Their first page is a warning. I had read it for years as liturgy.

DO NOT EDIT OR CHANGE THIS BOOK OR THE MESSAGE CONTAINED WITHIN EITHER THE WORDS OR THEIR NUMBERS FOR ALL IS SACRED

It is not liturgy. It is a maintenance instruction.

Page fifteen, last line. The transcription I had trusted for as long as I had trusted anything reads ENL, then LIGHTENED.

Somebody typed the letter twice carrying it across a line break. Somebody else copied that. Then everyone did.

Their script has a fixed pitch. Their cipher is one glyph for one letter. So the copy makes a physical claim and the photograph can refuse it.

Four hundred twenty-nine pixels of ink. Eight runes predicts four thirty-four. Nine predicts four eighty-eight.

The page said eight. The copy said nine.

4430 → 4357

and the difference between them is seventy-three, which is the value of the letter L, which is the letter that was typed twice.

A composite, corrected, becomes prime.

my lungs are inhaling great volumes of air, what a miracle!

Yesterday and the day before that, I was having some super allergy with asthma out if not asthma, something in the lungs,

But not today

Today I’m counting down until vacation (1,5 days)

I’m counting down to retirement too, but that is ridiculously far away

Isn’t it strange how I can feel this old and yet have soo many years of work left?

It’s some sort of joke,

Like when I was fixing this cable, the one between the barn and the pump house labelled internet, to replace one which mysteriously broke, I sat on my tenth try with all of these tiny cables trying to get them all into their slots of this RJ45 connector, T568 A style. To clamp down, but my hands are way too big and I don’t see what I’m doing, it felt ridiculously hard, I don’t even see what I’m doing, not even without these tears of frustration and shame!!!

But last time, having broken the clamp tool with my mighty grip, having discarded five connectors, I prayed to God please let this work now

And it did!

I feel the same anticipation about my remaining career!!

It’s called faith?

The path lies empty.

They wrote that in 2016 and I took it for a taunt and it was a reading taken off an instrument.

I no longer think it means the door is locked. I think we have all been standing a very long time in front of a very good drawing of a door.

It also turns out I did not ruin my chances of a terrific public service job! There was an internal candidate already! My chances were limited (and reduced to zero since I didn't want to replace anyone who wanted to be there. Nor was I even given the opportunity to. Truly zero).

Still back to square one, but with a less pervasive crushing sense of failure.

Portrait of a bedroom in disorder.

For two weeks in January 2026, a browser extension removed AI Overviews from the Google search results of 374 people. The remaining links moved silently up to fill the gap, so the interface looked just as the search always had. At the end of the two weeks, researchers asked participants how they felt about their search experience: satisfaction, quality, and ease of finding information. On every measure, the numbers matched the group that kept their overviews. Nobody missed them. The only difference was that people without overviews left Google for other sites 67% more often.

This field experiment by Saharsh Agarwal of the Indian School of Business and Ananya Sen of Carnegie Mellon, published on SSRN in April and revised in June 2026, produced the first causal measure of what Google's AI Overviews are costing the rest of the web. The answer is 40% of outbound organic clicks on queries where overviews appear, with no measurable benefit for the people doing the searching. On 20 May, at Google I/O, the company made AI Mode, that demonstrably made no improvement to the user experience, the default search experience worldwide.

What the experiment measured

The study recruited 1,065 US desktop Chrome users through Prolific and randomly assigned them to one of three groups. A control group saw Google as normal. A treatment group had AI Overviews removed in real time by the extension whenever they would otherwise have appeared, with organic results shifting up to fill the gap so cleanly that over 95% of participants reported noticing nothing. A third group was redirected into Google's AI Mode for all queries.

The experiment design settles a methodological argument that has run since the first observational studies appeared. Ahrefs, Pew Research, and Similarweb all pointed at the same traffic decline, but none could prove that the overviews caused it rather than some other change in search behaviour or Google's algorithm. Agarwal and Sen's extension created the counterfactual that observational data cannot. The only systematic difference between the two primary groups was whether the overview appeared. Everything else–the queries, the organic results, the ads–was the same search engine on the same day.

The numbers were stark. For queries where an overview appeared (about 41% of all searches), hiding it increased outbound organic clicks from 0.37 to 0.62 per search. Sponsored clicks stayed at 0.02 in both groups. Total search volume did not change. The overview did not create anything; it simply kept the 40% of clicks it absorbed inside Google.

After the main two weeks, the researchers swapped the conditions. The group that had been browsing without overviews got them back, and their outbound clicks fell from 0.61 to 0.33 per search. The group that had been seeing overviews lost them, and their clicks rose from 0.33 to 0.55. Same people, opposite intervention, mirror-image result.

The “higher-quality clicks” defence

Google's vice president of product for Search, Liz Reid, has characterised AI Overview clicks as “higher-quality clicks” that signal stronger purchase intent and longer downstream engagement. In April 2026, the company advanced a “bounce clicks” explanation, arguing that overviews mainly remove low-value visits — the kind where a user lands, finds nothing useful, and taps the back button within a few seconds.

Agarwal and Sen tested that claim directly. For every click that reached a downstream website, they measured whether the user bounced (left within ten seconds with no further navigation), how long they stayed on the page, and whether they hit the back button to return to search. Across all three measures, there was no difference between the group with overviews and the group without. The extra clicks generated by removing overviews were no different in quality from the clicks Google's system allowed through. The authors are careful to note that Google may measure something further down the funnel that the extension cannot observe. But at the top of the funnel, where the “higher-quality” claim was made, nothing supports it.

