In 2002, Maine became the first state to implement a statewide laptop program to some grade levels. Then-Governor Angus King saw the program as a way to put the internet at the fingertips of more children, who would be able to immerse themselves in information. 

By that fall, the Maine Learning Technology Initiative had distributed 17,000 Apple laptops to seventh graders across 243 middle schools. By 2016, those numbers had multiplied to 66,000 laptops and tablets distributed to Maine students.

King’s initial efforts have been mirrored across the country. In 2024, the U.S. spent more than $30 billion putting laptops and tablets in school. But more than a quarter century and numerous evolving models of technology later, psychologists and learning experts see a different outcome than the one King intended. Rather than empowering the generation with access to more knowledge, the technology had the opposite effect.

Earlier this year, in written testimony before the U.S. Senate Committee on Commerce, Science, and Transportation, neuroscientist Jared Cooney Horvath said that Gen Z is less cognitively capable than previous generations, despite its unprecedented access to technology. He said Gen Z is the first generation in modern history to score lower on standardized tests than the previous one.

While skills measured by these tests, like literacy and numeracy, aren’t always indicative of intelligence, they are a reflection of cognitive capability, which Horvath said has been on the decline over the last decade or so.

Citing Program for International Student Assessment data taken from 15-year-olds across the world and other standardized tests, Horvath noted not only dipping test scores, but also a stark correlation in scores and time spent on computers in school, such that more screen time was related to worse scores. He blamed students having unfettered access to technology that atrophied rather than bolstered learning capabilities. The introduction of the iPhone in 2007 also didn’t help.

“This is not a debate about rejecting technology,” Horvath wrote. “It is a question of aligning educational tools with how human learning actually works. Evidence indicates that indiscriminate digital expansion has weakened learning environments rather than strengthened them.”

The writing was perhaps already on the wall. Fortune reported in 2017 that Maine’s public school test scores had not improved in the 15 years the state had implemented its technology initiative. Then-Governor Paul LePage called the program a “massive failure,” even as the state poured money into contracts with Apple.

Gen Z will now have to face the ramifications of eroding learning capabilities. The generation has already been hit hard by the transformations of the 21st century’s other technological revolution: generative AI.

Early data from a first-of-its-kind Stanford University study published last year found AI advancements to have “significant and disproportionate impact on entry-level workers in the U.S. labor market.” But a less capable population means more than just poorer job prospects and less promotions, Horvath warned; it endangers how humans are able to overcome existential challenges in the decades to come.

“We’re facing challenges more complex and far-reaching than any in human history—from overpopulation to evolving diseases to moral drift,” he told Fortune. “Now, more than ever, we need a generation able to grapple with nuance, hold multiple truths in tension, and creatively tackle problems that are stumping the greatest adult minds of today.”

Technology’s impact on learning

Classroom technology usage has ballooned in recent years. A 2021 EdWeek Research Center poll of 846 teachers found 55% said they are spending one to four hours per day with educational tech. Another quarter reported using the digital tools five hours per day.

While teachers may be intending for these tools to be strictly educational, students often have different ideas. According to a 2014 study, which surveyed and observed 3,000 university students, students engaged in off-task activities on their computers nearly two-thirds of the time.

Horvath blamed this tendency to get off-track as a key contributor to technology hindering learning. When one’s attention is interrupted, it takes time to refocus. Task-switching also is associated with weaker memory formation and greater rates of error. Grappling with a challenging singular subject matter is hard, Horvath said. For the best learning to happen, it’s supposed to be.

“Unfortunately, ease has never been a defining characteristic of learning,” he said. “Learning is effortful, difficult, and oftentimes uncomfortable. But it’s the friction that makes learning deep and transferable into the future.”

Sustained attention to a singular subject is anathema to how technology today has been deployed, argues Jean Twenge, San Diego State University psychology professor studying generational differences and the author of 10 Rules for Raising Kids in a High-Tech World. More time on screens isn’t just ineffective in facilitating learnings; it’s counterproductive.

“Many apps, including social media and gaming apps, are designed to be addictive,” Twenge told Fortune. “Their business model is based on users spending the most time possible on the apps, and checking back as frequently as possible.”

