I asked Claude a small question a few days ago. The Research feature produces reports that aggregate real sources in response to specific questions, with lots of citations, structured into sections, the kind of thing that would have taken a full afternoon of tab-juggling to assemble by hand. I wanted to know: is anyone publishing these? Not as polished essays, not laundered into think-pieces, but as themselves — the reports as artifacts. Surely, I thought, someone has built an archive. Someone must be treating these as a new kind of knowledge object and putting them somewhere a stranger could find them.
The answer turned out to be: not really. I found tools for generating reports, and plenty of people discussing the tools. What I did not find — what continued to be absent the more I looked, in repositories and on Substack and on personal sites and in forum threads — was a recognizable public genre. Curated, intentionally preserved AI research reports as reports.
That surprised me, and the more I looked at it the less it looked like a gap waiting to be filled and the more it looked like a place where several currents that should be flowing into each other are not yet doing so. I don’t know whether the empty drawer should be filled, or filled by me. But I do know that the shape of the absence is interesting, and that the historical company an absence keeps tells you something about why it persists.
The shape of the empty space
I went looking. GitHub: there are dozens of repositories that generate research reports — scientific writing pipelines, autonomous research agents, plugins for Claude Code that orchestrate literature searches. There are exactly zero notable repositories that archive the outputs as a corpus. The closest thing is Daniel Rosehill’s collection of two thousand prompt-response pairs1, which is more a working archive of LLM conversations than a curated drawer of research reports specifically. On Substack, on Notion, on Quarto, on Obsidian Publish: scattered one-offs where someone embedded a research report inside a longer post as illustration. No curated streams. No “best of.” No newsletters. No taxonomies.
The forums tell a related story. r/ClaudeAI talks about Research as a feature — its rate limits, its quality, how it compares to ChatGPT’s deep research and Perplexity’s. Nobody talks about publishing the outputs. LessWrong, where you might expect the rationalist instinct toward epistemically-tagged knowledge artifacts to land most naturally, has not produced this. The EA Forum, with its existing convention of marking posts with epistemic status, has not produced it. Maggie Appleton’s digital gardeners have not produced it.
This is the part that surprised me most. The digital garden movement has spent a decade building exactly the conceptual infrastructure that AI research reports need. Growth metaphors for maturity (seedling, budding, evergreen). Epistemic disclosure as a formal pattern. The idea that imperfect, in-progress, half-tended knowledge is a legitimate publication target. And yet the gardeners haven’t reached for the research reports. The reports remain in chat windows, where they are technically saved but feel disposable, the way a long email thread feels disposable even when it contains careful thinking.
Why the silence makes sense
It would be easy to read the empty drawer as oversight, but it isn’t. The silence is overdetermined. There are at least four reasons not to publish, and they compound.
The first is that hallucinated citations cost people. The HEC Paris researcher Damien Charlotin maintains a database of court filings containing fabricated AI citations2; it has grown into the thousands and continues to expand, with Charlotin reporting that new cases now arrive at a rate of two or three a day. The lawyers in Mata v. Avianca and their firm were jointly fined five thousand dollars in 2023 for submitting six cases that did not exist3. The legal world has learned, painfully, that AI-aggregated citations are not safe to put your name on. That lesson has migrated into the broader culture as a kind of background dread. The reports look authoritative — that is precisely the property that makes publishing them feel risky.
The second is that the verification work negates the time savings. If you publish a forty-citation research report, are you on the hook for all forty? If you only spot-checked five, do you have to say so? The honest answer is yes, and the cost of doing it well — three or four hours of cross-referencing per report — might undo the reason you generated the report in the first place. There is a paradox here. The faster the research becomes, the harder it gets to claim that you have stood behind it.
The third is that “AI slop” has become a category with moral weight. Iris van Rooij wrote about AI-generated definitions appearing on ScienceDirect; her colleague Olivia Guest called the phenomenon “epistemicide”4. Science published an editorial called “Resisting AI slop”5. Judd Antin coined “ResearchSlop”6. A formal typology — “the 7Vs of AI Slop” — exists on SSRN7. Whatever you publish enters this discourse whether or not you want it to. Adding to the pile, even with good intentions, is felt as a small act against the commons.
The fourth is authorship contamination. The Authors Guild has been blunt: “When you use AI to generate text that you include in a work, you are not writing — you are prompting. Choosing to be a professional prompter is not the same as being a writer.”8 This is not a position I agree with, but it is the air the writing world currently breathes. The people most able to curate these reports responsibly are often the people most invested in not having their intellectual labor mistaken for machine extrusion. It is not only individual reputation; it is class position, guild boundary, and the symbolic economy in which proximity to AI-generated text degrades perceived authorship.