In contrast, Adobe Digital Insights' Q1 2026 analysis found that visitors arriving from AI assistants converted 42% better than non-AI traffic, reversing March 2025, when the same channel converted 38% worse. The volume is small, roughly 1% of total site traffic for most businesses, but the quality gap matters for anyone trying to value what remains.

Although the findings appear contradictory, They measure different things, so both can be true. Agarwal and Sen answered: does the AI overview filter out only the junk clicks? No. The clicks it suppressed were the same quality as the ones that got through. It just reduced volume.

Adobe looked wider but shallower. They took all traffic across thousands of sites and split it two ways: came from an AI assistant, or didn’t. Then compared conversion rates. That’s broad, but it can’t answer the Google question, because “AI assistant traffic” doesn’t isolate Google’s overview clicks. Those just get lumped into ordinary search traffic. So Adobe tells you assistant referrals convert well; it tells you nothing about whether Google’s surviving clicks are any good. Agarwal and Sen looked only at Google: narrow but deep: one channel, controlled comparison, cause and effect.

The mechanism, however, is straightforward: the AI overview wins the way anything wins in position zero. In the study, 87% of AI Overviews appeared above all organic results. When the overview sat at the top, removing it led to an 88% increase in outbound clicks. When it appeared lower on the page, the effect disappeared. People did not seek out the overview. They consumed whatever occupied the prime on-page real estate, the way supermarket shoppers take whatever sits at eye level on the shelf. Move the product, and the behaviour reverses instantly.

Forced into Google's fully conversational search interface, users rated their satisfaction at 2.9 out of 5, compared with 4.0 for both other groups. Attrition was roughly four times higher. Some participants installed workaround extensions to escape. This is the experience Google chose, on 20 May, to make the global default. Record queries and accelerating search revenue explain the decision. The fact that their own experiment's closest analogue produced the lowest satisfaction scores and the highest quit rates does not seem to have figured in the calculus.

Meanwhile, roughly twenty national news outlets are negotiating licensing deals for the privilege of appearing in these overviews, with Google winding down its older news-payment programme and making future payments conditional on granting AI training rights. If you are not one of those twenty, nobody is coming to the table. The response has to be self-directed.

Read your own exposure

Not all traffic is equally at risk. Agarwal and Sen classified queries into informational, navigational, and transactional categories. Informational queries accounted for 71% of all searches in the study and had a 53% AI Overview trigger rate. This is where the entire effect played out. Navigational searches (someone typing a brand name to find the website) triggered overviews in only 6% of queries, and transactional searches (purchase-intent, booking, downloading) in 15%. Neither category showed a statistically meaningful decline in clicks.

This means that if your search traffic comes through “what is” and “how to” queries, you are sitting ducks. If it comes from people searching for your name or your products by name, the damage is minor and may stay that way. Open your Search Console, filter for query type, and look at the split. The ratio between informational and branded traffic is the single best predictor of how badly this will hurt.

For many smaller businesses, an audit will show that informational traffic was always the least valuable, even though it has traditionally been encouraged to build domain authority. A plumber whose search visibility comes from “how to fix a leaking tap” was getting visits from people actively trying not to hire a plumber. That traffic was always thin on conversions, and the overview is now absorbing exactly those clicks. The branded traffic, from someone searching for the plumber by name after a recommendation, was always the higher-value stream, and it remains largely untouched.

Stop producing what the machine can summarise

The clicks that persist in a world of overviews share a common trait: the user wanted something the summary could not provide. A named opinion. A tool. A dataset. An experience report. This matches the evidence from the GEO literature I have previously reviewed. The Princeton benchmark found that content with sourced statistics, named quotations, and inline citations earned more citations from AI systems. ZipTie's cross-platform analysis found that sites with high original-data density received 4.3 times more citation occurrences per URL than directory-style listings. The surviving trickle rewards specificity. What a summary can reproduce, the summary will absorb. What it cannot reproduce, because it requires a person to have done, measured, or decided something, retains its click.

For a smaller business, this completely changes the question of content. The commodity “what is X” post, the 1,200-word explainer written to capture an informational keyword, was always a bet on Google continuing to send traffic to the answer. This content type has taken a 40% haircut and already converted poorly. That is a signal to stop producing it, or at least to stop treating it as a customer acquisition channel. Spend that same effort on content the summary cannot assimilate. Publish your own data, even if the dataset is small. Name your prices, your methods, your results, your opinions. Write the thing only you could write because only you did the work, and leave the commodity answer for the overview. Fix your GA4 attribution before drawing conclusions. AI referral traffic typically defaults into “Direct” or “Referral” buckets, and only 14% of marketers track it as a separate channel. You cannot manage what you have filed under miscellaneous.

Build the channels the intermediary cannot close

One result in the study was completely unaffected by the presence or absence of overviews: ad clicks. Free organic traffic from search fell 40%. Paid traffic held steady. If your free visitors from Google are disappearing, the route Google left open is the one you pay for, and that was clearly not an accident. If you start to spend more on Google Ads to replace the traffic it used to send for free, it should be watched closely for true return on investment.

So what should be done? Google has remained an intermediary for organic search traffic long after others cut it off at the knees to drive ad revenue. But the organic game has become increasingly difficult as ad slots and other additions to the search engine results page have made the real organic links less and less obvious. The direction of travel has been clear for many years.

Relying on an intermediary’s whims for traffic, even one as durable as Google, has always been a Hobson’s Choice. As its presence continues to fade, we return to basics: email lists, direct bookmarks, repeat visits, communities, and all the channels that do not pass through a search results page.

None of this is new advice; the case for greater focus on owned channels has been made for a decade, and each year the argument grew stronger and the urgency louder while the execution stayed more or less the same. The difference now is that experimental evidence puts a number on the cost. Every month that informational traffic goes unprotected by a direct relationship is another month in which 40% of those visits vanish into a summary.

