Re: Do we even know what a good AI Optimization strategy would be for Wikipedia? Re: Re: Google Zero is coming [was Re: Wikipedia at 25: A Wake-Up Call (essay)]

Christophe Henner via Wikimedia-l <[email protected]> Sat, 11 Jul 2026 09:33:28 +0200
Newsgroups gmane.org.wikimedia.foundation
Message-ID <CAFaJbjf-084iTNx63N6TByZ8Rr94Ar4JXy_iyvsiFtQhhNiaCg@mail.gmail.com>
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What do you mean by "we have succeeded"?

--
Christophe


On Sat, 11 Jul 2026 at 07:44, Todd Allen via Wikimedia-l <
[email protected]> wrote:

> We sure do know what a good AI strategy looks like for Wikipedia. No AI o=
n
> Wikipedia.
>
> We have not succeeded by being FaceGramTwitTube. We have succeeded by not
> being like them.
>
> So, same here. No "latest and greatest". No AI on Wikipedia. Ever, for an=
y
> reason, period. Wikipedia is written by people for people.
>
> Todd
>
> On Fri, Jul 10, 2026 at 11:09=E2=80=AFPM James Heilman via Wikimedia-l <
> [email protected]> wrote:
>
>> What has motivated me to spend time writing Wikipedia over the years is
>> writing for humans. The fact that the content is openly licensed and the
>> work is supported by an NGO is also key.
>>
>> Personally i do not feel any motivation to write primarily for trillion
>> dollar machines surrounded by venture capital folks hoping to make a
>> killing. If the machines want to adapt to human facing content sure.
>>
>> The approaches you mention is how Healthline succeeded, they basically
>> have dozens of articles covering the same topic just addressing it from =
a
>> slightly different question.
>>
>> J
>>
>>
>> Sent from Gmail Mobile
>>
>> On Fri, Jul 10, 2026 at 21:24 Alex Stinson via Wikimedia-l <
>> [email protected]> wrote:
>>
>>> Forking this conversation, because I don't think we have a shared
>>> framing of what we are competing for in a "Google" Zero landscape domin=
ated
>>> by ChatBot/AI search style RAG citations (i.e.
>>> https://en.wikipedia.org/wiki/Retrieval-augmented_generation).
>>>
>>> For the last 9 months, I've been examining how civil society content
>>> should be showing up in AI search, and there is a missing perspective i=
n
>>> our "we will build it and they will come" approach to Wikipedia. I don'=
t
>>> think we can wait for the big tech companies or European regulatory bod=
ies
>>> to adopt a different idea of how RAG should work.   Here is my take fro=
m
>>> what I have been engaging with in the AIO/AEO/SEO space:
>>>
>>> *Wikipedia doesn't have content that is SEO/AEO optimized*
>>>
>>> Part of the problem, even if we did have an MCP server is that the
>>> models (at least in my tracking), are pushing many citations away from
>>> "factual" websites, towards "authoritative" websites. This authoritativ=
e
>>> content includes:
>>>
>>>    - Expert original, analysis that makes strong claims based on facts
>>>    (i.e. blog posts by authoritative companies or recently published
>>>    ScienceDirect articles)
>>>    - Content that has been updated recently, with the biggest "hot
>>>    takes" (i.e. I have monitored a couple of prompt pools where citatio=
ns
>>>    shift to newer content after 2-3 months)
>>>    - Content that helps users make a decision between different choices
>>>    (i.e. review websites, etc)
>>>
>>>
>>> This is following Google's longer-term push towards "human centered and
>>> useful" content (sometimes called  E-E-A-T an abbreviation of  experien=
ce,
>>> expertise, authoritativeness, and trustworthiness, in SEO world).