These four pressures together explain the silence without anyone having to choose silence deliberately. You generate the report, find it useful, and then notice that there is nowhere natural to put it. So you put it in a folder. So does everyone else.
The drawer that doesn’t exist
The thing the four pressures are protecting people from is real: a knowledge commons polluted by uncurated machine output. But the way they protect is by keeping all AI-aggregated knowledge private, which is also a kind of commons collapse — the slow disappearance of a genre that could, under the right conditions, be useful. It is the failure mode where the only people willing to publish are the ones who shouldn’t.
What’s missing is not the technology. The metadata schemas exist; PROV-O has been a W3C recommendation since 20139, the Provenance, Authoring, and Versioning ontology distinguishes the system that produced a thing from the agent who authored it. The W3C, the IPTC, the Coalition for Content Provenance — they are all building the infrastructure for marking AI provenance. None of them have profiled it for research reports specifically, but the building blocks are sitting there waiting.
What’s missing is also not the conventions for marking provisional knowledge. Gwern Branwen tags every page on his site with a status (notes, draft, in progress, finished), a confidence level drawn from intelligence-community estimative language (certain, likely, possible, unlikely), and an importance rating from one to ten10. Scott Alexander has been writing “epistemic status: very speculative” at the top of essays for over a decade. The EA Forum has its own version. Wikipedia has built the most elaborate inline-verification vocabulary on the web — citation needed, failed verification, dubious, verify source, unreliable source — a graduated set of public signals for “the editor wasn’t sure.” A research report could be marked with the same care.
What’s missing is the willingness to put these pieces together and call the result a publication. The cultural permission, the small social fact of “this is a thing one does.”
A current that has been flowing for a long time
Another reason the absence keeps catching at me is that the historical currents are running directly toward this practice and have been for centuries.
The commonplace book is the most obvious ancestor. Aristotle’s koinoi topoi — the common topics, lines of argument shared across domains — gave the later commonplace tradition its name and its conceptual frame, though Aristotle himself was not yet describing a notebook practice. Erasmus published De Copia in 1512, instructing students to keep notebooks organized by topic, into which they would copy the quotations and observations they encountered. John Locke published his indexing method in 1706. Robert Darnton, the historian of reading, observed that “by keeping an account of your readings, you made a book of your own, one stamped with your personality.”11 The intellectual contribution lived in the selection and arrangement. You were not claiming to have originated the material. You were claiming to have noticed which material was worth keeping, and to have put it next to other material in a way that made both more interesting.
The medieval florilegium — literally “a gathering of flowers” — was a theological compilation. Monks would assemble passages from the Church Fathers under headings: prayer, charity, the sacraments, the nature of the soul. The florilegium had no author in the modern sense. Its compiler was an editor, a curator, a steward. It was understood that the value of the form did not depend on the compiler having written the passages. It depended on the compiler having read carefully and chosen well.
This is the genre an AI research report most naturally belongs to. A computational florilegium: a machine-gathered collection, organized by theme, awaiting a human reader’s judgment. Not a thesis. Not a paper. A curated arrangement of what is currently being said about a question, with the human contribution being the question itself, the editorial second pass, and the willingness to share the result in public.
The analogy is imperfect, though, and worth pressure-testing. It would be easy to say the medieval compiler copied from texts whose existence could be checked while the machine may invent. But this is too clean. Florilegia often copied from other florilegia — the Sacra Parallela and its many derivatives, the great fourteenth-century Manipulus florum of Thomas of Ireland, whose modern editors note that “a large number of the quotations vary significantly from the original source or sources.”12 Patristic excerpts drifted across centuries of recopying; passages were misattributed across compilations; pseudo-Augustines and pseudo-Chrysostoms accumulated. The compiler often did not have access to the originals, only to other compilers’ selections, and the floor of reliability sat lower than nostalgia would have it.
But the difference is real, even if it is one of degree rather than kind. Medieval compilation drift was slow accretion of small human errors across copyists who could in principle be traced. The machine can produce a fluent sentence that has no source at all — not a corrupted source, not a misattributed source, but no source. The artificial flowers, the mislabeled flowers, the flowers described from memory by a very confident gardener who has never been to the meadow. This is why the slop objection matters, and why the genre would fail if it meant dumping model output onto the web. The florilegium only becomes a florilegium at the point where the report is framed, dated, checked, annotated, and made answerable to a keeper. The raw report is not yet anything. The kept report — moved out of the chat window, given a date and a confidence tag and a folder it belongs to — is an object. The annotated report, with margins of human judgment and verification visible alongside the machine’s gathering, is a publication.