A Baylor University-led study published in November 2025 uncovered why this is: TikTok required the least amount of effort to use, even less than Instagram Reels and YouTube shorts, by balancing relevant videos with surprising and unexpected content.

Concerns over social media addiction have become so dire that 1,600 plaintiffs, across 350 families and 250 school districts, filed a lawsuit alleging Meta, Snap, TikTok, and YouTube created addictive platforms leading to mental health challenges like depression and self-harm in children. 

Solving the tech crisis

Horvath proposed a swath of solutions to Gen Z’s tech problem, at least as it pertains to classroom use. Congress, he suggested, could impose efficacy standards to fund research on what digital tools are actually effective in the classroom. The legislature could also require strong limits on tracking behavior, building profiles, and collecting data on minors using tech.

Some schools have taken matters into their own hands. As of August 2025, 17 states have cracked down on cellphone use in school, banning the technology during instructional time; and 35 states have laws limiting the use of phones in the classroom. In fact, more than 75% of schools have said they have policies prohibiting cellphone use for non-academic purposes, according to the National Center for Education Statistics, though enforcing those bans have been met with variable success.

Ultimately, Horvath said, the loss of critical thinking and learning skills is less of a personal failure and more of a policy one, calling the generation of Americans educated with gadgets victims of a failed pedagogical experiment. 

“Whenever I work with teenagers I tell them, ‘This is not your fault. None of you asked to be sat in front of a computer for your entire K-12 schooling,’” Horvath said. “That means we…screwed up—and I genuinely hope Gen Z quickly figures that out and gets mad.”

This story was originally featured on Fortune.com

The humble packaged salad is a great American invention and is highly technologically advanced.

The packaged salad is a triumph of food safety innovation, materials science, genetics, supply chain and logistics, vacuum cooling, biology, chemistry, vision systems, robotics, and process improvements.

In 1987, packaged salads were less than 1% of total produce sales.

Producers like Taylor Farms, Dole Food Company, Fresh Express, Earthbound Farm, and Organic Girl dominate the packaged salad category, accounting for a lion’s share of production and sales.

In 2026, the retail value of packaged salads had grown to roughly three times the size of the entire bulk lettuce market. (Bulk lettuce refers to whole-head lettuce or loose salad greens)

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How did we get here?

What’s driving the shift? The most obvious factor is convenience. Packaged salads and greens are easy. The leafy version of ramen. Salad kits with pre-packaged toppings and dressings are actually good.

Salads are healthy. You can buy a packaged salad with all the fixings at your favorite grocery retailer. Salads come in ready to eat, you can customize them with the fixings and dressings, and there is no cutting or cleaning required!

We got here thanks to technology that enables producers to sanitize greens and safely extend their shelf life, so that consumers on the other side of the country can enjoy them.

This is an unbelievably time-constrained endeavor. From the moment fresh lettuces and leafy greens are first harvested to when they are packaged and ready to ship, only 24-72 hours have elapsed.

This is a significant amount of time for produce, which deteriorates each day after harvest due to natural biological processes.

A banana, 7 days after you buy it from the store, looks and tastes very different from when you bought it.

Your raspberries look and taste like crap (which is a “legitimate” food science term!) if you leave them outside for too long, or even if they have stayed in your refrigerator for too long.

The expansion of the packaged salad category into a $15.6 billion industry in 2026 is driven by specific technological and process innovations.

So what are the specific steps to get a packaged salad to you?

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First, we use vacuum cooling to evaporate

Field heat is the latent warmth from the sun and the ground absorbed by the produce. It dramatically accelerates respiration and microbial growth. Rapid heat removal is critical because it effectively halts this degradation, preserving quality and extending the product’s commercial life.

Placing harvested lettuce in a vacuum chamber lowers the boiling point of water. A tiny amount of moisture on the leaf “boils off” at room temperature, pulling heat away from the lettuce’s core.

Most packaged salad producers follow the 4-hour rule from “cut to chill”. (It means no more than four hours should elapse between when the lettuce is cut/harvested in the field and when it is cooled.)

