There are many conversations to be had about the value and dangers of AI. I
don't discount anyone's opinion. My own is AI has many good and important
uses, many bad—and is a particular disaster for education.

But Code4Lib is at a minimum about code, and AI coding has absolutely
transformed the software development industry over the last six months. If
it hasn't hit you yet, it will. It is the most significant change in
decades. It would be short sighted to shut down or stigmatize the
discussion of it here.

Tim Spalding
Founder, LibraryThing


On Thu, Jul 9, 2026 at 11:39 AM Karen Coyle <[log in to unmask]> wrote:

> This reminds me of what we were told in school when calculators first
> became affordable:
>
> "You need to study math and learn to use it even though you now have a
> calculator. Only if you understand math will you be aware if some
> mistake has been made."
>
> Like when I hit the multiply key rather than the divide key.
>
> I'm good with using computers, whether than LLM or some other software,
> for crunching data. I'm much less confident that I can trust computers
> to operate with human language. Crunched data can be checked, and the
> output is factual. Language is not. I'm back to "the right tool for the
> job" but also "understand the limits of your tools."
>
> kc
>
> On 7/8/26 2:53 PM, Vishal Patel wrote:
> > Given Alex’s strong response, I feel compelled to weigh in.
> >
> >    1.
> > It’s clear that LLMs are divisive. We (namely, Mackenzie Salisbury)
> started one dedicated to LLMs at [log in to unmask]
> - it leans more LLM-curious.
> >    2.
> > I don’t detect any “LLM slop” in this thread. This appears to me be a
> constructive evaluation of an LLM case study.
> >    3.
> > I would advise against snubbing or canceling a forum or a person if you
> (even by mistake) catch a whiff of LLM generated content.
> >       *
> > Language, ultimately, is just a collection of symbols to which we have
> assigned meaning, and, when we find ourselves have strong emotional
> reactions to those symbols, the empirical evidence indicates that it will
> serve us - individually and collectively - better if we learn to be curious
> about those emotions, rather than checking out or leaving the group
> entirely.
> >       *
> > It is true that today’s symbols are rapidly commingling with
> machine-generated symbols (linguistically, visually, & audibly), but
> librarians have always existed to serve as stewards of collections of
> symbols for the community. If we opt out when we see or hear a new dialect
> (e.g. AI-infused English) being written or spoken, not only is that
> antithetical to the professional values of librarianship, but it fractures
> our professional body.
> >
> > Going back to the purpose of Eric’s thought starter, I am greatly
> appreciating the value of LLMs. As an example, within the paste 24 hrs, I
> was able to:
> >
> >    1.
> > Write SQL queries in BigQuery to analyze 6 months of traffic & search
> patterns on Lane library’s website
> >    2.
> > Analyze 6 years of historical data from our LibAnswers & LibCal systems
> >    3.
> > Analyze 16 years worth of proxy server data
> >    4.
> > Synthesize all analyzes into a strategic plan
> >    5.
> > Summarize the findings as an infographic to share with my executive team
> >
> > As a former data scientist, I can attest that this type of analysis
> would have previously taken me 2-3 weeks to assemble, and the polished data
> visualization would have taken another week itself. LLMs make easy work of
> data analysis & coding.
> >
> > Sincerely,
> >
> > Vishal Patel, MD, PhD
> > Director, Digital Strategy & Library Technology
> >
> > Lane Medical Library
> >
> > Stanford School of Medicine
> >
> >
> > 300 Pasteur Drive, L109, Stanford, CA 94305-5123
> >
> > [log in to unmask]<mailto:[log in to unmask]>
> >
> > (650) 723-7196 *41425
> >
> > Pronouns:  he, him, his
> >
> > [cid:[log in to unmask]]
> >
> > From: Code for Libraries <[log in to unmask]> on behalf of Alex
> Dunn <[log in to unmask]>
> > Date: Wednesday, July 8, 2026 at 2:18 PM
> > To: [log in to unmask] <[log in to unmask]>
> > Subject: Re: [CODE4LIB] llm technology is especially useful
> >
> > I think it's high time for this mailing list to enact a ban on LLM
> > slop.  In the meantime, I'm unsubscribing.  See you all around.
> >
> > On Wed, Jul 8, 2026 at 8:39 AM Eric Lease Morgan
> > <[log in to unmask]> wrote:
> >> On Jul 4, 2026, at 7:44 PM, Karen Coyle <[log in to unmask]> wrote:
> >>
> >>> I would feel better about this if these results didn't sound like the
> platitudes of marketing speak. ("Collaborative refinement of library
> services" is something I don't think any of us would say about C4L.) Where
> did the model get this tripe?
> >>
> >> TL;DNR - I advocate the use of LLM technology in libraries. It can be a
> supplement to our existing processes, not a replacement.
> >>
> >>
> >> Thank you for the reply because I really feel our community good
> benefit from discussion on these topics.
> >>
> >> Tripe? I had to look up the definition of that word. Where did the
> result get such a response? Many places, but one of the more significant is
> my locally configured "system prompt". What's that? A system prompt is an
> extra little bit, behind the scenes configuration sent to a large-language
> model (LLM). My current system prompt follows:
> >>
> >>    Return results as if they were written by a student
> >>    attending a liberal arts college. Ask questions, sometimes,
> >>    but not always. The model is working within a generative-AI
> >>    system called a RAG, and therefore results are intended to
> >>    be primarily drawn from the underlying MCP system; results
> >>    drawn from outside the system are to be kept to a bare
> >>    minimum. The model is intended to be used as analysis tool
> >>    not an oracle. Do not voice results in the first person!!!
> >>    When citing sentences, include item and index values.
> >>
> >> If my system prompt said something like "Voice replies as if written by
> an eighth grader", then the results would be expressed differently.
> Differences in system prompts make a significant difference in results. You
