I’ve been trying a slightly different setup for working with Codex, give it a VM, connect to it remotely, and let it get on with setting up a development environment and making changes. Mainly so that I could trial this sort of more remote development from less powerful devices than my main daily driver, maybe even my phone! I did a bunch of research, and the easiest service to get off the ground with seemed to be boxd.sh.

One of the reasons for experimenting is disk space. The cloud environments that you can use with Codex / ChatGPT have had around 20 or 30 GB available, which can get rather tight for larger setups involving multiple projects, or even single repos that have lots of dependencies, and or need various docker images for various things.. most of my experiences with the cloud workspaces as part of chatGPT / codex have actually been rather disappointing! A few repositories, dependencies, container images and development databases later, and suddenly you are thinking about disk space rather than the thing you wanted to work on.

The boxd machines come with 100 GB of disk by default. That seemed like a much more useful starting point, and I wanted to see how little effort it would take to get one working with Codex and Wikimedia GitLab for a small feature for a-wikimedia-cli.

An account, some integrations, and a GitLab bot

I had already made an account at app.boxd.sh, which currently comes with $30 of free credit (and an offer for more free credit on your first top up). I have actually be using the VM on and off for a few weeks now, and only spent 10USD. The simplicity of the interfaces for turning them on and off, and the startup time really help in not wasting resources. For a 2 CPU and 4GB machine, not bad. And equivalent digital ocean droplet would be 24 USD per month, but it wouldn’t come with quick such a simple interface(but i’m up for trying that soon too).

I connected the basic integrations for Git, GitHub and Codex, which again really levels up the simplicity of the VM setup, if your only using it for private use. The idea is that the machine can pull repositories, push branches, and already have Codex CLI authenticated when I log in, without extra setup.

Wikimedia GitLab needed a little extra setup. I created a project access token and added it to boxd as a secret called WM_GITLAB_ADDSHORE_BOXD, scoped to gitlab.wikimedia.org. Such an option would naturally be available for basically all possible integrations, likely allowing for more fine grained control when it comes to scopes and access to other services and the outside world.

The token has an expiry and the Developer role, with api and write_repository scopes. It is scoped to this project, rather than giving the VM my normal GitLab account. Interestingly, GitLab actually represents it as a project-scoped bot user, so you can track the activity, and see the separated out actions.

Creating the machine

Heading to the machines page points you towards the CLI to create a machine. I called mine awm-1, said yes when asked whether I wanted to connect, and was straight into a shell.

~ boxd machine new
Name your machine: awm-1
    name: awm-1
      id: 20ced7dc-1c33-42cf-a361-44dc84a4ee01
     url: awm-1.boxd.sh
  source: standalone
    boot: 3ms

Connect:
  ssh       ssh awm-1.boxd
  cli       boxd machine connect awm-1
  browser   https://awm-1.boxd.sh

Connect to awm-1 now? [Y/n] yes
boxd@awm-1:~$

The reported boot time was 3ms, which is delightful.

Checking Codex confirmed that the integration had done its job, codex was already there, and already authed.

boxd@awm-1:~$ codex login status
Logged in using ChatGPT

Connecting Codex remotely

Next, I started remote control on the VM:

boxd@awm-1:~$ codex remote-control start
Starting app-server daemon with remote control enabled...
Installing daemon from CLI version 0.164.0 into /home/boxd/.codex/packages/app-server-daemon...
This machine is available for remote control as awm-1.
Daemon used app-server:
  path: /home/boxd/.codex/packages/app-server-daemon/current/bin/codex
  version: 0.164.0

Then, to pair it with the app:

codex remote-control pair

In the desktop app, Connections → Control other devices lets you add a device using the pairing code. After doing that, awm-1 appeared as connected.

You can also do this from a mobile phone, and yes you have to do that as an additional pairing and new pairing code (everything isn’t magically connected).

In a new chat, I could then select the remote machine and send it a prompt.