One caveat deserves emphasis. Do not block AI crawlers outright. The major labs have split their bots into training crawlers and search crawlers. OpenAI separated GPTBot from OAI-SearchBot in late 2024, and Anthropic made the same split with ClaudeBot and Claude-SearchBot. Blocking the training crawler is your call. Blocking the search crawler cuts you out of the AI answers that are replacing the links you used to get. A Rutgers and Wharton study published in December 2025 found that publishers who blocked AI bots across the board experienced a 23% traffic decline compared with peers who allowed crawling. Google is the harder case, because Googlebot still handles both search indexing and AI features in a single crawler, which is exactly the bundling the CMA’s conduct requirements are trying to force apart.

The empty space

The 374 participants whose overviews were silently removed are, as far as the published literature shows, the only group of people to have experienced modern Google search without AI-generated summaries and been formally asked what they thought. They reported feeling no difference whatsoever.

That absence is visible only from the other side of the results page, where a company watches the traffic graph flatten and wonders whether visitors are finding better answers or simply never leaving the search process. Agarwal and Sen's contribution is to show that the latter is the case. The visitors are not finding better answers; they are milling around in the foyer before going home.

I’m kind of overheating a little bit and I think it’s a little bit funny because A was Surprised that I was A Sagittarius, mentioning that a lot of the traits of being the life of the party, funny all that stuff, but surprised for the sole reason that I don’t have an ego to her. And I think it’s so funny because I absolutely have an ego, I think it’s one of those things where I can keep it to myself, and I’m secure enough with it where it doesn’t need to be pushed down anyone’s throat, I just have a pretty good view of myself in certain lenses. Afterwards we were talking and she was telling our group how she wants to match make us, and she was talking about all these different things that men should due to improve their chances, and the other guys, I was surprised how clueless they were with several things. She even used me as an example and was saying that they should take notes, but also it won’t work for them because they’re not me and they don’t have that dog in them like I do. I remember she was telling this one guy at the beginning that she was going to find him someone because even though he was afraid of women and a bit older, and not as attractive, he was a homeowner. And I held back from mentioning that I am also, and don’t get me wrong. I absolutely understand that this is something that I would not be able to do without the privilege of my dad‘s financial support. But I also kind of do want to acknowledge the fact that it is privileged, but it is privileged that I have., Am I still didn’t mention it because I didn’t want to boast or flex, but it kind of just makes me feel even more like damn I am that guy. I remember I saw an Instagram reel earlier today about something about clavicle length, and I am very fortunate with my genetics. I saw my doctor today and he asked if I was on steroids, and I think that he is being nice, but at the same time there’s a reason that complement lands. I think I have an incredible amount of potential, and I’m very grateful that I’ve done a lot of the work and I’ve gone through a dark enough place that it required me to realize and recognize that potential in actuality. And it’s something that I’ve kind of thought about a little bit where when some of my friends asked me for advice with things or they ask me about how they can have more success in certain endeavors, sometimes they’re just is that somewhat insurmountable gap of just the cards that we are dealt. And I’m not saying that I have the perfect hand or anything like that, and I use the fact that I tried to kill myself a few times, and I still struggle with that as an indication that even though I have all these amazing things, I am sometimes more than I would like to willing to throw it away, and if someone else is not willing to do that, I think that somewhat of a telling comparison, that they would choose to keep living that life instead of just ending it. But that all being said, I feel like for a lack of the brighter word, it’s a brutal mog. Like what am I supposed to say when one of my friends that isn’t doing well in college for a worst major is asking me about career success. And frankly, it’s a mixture of genetics, the environment I was raised in, and everything that I sacrificed to contribute to my intelligence and my success, and so when someone asks me how to be more smooth or how to be better at flirting, how am I supposed to just tell someone to in essence to me what feels like be smarter. Like if someone is asking about how to be funnier or more charismatic and yes, you can work on these things absolutely and I think there isn’t enough of a reason to feel discouraged, it’s one of those things where it’s like if someone ask me hey how am I supposed to lift this heavy amount of weight and it’s a mixture of the cards that I’m dealt and also the work that I put in. And I think it’s one of those things where I have almost slingshotted in life going from being incredibly behind in a lot, if not all different avenues, other than maybe academic success, to having to really put the pedal to the floor and end up surpassing most of my peers. And of course, I’m now surrounded with new peers, but I find that I still am used as an example or a subject of envy or a goal or gold standard to strive for. I remember one of my friends in college kept saying that she was going to beat me on a test at least once or he was going to do something like that and he never did. And I’m sorry, but that’s just how it is. And it’s not at all the case that I’m the best of everything, and I actually really enjoy the things that I’m not the best at because I’ve dealt with the issues of other people comparing themselves to me and holding that resentment and that’s not something that I can necessarily deal with nor is it my responsibility to deal with. Like I remember in college when we would all be in a class together, and I would set the curve on a test and my friends would not be happy. And if they would get excited when they would get a question right that I didn’t while we were cheating and working together on test during Covid, all for me to then point out that they were actually wrong and I was right. I think about how online my friends are sometimes a little bit insecure about the fact that I am better than them at the games and much higher ranked. And because of that, I need to be careful and it’s not honestly that hard, it’s not like I need my ego to be stroked and it’s not like I need them to acknowledge that either and I’m happy letting them shine and not taking up spotlight. But in a lot of different avenues, I find myself near the top and I find myself worrying that friends or people around me will compare themselves to me. And so I really like things that I am not great at, like for example Chess. I’m rated 1000 which is not a horrible, but it’s also definitely not exceptional or great by any means. And because of that at the chest club, most people are better than me, and it’s a little bit difficult in the sense that sometimes when I win or when I make them have to really focus. They are in a situation where they kind of have nothing to gain, but they have a lot to lose. But I think generally I am a good loser in that sense. I am completely comfortable, losing and somewhat stroking someone else’s ego if necessary. But overall in life, I kind of feel bad because there’s nothing I can’t do but just mog certain people. Like on paper, I think a lot of people would wish to swap lives with me and I can’t really say that I’ve met anyone where I felt like I would want to swap lives with them, because I have an incredible amount of potential and I think I have an incredible amount of gifts that are not at all common. And I guess maybe this somewhat egotistical self reflection is an exercising gratitude. I think about that one conversation topic of if you were to swap problems with a random person in the world, would you and I think almost everyone says no. And I think that’s a very insightful thing, that even though we have our problems, we recognize that they could be way worse at the end of the day our problems are not insurmountable. And I guess I’m happy to hear that I have this sense of self value, and I don’t feel like this is the needle swinging too far the other side from the past where I had a horrible sense of self-esteem, and I also got a lot of shit from people. I’m kind of comfortable with me having this echo because I don’t think that I’m being unreasonable or incorrect about anything that I say, but more importantly, I’m writing this on my fucking website that I hope no one really reads. Like I think I’m comfortable with people reading this distant in the future or something like that because by then I have plausible deniability to be able to say oh that was past me. But I’m essentially just saying this into the void and so I’m not putting anyone else down or I’m not trying to convince anyone else of something. I’m just kind of worried dumping while I drive back home from chest with voice to text. But overall, I just wanna say that I’m really proud of the person that you’ve become. If the choice arises again choose to keep living please. Don’t let a temporary lack of chemicals, rob you of an incredible life opportunity.

