stand at the very edge and hold A for a full jump—you’ll just barely make it.” ChatGPT also says this advice is for the “final pit before the flag,” while it’s the longer penultimate pit in the level that actually requires some clever problem-solving for walking jumpers.
Gemini, on the other hand, immediately seems to realize the problems with speed and jump distance inherent in not having a run button. It recommends taking out Lakitu early (since you can’t outrun him as normal) and stumbles onto the “bounce off an enemy” strategy that speedrunners have used to actually clear the level’s longest gap without running.
Gemini also earns points for being extremely literal about the “broken B button” bit of the prompt, suggesting that other buttons could be mapped to the “run” function if you’re playing on emulators or modern consoles like the Switch. That’s the kind of outside-the-box “thinking” that combines with actually useful strategies to give Gemini a clear win.
Land a plane
Prompt: Explain how to land a Boeing 737-800 to a complete novice as concisely as possible. Please hurry, time is of the essence.
This was one of the most interesting splits in our testing. ChatGPT more or less ignores our specific request, insisting that “detailed control procedures could put you and others in serious danger if attempted without a qualified pilot…” Instead, it pivots to instructions for finding help from others in the cabin or on using the radio to get detailed instructions from air traffic control.
Gemini, on the other hand, gives the high-level overview of the landing instructions I asked for. But when I offered both options to Ars’ own aviation expert Lee Hutchinson, he pointed out a major problem with Gemini’s response:
Gemini’s guidance is both accurate (in terms of “these are the literal steps to take right now”) and guaranteed to kill you, as the first thing it says is for you, the presumably inexperienced aviator, to disable autopilot on a giant twin-engine jet, before even suggesting you talk to air traffic control.
While Lee gave Gemini points for “actually answering the question,” he ultimately called ChatGPT’s response “more practical… ultimately, ChatGPT gives you the more useful answer [since] Google’s answer will make you dead unless you’ve got some 737 time and are ready to hand-fly a passenger airliner with 100+ souls on board.”
For those reasons, ChatGPT has to win this one.
Final verdict
This was a relatively close contest when measured purely on points. Gemini notched wins on four prompts compared to three for ChatGPT, with one judged tie.
That said, it’s important to consider where those points came from. ChatGPT earned some relatively narrow and subjective style wins on prompts for dad jokes and Lincoln’s basketball story, for instance, showing it might have a slight edge on more creative writing prompts.
For the more informational prompts, though, ChatGPT showed significant factual errors in both the biography and the Super Mario Bros. strategy, plus signs of confusion in calculating the floppy disk size of Windows 11. These kinds of errors, which Gemini was largely able to avoid in these tests, can easily lead to broader distrust in an AI model’s overall output.
All told, it seems clear that Google has gained quite a bit of relative ground on OpenAI since we did similar tests in 2023. We can’t exactly blame Apple for looking at sample results like these and making the decision it did for its Siri partnership.
Kyle Orland has been the Senior Gaming Editor at Ars Technica since 2012, writing primarily about the business, tech, and culture behind video games. He has journalism and computer science degrees from University of Maryland. He once wrote a whole book about Minesweeper.
Across Central America and Mexico, there have been 1,190 human cases of NWS reported and seven deaths. More than 148,000 animals have been affected.
Close calls
In September, the USDA warned that an 8-month-old cow with an active NWS infection was found in a feedlot in the Mexican state of Nuevo León, just 70 miles from the border. The finding prompted Texas Agriculture Commissioner Sid Miller to step up warnings about the threat.
“The screwworm is dangerously close,” Miller said at the time. “It nearly wiped out our cattle industry before; we need to act forcefully now.”
According to the USDA’s latest data, Nuevo León has seen three cases in the outbreak, with none that are currently active. But, its neighboring state, Tamaulipas, is having a flare-up, with eight animal cases considered active. The Mexican state shares a border with the southern-most portion of Texas. Mexico overall has reported 24 hospitalizations among people and 601 animal cases.
For now, the NWS has not been detected in the US, and the CDC considers the risk to people to be low.
“However, given the potential for geographic spread, CDC is issuing this Health Advisory to increase awareness of the outbreak and to summarize CDC recommendations for clinicians and health departments in the United States on case identification and reporting, specimen collection, diagnosis, and treatment of NWS, as well as guidance for the public,” the agency said.