There is one more thing the historical analogy clarifies, and it cuts the other way. Many of the lost works of antiquity survive only through compilation. Most of what we know of Heraclitus comes through later quotation; Stobaeus’s fifth-century anthology preserves substantial portions of pre-Socratic philosophers whose primary works are entirely gone. Diogenes Laertius transmits philosophical schools we would otherwise know almost nothing about. The compiler was not just doing intellectual work in the present tense; the compiler was performing a function only visible in retrospect — preserving, against future loss, the configuration of an intellectual moment.
A research report generated today aggregates what is currently being said about a question. In ten years, some of its cited URLs will be 404s. Some of the blog posts will be gone. Some of the news articles will be locked behind archive paywalls the public cannot reach. The aggregation may be preserving, imperfectly, the shape of attention at a particular moment — what people were saying about X in spring 2026, with which sources, arranged how. That has a kind of historiographical value independent of whether each individual citation holds up under verification. It is the same value Stobaeus offers: not the truth of pre-Socratic philosophy, but a frozen image of how a later reader had access to it and chose to organize it.
This does not turn the AI research report into a civilizational treasure. It does suggest that one of the real reasons to keep these — to give them dates, locations, custodial care — is that we do not yet know what about them will turn out to matter. The medieval compiler did not know either. The work of keeping is partly a wager on attention being valuable in ways the present moment cannot see.
The marginalia tradition extends the precedent. Coleridge coined the word marginalia in 1819 to describe his own habit of writing in the margins of books; his marginal notes were collected over two decades into the six-volume Princeton edition and sometimes surpass the texts they annotate. Erasmus read with pen always in hand, publishing annotated editions whose marginal commentary became a form in its own right. Voltaire’s marginalia have been collected separately. Edgar Allan Poe published a series called “Marginalia” in the late 1840s. The tradition establishes, beyond reasonable doubt, that reactive intellectual work — work that responds to an existing text rather than originating its own — is a legitimate publication genre. An AI research report annotated with human marginalia is structurally analogous to Coleridge in his books. The text is machine-written. The annotation is human. Neither alone would be the artifact; the layered thing is.
A.G. Sertillanges, writing as a Dominican in 1921, treats the organization of one’s notes and reading as a spiritual practice. The Intellectual Life13 is a book about how to keep a working archive — a card file, indexed, annotated, returned to over years. Sertillanges grounds his method in Aquinas’s sixteen precepts for acquiring knowledge. The vision he offers is collaborative: the intellectual worker is never truly alone, but receives an inheritance of the ages — thinking happens in company with those who have read and thought before. It is hard to read this without noticing that the AI research report is, among other things, a new species of company. Whether one accepts the framing or not, Sertillanges’s tradition has no metaphysical objection to thinking with a non-human collaborator and then keeping the result.
And then there is the digital garden movement, which has spent a decade developing the closest contemporary analog. Maggie Appleton’s 2020 essay on the form names six patterns that translate without modification: topography over timelines, continuous growth, imperfection and learning in public, playful and personal experimentation, intercropping and content diversity, independent ownership14. Her concept of epistemic disclosure — writing about how you came to know what you know — is precisely the missing piece. Andy Matuschak’s principle of “working with the garage door up,” riffed from a passage in Robin Sloan’s newsletter about a woodworker who keeps his shop door propped open as a small public gesture, names the same instinct from a different angle15. A public drawer of annotated AI research reports, kept openly with their provenance and their uncertainties intact, would be the garage door propped open: visible process, not finished product. The raw report alone is closer to the pile of materials after a trip to the lumberyard. What makes it a publication is the keeping.
Where I sit with it
I have not decided what to do with my own reports. This exploration so far suggests three possibilities.
The first is to keep them privately, in Obsidian, as inputs to my own synthesis later. The labor of rewriting and connecting is the entire point, and a public-facing container would distort it by making me performative about a process that needs to be quiet to work. There is a dignity in this option that I find hard to set aside. Not everything wants to be published. Some thinking gets worse when it is watched.
The second is to keep them in a private repository, version-controlled, timestamped, retrievable but not visible. This buys me Git’s provenance properties — the diff history of my own annotations, the record of what I added when — without the publishing pressure. It is the drawer, in the most literal sense.
The third is to put them on my Quarto site under a section called something like “Drawer” or “Florilegium” or “Field Notes,” with the kind of epistemic disclosure the digital gardeners and the rationalists and Gwern have already worked out: a generation date, a model version, a confidence tag, a one-line note on whether I have spot-checked anything, and the original prompt preserved alongside the output. This is the pioneering option. It would also be the one that asks the most of me per report, and the one most exposed to the four pressures I named earlier.