You can also just use Codex CLI directly on the machine. In fact, I might try doing the whole thing from the console next time, and maybe that’ll stop me needing to switch between my personal and work OpenAI accounts in the desktop app over and over again…

Let it set itself up

My first prompt was simply:

I want you to prepare a local development environment for https://gitlab.wikimedia.org/repos/releng/cli
You should have a secret WM_GITLAB_ADDSHORE_BOXD which should allow you to read from that repo, and push branches in the future
Get setup and let me know how it goes

That gave Codex the repository and the name of the secret it should use, with the intention of being able to push branches later. Once the development environment was set up, I took a snapshot before giving it something more interesting to try. This is also a good point in time to note that you can snapshot the VMs, pause them, resize them and even fork them. So I am unlikely to need to do this whole setup again.

A real change: Toolviews in a Wikimedia CLI

For the actual development task, I picked something I wanted in a Wikimedia CLI: access to Toolviews, which has an API for tool traffic statistics (so that I could easily find the most used tools, and in turn see if I should add any CLI support within the tool).

We had recently added pageview metrics using the Wikimedia analytics APIs, including terminal graphs. It seemed like some of that could be reused here. There was also a small command-layout question, as tools and toolforge were aliases, and adding this functionality might mean separating them. This was all decided ahead of time by me, not left for Codex to try and figure it out (that would likely be a waste).

My prompt, typos and all, was:

I want you to take a look at https://toolviews.toolforge.org/ and the API https://toolviews.toolforge.org/api/ that as far as I can tell is currently un authenticated
I think it would be neat to include this as part of the CLI tooling!
(remember to always send the a-wikimedia-cli UA)
We recently implements pageview metrics etc based on the official wikimedia analytics APIS
Some parts of that will be reusable, such as the graphs
At a guess, the command should be under `mw tools views” or something?
Which means I think we will be splitting the tools vs toolforge alias that currently exists..!

Manage Toolforge tools, jobs, builds and deployments

Usage:
  mw tools [command]

Aliases:
  tools, toolforge

So we end up with “mw tools toolviews” for example
Can you go ahead and try to implement this

The result, after a few mins, was a pushed branch and draft merge request !768.

There is not yet an Agents.md file in this repo, so I did a little bit of hand holding in terms of commit message styling, and also making sure that it ran the appropriate tests and linting checks before submission. There was also a dead part of the API that it implemented, but always returned 0s, so I got it to remove it!

And there was something useful to try in the terminal. For example, a graph of hits for the Toolviews tool itself:

mw tools toolviews toolviews --output graph

Or a table of the previous day’s tool views, now one of the examples in the command help:

mw tools views --date "$(date -d yesterday +%F)" --output table | head -n 11

There are also JSON and CSV outputs too, as these all “come for free” as part of the rest of the CLI setup that I have been “refining” here for years.

This was a useful first test of the setup: get a development environment ready, work on a feature, and get the result back into GitLab as a branch and merge request. And I’ll probably end up reviewing and merging the feature for the next release today!

More to try

There is quite a bit more to boxd than I used here. Network restrictions, automatic sleeping, snapshots, machine forks and checkpoints all look interesting for development environments. Being able to save a working setup before trying something is particularly appealing when the next step is handing an agent a fairly loose brief.

I haven’t worked out an exact bill for this experiment, but I expect it to have cost pennies, as long as I remember to turn the VM off after writing this post. More importantly for me, I’ll keep trying this setup for this sort of one off easy implementation. And it’s really nice to not be tied too much into weird odd complex infrastructure (such as via devin.ai which I tried previously too).

In a work context, I’m also looking forward to exploring USB proxying through to the VM for a Raspberry Pi sitting locally, proxying COM port for development on local ESPs etc. I haven’t tried that yet, but have been working on some easy open source tooling for it.

And next time, perhaps I’ll just SSH in and use Codex in the console, rather than bringing it into the app :D That alone removes a few steps and complexity here!

