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)]

Charles Roberson via Wikimedia-l <[email protected]> Sat, 11 Jul 2026 02:03:21 -0400
Newsgroups gmane.org.wikimedia.foundation
Message-ID <CALPDdNOwVMaMsFtNmEXM-CEeA5eD6sb8Nsw-cZJkG5ajZxHM+A@mail.gmail.com>
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Wikimedia-I used to be a premium listserve of high minded ideas about how
to move the Foundation into the future. The past few months it has drifted
into a lot of whining about AI with no real effort to accomplish anything
or even plan to do so.

 - Charles

On Sat, Jul 11, 2026 at 1:44=E2=80=AFAM 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],
>>>>> guidelines at:
>>>>> https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and
>>>>> https://meta.wikimedia.org/wiki/Wikimedia-l
>>>>> Public archives at
>>>>> https://lists.wikimedia.org/hyperkitty/list/[email protected]=
ia.org/message/HNDPDZBBDMILF7WGMUBVJVIAZYQ7OXOS/
>>>>> To unsubscribe send an email to wikimedia-l-leave-RusutVdil2icGmH+5r0DM0B+6BGkLq7r@public.gmane.org
>>>>
>>>> _______________________________________________
>>>> Wikimedia-l mailing list -- [email protected],
>>>> guidelines at: https://meta.wikimedia.org/wiki/Mailing_lists/Guideline=
s
>>>> and https://meta.wikimedia.org/wiki/Wikimedia-l
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>>>> To unsubscribe send an email to wikimedia-l-leave-RusutVdil2icGmH+5r0DM0B+6BGkLq7r@public.gmane.org
>>>
>>> _______________________________________________
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>>> at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and
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>>> Public archives at
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>>
>> _______________________________________________
>> Wikimedia-l mailing list -- [email protected], guidelines
>> at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and
>> https://meta.wikimedia.org/wiki/Wikimedia-l
>> Public archives at
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org/message/5MPMZGZ2MXLLHER3NTNUS6KHIMAXIIBD/
>> To unsubscribe send an email to wikimedia-l-leave-RusutVdil2icGmH+5r0DM0B+6BGkLq7r@public.gmane.org
>
> _______________________________________________
> Wikimedia-l mailing list -- [email protected], guidelines
> 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">Wikimedia-I used to be a premium listserve=C2=A0of high mi=
nded ideas about how to move the Foundation into the future. The past few m=
onths it has drifted into a lot of whining about AI with no real effort to =
accomplish anything or even plan to do so.<div><br></div><div>=C2=A0- Charl=
es</div></div><br><div class=3D"gmail_quote gmail_quote_container"><div dir=
=3D"ltr" class=3D"gmail_attr">On Sat, Jul 11, 2026 at 1:44=E2=80=AFAM Todd =
Allen via Wikimedia-l &lt;<a href=3D"mailto:[email protected]=
">[email protected]</a>&gt; wrote:<br></div><blockquote class=
=3D"gmail_quote" style=3D"margin:0px 0px 0px 0.8ex;border-left:1px solid rg=
b(204,204,204);padding-left:1ex"><div dir=3D"ltr"><div>We sure do know what=
 a good AI strategy looks like for Wikipedia. No AI on Wikipedia.</div><div=
><br></div><div>We have not succeeded by being FaceGramTwitTube. We have su=
cceeded by not being like them.</div><div><br></div><div>So, same here. No =
&quot;latest and greatest&quot;. 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 class=3D"gmail_quote"><div dir=3D"ltr" class=3D"g=
mail_attr">On Fri, Jul 10, 2026 at 11:09=E2=80=AFPM James Heilman via Wikim=
edia-l &lt;<a href=3D"mailto:[email protected]" target=3D"_bl=
ank">[email protected]</a>&gt; wrote:<br></div><blockquote cl=
ass=3D"gmail_quote" style=3D"margin:0px 0px 0px 0.8ex;border-left:1px solid=
 rgb(204,204,204);padding-left:1ex"><div dir=3D"auto">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 NG=
O is also key.</div><div dir=3D"auto"><br></div><div dir=3D"auto">Personall=
y i do not feel any motivation to write primarily for trillion dollar machi=
nes surrounded by venture capital folks hoping to make a killing. If the ma=
chines want to adapt to human facing content sure.</div><div dir=3D"auto"><=
br></div><div dir=3D"auto">The approaches you mention is how Healthline suc=
ceeded, they basically have dozens of articles covering the same topic just=
 addressing it from a slightly different question.=C2=A0</div><div dir=3D"a=
uto"><br></div><div dir=3D"auto">J</div><div><br clear=3D"all"><br clear=3D=
"all"><div><div dir=3D"ltr" class=3D"gmail_signature">Sent from Gmail Mobil=
e</div></div></div><div><br><div class=3D"gmail_quote"><div dir=3D"ltr" cla=
ss=3D"gmail_attr">On Fri, Jul 10, 2026 at 21:24 Alex Stinson via Wikimedia-=
l &lt;<a href=3D"mailto:[email protected]" target=3D"_blank">=
[email protected]</a>&gt; wrote:<br></div><blockquote class=