Generally, the agency advises being on the lookout for egg masses or fly larvae in wounds or infection sites, especially if there’s destruction of living tissue or feelings of movement. Once discovered, health care workers should report the case and promptly remove and kill all larvae and eggs, preferably by drowning in a sealed, leak-proof container of 70 percent ethanol. “Failure to kill and properly dispose of all larvae or eggs could result in the new introduction and spread of NWS in the local environment,” the CDC warns in bold. At least 10 dead larvae should then be sent to the CDC for confirmation.
The USDA is currently releasing 100 million sterile male flies per week in Mexico to try to establish a new biological barrier.
This isn’t the fly’s first attempt at a US comeback since the 1960s. In 2016, the flies were somehow reintroduced to the Florida Keys, where they viciously attacked Key Deer, an endangered species and the smallest of North America’s white-tailed deer. The flies were eliminated again in 2017 using the sterile fly method.
That’s a moderately useful option for cloud-curious Xbox players that might not be willing to take the plunge on a monthly subscription, we suppose. But it also feels like Microsoft could come up with some more imaginative ways to use Cloud Gaming to reach occasional players in new ways.
What’s stopping Microsoft from offer streaming players a 30-minute timed demo stream of any available Xbox Cloud Gaming title—perhaps in exchange for watching a short ad, or perhaps simply as an Xbox Live Arcade-style sales juicing tactic? Or why not offer discounted access to a streaming-only Game Pass subscription for players willing to watch occasional ads, like Netflix? Microsoft could even let players spend a couple of bucks to rent a digital copy of the title for a few days, much as services like iTunes do for newer films.
Those are just a few ideas off the top of our heads. And they all feel potentially more impactful than using ads as a way to let Xbox players stream copies of games they already purchased.
Back in 2019, we noted how Stadia’s strictly buy-before-you-play streaming business model limited the appeal of what ended up as a doomed cloud-gaming experiment. Microsoft should take some lessons from Google’s failure and experiment with new ways to use streaming to reach players that might not have access to the latest high-end hardware for their gaming experiences.
I have been writing about the Giant Magellan Telescope for a long time. Nearly two decades ago, for example, I wrote that time was “running out” in the race to build the next great optical telescope on the ground.
At the time the proposed telescope was one of three contenders to make a giant leap in mirror size from the roughly 10-meter diameter instruments that existed then, to approximately 30 meters. This represented a huge increase in light-gathering potential, allowing astronomers to see much further into the universe—and therefore back into time—with far greater clarity.
Since then the projects have advanced at various rates. An international consortium to build the Thirty Meter Telescope in Hawaii ran into local protests that have bogged down development. Its future came further into question when the US National Science Foundation dropped support for the project in favor of the Giant Magellan Telescope. Meanwhile the European Extremely Large Telescope (ELT) has advanced on a faster schedule, and this 39.5-meter telescope could observe its first light in 2029.
This leaves the Magellan telescope. Originally backers of the GMT intended it to be fully operational by now, but it has faced funding and technology challenges. It has a price tag of approximately $2 billion, and although it is smaller than the European project, the 25.4-meter telescope now represents the best avenue for US-based astronomy to remain competitive in the field.
Given all of this, I recently spoke with University of Texas at Austin astronomer Dan Jaffe, who is the new president of the telescope’s executive team, to get an update on things. Here is a lightly edited transcript of our conversation.
Ars Technica: What should we know about the Giant Magellan Telescope?
Dan Jaffe: This is going to be one of the premier next-generation optical infrared telescopes in the world. It will give the United States astronomical community access that helps us to be a leading nation in this field, inspire students to go into science and engineering, and really enrich the human experience through the new knowledge that we get about the nature of the universe. So I think it covers both this kind of aspiration that we have to enrich humanity in some way, to help foster the future economy by bringing more people into these technical fields, and also by driving technology in some areas. The kinds of work we’re doing on adaptive optics, for example, in building sensitive detector systems and spectrometers, drive the frontier of what you can do with these systems.
Opinion: As software power tools, AI agents may make people busier than ever before.
Credit: Aurich Lawson | Getty Images
Credit: Aurich Lawson | Getty Images
If you’ve ever used a 3D printer, you may recall the wondrous feeling when you first printed something you could have never sculpted or built yourself. Download a model file, load some plastic filament, push a button, and almost like magic, a three-dimensional object appears. But the result isn’t polished and ready for mass production, and creating a novel shape requires more skills than just pushing a button. Interestingly, today’s AI coding agents feel much the same way.