I came to Kochi to learn from the Wikimedia community. I left with new perspectives, meaningful connections, and a deeper understanding of how communities help us grow -not only as contributors, but also as people.

In September 2026, I travelled to Kochi, Kerala, for my first WikiConference India (WCI). As a Wikimedian from Vidisha, Madhya Pradesh, I was excited to meet contributors from across India, discover projects beyond my experience, and learn how different communities contribute to free knowledge.

I returned with more than new perspectives and connections. I had shared Wiki Club SATI’s journey on a national stage, spoken about my personal growth, and discovered how much a community can help us grow-not only as contributors, but also as people.

A beginning filled with people and possibilities

The conference began with the opening ceremony and a celebration of Wikipedia’s 25th anniversary. Being part of the cake-cutting celebration was a memorable way to mark a milestone in the history of a project that connects millions of people with free knowledge.

Interactive games, laughter, and conversations with Wikimedians from different regions made the experience even more welcoming. People I had previously known through online projects and discussions became familiar faces, and new connections began through simple introductions.

I quickly realised that a conference is about more than its scheduled sessions. It is also about the people who welcome newcomers, the conversations that happen between activities, and the shared experiences that bring a diverse movement closer together.

Bringing Wiki Club SATI’s journey to the national stage

One of the highlights of my first WCI was presenting the lightning talk “Want to Start a Wiki Club: Learn from Our Journey” alongside Uday Dongre.

We represented Wiki Club SATI, a student-led Wikimedia community at Samrat Ashoka Technological Institute in Vidisha, Madhya Pradesh.

Our journey began with five founding members and grew into a community with more than 140 members on Meta-Wiki. This growth came through consistent efforts to welcome newcomers, encourage peer learning, and create opportunities for students to participate in Wikimedia.

Our activities have included edit-a-thons, workshops, Wikimedia Commons training, documentation sessions, and community initiatives that bring students together through different interests.

During our talk, we shared lessons about onboarding, community engagement, and helping members find meaningful ways to contribute.

Presenting at WCI gave us an opportunity to share our experiences with people interested in starting Wiki Clubs of their own. It also made me reflect on the difference between starting a community and sustaining one.

A community needs more than enthusiastic founders. It needs an environment where newcomers feel welcome, members discover opportunities to participate, and people gradually gain the confidence to take ownership.

A community grows stronger when its members become confident enough to create opportunities for others.

For me, representing Wiki Club SATI was an opportunity to celebrate the collective effort behind our journey and share what we had learned along the way.

When a campus idea becomes a conversation across the movement

Another highlight was presenting “Open Mic Series: Celebrating Creativity Beyond Wikimedia” alongside Shreya Dwivedi, Suyash Dwivedi, and Uday Dongre.

The initiative grew from Wiki Club SATI’s efforts to create spaces where students could connect through creativity beyond Wikimedia editing and technical work.

Open Mic makes room for music, poetry, storytelling, comedy, dance, and other forms of expression. These activities may seem different from building an encyclopedia, but they can help people connect, discover shared interests, and feel part of a community.

Presenting the initiative at WCI allowed us to share a campus experience with a wider Wikimedia audience. It also encouraged me to think about how communities can welcome people with different talents, interests, and ways of participating.

Not every community interaction needs to begin with an edit. Sometimes, the first step is simply finding a space where people feel comfortable being themselves.

Seeing an initiative that began within Wiki Club SATI become part of a national conference reminded me that local ideas can inspire conversations across the wider movement.

Finding my voice: From being an introvert to opening up

Some of the most meaningful moments of WCI 2026 were not about presentations or technical sessions. They were about reflecting on the person I have become.

During WikiWomen’s Lunch, I shared a personal part of my journey: how I gradually moved from being an introvert to opening up, expressing myself, and connecting more comfortably with people.

For me, this change has meant learning to step outside my comfort zone, initiate conversations, share my thoughts, and approach unfamiliar situations with greater confidence.