>>> https://developers.google.com/search/docs/fundamentals/creating-helpful=
-content
>>>
>>>
>>> To win in an AI optimization battle -- its less about Wikipedia doing
>>> well in the keyword search indexes that led to our content being visibl=
e
>>> (which is why we have a reputation as a "fact checking" website) and mo=
re
>>> about "winning" in the criteria for what makes a good RAG citation --- =
and
>>> our content format, is the exact opposite of the EAAT criteria:
>>>
>>>    - Wikipedia is not authoriative, but rather points to other
>>>    authorities
>>>    - We ground our content in anonymity instead of named experts or
>>>    instutional process/opinoin
>>>    - We rarely do original analysis instead summarizing the experience
>>>    and expertise of others,
>>>    - Alot of our content is out of date, and self-aware of its gaps
>>>    (i.e. maintenance tags), so also is likely to be undermining its own
>>>    trustworthiness
>>>
>>>
>>> *All the data points to us being used, but without an official roundup
>>> we are all talking in the dark about different assumed reputation losse=
s*
>>>
>>> RAG unlike Google Search Indexing, seems to be using Wikipedia for a
>>> fraction of a fraction of responses, favoring these other kinds of
>>> sources:
>>>
>>>    - Only 5% of AI overviews have Wikipedia in them:
>>>    https://ahrefs.com/blog/most-cited-domains-ai-overviews/
>>>    - I have access to SERanking's corpus of prompt monitoring across 5
>>>    models (ChatGPT, Perplexity, Google Models and they suggest that in =
May
>>>    ~16% of prompts included Wikipdia, and in their most recent month (J=
une),
>>>    ~13% of prompts. SERankings corpus is probably the # 4 or 5 in comme=
rcial
>>>    AIO data -- so could have gaps.
>>>    - Studies from earlier in the year put Wikipedia at about ~13% of
>>>    CHATGPT citations (
>>>    https://www.prnewswire.com/news-releases/wikipedia-and-reddit-now-dr=
ive-over-25-of-chatgpt-citations-in-the-us-new-5w-research-finds--wsj-nyt-a=
nd-bloomberg-do-not-appear-in-the-top-20-302768339.html
>>>    but chatgpt on average includes >20 sources in a response, compared =
to
>>>    googles 5-10 and doesn't expose it in the interface very well)
>>>    - Comparable "top" Websites, like Youtube, Reddit, and LinkedIn tend
>>>    to represent a greater % of content (in the SERanking data pool near=
ly 30%
>>>    of responses had a Youtube Video cited for instance)
>>>    - Domain specific citation pools have pretty significant differences
>>>    in "which" sources are being called, with Wikipedia doing well on so=
me
>>>    prompt pools: https://generativepulse.ai/report/
>>>
>>>
>>>
>>>
>>> *RAG/AI search optimization focuses more on intent than keywords, and w=
e
>>> aren't very effective at serving intent, and we don't know where our
>>> optimization options are*
>>> What we need is an understanding of "which actual user reader behavior
>>> are we seeking to serve?". In the past we were extremely lazy, because
>>> keyword search always delivered Wikipedia as "a first". Now we need our
>>> content to be more optimized for the kind of user curiosity driving the=
ir
>>> use of a chatbot/search tool:
>>>
>>>    - What percentage of prompts or AI searches are informational vs
>>>    opinion forming? Are we even a competitor for grounding opinion base=
d
>>>    questions or only the informational ones?
>>>    - How many of the interactions are two or three steps down a chain
>>>    of more "specific" interactions with the chatbot and thus no longer =
need
>>>    "general knowledge" information from Wikipedia, but rather the kinds=
 of
>>>    stuff that we rely on our citations to provide ?
>>>    - How much are the AI companies optimizing for "sales" or
>>>    "addiction" rather than for leading users to reliable content? (I wa=
s
>>>    tracking a series of informational topics about food that (on ChatGP=
T and
>>>    Google), kept wanting me to continue the conversation by *inviting
>>>    me to go to local hamburger restraunts)*. Do we even have a
>>>    reasonable chance to be in those searches?
>>>    - How much is geolocation forcing more and more responses into
>>>    "local" sources rather than "global" websites? In one dataset I trac=
ked, in
>>>    Global South countries citations were overwhelmingly to Facebook and
>>>    Instagram despite more authoritative academic, news and Wikipedia-ty=
pe
>>>    sites in the same searches from the UK.