=3D"gmail_quote" style=3D"margin:0px 0px 0px 0.8ex;border-left:1px solid rg=
b(204,204,204);padding-left:1ex"><div dir=3D"ltr"><div dir=3D"ltr">Forking =
this conversation, because I don&#39;t think we have a shared framing of wh=
at we are competing for in a &quot;Google&quot; Zero landscape dominated by=
 ChatBot/AI search style RAG citations (i.e. <a href=3D"https://en.wikipedi=
a.org/wiki/Retrieval-augmented_generation" target=3D"_blank">https://en.wik=
ipedia.org/wiki/Retrieval-augmented_generation</a>).<br><br>For the last 9 =
months, I&#39;ve been examining how civil society content should be showing=
 up in AI search, and there is a missing perspective in our &quot;we will b=
uild it and they will come&quot; approach to Wikipedia. I don&#39;t think w=
e can wait for the big tech companies or European regulatory bodies to adop=
t a different idea of how RAG should work.=C2=A0 =C2=A0Here is my take from=
 what I have been engaging with in the AIO/AEO/SEO space:<br><br><b>Wikiped=
ia doesn&#39;t have content that is SEO/AEO optimized</b><br><br>Part of th=
e problem, even if we did have an MCP server is that the models=C2=A0(at le=
ast in my tracking), are pushing many citations away from &quot;factual&quo=
t; websites, towards &quot;authoritative&quot; websites. This authoritative=
 content includes:=C2=A0<br><ul><li>Expert original, analysis that makes st=
rong claims based on facts (i.e. blog posts by authoritative companies or r=
ecently published ScienceDirect articles)</li><li>Content that has been upd=
ated recently, with the biggest &quot;hot takes&quot; (i.e. I have monitore=
d a couple of prompt pools where 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; conten=
t (sometimes called=C2=A0=C2=A0E-E-A-T an abbreviation of=C2=A0 experience,=
 expertise, authoritativeness, and trustworthiness, in SEO world).=C2=A0<a =
href=3D"https://developers.google.com/search/docs/fundamentals/creating-hel=
pful-content" target=3D"_blank">https://developers.google.com/search/docs/f=
undamentals/creating-helpful-content</a>=C2=A0<br><br>To win in an AI optim=
ization battle -- its less about Wikipedia doing well in the keyword search=
 indexes that led to our content being visible (which is why we have a repu=
tation as a &quot;fact checking&quot; website) and more about &quot;winning=
&quot; in the criteria for what makes a good RAG citation --- and our conte=
nt format, is the exact opposite of the EAAT criteria:=C2=A0<br><ul><li>Wik=
ipedia is not authoriative, but rather points to other authorities</li><li>=
We ground our content in anonymity instead of named experts or instutional =
process/opinoin</li><li>We rarely do original analysis instead summarizing =
the experience and expertise of others,=C2=A0</li><li>Alot of our content i=
s out of date, and self-aware 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 used, but without an official roundup we are all=
=C2=A0talking in the dark about different assumed reputation losses</b><br>=
<br>RAG unlike Google Search Indexing, seems to be using Wikipedia for a fr=
action of a fraction of responses, 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/" tar=
get=3D"_blank">https://ahrefs.com/blog/most-cited-domains-ai-overviews/</a>=
</li><li>I have access to SERanking&#39;s corpus of prompt monitoring acros=
s 5 models (ChatGPT, Perplexity, Google Models and they suggest that in May=
 ~16% of prompts included Wikipdia, and in their most recent month (June), =
~13% of prompts. SERankings corpus is probably the # 4 or 5 in commercial A=
IO data -- so could have gaps.</li><li>Studies from earlier in the year put=
 Wikipedia at about ~13% of CHATGPT citations ( <a href=3D"https://www.prne=
wswire.com/news-releases/wikipedia-and-reddit-now-drive-over-25-of-chatgpt-=
citations-in-the-us-new-5w-research-finds--wsj-nyt-and-bloomberg-do-not-app=
ear-in-the-top-20-302768339.html" target=3D"_blank">https://www.prnewswire.=
com/news-releases/wikipedia-and-reddit-now-drive-over-25-of-chatgpt-citatio=
ns-in-the-us-new-5w-research-finds--wsj-nyt-and-bloomberg-do-not-appear-in-=
the-top-20-302768339.html</a> but chatgpt on average includes &gt;20 source=
s in a response, compared to googles 5-10 and doesn&#39;t expose it in the =
interface very well)=C2=A0</li><li>Comparable &quot;top&quot; Websites, lik=
e Youtube, Reddit, and LinkedIn tend to represent a greater % of content (i=
n the SERanking data pool nearly 30% of responses had a Youtube Video cited=
 for instance)</li><li>Domain specific citation pools have pretty significa=
nt differences in &quot;which&quot; sources are being called, with Wikipedi=
a doing well on some prompt pools:=C2=A0<a href=3D"https://generativepulse.=
ai/report/" target=3D"_blank">https://generativepulse.ai/report/</a></li></=