Being part of the Wikimedia community has given me opportunities to practise these skills. Through community activities, event organisation, public speaking, and collaboration, I have gradually become more comfortable meeting people and taking on new responsibilities.

Each opportunity brought its own challenge. Sometimes it meant speaking up; sometimes it meant introducing myself to someone new; and sometimes it meant trusting that my experiences and ideas were worth sharing.

At WikiWomen’s Lunch, sharing this journey helped me recognise how much these small steps had contributed to my growth. Listening to others also reminded me that everyone has a different story and that personal growth often happens through experiences we may not recognise as significant at first.

I still have more to learn, but I now approach opportunities differently from how I once did.

One of the most valuable things the Wikimedia community has given me is not just a place to contribute, but also the confidence to find my voice.

Learning beyond my own experience

WCI 2026 broadened my understanding of the Wikimedia ecosystem through discussions about artificial intelligence and open knowledge, emerging technologies, Wikimedia tools, readership data, gamification, and cross-community collaboration.

During “Unfiltered Conversations: Women in Wikimedia (Over Coffee),” I had another opportunity to reflect on my journey, from contributing to Wikimedia projects to exploring technical writing, documentation, open-source development, public speaking, and community leadership.

Listening to others helped me appreciate that there is no single path to becoming an active Wikimedian. People enter the movement with different interests and develop their skills in different directions. A supportive community helps make those possibilities visible.

Another particularly relevant session was “Bridging the Gap Between Editors and Developers.” As someone exploring MediaWiki and technical contributions, I was interested in how the needs of editors and the work of developers can come together more effectively.

The discussion reinforced an important lesson: editors understand the challenges they encounter while using Wikimedia projects, while developers can help address those challenges through tools and technical improvements. Meaningful progress depends on creating opportunities for these perspectives to meet.

I returned with new questions to explore, ideas to bring back to Wiki Club SATI, and a stronger appreciation for the different forms of contribution that support free knowledge.

The people behind the movement

Perhaps the most valuable part of my first WCI experience was connecting with Wikimedians from different communities.

Conversations introduced me to different experiences of volunteering, community leadership, technical development, and long-term participation in Wikimedia. Meeting people in person made the movement feel larger and more connected than it can appear through online projects alone.

Every contributor brings a different perspective. Some focus on technical tools, others on content, languages, outreach, research, documentation, or organising activities that help newcomers participate.

These conversations reminded me that the Wikimedia movement is sustained by people who bring different skills and experiences to a shared purpose.

I also developed a greater appreciation for the work behind the scenes. Conferences depend on organisers, volunteers, speakers, and facilitators whose efforts make it possible for people to gather, learn, and collaborate.

On the final day, I attended the conversation with the Wikimedia Foundation Board of Trustees, along with sessions on collaboration across languages and bridging the gap between editors and developers. These discussions gave me further opportunities to reflect on how the movement can continue learning and working together.

From participating to taking responsibility

One of the most memorable moments of WCI 2026 was delivering the Vote of Thanks.

After spending the preceding days listening, learning, meeting people, and presenting, standing on stage to express gratitude to the organisers, speakers, volunteers, and everyone who contributed to the conference felt particularly meaningful.

It was an opportunity to recognise the collective effort behind a successful event. Every conference depends on people who share their time, knowledge, energy, and support, often without being in the spotlight.

The moment also made me reflect on how my own participation had evolved. I arrived hoping to learn from others. By the end, I had shared my community’s journey, presented an initiative, spoken about my experiences, and expressed gratitude on stage.

Each experience taught me something different about contribution.

We can participate by attending sessions, asking questions, sharing knowledge, organising activities, supporting others, or taking responsibility when opportunities arise. These roles are different, but each can strengthen a community.

For me, WCI 2026 brought these different aspects of participation together.

What I brought back from Kochi

Three lessons from my first WikiConference India will stay with me.

Communities grow when people are empowered to participate. Welcoming newcomers matters, but so does giving them opportunities to learn, contribute, and eventually help others.