>>>
>>>
>>> *We may need to radically change the "readable signals" on our content
>>> pages, meaning changing the Manual of Style, Editing Practices, and AI
>>> enabled enrichment.*
>>>
>>> If we are trying to market Wikipedia's content into AI interfaces, we
>>> also can't do what most AI optimization/marketing agencies would sugges=
t:
>>> writing listicle/FAQ type content that closely matches the user-queries
>>> that folks are giving the IA models (i.e. analysis like:
>>> https://neilpatel.com/marketing-stats/trust-signals-ai-engines-reward-m=
ost/
>>> ).
>>>
>>> We would then have to experiment with other content types, that _no
>>> longer look like the encyclopedia_. Or we would need to be reconfigurin=
g
>>> the Encyclopedic content to expose enrichments to paragraphs or section=
s
>>> within the encyclopedia  that pretty radically change editorial assupmt=
ions
>>> and our Manual of Style (i.e. instead of simple 1-2 word section headin=
gs,
>>> like "History" we may need intent-focused headings like "What is the
>>> history of [x topic]?).
>>>
>>> If we want to compete in the shifting AI search landscape -- we would
>>> need a lot more data from the Foundation on where we are succeeding or =
not,
>>> and then consider *_radically different_ *ways of exposing our content
>>> in terms of treating RAG systems as a user that needs correct paths to
>>> Wikipedia pages.
>>>
>>> However, this doesn't necessarily need to change the *human reader
>>> experience *, but would need to be about configuring the content
>>> (beyond an MCP server or Enterpise APIs) *for an AI audience/consumer
>>> experience -- *which I haven't seen addressed in any WMF publications
>>> or community conversations. Without a firm theory of "What kind of cons=
umer
>>> is an AI search agent/RAG index?" and "How does our content need to ser=
ve
>>> that AI audience?" the editing community won't be able to adjust its
>>> editing practices or weigh in on feature recommendations that make our
>>> content "AI useful".
>>>
>>> As I have written elsewhere, I think there is a inherent audience for
>>> editing/using the Wikis organically:
>>> https://en.wikipedia.org/wiki/Wikipedia:Wikipedia_Signpost/2026-06-21/O=
p-ed
>>> -- but its a different question than competing "with other information
>>> sources" for AI as an audience.
>>>
>>>
>>>
>>>
>>>
>>> On Fri, Jul 10, 2026 at 2:30=E2=80=AFPM Steven Walling via Wikimedia-l =
<
>>> [email protected]> wrote:
>>>
>>>>
>>>>
>>>> On Fri, Jul 10, 2026 at 9:52=E2=80=AFAM Erik Moeller via Wikimedia-l <
>>>> [email protected]> wrote:
>>>>
>>>>> On Fri, Jul 10, 2026 at 5:59=E2=80=AFPM James Heilman via Wikimedia-l
>>>>> <[email protected]> wrote:
>>>>>
>>>>> > Yah a search engine that actually gives real references that
>>>>> supports the statements in question would be amazing.
>>>>>
>>>>> Almost like .. a Knowledge Engine. ;-)
>>>>>
>>>>
>>>> Is the WMF building an MCP server to connect Wikipedia and Wikidata
>>>> directly to Gemini, Claude, and ChatGPT? This is a more lightweight,
>>>> backdoor way to leverage the audience of those platforms but present
>>>> structured outputs to AI chats for users based on Wikimedia knowledge.=
 If
>>>> we did so, we could present citations within the returned responses to
>>>> users, and those platforms make it transparent to the user when they a=
re
>>>> calling a particular tool.
>>>>
>>>> Steven Walling
>>>>
>>>> Sadly, the only realistic path I see there would be through
>>>>> acquisition, and even if that was financially feasible, you'd begin b=
y
>>>>> inheriting a lot of corporate practices that aren't really consistent
>>>>> with Wikimedia values.
>>>>>
>>>>> But perhaps there is a middle ground where Wikimedia seeks to define
>>>>> more clearly the terms of engagement that it wants with search engine=
s
>>>>> (clear attribution, clear and correct references, calls-to-edit,
>>>>> etc.), and then finds and recognizes search partners who implement
>>>>> those. To Luis' point, that need not be done by WMF.