> should see the sort of things I get back when I specify second graders or
> erudite college professors.  :-D
> >>
> >>
> >>> But what really concerns me is that the system is a black box (others
> have noted this), which means that there is no way to evaluate the result
> other than ones' gut feeling that it's "right." Your gut feeling returns
> "true and accurate" while mine concludes that honestly some of the "facts"
> in the statements below could be wrong. For all that C4L has great
> discussions, I don't see "code sharing" as taking place often in the body
> of the emails. (Maybe a snippet or two, but not as stated here.) The last
> paragraph on MARC doesn't convince me much. The phrase "annoying data
> format" comes up only once when I search on the C4L archive, and it's in
> one of your posts, Eric. I wouldn't include this in a summary of C4L list
> users' statements on MARC even though we are pretty critical of it. I also
> have doubts that one can conclude from the list that the group is "focusing
> heavily on MARC records—the standard format for library catalog data."
> There is a fair amount of discussion about MARC but have posters actually
> said here that it's the standard format for library catalog data? (We
> probably assume that everyone here knows that.) Could the software have
> gotten that from elsewhere, given that there is a fair amount of
> documentation online?
> >>>
> >>> --
> >>> Karen Coyle
> >>> [log in to unmask]
> https://urldefense.com/v3/__http://kcoyle.net__;!!G92We9drHetJ8EofZw!emYRrTgEe2gQVprd47jFZCCIprO0hxT1USRlq7XMgipz5vbj2Jf6kauD7i8DN_ZAehOjotejg5xnn7JIIk41Ww$
> >>
> >> Granted, above is more difficult; I more or less (mostly more) agree,
> but...
> >>
> >> The box is more gray than black. The whole process is rooted in the
> computation of geometric distances between words mapped in a VERY large
> n-dimentional space. To elaborate, it works something like this. A HUGE
> pile of text is accumulated. The text is parsed into tokens (think "words")
> to create a vocabulary. This results in a matrix where each row (millions
> or billions of them) is a document, and each column is a token from the
> vocabulary. At the intersection of each row & column is a measurement, and
> the measurement might be the number of times the given token is found in
> the given row. This results an a GREAT BIG set of vectors "pointing" to
> locations in the space. Given some input (at least a word or better yet a
> large set of words), the input is vectorized in the same manner as the
> original LLM. The vector is compared to all of the other vectors in the set
> to identify most similar vectors, where similarity is denoted to something
> like cosine distance. This is a process of linear algebra, and it is a kind
> of find or search process. Works in the manner similar to auto-completion
> or auto-correct but on a REALLY big scale.
> >>
> >> For example, in English, the word "the" is very frequently followed by
> an adjective but ultimately by a noun. These patterns are manifested in the
> LLM.
> >>
> >> Using the sort of process outlined above, given words are mapped with
> similar words, and the similar word are output. It does not necessarily
> identify nor extract exact phrases from text unless specifically asked to
> do so. Also, in my example, I only read one month's of Code4Lib archives,
> and in that month there may have been more discussion about MARC than not.
> In any event, the process does work (for the most part), and it is a
> real-world application of something first articulated by a man named John
> Firth around 1957 who said, "You shall know a word by the company it keeps"
> -- context.
> >>
> >> It is a black box? Yes, mostly. It black in the same way Google's
> search algorithms are black. It is back in the same way our bibliographic
> indexes rank relevance. It is as black as relational database
> implementations perform join queries through many-to-many relationships.
> >>
> >> Very important: I do not advocate the use of LLMs sans context. In
> other words, I do not advocate asking very general questions, like "What is
> the best Shakespeare play?" to LLMs because the only context included in
> the response is what is in the model. On the other hand, I very much
> advocate the use of retrieval-augmented generation (RAG) and/or model
> context protocol (MCP) servers. These tools get input from known and
> verifiable collections of text. The results of RAG and/or MCP queries are
> sent to an LLM for interpretation, and well-implemented results will
> include ways to backtrack results to the source. I think the use of RAG
> and/or MCP technologies applied to library collection can be very useful.
> LLM are not panaceas though.
> >>
> >> For example, the other day I queried various bibliographic indexes for
> the phrase 'big science'. This resulted in 1,200 abstracts from scholarly
> journals for a total of 350,000 words (which is bigger than Moby Dick). I
> then RAG-ed against it to extract definitions of 'big science', learned who
> helped define it, and how that definition changed over time. It worked. It
> worked well. It saved me a whole lot of time. It supplemented my reading
> process, not replaced it.
> >>
> >> I have learned two additional things. First and foremost, I take the
> results as plausible, not truth. Thus, I like to believe I practice
> information literacy along the way. Second, I am always dubious of the
> adjectives returned by LLM, especially the superlatives.
> >>
> >> What I would really like to see is the creation of one or more LLM
> built by the library profession. This way we would know whence the model
> came, how it was implemented, and remove the blackness. Such an effort
> would be akin to collaboration we have seen in the past when it comes to
> collection building or metadata sharing. Yes, it would be very expensive,
> but if we were to pool our resources, then I think it could be done.
> >>
> >> Lastly, those were a lot of words. Thank you for listening. I hope the
> discussion continues.
> >>
> >> --
> >> Eric Lease Morgan, Librarian Emeritus
> >> University of Notre Dame
>
> --
> Karen Coyle
> [log in to unmask]
> http://kcoyle.net
>
>

-- 
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