Local initiatives can inspire wider change. Experiences from a student community in Vidisha can offer useful lessons elsewhere when we share what we have tried and learned.

Personal growth is part of community growth. The opportunities we receive through Wikimedia can help us develop skills, build confidence, form meaningful connections, and discover abilities we might not have recognised in ourselves.

These lessons will continue to shape my work with Wiki Club SATI and my contributions to the Wikimedia movement.

And then there was Kochi itself: the atmosphere, the conversations that continued beyond the conference programme, and the final dinner on a cruise. These moments gave us time to pause, laugh, and celebrate the people behind the movement.

They were a fitting end to three days of learning, sharing, and connection.

The journey continues

My first WikiConference India helped me see the Wikimedia movement from a wider perspective. I learned from other communities, shared Wiki Club SATI’s experiences, and reflected on how far I have come personally.

I returned to Vidisha with ideas to bring back to Wiki Club SATI, new connections to nurture, and renewed motivation to contribute. I am grateful to everyone who made WCI 2026 possible and to those who made my first conference such a welcoming experience.

The conference has ended, but its lessons continue beyond Kochi. I hope to use what I learned to strengthen my community, explore new opportunities, and keep contributing to free knowledge.

I came to Kochi to learn from the Wikimedia community. I left with a deeper understanding of how I can help build it and how being part of it continues to help me grow.

Learn more about WikiConference India 2026.

On Saturday, 24 October 2026, the Dagbani Wikimedians User Group celebrated Wikidata’s birthday in Tamale with a learning session, an editing activity, and a cake-cutting session.

The celebration brought together participants to learn more about Wikidata and how they can contribute to the free knowledge movement. The program focused on the basics of creating Wikidata items and adding statements, allowing participants to understand how information is organized and represented on the platform.

Learning the Basics of Wikidata

The training session was led by Alhaj Darajaati, who introduced participants to the process of creating Wikidata items. Participants learned about the importance of items and how they represent people, places, organizations, and other subjects in the world.

The session also covered how to add statements to Wikidata items. Statements help describe an item by providing information about its properties and values. This is an important part of contributing to Wikidata because it allows information to be structured and connected with other knowledge in the database.

Participants were also introduced to how to add references to Wikidata statements and the importance of references.

Through the practical session, participants had the opportunity to become familiar with these basic editing processes and understand how their contributions can help improve the information available on Wikidata.

An Editing Session

Following the introductory session, Achiri Bitamsimli led participants in an editing activity to put their knowledge into practice. The session gave participants a chance to explore the platform and apply the skills introduced during the training.

Activities like this help contributors build confidence in editing Wikimedia projects. They also encourage participants to continue learning and contributing to the growth of free and open knowledge.

Celebrating Wikidata

The program ended with a cake-cutting session led by Ruky Wunpini to mark Wikidata’s 14th birthday. It was a simple way to celebrate the platform and recognize its role in making structured knowledge freely accessible to people around the world.

For the Dagbani Wikimedians User Group, the celebration was also an opportunity to bring learning and community participation together. By introducing participants to Wikidata item creation and statements, the group continued its efforts to encourage more people to contribute to Wikimedia projects.

Wikidata plays an important role in connecting information across languages and making knowledge more accessible. Continued participation by local communities can help improve the availability and representation of information about their people, places, culture, and heritage.

As the celebration came to an end, the message remained clear: everyone has a role to play in building and improving free knowledge.

Through ongoing workshops and community engagement, the Dagbani Wikimedians User Group continues to empower local contributors and expand digital knowledge representation. Looking ahead, the group aims to further preserve indigenous heritage and bridge the digital gap by making open knowledge accessible across all Wikimedia projects.

Happy Birthday, Wikidata!