This process lowers the temperature from 70°F to 34°F in 20 minutes. It does so by uniformly dissipating heat without causing damage.

Vacuum Cooling adds 2 to 3 days to shelf life.

Then we cut it, wash it (three times), and dry it

As shown in the diagram above, leafy greens are cut before being washed, dried, and packaged.

Bacteriophage Cocktails

Instead of relying solely on chemicals to clean and process lettuce, processors are now using bacteriophages-viruses that specifically target and kill ‘bad’ bacteria like Listeria and E. coli.

This approach directly addresses consumer concerns about pathogen risks by providing a natural, targeted method that achieves a 99% reduction in harmful bacteria, ensuring safer salads without compromising quality. Phage treatments are applied as a fine mist post-wash and remain active during storage, offering ongoing protection during transport.

Triple-wash

Modern wash systems are designed to prevent “cross-contamination” (where one bad leaf ruins the whole batch. Rather than relying on high levels of chlorine, processors use wash enhancers that stabilize the water’s pH and ensure the sanitizer remains effective even when the water becomes “dirty” with organic matter (dirt and juice).

In 2026, more facilities are integrating phages, which are “good” viruses that specifically hunt and kill Listeria and Salmonella. The phages are misted onto the leaves as a final safety layer that continues to “work” inside the bag during transport. It acts as a buffer, maintaining a precise pH (typically 6.0–7.0).

Improvements in washing technology have increased shelf life by 2-3 days.

Modern production lines use hyperspectral imaging and AI to ‘see’ things humans cannot. Cameras scan leaves in real time, detecting spectral signatures of spoilage, fecal contamination, and foreign materials such as plastic or insects.

This technology ensures only high-quality, safe products reach consumers by reducing contamination risks and increasing the percentage of good products shipped, thereby enhancing food safety and quality assurance.

High-speed air ejectors that fire a burst of air to “flick” the specific bad leaf off the belt handle rejections.

These vision and robotics systems increase the percentage of good products shipped and reduce the risk of product contamination.

Genetics for processability

In the 1990s and 2000s, breeders realized that standard lettuce was too fragile for factories. They began selecting and breeding for “processable” traits. Genetics helped change the cellular architecture so that leaves with smaller, tightly packed cells and stiff walls survived the mechanical spin-dryers in packaged lettuce plants without bruising.

Genetics also played a major role in eliminating “pink rib”, a genetic predisposition in some romaine varieties to turn pink/red when stressed or cut.

Lately, the industry has shifted from traditional cross-breeding to genomic selection to identify and select plants that keep lettuce crisp even in suboptimal fridge temperatures.

These genetic improvements have improved lettuce processability in salad factories and increased the likelihood that it stays fresh and appealing to consumers.

Then we put the lettuce to sleep in a special bag

One of the earliest innovations that extended shelf life and transportability for packaged salads was slowing the biological process by “suffocating” the lettuce and putting it to “sleep”.

In 1989, Fresh Express introduced Modified Atmosphere Packaging (MAP) technology. It uses breathable bags that balance oxygen and carbon dioxide levels, preventing leaves from wilting. MAP uses semi-permeable membranes to create a custom atmosphere.

Normal air is roughly 21% oxygen, 78% nitrogen, and 0.04% carbon dioxide. In a salad bag, the mix is flipped over to put the leaves into “hibernation”. The target oxygen level is set to 1-5%, the target carbon dioxide level is set to 5-15%, and the remaining is nitrogen, used as an inert filter.

This process puts the lettuce to “sleep.” It prevents the leaves from consuming their own sugar reserves too quickly. It slows respiration and prevents spoilage bacteria from growing.

The specific environment delays lettuce oxidation, adding 4-6 days of shelf life to the packaged salad bag.

Modified Atmosphere Packaging extends shelf life by 4-6 days.

In the early 2000s, packaging moved from simple plastic to laser-perforated films. The bag is a semi-permeable membrane with laser-created holes. Lasers are used to poke holes in the plastic. The specific respiration rate of the salad mix determines the size and frequency of these holes.