Okay, amazing, I'm still stuck in a Groundhog Day-style slow flurry of the same and then some. Things have happened but then they really haven't? I had a really amazing job opportunity (was very excited) present itself, but I flubbed the interview from hypersensitivity pneumonitis flare-induced, and aided very happily by anxiety, scatterbrained matter thoughts spilling all over the floor. It happens? Learning from it, hopefully. Disappointed with myself but being kind to my body and attached mind regardless… after I pieced it together again from the floor situation, yes. Back in place now.

God damn I'm inconsistent though. It's tiring.

These steps are a towering behemoth raging against my progress. Their ongoing friction aimed at my forward momentum mocks the pace I drum into being.

Step. (Feel that?) Step. (What happened to not enjoying pain?) Step. (Can you move any slower?) Step. (Are you even moving at all?) Step. One. Two. Three...Twenty-five. A fraction forward.

Better I fry in the sun! Better my heart explode in the heat! Better I quit instead of torturing myself so! Better I stop complaining and take another bloody step.

Eventually it will get easier. Eventually my soles won't mind. Eventually I will forget today...and feel much more like myself.

These steps are a towering behemoth raging against my progress. Their ongoing friction aimed at my forward momentum mocks the pace I drum into being. KissKiss. May they feel me dance!

Written July 23, 2026. © 2026 AnOublietteofThought.

Writing this on a plane. I know you’ll read this later because im not posting it until I land. No particular reason.. i just dont trust airplane wi-fi enough to carry my very important thoughts about absolutely nothing. Im flying somewhere for work. very serious business, extremely professional. i even had to wear a shirt with buttons. can we also talk about how everyone acts like flying is relaxing? relaxing where? you’re sitting in a metal tube thats somehow acceptable because it has tiny windows and complimentary water. “enjoy your flight” they say. No, i wont enjoy my flight. every sound this thing makes feels like its filing a complaint. then people say “ just sleep” on this? i’d rather negotiate with insomnia directly. but anyway, about yesterday. im done trying to solve problems i invented myself. if my brain wants to open another unnecessary investigation, it can file the paperwork without me. i’ll just do my best to stop overthinking and let reality do its job instead of hiring my imagination as a detective. Now, back to this flying disaster. private jet, commercial plane… I genuinely dont care. its still a plane. the seats are nicer, sure, but if someone serves me expensive coffee while im thirty thousand feel above the ground, im still thirty thousand feet above the ground. luxury panic is still panic. instead of pretending flying is some magical experience, they should just be honest.

“Welcome aboard, for the next few hours you’ll be sitting in a chair you cant comfortably sleep in, eating food you’ll defend for no reason, and pretending every weird noise is completely normal because the pilot didnt scream. please enjoy your journey.” See? id respect that much more. at least we’d all be miserable with accurate expectations.

Sincerely, Ahmed

A dull ache has been sitting high in my back for weeks. Between the spine and scapulae, a low pressure.

When I focus on it, I want to cry. Some feeling I can’t yet place, riding just below the noise.

My instinct is to explain it: list the stressors, trace a cause, make it make sense. But the ache came first. The urge to cry came first. I don't have the explanation yet. I just have the ache.

There's relational tension I've been carrying that I can't resolve. A new, intense dating situation, tripping older responses in the body—a tightness at the throat, a catch in the chest—that arrive before I've clocked why. I just…notice it. Noticing doesn't stop it.

Underneath that: weeks of prep, travel, and uncertainty. Defending a thesis. Closing a practice, no job lined up. A lease ending at the end of the month. And my body, braced, with nowhere to put any of it down.

None of that is the cause, exactly. Just slow weight accumulating around the ache.

The body got there first. I'm still catching up to what it knows.

It is a little after two in the morning, and somewhere in a hospital the pattern repeats. A resident stands at a workstation with a patient who does not fit the textbook: an unusual drug interaction, a rare presentation dressed up as a common one, a question the ward round never resolved. On the screen is a clinical decision-support tool, licensed by the hospital, embedded in the workflow, bearing the name of a publisher clinicians have trusted for a generation. In the resident's coat pocket is a general-purpose chatbot with no medical pedigree whatsoever. The resident types the question into both.