>>>>>
>>>>> Warmly,
>>>>>
>>>>> Erik
>>>>> _______________________________________________
>>>>> Wikimedia-l mailing list -- [email protected],
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>>>>> https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and
>>>>> https://meta.wikimedia.org/wiki/Wikimedia-l
>>>>> Public archives at
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>>>>> To unsubscribe send an email to wikimedia-l-leave-RusutVdil2icGmH+5r0DM0B+6BGkLq7r@public.gmane.org
>>>>
>>>> _______________________________________________
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s
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>>>
>>> _______________________________________________
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>>> at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and
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>>
>> _______________________________________________
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>> at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and
>> https://meta.wikimedia.org/wiki/Wikimedia-l
>> Public archives at
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>
> _______________________________________________
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> at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and
> https://meta.wikimedia.org/wiki/Wikimedia-l
> Public archives at
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<div dir=3D"ltr"><div>What do you mean by &quot;we have succeeded&quot;?=C2=
=A0</div><div><br></div><div><div dir=3D"ltr" class=3D"gmail_signature" dat=
a-smartmail=3D"gmail_signature">--<br>Christophe</div></div><br></div><br><=
div class=3D"gmail_quote gmail_quote_container"><div dir=3D"ltr" class=3D"g=
mail_attr">On Sat, 11 Jul 2026 at 07:44, Todd Allen via Wikimedia-l &lt;<a =
href=3D"mailto:[email protected]">[email protected]=
.org</a>&gt; wrote:<br></div><blockquote class=3D"gmail_quote" style=3D"mar=
gin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1=
ex"><div dir=3D"ltr"><div>We sure do know what a good AI strategy looks lik=
e for Wikipedia. No AI on Wikipedia.</div><div><br></div><div>We have not s=
ucceeded by being FaceGramTwitTube. We have succeeded by not being like the=
m.</div><div><br></div><div>So, same here. No &quot;latest and greatest&quo=
t;. No AI on Wikipedia. Ever, for any reason, period. Wikipedia is written =
by people for people.</div><div><br></div><div>Todd</div></div><br><div cla=
ss=3D"gmail_quote"><div dir=3D"ltr" class=3D"gmail_attr">On Fri, Jul 10, 20=
26 at 11:09=E2=80=AFPM James Heilman via Wikimedia-l &lt;<a href=3D"mailto:=
[email protected]" target=3D"_blank">[email protected]=
dia.org</a>&gt; wrote:<br></div><blockquote class=3D"gmail_quote" style=3D"=
margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-lef=
t:1ex"><div dir=3D"auto">What has motivated me to spend time writing Wikipe=
dia over the years is writing for humans. The fact that the content is open=
ly licensed and the work is supported by an NGO is also key.</div><div dir=
=3D"auto"><br></div><div dir=3D"auto">Personally i do not feel any motivati=
on to write primarily for trillion dollar machines surrounded by venture ca=
pital folks hoping to make a killing. If the machines want to adapt to huma=
n facing content sure.</div><div dir=3D"auto"><br></div><div dir=3D"auto">T=
he approaches you mention is how Healthline succeeded, they basically have =
dozens of articles covering the same topic just addressing it from a slight=
ly different question.=C2=A0</div><div dir=3D"auto"><br></div><div dir=3D"a=
uto">J</div><div><br clear=3D"all"><br clear=3D"all"><div><div dir=3D"ltr" =
class=3D"gmail_signature">Sent from Gmail Mobile</div></div></div><div><br>=
<div class=3D"gmail_quote"><div dir=3D"ltr" class=3D"gmail_attr">On Fri, Ju=
l 10, 2026 at 21:24 Alex Stinson via Wikimedia-l &lt;<a href=3D"mailto:wiki=
[email protected]" target=3D"_blank">[email protected]=
org</a>&gt; wrote:<br></div><blockquote class=3D"gmail_quote" style=3D"marg=
in:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1e=