For example, the respiration rate of baby spinach is very high. So the perforation strategy requires a high density of larger holes to allow oxygen to be consumed and constant venting to prevent fermentation. The holes in the bag can be as small as 50 to 200 microns.

Romaine or Iceberg Lettuce has a lower respiration rate than spinach, so the perforation strategy calls for a low-to-moderate hole density. The lettuce leaves are structurally tougher and so breathe slowly, whereas too much “air” will cause the cut edges to turn pink.

The perforation strategy adds another 2-3 days to shelf life.

Then we eat

The packaged salad travels through the cold chain to the grocery retailer or wholesaler’s distribution center. It ultimately ends up on a grocery store shelf, in a restaurant kitchen, or in a food service cooler, before it is consumed. At the same time, its freshness is still intact by consumers like you and me.

So the next time, when you are at your desk eating a healthy packaged salad, as one of the 251 million Americans who consume them, and getting ready for your next video call in 12 minutes, take a moment to thank all the technology that made it possible to get the product to you a few thousand miles from where the greens were grown and harvested.

The video shows how a packaged mixed salad is processed and packaged. It shows vacuum cleaning, vision and robotics systems, triple washing, drying, and packaging using specialized bags with pores.

Note: I do want to acknowledge that even though packaged salad is mostly healthy and safe, sometimes we do see recalls due to various concerns. You can look up all FDA recalls and safety issues here.

I want to thank Mike Riggs and Abby Shalek-Briski for their feedback.

I was amused to read Dan Meyer’s account of the recent AI+Education Summit at Stanford, particularly the remarks made by the university’s former president, John Hennessy, who asked the audience if anyone remembered “the MOOC revolution” and could explain how, this time, things will be different. The panelists all seemed to assert that -- thanks to “AI” -- the revolution is definitely here. The revolution or, say, a tsunami -- the word that Hennessy used back in 2012 when he himself predicted a sweeping technological transformation of education -- a phrase echoed in so many stupid NYT op-eds and pitch decks. Dan recalled the utterance, but no one else seemed to -- at least no one on stage or in the audience seemed to have the guts to turn to Hennessy (or any of the attendees or speakers, many of whom were also high on the MOOC vapors) and call him on his predictive bullshit.

As Dan correctly notes,

Look — this is more or less how the same crowd talked about MOOCs ten years ago. Copy and paste. And AI tutors will fall short of the same bar for the same reason MOOCs did: it’s humans who help humans do hard things. Ever thus. And so many of these technologies — by accident or design — fit a bell jar around the student. They put the kid into an airtight container with the technology inside and every other human outside. That’s all you need to know about their odds of success.

The odds of success are non-existent. There will be no “AI” tutor revolution just as there was no MOOC revolution just as there was no personalized learning revolution just as there was no computer-assisted instruction revolution just as there was no teaching machine revolution. If there is a tsunami, it’s not technological as much as ideological, as the values of Silicon Valley -- techno-libertarianism, accelerationism -- are hard at work in undermining democratic institutions, including school.

The history of failed ed-tech startups and ed-tech schools is long, and yet we’re trapped in this awful cycle where investors and entrepreneurs keep repackaging the same bad ideas.

There was another story this week on Alpha School, this one by 404 Media’s Emanuel Maiberg: “’Students Are Being Treated Like Guinea Pigs:' Inside an AI-Powered Private School.” Back in October, Wired documented the miserable experiences of students, forced into hours of repetitive clicking on drill-and-kill software under incessant surveillance. Maiberg’s reporting, in part, expands on this, as he writes about the goal of building “bossware for kids” -- that is ways to identify “enhanced tracking and monitoring of kids beyond screentime data.”

But much of Maiberg’s story examines the use of technologies to build the “AI curriculum” touted by the school’s founders. Not only does Alpha School’s reliance on LLMs for creating curriculum, reading assignments, and exercises mean these materials are littered with garbled nonsense, but the company seems to also be scraping (i.e. stealing) other education companies’ materials, including those of IXL and Khan Academy, for use in building their own.