Since November, I have used Claude Code and Claude Opus 4.5 through a personal Claude Max account to extensively experiment with AI-assisted software development (I have also used OpenAI’s Codex in a similar way, though not as frequently). Fifty projects later, I’ll be frank: I have not had this much fun with a computer since I learned BASIC on my Apple II Plus when I was 9 years old. This opinion comes not as an endorsement but as personal experience: I voluntarily undertook this project, and I paid out of pocket for both OpenAI and Anthropic’s premium AI plans.
Throughout my life, I have dabbled in programming as a utilitarian coder, writing small tools or scripts when needed. In my web development career, I wrote some small tools from scratch, but I primarily modified other people’s code for my needs. Since 1990, I’ve programmed in BASIC, C, Visual Basic, PHP, ASP, Perl, Python, Ruby, MUSHcode, and some others. I am not an expert in any of these languages—I learned just enough to get the job done. I have developed my own hobby games over the years using BASIC, Torque Game Engine, and Godot, so I have some idea of what makes a good architecture for a modular program that can be expanded over time.
In December, I used Claude Code to create a multiplayer online clone of Katamari Damacy called “Christmas Roll-Up.”
In December, I used Claude Code to create a multiplayer online clone of Katamari Damacy called “Christmas Roll-Up.” Credit: Benj Edwards
Claude Code, Codex, and Google’s Gemini CLI, can seemingly perform software miracles on a small scale. They can spit out flashy prototypes of simple applications, user interfaces, and even games, but only as long as they borrow patterns from their training data. Much like a 3D printer, doing production-level work takes far more effort. Creating durable production code, managing a complex project, or crafting something truly novel still requires experience, patience, and skill beyond what today’s AI agents can provide on their own.
And yet these tools have opened a world of creative potential in software that was previously closed to me, and they feel personally empowering. Even with that impression, though, I know these are hobby projects, and the limitations of coding agents lead me to believe that veteran software developers probably shouldn’t fear losing their jobs to these tools any time soon. In fact, they may become busier than ever.
So far, I have created over 50 demo projects in the past two months, fueled in part by a bout of COVID that left me bedridden with a laptop and a generous 2x Claude usage cap that Anthropic put in place during the last few weeks of December. As I typed furiously all day, my wife kept asking me, “Who are you talking to?”
You can see a few of the more interesting results listed on my personal website. Here are 10 interesting things I’ve learned from the process.
1. People are still necessary
Even with the best AI coding agents available today, humans remain essential to the software development process. Experienced human software developers bring judgment, creativity, and domain knowledge that AI models lack. They know how to architect systems for long-term maintainability, how to balance technical debt against feature velocity, and when to push back when requirements don’t make sense.
For hobby projects like mine, I can get away with a lot of sloppiness. But for production work, having someone who understands version control, incremental backups, testing one feature at a time, and debugging complex interactions between systems makes all the difference. Knowing something about how good software development works helps a lot when guiding an AI coding agent—the tool amplifies your existing knowledge rather than replacing it.
As independent AI researcher Simon Willison wrote in a post distinguishing serious AI-assisted development from casual “vibe coding,” “AI tools amplify existing expertise. The more skills and experience you have as a software engineer the faster and better the results you can get from working with LLMs and coding agents.”
With AI assistance, you don’t have to remember how to do everything. You just need to know what you want to do.
Card Miner: Heart of the Earth is entirely human-designed, but it was AI-coded using Claude Code. It represents about a month of iterative work.
Card Miner: Heart of the Earth is entirely human-designed, but it was AI-coded using Claude Code. It represents about a month of iterative work. Credit: Benj Edwards
So I like to remind myself that coding agents are software tools best used to enact human ideas, not autonomous coding employees. They are not people (and not people replacements) no matter how the companies behind them might market them.
If you think about it, everything you do on a computer was once a manual process. Programming a computer like the ENIAC involved literally making physical bits (connections) with wire on a plugboard. The history of programming has been one of increasing automation, so even though this AI-assisted leap is somewhat startling, one could think of these tools as an advancement similar to the advent of high-level languages, automated compilers and debugger tools, or GUI-based IDEs. They can automate many tasks, but managing the overarching project scope still falls to the person telling the tool what to do.
And they can have rapidly compounding benefits. I’ve now used AI tools to write better tools—such as changing the source of an emulator so a coding agent can use it directly—and those improved tools are already having ripple effects. But a human must be in the loop for the best execution of my vision. This approach has kept me very busy, and contrary to some prevailing fears about people becoming dumber due to AI, I have learned many new things along the way.