x"><div dir=3D"ltr"><div dir=3D"ltr">Forking this conversation, because I d=
on&#39;t think we have a shared framing of what we are competing for in a &=
quot;Google&quot; Zero landscape dominated by ChatBot/AI search style RAG c=
itations (i.e. <a href=3D"https://en.wikipedia.org/wiki/Retrieval-augmented=
_generation" target=3D"_blank">https://en.wikipedia.org/wiki/Retrieval-augm=
ented_generation</a>).<br><br>For the last 9 months, I&#39;ve been examinin=
g how civil society content should be showing up in AI search, and there is=
 a missing perspective in our &quot;we will build it and they will come&quo=
t; approach to Wikipedia. I don&#39;t think we can wait for the big tech co=
mpanies or European regulatory bodies to adopt a different idea of how RAG =
should work.=C2=A0 =C2=A0Here is my take from what I have been engaging wit=
h in the AIO/AEO/SEO space:<br><br><b>Wikipedia doesn&#39;t have content th=
at is SEO/AEO optimized</b><br><br>Part of the problem, even if we did have=
 an MCP server is that the models=C2=A0(at least in my tracking), are pushi=
ng many citations away from &quot;factual&quot; websites, towards &quot;aut=
horitative&quot; websites. This authoritative content includes:=C2=A0<br><u=
l><li>Expert original, analysis that makes strong claims based on facts (i.=
e. blog posts by authoritative companies or recently published ScienceDirec=
t articles)</li><li>Content that has been updated recently, with the bigges=
t &quot;hot takes&quot; (i.e. I have monitored a couple of prompt pools whe=
re citations shift to newer content after 2-3 months)</li><li>Content that =
helps users make a decision between different choices (i.e. review websites=
, etc)</li></ul><br>This is following Google&#39;s longer-term push towards=
 &quot;human centered and useful&quot; content (sometimes called=C2=A0=C2=
=A0E-E-A-T an abbreviation of=C2=A0 experience, expertise, authoritativenes=
s, and trustworthiness, in SEO world).=C2=A0<a href=3D"https://developers.g=
oogle.com/search/docs/fundamentals/creating-helpful-content" target=3D"_bla=
nk">https://developers.google.com/search/docs/fundamentals/creating-helpful=
-content</a>=C2=A0<br><br>To win in an AI optimization battle -- its less a=
bout Wikipedia doing well in the keyword search indexes that led to our con=
tent being visible (which is why we have a reputation as a &quot;fact check=
ing&quot; website) and more about &quot;winning&quot; in the criteria for w=
hat makes a good RAG citation --- and our content format, is the exact oppo=
site of the EAAT criteria:=C2=A0<br><ul><li>Wikipedia is not authoriative, =
but rather points to other authorities</li><li>We ground our content in ano=
nymity instead of named experts or instutional process/opinoin</li><li>We r=
arely do original analysis instead summarizing the experience and expertise=
 of others,=C2=A0</li><li>Alot of our content is out of date, and self-awar=
e of its gaps (i.e. maintenance tags), so also is likely to be undermining =
its own trustworthiness</li></ul><br><b>All the data points to us being use=
d, but without an official roundup we are all=C2=A0talking in the dark abou=
t different assumed reputation losses</b><br><br>RAG unlike Google Search I=
ndexing, seems to be using Wikipedia for a fraction of a fraction of respon=
ses, favoring these other kinds of sources:=C2=A0=C2=A0<br><ul><li>Only 5% =
of AI overviews have Wikipedia in them:=C2=A0<a href=3D"https://ahrefs.com/=
blog/most-cited-domains-ai-overviews/" target=3D"_blank">https://ahrefs.com=
/blog/most-cited-domains-ai-overviews/</a></li><li>I have access to SERanki=
ng&#39;s corpus of prompt monitoring across 5 models (ChatGPT, Perplexity, =
Google Models and they suggest that in May ~16% of prompts included Wikipdi=
a, and in their most recent month (June), ~13% of prompts. SERankings corpu=
s is probably the # 4 or 5 in commercial AIO data -- so could have gaps.</l=
i><li>Studies from earlier in the year put Wikipedia at about ~13% of CHATG=
PT citations ( <a href=3D"https://www.prnewswire.com/news-releases/wikipedi=
a-and-reddit-now-drive-over-25-of-chatgpt-citations-in-the-us-new-5w-resear=