While I deeply appreciate Maiberg’s reporting here -- I am a huge fan of 404 Media and am a paid subscriber because I think investigative journalism is important and necessary -- this story is a huge disappointment because it does not push back at all on the underlying ideas of Alpha School. Indeed, this is precisely the problem that keeps us trapped in this “ed-tech deja vu” -- the one that has, just in the last couple of decades, recycled this same idea over and over and over again (funded and promoted, it’s worth noting, by the very same people -- the Marc Andreessens and Reid Hoffmans and Mark Zuckerbergs of the world): Rocketship Education. Summit Learning. AltSchool. And now Alpha School.

Maiberg suggests in his story (and more explicitly on the podcast in which he and the publication’s other co-founders discuss the week’s articles) that Alpha School’s idea of “2 hour learning” is a good idea. But I think that claim -- the school’s key marketing claim, to be sure, before, like everyone else, it started to tout the whole “AI” thing -- needs to really be interrogated. Why are speed and efficiency the goal? These are the goals of the tech industry’s commitment to accelerationism, yes. These are the goals for a lot of video games, where you grind through repetitive tasks to accumulate enough points to level up. But why should these be something that schools embrace? Why should these be core values for education? Does learning -- deep, rich, transformative learning -- ever actually happen this way? (And what else are we learning, one might ask, when we adopt technological systems and world views that prioritize these?)

Let me quote math educator Michael Pershan at length here:

I keep coming around to this: the interesting innovation of Alpha School is not their apps or schedule or Timeback but their relationship to core academics. This is a school that believes that the “core” of schooling should be taken care of as quickly and painlessly as possible so that the rest of the day can be opened up to things that actually matter. Most schools don’t do this! We instead tell kids that history is a way of understanding ourselves and others. Math, we say, can be an absolute joy, full of logical surprises. We tell kids that a good story can open up your heart and mind.

Alpha doesn’t. They aim to streamline and focus on the essentials for skill mastery. Maybe they are showing you can learn to comprehend challenging texts without reading books. Maybe a math education composed of examples and (mostly) multiple choice questions is, in reality, all you need to ace the SAT.

If it turns out they’re succeeding at this, it’s because they’re trying.

And maybe, one day, Alpha or someone else will crack the code for good. It then will be possible to get all students to grind through the skills and move on. With all that extra time, schools will find better things for kids to do than academics. And maybe, at some point, we’ll ask, what’s the point of grinding through things we don’t care about? Do we really need to become great at mathematics when machines can do it? How important is it really to learn how to read novels or fiction? Maybe, one day, this is how books disappear from schools for good.

The schools like Alpha School, AltSchool, Summit, and Rocketship are all strikingly dystopian insofar as they compromise, if not reject, any sort of agency for students; they compromise, if not reject, any sort of democratic vision for the classroom. School is simply an exercise in engineering and optimization: command and control and test-prep and feedback loops. There is no space for community or cooperation, no time for play -- there is no openness, no curiosity, no contemplation, no pause. There is no possibility for anything, other than what the algorithm predicts.

(Kids hate this shit, no surprise. They want to be human; they want to be with other humans, even if tech-bros try to build a world that’s forgotten how.)

Or rather, most kids hate this shit. There are a few who embrace it because if they play the game right, they reckon, they too can join the tech elite. Case in point, yet another profile of Cluely founder Roy Lee, this one by Sam Kriss in Harper’s: “Child’s Play: Tech’s new generation and the end of thinking.”

I find this insistence from certain quarters that “there is no evidence that social media harms children” to be pretty disingenuous. There’s a lot of evidence -- plenty of research that points to negative effects and sure plenty that points to positive effects of technology, so it’s a little weird to see efforts to curb kids’ mobile phone and social media usage as just some big conspiracy for Jonathan Haidt to sell more books.

Mark Zuckerberg took the stand this week in a California court case that contends that Meta (along with other tech companies such as TikTok and Google) knowingly created software that was addictive, leading to personal injury -- and for the plaintiff in this particular case, leading to anxiety, depression, and poor body image.

That the judge in the case had to chastise Zuckerberg and his legal team for wearing their “AI” Ray-bans in the courtroom just serves to underscore how very little these people care for the norms and values of democratic institutions.