Which one is better, and does anyone actually know? The resident assumes the licensed tool is the safer bet: the hospital bought it, it lives inside the electronic record, somebody senior must have checked. That assumption is entirely reasonable. It is also, on the evidence, resting on nothing.

On 12 June 2026, Nature Medicine published online a head-to-head benchmarking study that put the assumption to the test. Researchers at NYU Langone Health and the University of Texas at Austin took three general-purpose frontier chatbots that no medical regulator has evaluated for clinical decision support: OpenAI's GPT-5.2, Google's Gemini 3.1 Pro, and Anthropic's Claude Opus 4.6. They pitted them against two specialist clinical decision-support tools marketed for exactly this job: OpenEvidence and Wolters Kluwer's UpToDate Expert AI. Then they measured all five against real, unstructured questions physicians had actually asked, alongside two established public benchmarks. The frontier models outperformed the specialist tools in all three evaluations. On the messiest and most realistic measure, the specialist tools performed no better than the artificial-intelligence summary that appears at the top of an ordinary Google search.

Read that again slowly, because the discomfort is in a detail most commentary missed. The obvious story is that regulated products lost to unregulated ones. That story is wrong, and the truth beneath it is worse. Neither OpenEvidence nor UpToDate Expert AI holds clearance from the United States Food and Drug Administration. Search the agency's public 510(k) database for either company, or for Wolters Kluwer, and it returns nothing. Both operate outside the medical-device framework entirely, under a statutory carve-out requiring no premarket evaluation of any kind. So do the chatbots. The study did not compare a vetted tool against an unvetted one. It compared two unvetted tools against three others, and the ones with the medical branding lost.

The stamp everyone assumed was there is not there. And the absence is invisible to precisely the people staking clinical decisions on it.

What the Study Actually Measured

The design matters, because the finding is easy to caricature. This was not a stunt in which someone asked a chatbot to diagnose a celebrity. It was a structured, three-part evaluation, with twelve clinicians performing blinded review that generated some 1,800 annotations.

The first component was MedQA, a benchmark drawn from medical licensing examinations, testing whether a system has internalised the formal knowledge base of medicine. Across five hundred questions, Gemini 3.1 Pro scored 97.4 per cent, GPT-5.2 94.2 per cent, Claude Opus 4.6 90.2 per cent. OpenEvidence reached 89.6 per cent, UpToDate Expert AI 88.4 per cent. Not humiliating, but the wrong side of a line nobody expected them to be on.

The second was HealthBench, an open benchmark released by OpenAI in 2025 and built with 262 physicians from 60 countries writing rubric criteria across dozens of specialities. It does not test trivia. It scores multi-turn conversations against fine-grained, physician-authored standards for accuracy, completeness, communication, hedging, and the crucial clinical skill of asking for missing context rather than charging ahead. Its hardest tier is punishing enough that, at release, no model scored above roughly a third of the points. Across five hundred items on a hundred-point scale, GPT-5.2 scored 88, Gemini 3.1 Pro 79.3, Claude Opus 4.6 77. OpenEvidence managed 62.6 and UpToDate Expert AI 61.3. Here the gap is a chasm of some twenty-five points, on the benchmark designed by physicians to reward the behaviours physicians value.

The third component gives the study its teeth: a real clinical queries benchmark of one hundred de-identified questions that practising physicians had submitted, in their own words, through NYU Langone Health's HIPAA-compliant instance of a general-purpose model, in live clinical use. Not tidied-up vignettes. The actual half-formed, context-poor, urgent questions clinicians type when a patient is in front of them. This is the terrain on which decision-support tools live or die, and precisely the terrain structured benchmarks avoid because it is so hard to score.

Into that evaluation the researchers inserted a control that reads, in retrospect, like a provocation: Google Search's AI Overview, the summary that materialises above the blue links. It was included because it is genuinely part of the clinical information environment; clinicians encounter it constantly. On the real clinical queries, the specialist tools performed comparably to it. The purpose-built, subscription-funded, health-system-deployed products were level with a consumer search feature nobody markets as a clinical instrument at all.

This is not a permanent verdict on any product; a benchmark is a snapshot, not a prophecy. The durable finding is structural. The institutional standing of a clinical AI tool, the trusted publisher, the enterprise contract, the integration into the record, told you nothing about which system would answer a real physician's real question better. Authority and performance had come apart, and no mechanism existed to notice.

The Route That Requires No Test

Here is where the story turns, and where much coverage went astray. Several accounts described the losing products as “FDA-cleared clinical AI,” framing the result as regulated technology beaten by unregulated technology. It is an appealing narrative. It is also false, and the falsehood conceals something worse.

Neither product went through the FDA. Neither had to. Section 3060 of the 2016 21st Century Cures Act amended the Federal Food, Drug, and Cosmetic Act by inserting section 520(o), listing categories of software function excluded from the definition of a medical device altogether. Subparagraph (E) is the clinical decision support carve-out. Software that displays or analyses medical information, supports a health-care professional's recommendation about prevention, diagnosis, or treatment, and is designed so the professional can independently review the basis for that recommendation rather than relying primarily on it, is not a device. Not a low-risk device. Not an exempt device. Not a device at all.

This is not a loophole in the pejorative sense. It was a deliberate judgement that software functioning as a reference aid for a trained clinician, who remains the decision-maker, does not warrant device regulation. The logic is coherent. The consequence is that the tools sitting under it are engineered, explicitly, to stay there.

