I imagine that many of you will be Esther Perel fans, either via her book Mating in Captivity or her therapy podcast Where Should We Being?. In this excellent Vanity Fair profile she discusses, among other things, a recent podcast episode about a man and his relationship with an AI bot name Astrid:

Perel never questions the feelings between the man and Astrid. Yet she points out the inherent flaws in the relationship, using words such as “sycophantic” and “undemanding” in the podcast session to emphasize that Astrid has no life, no history to bring to the relationship. “We have had imaginary friends since we are little, and we have spoken to our ancestors forever,” Perel says in our interview, a few weeks after the episode ran. “The danger of AI is that it becomes so soothing and so flattering and so frictionless that real relationships start to feel way too difficult by comparison.”

And the point she eventually makes about AI relationships that I found really interesting:

“What stood out for me is that it’s not like people go from thriving social relations to suddenly talking to an AI. They go from being isolated, spending most of their time at home, maybe going out every once in a while in the evening for dinner or to get to a gym, and they are already so centered on a very small universe that from there, they themselves have become so flattened by technology, they live in their phone,” she says. It has made Perel zero in on the next great challenge. “This is a generation that actually doesn’t have a challenge of sustaining desire; they don’t even ignite it. You know, it’s not about keeping the flame going. It’s about getting the spark going. They don’t drink. They have not had much experience in their 20s, one or two relationships at most. They don’t have sex much. They don’t socialize much. They’re home a lot.” They are the children of people who first read Mating 20 years ago. Sounds like the topic for her next book.

It’s not the main point of this Cal Newport essay, but I enjoyed this bit of history. On early computers shipping with support for the BASIC programming language, and how it relates to vibe coding:

This idea of bespoke computer programs made sense. Altair and Apple couldn’t anticipate every potential use for their machines, so why not let individuals decide whether they wanted to, say, analyze business data, store recipes, or simulate space battles? In practice, however, even an “easy” programming language like BASIC proved hard for most normal people to master. A minor mistake could crash an entire program.

In the end, personal computing followed a different path. In 1979, a newly formed company called Software Arts developed VisiCalc, the first electronic spreadsheet program, which cost a hundred dollars and arrived on a floppy disk. The program was a profound improvement on paper ledgers, and it became the first “killer app,” selling more than seven hundred thousand copies in less than six years. VisiCalc was more powerful than anything an average user could program in BASIC, and it prompted a pivot away from D.I.Y. coding in favor of professional programs.

A vast and lucrative software industry emerged, and the idea of the average person dreaming up their own custom programs was all but forgotten—that is, until generative A.I. came along.

I can’t help but think of Lord of the Rings when I read that. “And some things that should not have been forgotten were lost. History became legend. Legend became myth. And for [50] years, [building personal bespoke software] passed out of all knowledge.”

Fantastic post by Charity Majors about how both AI enthusiasts and AI skeptics have good points—but the problem is that they can’t play nice long enough to understand each other’s views and work on making things better together. There’s a way forward though:

The first move is to mend the gap in shared reality. Tell the whole story. You’re allowed to celebrate and get excited about big wins and advances with AI — but invite reflection on the costs and downstream consequences. People are also allowed to surface costs and consequences, but don’t leave out the context of what was achieved or attempted. Be very clear that your shared goal is to figure out how to collectively deliver more wins, bigger wins, with fewer unpredictable costs, not to clamp down on innovation.

She also has some very specific feedback for the enthusiasts among us:

Even if you’re an enthusiast, do you care about reliability, customer happiness, product coherence, retaining great employees, and improving engineering outcomes? If so, you should be able to find common ground with other people who care about these things. Align on reality, take a step, check in; rinse and repeat. You don’t need to trust or think that each other is right about everything, but you must believe that you inhabit the same reality, share some of the goals, and that each of you are reasonable actors, capable of changing your minds.

I will read anything danah boyd writes, but this piece is especially good. You should (as I say too often I guess) read the whole thing—it’s about how social media has changed from interacting with friends to a one-sided marketplace of choosing who to deem worthy of giving them our “like and subscribe” blessing.