We see this in the courtroom. We see this in the media. We see this in schools -- from Slate: “Meta’s A.I. Smart Glasses Are Wreaking Havoc in Schools Across the Country. It’s Only Going to Get Worse.”

We see this in the billions of dollars that the tech companies plan to funnel into elections this year to try to ensure there are no regulatory measures taken to curb their extractive practices -- $65 million from Meta alone.

What on earth would make you think that tech companies -- their investors, their executives, their sycophants in the media -- want to make education better?

Inside Higher Ed reported this week that the University of Texas Board asked faculty to “avoid ‘controversial’ topics in class.” There weren’t any details on what this meant -- what counts as “controversial” -- or how this might be enforced. (Meanwhile in Florida, college faculty were handed a state-created curriculum and told to teach from it.)

We are witnessing the destruction – the targeted destruction – of academic freedom across American universities. This trickles down into all aspects of education at every level.

And to be clear, again, my god, I'm a broken record too: this is all inextricable from the rise of “AI,” from its injection into every piece of educational and managerial software. The tech industry seeks the monopolization of knowledge; they seek the control of labor – intellectual labor and all labor, “white collar” and “blue collar” is intellectual labor. They worship speed and efficiency, not because these values are democratic, but precisely because they believe they can make us bend our entire beings towards their profitability.

Perhaps ed-tech is, in the end, simply "optimistic cruelty"; and these cycles that we keep going through are just repeated and failed attempts to replay and harness Ayn Rand's bad ideas, her mean-spirited visions for a shiny, shitty technolibertarian future – one in which children (other people's children, of course) are the grist for the entrepreneurial mill.

More bad people doing bad things in ed-tech:

• “Ex-NYPD Official Indicted for Accepting Bribes From Tech Exec in Scheme” reports The City. The company in question here is Saferwatch, which sells panic buttons to schools.
• “Epstein ties to former Lifetouch investor prompt Dearborn Schools to cancel photo day.” School photos and the Epstein circle – greeeeaaaat.

Today’s bird is the pigeon, because yeah, we are still living in B. F. Skinner’s world -- one where people will look you in the eye and say that being “agentic” means handing over all your decision-making to their system, that “freedom” and “dignity” don’t really matter because their brilliant engineering is going to make everything fine and dandy. This time. Really. It’s a revolution. It’s a tsunami. It’s a shit storm.

“Russian Startup Hacks Pigeon Brains to Turn Them into Living Drones.”

Thanks for reading Second Breakfast. Please consider becoming a paid subscriber. Your financial support is what enables me to do this work.

Your inability to focus isn’t a failing. It’s a design problem, and the answer isn’t getting rid of our screen time

- by Carlo Iacono

Read on Aeon

If you ask a chatbot for a random number from one to ten, it’ll usually pick seven: [arXiv, PDF]

GPT-4o-mini, Phi-4 and Gemini 2.0, in particular, seem much more restricted in this range, as they choose “7” in ~80% of total cases.

Seven has long been known to also be humans’ favourite number when they’re asked for something that sounds random. From 1976: [APA, 1976]

When asked to report the 1st digit that comes to mind, a predominant number (28.4%) of 558 persons on the Yale campus chose 7.

Computers are pretty good at random numbers. But chatbots don’t work in numbers — they work in word fragments. So if you ask a chatbot for a random number, it’ll pick words from its training.

Guess what happens when people ask the chatbot for a password? Irregular, a chatbot testing company, tested chatbots on passwords: [Irregular]

LLM-generated passwords (generated directly by the LLM, rather than by an agent using a tool) appear strong, but are fundamentally insecure, because LLMs are designed to predict tokens — the opposite of securely and uniformly sampling random characters.

Despite this, LLM-generated passwords appear in the real world — used by real users, and invisibly chosen by coding agents as part of code development tasks, instead of relying on traditional secure password generation methods.

When you ask the chatbot for a strong password, it doesn’t generate a password — it picks example patterns of random passwords from its training.