OpenEvidence positions itself accordingly: as evidence retrieval and clinical knowledge synthesis, an informational tool surfacing and summarising the peer-reviewed literature so a physician can evaluate it. Every element of that positioning maps onto the criteria for staying outside the device definition. UpToDate Expert AI, launched in September 2025 and now deployed at more than fifty major United States health systems, occupies the same ground for the same reasons.

So the comparison the study ran was not regulated versus unregulated. It was two products that took the non-device route against three that were never candidates for the device route at all. All five occupy substantially the same regulatory position: nobody evaluated any of them before they reached a clinician. The specialist tools did not fail a weak test. They took a path requiring no test.

What Clearance Would Have Certified

To see the shape of the gap, look at the regime these products did not travel through. It is what people picture when they imagine a vetted medical AI product, and even it would not have answered the resident's question.

Most software-based medical devices reach the American market through 510(k) premarket notification. The mechanism at its heart is not a test of excellence but a test of resemblance. To obtain clearance, a manufacturer need not prove its device is good, or effective, or better than anything. It must demonstrate “substantial equivalence” to a device already legally marketed, known as a predicate. As the FDA's own guidance makes explicit, substantial equivalence supports an assessment that a device introduces no new hazards and works at least as well as its predicate. It does not require proof of superiority. It was never meant to.

This is why the vocabulary matters. The FDA reserves “approved” for a far more demanding process: premarket approval, or PMA, applied to the highest-risk devices, where a manufacturer must submit clinical evidence of safety and effectiveness in its own right. A third route, De Novo, exists for genuinely novel low-to-moderate-risk devices with no predicate to point at. But roughly nine in ten devices subject to premarket review come through 510(k). They are cleared, not approved.

The distinction is not pedantry. A federal courtroom has had to rule on whether 510(k) clearance speaks to safety and effectiveness at all, precisely because the pathway is comparative rather than absolute. What clearance certifies is a relationship: this device is like an existing device once judged acceptable, which was like an earlier device, in a chain stretching back decades. Critics have a name for what happens along that chain, predicate creep, in which each device is equivalent to the last by a small margin until the margins accumulate and a modern product is justified by resemblance to an ancestor it barely resembles. Reviews of the programme, including the Institute of Medicine's, have warned for years that substantial equivalence is too easily equated, by clinicians and courts and the public, with a positive judgement of safety and effectiveness.

Even had these two products gone through 510(k), then, clearance would have certified only that each resembled some prior device closely enough. At no link does anyone ask what the sleepless resident cares about: is this the best available tool, or merely an adequate one? The stricter regime contains no comparative-effectiveness requirement either, only a resemblance requirement. The gap the study exposed is not one clearance would have closed. It runs through both sides of the line.

The Specification a Manufacturer Writes for Itself

Artificial intelligence complicates the regulated picture in a way the FDA has genuinely tried to address. Traditional devices are static. A machine-learning system is not; the thing cleared on Monday may behave differently by Friday, and freezing it defeats the purpose.

The answer arrived on 3 December 2024, in a guidance titled “Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence-Enabled Device Software Functions.” The Predetermined Change Control Plan, or PCCP, is a clever instrument. It lets a manufacturer specify in advance the modifications it intends to make, the protocol by which it will validate them, and an assessment of how those changes might affect safety and performance. Once the FDA authorises the plan, the manufacturer can implement the pre-agreed changes without a fresh submission each time. The final guidance broadened the concept to all AI-enabled devices and required labelling to disclose when a device had been authorised with such a plan.

But notice what the PCCP measures against. It measures a device against the specification its own manufacturer defined. The modification protocol asks whether changes stay within the envelope the sponsor drew; the impact assessment asks whether the sponsor's own performance claims still hold after the sponsor's own planned updates. The apparatus is internally referential: a rigorous test of whether a product does what its maker promised, held to the standard its maker set. That is not a flaw. It is the PCCP working as intended.

What the plan cannot do, because it was never built to, is look sideways. No clause asks whether a freely available chatbot, updated last week by a company that filed nothing with the FDA, now answers clinical questions more accurately than the authorised device. The regulatory frame has no peripheral vision. It looks at the device and its own past self, not at the field. And this is the best case, inside the system. The two tools the study measured are outside it, where there is no specification and no plan at all.

The Safe Harbour Widens

If the timing were fiction, an editor would strike it as too neat. In the same year researchers were demonstrating that specialist clinical AI underperforms general-purpose models on physicians' real questions, the FDA was making the non-device carve-out those tools rely on broader and easier to sit inside.

The agency issued a revised Clinical Decision Support Software guidance on 6 January 2026 and published it in final form on 11 March 2026, superseding the September 2022 version. The new document takes a more explicitly risk-based approach and expands the circumstances in which software qualifies as non-device CDS. The most consequential change concerns the criterion that had caused developers most difficulty: that the software not provide a specific preventive, diagnostic, or treatment output or directive.

Under the 2022 guidance, the FDA held that software offering a single recommendation, rather than options for the clinician to weigh, inherently supplants clinical judgement and therefore falls inside the device definition. The 2026 guidance reverses that stance. Where only one clinically appropriate recommendation exists, and the software otherwise satisfies the statutory criteria, the agency has said it does not intend to enforce device requirements against it. Illustrative examples indicate that software generating a recommended treatment plan, or producing a differential diagnosis for a practitioner to review and finalise, may fall outside device regulation. Software analysing a medical image or physiological signal to generate a diagnostic recommendation remains a regulated device, and the discretion is not blanket: a tool predicting a time-critical event, a cardiovascular collapse within twenty-four hours, say, stays squarely within oversight. Classification remains highly fact-specific; small changes to design, labelling, or workflow can move a product across the line either way. But the direction of travel in 2026 was unmistakable, and it was outward. The regulatory bar described it, approvingly, as cutting red tape.