ch-finds--wsj-nyt-and-bloomberg-do-not-appear-in-the-top-20-302768339.html"=
 target=3D"_blank">https://www.prnewswire.com/news-releases/wikipedia-and-r=
eddit-now-drive-over-25-of-chatgpt-citations-in-the-us-new-5w-research-find=
s--wsj-nyt-and-bloomberg-do-not-appear-in-the-top-20-302768339.html</a> but=
 chatgpt on average includes &gt;20 sources in a response, compared to goog=
les 5-10 and doesn&#39;t expose it in the interface very well)=C2=A0</li><l=
i>Comparable &quot;top&quot; Websites, like Youtube, Reddit, and LinkedIn t=
end to represent a greater % of content (in the SERanking data pool nearly =
30% of responses had a Youtube Video cited for instance)</li><li>Domain spe=
cific citation pools have pretty significant differences in &quot;which&quo=
t; sources are being called, with Wikipedia doing well on some prompt pools=
:=C2=A0<a href=3D"https://generativepulse.ai/report/" target=3D"_blank">htt=
ps://generativepulse.ai/report/</a></li></ul><br><br><b>RAG/AI search optim=
ization focuses more on intent than keywords, and we aren&#39;t very effect=
ive at serving intent, and we don&#39;t know where our optimization options=
 are<br></b><br>What we need is an understanding of &quot;which actual user=
 reader behavior are we seeking to serve?&quot;. In the past we were extrem=
ely lazy, because keyword search always delivered Wikipedia as &quot;a firs=
t&quot;. Now we need our content to be more optimized for the kind of user =
curiosity driving their use of a chatbot/search tool:=C2=A0<br><ul><li>What=
 percentage of prompts or AI searches are informational vs opinion forming?=
 Are we even a competitor for grounding opinion based questions or only the=
 informational ones?</li><li>How many of the interactions are two or three =
steps down a chain of more &quot;specific&quot; interactions with the chatb=
ot and thus no longer need &quot;general knowledge&quot; information from W=
ikipedia, but rather the kinds of stuff that we rely on our citations to pr=
ovide ?=C2=A0</li><li>How much are the AI companies optimizing for &quot;sa=
les&quot; or &quot;addiction&quot; rather than for leading users to reliabl=
e content? (I was tracking a series of informational topics about food that=
 (on ChatGPT and Google), kept wanting me to continue the conversation by <=
i>inviting me to go to local hamburger restraunts)</i>. Do we even have a r=
easonable chance to be in those searches?</li><li>How much is geolocation f=
orcing more and more responses into &quot;local&quot; sources rather than &=
quot;global&quot; websites? In one dataset I tracked, in Global South count=
ries citations were overwhelmingly to Facebook and Instagram despite more a=
uthoritative academic, news and Wikipedia-type sites in the same searches f=
rom the UK.</li></ul><br><b>We may need to radically change the &quot;reada=
ble signals&quot; on our content pages, meaning changing the Manual of Styl=
e, Editing Practices, and AI enabled enrichment.</b><br><br>If we are tryin=
g to market Wikipedia&#39;s content into AI interfaces, we also can&#39;t d=
o what most AI optimization/marketing agencies would suggest: writing listi=
cle/FAQ type content that closely matches the user-queries that folks are g=
iving the IA models (i.e. analysis like: <a href=3D"https://neilpatel.com/m=
arketing-stats/trust-signals-ai-engines-reward-most/" target=3D"_blank">htt=
ps://neilpatel.com/marketing-stats/trust-signals-ai-engines-reward-most/</a=
> ). <br><br>We would then have to experiment with other content types, tha=
t _no longer look like the encyclopedia_. Or we would need to be reconfigur=
ing the Encyclopedic content to expose enrichments to paragraphs or section=
s within the encyclopedia=C2=A0 that pretty radically change editorial assu=
pmtions and our Manual of Style (i.e. instead of simple 1-2 word section he=
adings, like &quot;History&quot; we may need intent-focused headings like &=
quot;What is the history of [x topic]?).=C2=A0<br><br>If we want to compete=
 in the shifting AI search landscape -- we would need a lot more data from =