On 9 August 2026, I was the lead trainer in a training programme (WikiLatih) held in collaboration between Wikimedia Indonesia and the English Club Project, held at the Kopi Godog cafe in South Jakarrta. The collaboration was to introduce the Wikipedia project, its sister project, as well as the greater Wikimedia ecosystem as a hub of self development and building new connections. Unlike usual WikiLatihs organized by the chapter, the training program is held using English as an instruction language, with Indonesian being the fallback language to describe local context and technical stuff that would be better off explained in Indonesian.

The program was directed by Naveesha Mazaya Prayoga as the Wikimedia Indonesia’s person-in-charge for the program and C. Cecilia was English Club Project’s lead for the program, with assistance from other English Club Project members: Saphira and Naila. Aside from me as the lead trainer, there were two facilitators, Naufaldi Anindya and Jeanne Charlene, who provided hands-on assistance to the WikiLatih participants should they encounter deadlocks during the practical session or questions that require a more personalized answer.

A technical coordination meeting took place five days prior to the WikiLatih to align event flows, setup registration links, and anticipate common technical hurdles. One frequent obstacle when hosting workshops in shared venues or public Wi-Fi environments is the triggering of automated open proxy blocks or IP restriction limits on Wikipedia during mass account creation. To ensure every participant could register smoothly without getting blocked by anti-abuse measures, account requests were managed ahead of time using the Account Creation Improvement Tool (ACC) alongside granting IP Block Exempt permissions where necessary. Participants were encouraged to create anonymous accounts prior to the event to protect their privacy while contributing.

Aside from the usual materials on Wikipedia and its sister projects, such as intro to the Wikimedia movement and governance, policy and community norms, editing and writing articles, and personalizing their userpage, I also introduced some out-of-the box materials to entice the WikiLatih participants to actively engage in discussions by presenting vandalism in the Indonesian Wikipedia. Though being presented as a humorous material due to the funny changes it caused to the article, it also acts as a lesson learned to warn the participants from jeopardizing the integrity of existing articles, given the effects are as demonstrated. 

Link to the presentation (Google slides)

Other supplementary material introduced during the training program was opportunities one can get from contributing to Wikipedia and other projects. Conferences, regular meetings, valuable connections with experienced and seasoned Wikimedia volunteers and staffs, are just a few of the many benefits one can get from regular contributions to Wikimedia projects and communities. 

My strategies in presenting these custom-tailored materials for the ECP were successful, and participants were in general attentive of the presentation, as well as actively providing response and lodging inquiries should there be anything of interest or unclear in the presentation, to either me and the facilitators.

By the close of the session at 4:00 PM WIB, participants had successfully created their accounts, customized their user profile pages, and published their first contributions to Wikipedia. Participants generally give back positive feedback, a strong enthusiasm for continuing their journey in contributing to Wikimedia projects, as well as gratitude for “inspiring them to write” and making wiki editing accessible and fun. By empowering youth communities with open web editing skills, partnerships like the Wikimedia Indonesia x English Club Project Wiki training project help diversify online perspectives and build a sustainable community of lifelong contributors to free knowledge.

The Wikimedia Jakarta Community has just initiated a new and unique concrete step in preserving culture through the Betawi language Wiktionary, in the form of a collaboration to produce Betawi-language content with a well-known national private radio station, Bens Radio 106.2 FM.

Initial idea

It started from how often we listened to the radio station founded by the legendary Betawi cultural icon, H. Benyamin Sueb, while driving. The radio station, which has a loyal listenership of 1.5 million people in the Jabodetabek area, is characteristically known for always highlighting the Betawi language and culture in its various broadcast programs and activities. It crossed our minds that it would be a perfect fit if the Wikimedia Jakarta Community could collaborate with the station. A hope sparked: What if the rich vocabulary of the Betawi language that frequently fills the airwaves does not just ‘pass by’ on air, but is also permanently documented in the digital world? This led to the idea for the WikiUmrup project, which aims to collaborate. The word “umrup” itself in the Betawi language means radio, absorbed from the Dutch word “omroep” which means broadcast or broadcasting.