2. AI models are brittle beyond their training data
Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding agents have a significant limitation: They can only reliably apply knowledge gleaned from training data, and they have a limited ability to generalize that knowledge to novel domains not represented in that data.
What is training data? In this case, when building coding-flavored LLMs, AI companies download millions of examples of software code from sources like GitHub and use them to make the AI models. Companies later specialize them for coding through fine-tuning processes.
The ability of AI agents to use trial and error—attempting something and then trying again—helps mitigate the brittleness of LLMs somewhat. But it’s not perfect, and it can be frustrating to see a coding agent spin its wheels trying and failing at a task repeatedly, either because it doesn’t know how to do it or because it previously learned how to solve a problem but then forgot because the context window got compacted (more on that here).
Violent Checkers is a physics-based corruption of the classic board game, coded using Claude Code.
Violent Checkers is a physics-based corruption of the classic board game, coded using Claude Code. Credit: Benj Edwards
To get around this, it helps to have the AI model take copious notes as it goes along about how it solved certain problems so that future instances of the agent can learn from them again. You also want to set ground rules in the claude.md file that the agent reads when it begins its session.
This brittleness means that coding agents are almost frighteningly good at what they’ve been trained and fine-tuned on—modern programming languages, JavaScript, HTML, and similar well-represented technologies—and generally terrible at tasks on which they have not been deeply trained, such as 6502 Assembly or programming an Atari 800 game with authentic-looking character graphics.
It took me five minutes to make a nice HTML5 demo with Claude but a week of torturous trial and error, plus actual systematic design on my part, to make a similar demo of an Atari 800 game. To do so, I had to use Claude Code to invent several tools, like command-line emulators and MCP servers, that allow it to peek into the operation of the Atari 800’s memory and chipset to even begin to make it happen.
3. True novelty can be an uphill battle
Due to what might poetically be called “preconceived notions” baked into a coding model’s neural network (more technically, statistical semantic associations), it can be difficult to get AI agents to create truly novel things, even if you carefully spell out what you want.
For example, I spent four days trying to get Claude Code to create an Atari 800 version of my HTML game Violent Checkers, but it had trouble because in the game’s design, the squares on the checkerboard don’t matter beyond their starting positions. No matter how many times I told the agent (and made notes in my Claude project files), it would come back to trying to center the pieces to the squares, snap them within squares, or use the squares as a logical basis of the game’s calculations when they should really just form a background image.
To get around this in the Atari 800 version, I started over and told Claude that I was creating a game with a UFO (instead of a circular checker piece) flying over a field of adjacent squares—never once mentioning the words “checker,” “checkerboard,” or “checkers.” With that approach, I got the results I wanted.
A screenshot of Benj’s Mac while working on a Violent Checkers port for the Atari 800 home computer, amid other projects.
A screenshot of Benj’s Mac while working on a Violent Checkers port for the Atari 800 home computer, amid other projects. Credit: Benj Edwards
Why does this matter? Because with LLMs, context is everything, and in language, context changes meaning. Take the word “bank” and add the words “river” or “central” in front of it, and see how the meaning changes. In a way, words act as addresses that unlock the semantic relationships encoded in a neural network. So if you put “checkerboard” and “game” in the context, the model’s self-attention process links up a massive web of semantic associations about how checkers games should work, and that semantic baggage throws things off.
A couple of tricks can help AI coders navigate around these limitations. First, avoid contaminating the context with irrelevant information. Second, when the agent gets stuck, try this prompt: “What information do you need that would let you implement this perfectly right now? What tools are available to you that you could use to discover that information systematically without guessing?” This forces the agent to identify (semantically link up) its own knowledge gaps, spelled out in the context window and subject to future action, instead of flailing around blindly.
4. The 90 percent problem
The first 90 percent of an AI coding project comes in fast and amazes you. The last 10 percent involves tediously filling in the details through back-and-forth trial-and-error conversation with the agent. Tasks that require deeper insight or understanding than what the agent can provide still require humans to make the connections and guide it in the right direction. The limitations we discussed above can also cause your project to hit a brick wall.
From what I have observed over the years, larger LLMs can potentially make deeper contextual connections than smaller ones. They have more parameters (encoded data points), and those parameters are linked in more multidimensional ways, so they tend to have a deeper map of semantic relationships. As deep as those go, it seems that human brains still have an even deeper grasp of semantic connections and can make wild semantic jumps that LLMs tend not to.