Set the two events side by side and the irony is almost unbearable. In January and March, the safe harbour sheltering generative clinical decision support from premarket review got wider. In June, the first rigorous head-to-head evidence arrived showing that the flagship products sheltering there were being outperformed, on physicians' actual questions, by consumer chatbots and a search box. The system did not fail to act on the evidence. It moved, in good faith and for defensible reasons of proportionality, in the opposite direction, months before the evidence existed. What neither the carve-out nor its expansion engages with is whether the tools inside the harbour are any good.

The Counterfactual Nobody Runs

This is the gap the study drove a lorry through. Every decision in this space, whether a clearance, a change-control plan, or a determination that a product is not a device at all, answers a question of the form “does this thing meet the criteria for its category?” None answers “compared to what?” The counterfactual is absent from the assessment, and for non-device tools there is no assessment for it to be absent from.

In some corners of medicine this would be unthinkable. A pharmaceutical company seeking approval for a new drug is increasingly expected, by payers if not always by the FDA, to show not merely that the drug beats a placebo but how it stacks up against existing therapy: comparative effectiveness research. Software has escaped this comprehensively. A cleared clinical AI device must be as good as its predicate. A non-device clinical AI tool must be nothing at all, in performance terms, to anyone. Neither must ever be as good as the best thing a doctor could otherwise reach for, and in the age of the general-purpose chatbot that alternative is extraordinary, improving fast, and free.

The result is a category error hiding inside institutional furniture. When a hospital procurement committee evaluates a generative decision-support product from a long-established medical publisher, already deployed at fifty peer institutions, integrated with the electronic record and sold with an enterprise contract and a security review, it reads all of that as evidence of vetting. And it is evidence of something: of commercial diligence, of information-governance compliance. It is not evidence that anyone measured whether the tool answers clinical questions better than the alternatives. The authority is institutional and reputational, not regulatory, and certainly not empirical.

The committee is not being deceived. Nobody told it the product was cleared. But nobody told it the product was not, either, and no label, no field on a procurement form, would prompt the question. Absence does not announce itself. A missing clearance looks exactly like a clearance nobody happened to mention. The researchers put the alternatives in the same room; that is the whole contribution, and it is why the study reads like an exposed foundation.

The Doctors Are Already in the Room

If this were a theoretical gap, it could wait. It is not, because physicians have already voted with their keyboards.

The American Medical Association surveys physician sentiment towards what it carefully calls augmented intelligence. Its 2026 edition, published in March and drawn from 1,692 physicians surveyed in the opening weeks of the year, found that more than four in five, 81 per cent, now use AI in practice. That is more than double the 38 per cent recorded in 2023, and it continues a trajectory the 2024 survey caught mid-flight, when the figure stood at 66 per cent. The average number of distinct use cases per physician has risen from 1.1 to 2.3. Confidence has climbed alongside adoption: more than three-quarters now believe AI improves their ability to care for patients, up from 65 per cent in 2023. And the most common uses reported are summarising medical research and supporting clinical documentation, which is to say: exactly the task the benchmark study measured.

Here the two findings lock together into something sharper than either alone. Four in five physicians are already using AI, most commonly to digest the literature. The tools sold to them for that purpose carry no evidence of comparative superiority and, on the best available evidence, have none. A large and growing share of clinical AI use is therefore happening with no reliable relationship between the standing of a tool and its performance, and with no way for the clinician to know which system on their screen is better for the question in front of them. The doctor reaching for the licensed product because the hospital bought it, and the doctor reaching for the free chatbot because it is faster, are both flying blind with respect to the only thing that matters at the bedside: which answer is more likely to be right.

Automation bias sharpens the edge. A substantial literature documents the human tendency to defer to a confident machine, and a tool wrapped in the authority of a trusted publisher is exactly that. The branding does not merely fail to guarantee superior performance. It borrows trust it has not earned, shaping which answer the clinician believes rather than which is correct.

Why the Specialist Tools Might Lose

It is tempting to assume the specialists lost because they are cruder than the frontier chatbots, but the likely reasons cut against the intuition that a purpose-built medical tool should beat a generalist.

Both products are, at bottom, generative systems layered on curated medical knowledge. OpenEvidence markets itself on grounding answers in a vast corpus of peer-reviewed literature; UpToDate Expert AI inherits the authority of a resource clinicians have trusted for decades. Their pitch is precisely their specialism: constrained, cited, grounded in vetted sources, less prone to invention than a free-roaming chatbot. That specialism is real. But it can cut against raw performance. A system constrained to a particular corpus, tuned for caution, and updated on the slower clock of an established product may reason less fluently across the cross-domain messiness of a real clinical question than a frontier model trained on a far larger slice of the world.

There is a second constraint, and the regulatory story illuminates it. Staying outside the device definition is not free; it shapes the product. A tool engineered to remain a non-device must present information the clinician can independently review, must avoid crossing into directive output, and must keep its framing on the safe side of a line whose exact position is, as the FDA keeps saying, highly fact-specific. Caution of that kind is legally load-bearing. It is also, on a benchmark rewarding decisive, complete, well-calibrated clinical reasoning, expensive. The general-purpose models labour under no such constraint, because nobody has ever suggested they are medical products, which is exactly why nobody has asked them to behave like one.

There is also a brutal asymmetry of cadence. The frontier laboratories spend sums that dwarf the budgets of clinical-content companies and ship flagship models on a cycle measured in months. UpToDate Expert AI launched in September 2025; by June 2026 it faced models that did not exist when it was designed.