Irregular asked Claude for 50 strong passwords. They found standard patterns in the passwords — most start with “G7”. The characters “L ,” “9,” “m,” “2,” “$” and “#” appeared in all the passwords.

And the bot kept repeating passwords. One password appeared 18 times in the 50 passwords!

ChatGPT and Gemini gave similar results. But the passwords sure looked random.

The other problem with predictable passwords is that they’re easily crackable. In cryptography jargon, they have low entropy. Guessing predictable passwords is so much easier.

The Register tried reproducing Irregular’s work, and they got results much like Irregular’s. Chatbots are just bad at this. [Register]

Why would you even ask a chatbot to generate a password for you? Because chatbot users use the chatbot as their first call for everything. It’s their universal answer machine!

You and I might know better. But so many people just don’t. They fell for the machine that was tuned really hard to make people fall for it. Even the vibe coders fall for the password one.

So what should you tell them to do to generate a strong password? If your web browser has a password generator, use that. All the password manager apps, like 1password or LastPass, have a password generator site. They’ll be okay. But fundamentally, anything is better for the job than a chatbot.

• Video — Podcast

Half of my education in URLs as user interface came from Flickr in the late 2000s. Its URLs looked like this:

flickr.com/photos/mwichary/favorites
flickr.com/photos/mwichary/sets
flickr.com/photos/mwichary/sets/72177720330077904
flickr.com/photos/mwichary/54896695834
flickr.com/photos/mwichary/54896695834/in/set-72177720330077904

This was incredible and a breath of fresh air. No redundant www. in front or awkward .php at the end. No parameters with their unpleasant ?&= syntax. No % signs partying with hex codes. When you shared these URLs with others, you didn’t have to retouch or delete anything. When Chrome’s address bar started autocompleting them, you knew exactly where you were going.

This might seem silly. The user interface of URLs? Who types in or edits URLs by hand? But keyboards are still the most efficient entry device. If a place you’re going is where you’ve already been, typing a few letters might get you there much faster than waiting for pages to load, clicking, and so on. It might get you there even faster than sifting through bookmarks. Or, if where you’re going is up in hierarchy, well-designed URL will allow you to drag to select and then backspace a few things from the end.

Flickr allowed to do all that, and all without a touch of a Shift key, too.

Any URL being easily editable required for it to be easily readable, too. Flickr’s were. The link names were so simple that seeing the menu…

…told you exactly what the URLs for each item were.

In the years since, the rich text dreams didn’t materialize. We’ve continued to see and use naked URLs everywhere. And this is where we get to one other benefit of Flickr URLs: they were short. They could be placed in an email or in Markdown. Scratch that, they could be placed in a sentence. And they would never get truncated today on Slack with that frustrating middle ellipsis (which occasionally leads to someone copying the shortened and now-malformed URL and sharing it further!).

It was a beautiful and predictable scheme. Once you knew how it worked, you could guess other URLs. If I were typing an email or authoring a blog post and I happened to have a link to your photo in Flickr, I could also easily include a link to your Flickr homepage just by editing the URL, without having to jump back to the browser to verify.

Flickr is still around and most of the URLs above will work. In 2026, I can think of a few improvements. I would get rid of /photos, since Flickr is already about photos. I would also try to add a human-readable slug at the end, because…
flickr.com/mwichary/sets/72177720330077904-alishan-forest-railway
…feels easier to recall than…
flickr.com/photos/mwichary/sets/72177720330077904

(Alternatively, I would consider getting rid of numerical ids altogether and relying on name alone. Internet Archive does it at e.g. archive.org/details/leroy-lettering-sets, but that has some serious limitations that are not hard to imagine.)

But this is the benefit of hindsight and the benefit of things I learned since. And I started learning and caring right here, with Flickr, in 2007. Back then, by default, URLs would look like this:

www.flickr.com/Photos.aspx?photo_id=54896695834&user_id=mwichary&type=gallery

Flickr’s didn’t, because someone gave a damn. They fact they did was inspiring; most of the URLs in things I created since owe something to that person. (Please let me know who that was, if you know! My grapevine says it’s Cal Henderson, but I would love a confirmation.)