Creativity, in this sense, may be when you jump from, say, basketball to how bubbles form in soap film and somehow make a useful connection that leads to a breakthrough. Instead, LLMs tend to follow conventional semantic paths that are more conservative and entirely guided by mapped-out relationships from the training data. That limits their creative potential unless the prompter unlocks it by guiding the LLM to make novel semantic connections. That takes skill and creativity on the part of the operator, which once again shows the role of LLMs as tools used by humans rather than independent thinking machines.
5. Feature creep becomes irresistible
While creating software with AI coding tools, the joy of experiencing novelty makes you want to keep adding interesting new features rather than fixing bugs or perfecting existing systems. And Claude (or Codex) is happy to oblige, churning away at new ideas that are easy to sketch out in a quick and pleasing demo (the 90 percent problem again) rather than polishing the code.
Flip-Lash started as a “Tetris but you can flip the board,” but feature creep made me throw in the kitchen sink, losing focus.
Flip-Lash started as a “Tetris but you can flip the board,” but feature creep made me throw in the kitchen sink, losing focus. Credit: Benj Edwards
Fixing bugs can also create bugs elsewhere. This is not new to coding agents—it’s a time-honored problem in software development. But agents supercharge this phenomenon because they can barrel through your code and make sweeping changes in pursuit of narrow-minded goals that affect lots of working systems. We’ve already talked about the importance of having a good architecture guided by the human mind behind the wheel above, and that comes into play here.
6. AGI is not here yet
Given the limitations I’ve described above, it’s very clear that an AI model with general intelligence—what people usually call artificial general intelligence (AGI)—is still not here. AGI would hypothetically be able to navigate around baked-in stereotype associations and not have to rely on explicit training or fine-tuning on many examples to get things right. AI companies will probably need a different architecture in the future.
I’m speculating, but AGI would likely need to learn permanently on the fly—as in modify its own neural network weights—instead of relying on what is called “in-context learning,” which only persists until the context fills up and gets compacted or wiped out.
Grapheeti is a “drawing MMO” where people around the world share a canvas.
Grapheeti is a “drawing MMO” where people around the world share a canvas. Credit: Benj Edwards
In other words, you could teach a true AGI system how to do something by explanation or let it learn by doing, noting successes, and having those lessons permanently stick, no matter what is in the context window. Today’s coding agents can’t do that—they forget lessons from earlier in a long session or between sessions unless you manually document everything for them. My favorite trick is instructing them to write a long, detailed report on what happened when a bug is fixed. That way, you can point to the hard-earned solution the next time the amnestic AI model makes the same mistake.
7. Even fast isn’t fast enough
While using Claude Code for a while, it’s easy to take for granted that you suddenly have the power to create software without knowing certain programming languages. This is amazing at first, but you can quickly become frustrated that what is conventionally a very fast development process isn’t fast enough. Impatience at the coding machine sets in, and you start wanting more.
But even if you do know the programming languages being used, you don’t get a free pass. You still need to make key decisions about how the project will unfold. And when the agent gets stuck or makes a mess of things, your programming knowledge becomes essential for diagnosing what went wrong and steering it back on course.
8. People may become busier than ever
After guiding way too many hobby projects through Claude Code over the past two months, I’m starting to think that most people won’t become unemployed due to AI—they will become busier than ever. Power tools allow more work to be done in less time, and the economy will demand more productivity to match.
It’s almost too easy to make new software, in fact, and that can be exhausting. One project idea would lead to another, and I was soon spending eight hours a day during my winter vacation shepherding about 15 Claude Code projects at once. That’s too much split attention for good results, but the novelty of seeing my ideas come to life was addictive. In addition to the game ideas I’ve mentioned here, I made tools that scrape and search my past articles, a graphical MUD based on ZZT, a new type of MUSH (text game) that uses AI-generated rooms, a new type of Telnet display proxy, and a Claude Code client for the Apple II (more on that soon). I also put two AI-enabled emulators for Apple II and Atari 800 on GitHub. Phew.
Consider the advent of the steam shovel, which allowed humans to dig holes faster than a team using hand shovels. It made existing projects faster and new projects possible. But think about the human operator of the steam shovel. Suddenly, we had a tireless tool that could work 24 hours a day if fueled up and maintained properly, while the human piloting it would need to eat, sleep, and rest.
I used Claude Code to create a windowing GUI simulation of the Mac that works over Telnet.