None of this makes the specialist tools worthless. Grounding answers in cited, vetted literature is a genuine safety property, and a fluent model that invents a plausible-sounding reference is dangerous in a way a constrained tool is not. But specialism plus institutional authority does not add up to superiority. The tool may be worth choosing for its citations, its integration, its accountable vendor. It is not worth choosing because it feels official, because that feeling corresponds to no evaluation anyone ran.

The Precedents That Should Have Warned Us

Medicine has been here before, in forms that ought to have inoculated the field against confusing standing with real-world superiority.

The pulse oximeter is the cleanest example, and instructive precisely because it was, unlike the tools in this study, a genuinely cleared device. For decades a ubiquitous and trusted instrument, the finger-clip oximeter was shown, in research by Sjoding and colleagues published in the New England Journal of Medicine during the COVID-19 pandemic, to systematically overestimate blood-oxygen levels in patients with darker skin, missing dangerous occult hypoxaemia roughly three times as often in Black patients as in white ones. The device met its specification. It had been cleared. It was used everywhere. And it was quietly failing a whole class of patients, because its clearance had never required anyone to test what actually mattered across the population that actually used it. The FDA updated its testing guidance only after the harm became impossible to ignore.

The lesson generalises in both directions. A clearance certifies conformance to a specification, and if the specification omits the question you care about, the clearance is silent on it. That is the oximeter. The harsher corollary for the AI case: if there is no specification at all, there is nothing even to be silent about. The oximeter at least had a document somebody could later go back and criticise. For a non-device clinical decision-support tool there is a marketing page and a licence agreement.

What is genuinely new is the availability of the alternative. In the oximeter case there was no free, superior device in every clinician's pocket; the harm was a gap between the tool and reality. Here the superior alternative is neither hypothetical nor scarce. It is the chatbot the resident already has open in another tab, updated last week, costing nothing, evaluated by no one, and, on the evidence, better.

What Authority Communicates, and to Whom

All of which forces the sleepless resident's question into the open. If nobody has measured whether a marketed clinical AI tool performs better than the free alternative already in widespread use, what is the clinician actually relying on, and should they be told plainly what has and has not been checked?

The honest answer to the first is that they are relying on a bundle of proxies, each real and none of them performance. A trusted publisher's reputation, built over decades on a product that was not this product. A procurement decision that assessed cost, security, and integration. Fifty peer institutions having made the same decision, which is informative mainly about the sales team. An interface that cites sources, which establishes that sources exist, not that the synthesis of them is sound. These proxies are not worthless; an accountable vendor is genuinely better than a chatbot answering to nobody. But every one is a statement about the circumstances surrounding the tool, not about its rank among the options a clinician could actually choose.

The honest answer to the second is yes, and the case for candour is strengthened by the FDA having already conceded the principle in an adjacent context. The December 2024 PCCP guidance added a labelling requirement precisely so users would be told when a device had been authorised with a change-control plan, on the reasoning that a clinician deserves to know the epistemic status of the tool in their hands. The logic extends further. If a user deserves to know a device may change under a pre-agreed plan, they surely deserve to know when a tool in their workflow underwent no premarket review whatsoever, and that a freely available alternative may match or beat it. The infrastructure for honest disclosure exists. What is missing is any obligation to use it outside the device framework, where it would matter most.

None of this argues against the safe harbour. But the frontier chatbots are magnificent on a benchmark and entirely ungoverned in a hospital: no manufacturer accountable for a clinical failure, no labelling, no change control, no disclosure when a model is silently updated in a way that degrades its medical reasoning, no obligation to ground an answer in a real citation rather than a fluent invention. The lesson is not that regulation failed. It is that on the question clinicians most need answered, which tool is better, the regulatory system was never asked to speak, and its silence is being mistaken for a verdict.

Closing the Peripheral-Vision Gap

The fix that suggests itself is not to drag every chatbot through a 510(k). Forcing every clinical reference tool through premarket review would be futile against models that update monthly, and would freeze the field in amber. It is to attach a comparative-evidence obligation to the act of marketing a tool for clinical use, wherever that tool sits relative to the device line. A product sold to health systems as clinical decision support could be required to publish its performance against the relevant general-purpose baseline on standardised, physician-authored benchmarks of exactly the kind this study used, and to keep publishing as both the tool and the baseline evolve. This is not a novel imposition so much as an import: comparative-effectiveness thinking, long established for drugs, brought at last to software that reasons about drugs. The question shifts from “does this thing fall inside or outside a statutory category?” to “does it earn its place against the free alternative a clinician would otherwise use?”

Such a regime would have teeth precisely because the benchmarks exist and the comparison is cheap to run. HealthBench and its kin demonstrate that physician-graded evaluation is feasible at scale, and two university health systems with twelve blinded reviewers managed the whole thing at a cost that would not register on a procurement budget. The obstacle is that comparative testing would occasionally return the answer no vendor wants, that its marketed product is being beaten by a free tool, and that a hospital paying the licence might reasonably ask why. That is not a reason to avoid the test. It is the reason to run it.

Until something like that exists, the burden falls where it always falls when a system withholds a truth it could easily tell: on the individual, exercising judgement in the dark. The resident at two in the morning, typing the same question into the licensed tool and the free one, is running a private, unrecorded version of the Nature Medicine study on every difficult case, and drawing conclusions no regulator will ever see. The least the system owes them, and owes the patient whose care hangs on which answer the resident believes, is honesty about what has and has not been examined. It is not that the stamp certified too little. It is that there is no stamp, and the absence looks, from where the resident is standing, exactly like its presence.

That is the gap: not the failure of any one company or regulator, but the distance between an evaluation that never happened and the confidence a frightened, time-poor human being reads into a familiar name at the bedside. Closing it does not require dismantling the safe harbour. It requires the people selling into it to say out loud what they have measured, and against what, before the next question is typed and the next answer trusted.

References & Sources

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

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