ul><br><br><b>RAG/AI search optimization focuses more on intent than keywor=
ds, and we aren&#39;t very effective at serving intent, and we don&#39;t kn=
ow where our optimization options are<br></b><br>What we need is an underst=
anding of &quot;which actual user reader behavior are we seeking to serve?&=
quot;. In the past we were extremely lazy, because keyword search always de=
livered Wikipedia as &quot;a first&quot;. Now we need our content to be mor=
e optimized for the kind of user curiosity driving their use of a chatbot/s=
earch 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 op=
inion based questions or only the informational ones?</li><li>How many of t=
he interactions are two or three steps down a chain of more &quot;specific&=
quot; interactions with the chatbot and thus no longer need &quot;general k=
nowledge&quot; information from Wikipedia, but rather the kinds of stuff th=
at we rely on our citations to provide ?=C2=A0</li><li>How much are the AI =
companies optimizing for &quot;sales&quot; or &quot;addiction&quot; rather =
than for leading users to reliable content? (I was tracking a series of inf=
ormational topics about food that (on ChatGPT and Google), kept wanting me =
to continue the conversation by <i>inviting me to go to local hamburger res=
traunts)</i>. Do we even have a reasonable chance to be in those searches?<=
/li><li>How much is geolocation forcing more and more responses into &quot;=
local&quot; sources rather than &quot;global&quot; websites? In one dataset=
 I tracked, in Global South countries citations were overwhelmingly to Face=
book and Instagram despite more authoritative academic, news and Wikipedia-=
type sites in the same searches from the UK.</li></ul><br><b>We may need to=
 radically change the &quot;readable signals&quot; on our content pages, me=
aning changing the Manual of Style, Editing Practices, and AI enabled enric=
hment.</b><br><br>If we are trying to market Wikipedia&#39;s content into A=
I interfaces, we also can&#39;t do what most AI optimization/marketing agen=
cies would suggest: writing listicle/FAQ type content that closely matches =
the user-queries that folks are giving the IA models (i.e. analysis like: <=
a href=3D"https://neilpatel.com/marketing-stats/trust-signals-ai-engines-re=
ward-most/" target=3D"_blank">https://neilpatel.com/marketing-stats/trust-s=
ignals-ai-engines-reward-most/</a> ). <br><br>We would then have to experim=
ent with other content types, that _no longer look like the encyclopedia_. =
Or we would need to be reconfiguring the Encyclopedic content to expose enr=
ichments to paragraphs or sections within the encyclopedia=C2=A0 that prett=
y radically change editorial assupmtions and our Manual of Style (i.e. inst=
ead of simple 1-2 word section headings, like &quot;History&quot; we may ne=
ed 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 succeedin=
g or not, and then consider <i>_radically different_ </i>ways of exposing o=
ur content in terms of treating RAG systems as a user that needs correct pa=
ths to Wikipedia pages.<br>=C2=A0<br>However, this doesn&#39;t necessarily =
need to change the <i>human=C2=A0reader experience </i>, but would need to =
be about configuring the content (beyond 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 publications or community conversations. Without =
a firm theory of &quot;What kind of consumer is an AI search agent/RAG inde=
x?&quot; and &quot;How does our content need to serve that AI audience?&quo=
t; the editing community won&#39;t be able to adjust its editing practices =
or weigh in on feature recommendations that make our content &quot;AI usefu=
l&quot;.<br><br>As I have written elsewhere, I think there is a inherent au=
dience for editing/using the Wikis organically:=C2=A0<a href=3D"https://en.=
wikipedia.org/wiki/Wikipedia:Wikipedia_Signpost/2026-06-21/Op-ed" target=3D=
"_blank">https://en.wikipedia.org/wiki/Wikipedia:Wikipedia_Signpost/2026-06=
-21/Op-ed</a> -- but its a different question than competing &quot;with oth=
er information sources&quot; for AI as an audience.<br><br><br><br><br></di=
v><br><div class=3D"gmail_quote"><div dir=3D"ltr" class=3D"gmail_attr">On F=
ri, Jul 10, 2026 at 2:30=E2=80=AFPM Steven Walling via Wikimedia-l &lt;<a h=
ref=3D"mailto:[email protected]" target=3D"_blank">wikimedia-=
[email protected]</a>&gt; wrote:<br></div><blockquote class=3D"gmail_qu=
ote" style=3D"margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,20=
4);padding-left:1ex"><div dir=3D"ltr"><div dir=3D"ltr"><br></div><br><div c=
lass=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]" 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">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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