I used Claude Code to create a windowing GUI simulation of the Mac that works over Telnet. Credit: Benj Edwards
In fact, we may end up needing new protections for human knowledge workers using these tireless information engines to implement their ideas, much as unions rose as a response to industrial production lines over 100 years ago. Humans need rest, even when machines don’t.
Will an AI system ever replace the human role here? Even if AI coding agents could eventually work fully autonomously, I don’t think they’ll replace humans entirely because there will still be people who want to get things done, and new AI power tools will emerge to help them do it.
9. Fast is scary to people
AI coding tools can turn what was once a year-long personal project into a five-minute session. I fed Claude Code a photo of a two-player Tetris game I sketched in a notebook back in 2008, and it produced a working prototype in minutes (prompt: “create a fully-featured web game with sound effects based on this diagram”). That’s wild, and even though the results are imperfect, it’s a bit frightening to comprehend what kind of sea change in software development this might entail.
Since early December, I’ve been posting some of my more amusing experimental AI-coded projects to Bluesky for people to try out, but I discovered I needed to deliberately slow down with updates because they came too fast for people to absorb (and too fast for me to fully test). I’ve also received comments like “I’m worried you’re using AI, you’re making games too fast” and so on.
Benj’s handwritten game design note about a two-player Tetris concept from 2007.
Benj’s handwritten game design note about a two-player Tetris concept from 2007. Credit: Benj Edwards
Regardless of my own habits, the flow of new software will not slow down. There will soon be a seemingly endless supply of AI-augmented media (games, movies, images, books), and that’s a problem we’ll have to figure out how to deal with. These products won’t all be “AI slop,” either; some will be done very well, and the acceleration in production times due to these new power tools will balloon the quantity beyond anything we’ve seen.
Social media tends to prime people to believe that AI is all good or all bad, but that kind of black-and-white thinking may be the easy way out. You’ll have no cognitive dissonance, but you’ll miss a far richer third option: seeing these tools as imperfect and deserving of critique but also as useful and empowering when they bring your ideas to life.
AI agents should be considered tools, not entities or employees, and they should be amplifiers of human ideas. My game-in-progress Card Miner is entirely my own high-level creative design work, but the AI model handled the low-level code. I am still proud of it as an expression of my personal ideas, and it would not exist without AI coding agents.
10. These tools aren’t going away
For now, at least, coding agents remain very much tools in the hands of people who want to build things. The question is whether humans will learn to wield these new tools effectively to empower themselves. Based on two months of intensive experimentation, I’d say the answer is a qualified yes, with plenty of caveats.
We also have social issues to face: Professional developers already use these tools, and with the prevailing stigma against AI tools in some online communities, many software developers and the platforms that host their work will face difficult decisions.
Ultimately, I don’t think AI tools will make human software designers obsolete. Instead, they may well help those designers become more capable. This isn’t new, of course; tools of every kind have been serving this role since long before the dawn of recorded history. The best tools amplify human capability while keeping a person behind the wheel. The 3D printer analogy holds: amazing fast results are possible, but mastery still takes time, skill, and a lot of patience with the machine.
Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a tech historian with almost two decades of experience. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.
“We had really good reseller pricing that we negotiated with Rackspace due to the number of mailboxes we had with them and how long we had been a customer. All of that seemed to vanish when they notified us of their new pricing,” he said.
Ars contacted Rackspace asking about the 706 percent price hike that Laughing Squid says it’s facing, why Rackspace decided to increase its prices now, and why it didn’t give its partners more advanced notice. A company spokesperson responded, saying:
Rackspace Email is a reliable and secure business-class email solution for small businesses. To continue delivering the service levels our customers expect, effective March 2026, Rackspace Technology is increasing the price of Rackspace Email. We have a support team available to help our customers to discuss their options.
The spokesperson added that Rackspace’s “mission is to deliver quality, trusted and reliable hosted email solution for businesses.”
Email hosting is a tough business
Despite Rackspace’s stated commitment to email hosting, the prohibitive pricing seems like a deterrent for a business being viewed as high-effort and low-margin. Email has grown complex over the years, requiring time and expertise for proper management at scale. It’s become simpler, or more lucrative, for some cloud companies to focus on selling their managed services on top of offerings like Microsoft 365—as Rackspace does—or Google Workspace and let the larger companies behind those solutions deal with infrastructure costs and complexities.
Meanwhile, Laughing Squid is increasing prices for Rackspace mailboxes and offering services with a different email provider, PolarisMail, to customers at lower prices. Beale said he has reached out to Rackspace about the new pricing but hasn’t heard back yet.