the Foundation on where we are succeeding or not, and then consider <i>_rad=
ically different_ </i>ways of exposing our content in terms of treating RAG=
 systems as a user that needs correct paths to Wikipedia pages.<br>=C2=A0<b=
r>However, this doesn&#39;t necessarily need to change the <i>human=C2=A0re=
ader experience </i>, but would need to be about configuring the content (b=
eyond an MCP server or Enterpise APIs)=C2=A0<i>for an AI audience/consumer =
experience -- </i>which I haven&#39;t seen addressed in any WMF publication=
s or community conversations. Without a firm theory of &quot;What kind of c=
onsumer is an AI search agent/RAG index?&quot; and &quot;How does our conte=
nt need to serve that AI audience?&quot; the editing community won&#39;t be=
 able to adjust its editing practices or weigh in on feature recommendation=
s that make our content &quot;AI useful&quot;.<br><br>As I have written els=
ewhere, I think there is a inherent audience for editing/using the Wikis or=
ganically:=C2=A0<a href=3D"https://en.wikipedia.org/wiki/Wikipedia:Wikipedi=
a_Signpost/2026-06-21/Op-ed" target=3D"_blank">https://en.wikipedia.org/wik=
i/Wikipedia:Wikipedia_Signpost/2026-06-21/Op-ed</a> -- but its a different =
question than competing &quot;with other information sources&quot; for AI a=
s an audience.<br><br><br><br><br></div><br><div class=3D"gmail_quote"><div=
 dir=3D"ltr" class=3D"gmail_attr">On Fri, Jul 10, 2026 at 2:30=E2=80=AFPM S=
teven Walling via Wikimedia-l &lt;<a href=3D"mailto:[email protected]=
edia.org" target=3D"_blank">[email protected]</a>&gt; wrote:<=
br></div><blockquote class=3D"gmail_quote" style=3D"margin:0px 0px 0px 0.8e=
x;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir=3D"ltr"=
><div dir=3D"ltr"><br></div><br><div class=3D"gmail_quote"><div dir=3D"ltr"=
 class=3D"gmail_attr">On Fri, Jul 10, 2026 at 9:52=E2=80=AFAM Erik Moeller =
via Wikimedia-l &lt;<a href=3D"mailto:[email protected]" targ=
et=3D"_blank">[email protected]</a>&gt; wrote:<br></div><bloc=
kquote class=3D"gmail_quote" style=3D"margin:0px 0px 0px 0.8ex;border-left:=
1px solid rgb(204,204,204);padding-left:1ex">On Fri, Jul 10, 2026 at 5:59=
=E2=80=AFPM James Heilman via Wikimedia-l<br>
&lt;<a href=3D"mailto:[email protected]" target=3D"_blank">wi=
[email protected]</a>&gt; wrote:<br>
<br>
&gt; Yah a search engine that actually gives real references that supports =
the statements in question would be amazing.<br>
<br>
Almost like .. a Knowledge Engine. ;-)<br></blockquote><div><br></div>Is th=
e WMF building an MCP server to connect Wikipedia and Wikidata directly to =
Gemini, Claude, and ChatGPT? This is a more lightweight, backdoor way to le=
verage the audience of those platforms but present structured outputs to AI=
 chats for users based on Wikimedia knowledge.=C2=A0<span style=3D"backgrou=
nd-color:transparent">If we did so, we could present citations within the r=
eturned responses to users, and those platforms make it transparent to the =
user when they are calling a particular tool.=C2=A0</span><span style=3D"ba=
ckground-color:transparent">=C2=A0</span></div><div class=3D"gmail_quote"><=
span style=3D"background-color:transparent"><br></span></div><div class=3D"=
gmail_quote"><span style=3D"background-color:transparent">Steven Walling=C2=
=A0</span></div><div class=3D"gmail_quote"><br><blockquote class=3D"gmail_q=
uote" style=3D"margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,2=
04);padding-left:1ex">Sadly, the only realistic path I see there would be t=
hrough<br>
acquisition, and even if that was financially feasible, you&#39;d begin by<=
br>
inheriting a lot of corporate practices that aren&#39;t really consistent<b=
r>
with Wikimedia values.<br>
<br>
But perhaps there is a middle ground where Wikimedia seeks to define<br>
more clearly the terms of engagement that it wants with search engines<br>
(clear attribution, clear and correct references, calls-to-edit,<br>
etc.), and then finds and recognizes search partners who implement<br>
those. To Luis&#39; point, that need not be done by WMF.<br>
<br>
Warmly,<br>
<br>
Erik<br>
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