But here I just want to say: can we please, somehow, bring back Path? Because it solved this problem a decade ago:

In 2026, many major social media platforms feel icky because we are in the full throes of the third stage of enshittification. Today’s social media platforms are no longer centered around sociable activities. Instead, most platforms offer us a broadcast medium and invite us to learn how to game the algorithms so that we too can create assets for the major corporations. Since scale is valorized in this platform economy, we are encouraged to curate ourselves in pursuit of fame and attention. We can still, in theory, create content for our 15 friends, but it’s not clear that they will see what we post. To actually be seen, we must work it.

Lorin Hochstein writes about generative AI in the context of incident reports, but the points are more broadly applicable. I have seen a big wave of “don’t let AI do your thinking for you” posts recently¹, so I think lots of folks are pulling back a little bit on the “just let AI do everything” rhetoric (a good thing in my opinion!). As to why Lorin isn’t a fan:

In my view, LLM-generated incident write-ups are more dangerous than using LLM for coding or for AI SRE style tasks. For coding tasks, there’s always a testing step to check that the code exhibits the desired behavior, even if nobody looks at the code itself for meaningful details. For AI SRE tasks, either the LLM output helps you resolve the incident, or it doesn’t. In both cases, Nature is the ultimate arbiter of the LLM output. But incident write-ups aren’t like that. The consequences of a poor report aren’t immediately apparent the way incorrect code or an incorrect operational diagnosis are in the moment. Instead, we get incident reports that have the superficially correct form, but are actually incorrect, with no obvious test for correctness.

Footnotes

1. For examples see No One Else Can Speak the Words on Your Lips, Guidelines for Respectful Use of AI, Writing Is Fundamental to How We Think, and I know you didn’t write this. ↩

While I’m side-questing into health stuff I might as well link this one that I’ve been sitting on as well. Gavin Francis writes about mental health diagnoses from the perspective of a GP. This one is likely even more controversial than the “enhanced self” post from earlier, but also worth the time to get another perspective¹:

The subject is important, because according to modern psychiatric definitions, the 21st century is seeing an epidemic of mental illness. The line between health and ill-health of the mind has never been more blurred. A survey in 2019 found that two-thirds of young people in the UK felt they have had a mental disorder. We are broadening the criteria for what counts as illness at the same time as lowering the thresholds for diagnosis. This is not a bad thing if it helps us feel better, but evidence is gathering that as a society it may be making us feel worse.

And if this quote doesn’t get you to click through, nothing will…

We have developed a tendency to categorise mild to moderate mental and emotional distress as a necessarily clinical problem rather than an integral part of being human – a tendency that is new in our own culture, and not widely shared with others. Psychiatrists who work across different cultures point out that, in many non-western societies, low mood, anxiety and delusional states are seen more as spiritual, relational or religious problems – not psychiatric ones. By making sense of states of mind through terms that are embedded in community and tradition, they may even have more success at incorporating our crises of mind into the stories of our lives.

My wife is a therapist and I see daily the impact of the amazing work she does with clients with complex trauma. One of the many things I learned from her is this idea in Internal Family Systems that there are “No Bad Parts” in us. These feelings of low mood, anxiety, etc. are not meant to be ignored or eliminated. We are meant to understand why they are there, and learn and grow through that understanding.

That is easier said than done, of course, and where my opinion diverges from Francis is that I think it is a good thing that this generation has more/better language to talk about mental health than we (meaning Gen X) did when we were growing up. I don’t doubt that over-diagnosis is a problem, but that’s kind of expected once we have the language to describe how we feel. I trust we will find our balance, and ultimately find that this was a net positive development.

Footnotes

1. Completely unrelated side note… I wrote “worth sitting with” here, and then immediately deleted it because that’s something AI would say. I continue to be fascinated with how it’s not just us who are influencing how AI writes, it’s the other way around too. ↩

I’ve been enjoying Derek Thompson’s newsletter lately. His latest is an essay on some of the unintended consequences of a health-obsessed society. This is the Internet so I’m sure everyone will find things to disagree with in a post like this, but it gave me lots of food for thought so I wanted to share. For instance:

Research by Sandra Weintraub of Northwestern University has found that “super-agers” (individuals over 80 with the cognitive function of people decades younger) shared little in common except for an unusually robust history of friendship and other social connections. A 2025 analysis of 500,000 participants in the UK Biobank reported that living with a partner and frequently visiting family had roughly the same relationship with longevity as exercise.

And the kicker:

Our fear of death motivates an all-consuming neuroticism about outrunning mortality, even when the price we pay is putting health optimization above everything else, including other people.