I think none of these is wrong. The private vault is the contemplative option — the cell, the cloister, the working archive that exists to feed a slower kind of synthesis. The public drawer is the conversational option — the garage door propped open, the willingness to be in some kind of dialogue with whoever passes by. Both are ways of being a person who reads and thinks. Neither requires the other.
What I am sure of is that something is corrosive about doing work inside an interface that treats it as ephemeral. Claude.ai conversations are saved, technically, but they are saved in a way that does not honor them — they accumulate without organization, they cannot be cited from outside, they live in a substrate I do not control. Even moving the reports into Obsidian, regardless of what I do with them after, is an act of taking the work seriously. The first decision is not “publish or don’t.” The first decision is “treat these as objects.”
The empty drawer will probably stay empty for a while longer. The four pressures are not going to lift soon. But the historical company the absence is keeping — the florilegium, the commonplace book, Coleridge in his margins, Sertillanges with his card file, Appleton tending her garden — is good company, and it is suggestive. The genre exists, in the older sense of exists that means has existed before, has had practitioners, has been recognized as legitimate by people whose judgment we still trust. We are not being asked to invent it. We are being asked to notice that it has a new form and to decide whether to give that form a place to live.
I think, for now, I will start by moving the reports out of the chat window and into a folder I control. Whatever else happens after that can happen slowly.
Footnotes
Daniel Rosehill, Prompts-And-Outputs (CC-BY-4.0). https://github.com/danielrosehill/Prompts-And-Outputs↩︎
Damien Charlotin, “AI Hallucination Cases” database, HEC Paris. https://www.damiencharlotin.com/hallucinations/↩︎
Mata v. Avianca, Inc., 22-cv-1461 (S.D.N.Y. June 22, 2023). Sanctions opinion by Judge P. Kevin Castel.↩︎
Iris van Rooij, “AI slop and the destruction of knowledge,” August 12, 2025. https://irisvanrooijcogsci.com/2025/08/12/ai-slop-and-the-destruction-of-knowledge/↩︎
H. Holden Thorp, “Resisting AI slop,” Science (editorial). https://www.science.org/doi/10.1126/science.aee8267↩︎
Judd Antin, “ResearchSlop: When AI Research Goes Wrong,” One Big Thought, Medium. https://medium.com/onebigthought/researchslop-420005b7faa4↩︎
Dag Øivind Madsen and Richard W. Puyt, “The 7Vs of AI Slop: A Typology of Generative Waste,” SSRN 5558018. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5558018↩︎
The Authors Guild, “AI Best Practices for Authors.” https://authorsguild.org/resource/ai-best-practices-for-authors/↩︎
Timothy Lebo, Satya Sahoo, and Deborah McGuinness, eds., PROV-O: The PROV Ontology, W3C Recommendation, 30 April 2013. https://www.w3.org/TR/prov-o/↩︎
Gwern Branwen, “About This Website,” gwern.net. The full tagging scheme is documented in the site’s manual of style. https://gwern.net/about↩︎
Robert Darnton, “Extraordinary Commonplaces,” New York Review of Books, December 21, 2000. Reprinted in The Case for Books: Past, Present, and Future (PublicAffairs, 2009). https://www.nybooks.com/articles/2000/12/21/extraordinary-commonplaces/↩︎
The Electronic Manipulus Florum Project, “About,” directed by Chris L. Nighman, Wilfrid Laurier University. The project’s open-access critical edition of Thomas of Ireland’s Manipulus florum (c. 1306) catalogs roughly 6,000 quotations across its 5,821 entries. https://manipulus-project.wlu.ca/about.html↩︎
A.G. Sertillanges, La Vie Intellectuelle: Son esprit, ses conditions, ses méthodes (Paris: Nouvelle Librairie Nationale, 1921). English translation by Mary Ryan as The Intellectual Life: Its Spirit, Conditions, Methods (Newman Press, 1948; reprinted Catholic University of America Press, 1998).↩︎
Maggie Appleton, “A Brief History & Ethos of the Digital Garden,” 2020. https://maggieappleton.com/garden-history↩︎
Andy Matuschak, “Work with the garage door up,” About these notes. Matuschak coins the phrase as a riff on Robin Sloan’s newsletter “Week 43” (the original Sloan link is broken as of late 2024 but is preserved within Matuschak’s note). https://notes.andymatuschak.org/Work_with_the_garage_door_up↩︎