Exploring on-air and digital collaboration

From a wishful thinking, we finally tried to make it a reality. The first step was visiting the radio station’s office in May 2025 to introduce ourselves. We introduced the Wikimedia Jakarta Community and its activities, and inquired whether there was an opportunity to collaborate. Luckily, Bens Radio welcomed our plan warmly because they already have a program called “Kamus Betawi“ (Betawi Dictionary), an educational program showcasing Betawi language lemmas and examples of their usage. This was a perfect match for our community’s interest. Ultimately, that initial introduction provided a hope that our concrete step to contribute to preserving the regional language of Jakarta, the Betawi language, had the potential to be realized. With support from Wikimedia Indonesia (WMID), an agreement was finally reached between both parties, and the memorandum of understanding (MoU) between the Wikimedia Jakarta Community and Bens Radio 106.2 FM was officially signed.

Recording and documentation

The next step was technical discussions regarding the material and licensing. To ensure the recorded material strictly follows the rules of the Betawi language, the content was prepared by Bang Rapip, one of the volunteers and a native Betawi speaker in the Wikimedia Jakarta Community.

Under the professional direction of the Head of Bens Radio, Bang Kevin, and the announcer as well as our contact person, Mpok Bunga, the first recording session began this October 2026! The long-awaited moment arrived when we recorded our voices in the studio, serving as proof of our concrete action to play a role in preserving a regional language so it does not go extinct. The recordings will be provided with background music by the producer and edited according to the planned duration standards. Further recordings are planned to take place several more times over the next few months. Not stopping at the on-air broadcasts, we will also preserve the results of this collaboration in the digital realm. Later, all vocabularies and phrases from this “Kamus Betawi” will be documented structurally in our “WikiKamus” (Wiktionary) so that their definitions can be read by anyone. The voice recordings contributed by the volunteers will also be uploaded to Wikimedia Commons, allowing the native pronunciation of Betawi language lemmas and examples of their use in everyday conversation to be heard by the global community freely and permanently.

Conclusion and partnership hopes

In today’s modern era, thousands of regional languages around the world face major challenges, and even the threat of extinction, due to being eroded by global languages and modernization. As a dynamic capital city, Jakarta is not immune to this phenomenon. The Betawi language, as one of the regional languages of the city’s native inhabitants, is increasingly shifting away from the daily lives of its speakers. Because of this, digital documentation is no longer just an option, but the last bastion of defense to ensure that oral heritage is not lost to time. From this collaborative journey, there is one important lesson that can be shared with Wikimedia communities in various parts of the world: Preserving and protecting a mother tongue does not always have to be done alone within the internal circles of our movement. Cross-sector partnerships that connect the open knowledge volunteer movement with broadcasting media like radio and other platforms can be a highly effective strategy. This creative step serves as an efficient alternative to directly reach native speakers, enrich Wikimedia platforms, and at the same time, bring free knowledge closer to the wider public who might not yet be familiar with the “Wiki World.”

MUDCon Fall 2026 Program announced

October 9, 2026

The program for MediaWiki Users and Developers Conference (MUDCon) Fall 2026 in Ljubljana, Slovenia (November 11–13, 2026) has now been announced.

It is compiled from more than 30 contributions, ranging from structured data and cultural heritage to AI and the development of MediaWiki. The keynotes will be held on November 11 by Marko Robnik-Šikonja of the University of Ljubljana, Faculty of Computer and Information Science, on AI in transition from LLMs to agents, and on November 12 by Simon Colnar of the University of Ljubljana, School of Economics and Business, on knowledge management as the foundation of economy and society. See all the details in the program.

To attend in person at the Jožef Stefan Institute, please buy a ticket on Luma. Places are limited to 120 participants. The conference will also be streamed live on YouTube, where no ticket is needed.

The conference is organised by the MediaWiki Stakeholders' Group, the ECHOLOT project and the Jožef Stefan Institute. It is kindly supported by gesinn.it, KM-A, MyWikis Europe, Professional Wiki, ArchiXL and Wikibase Solutions.

MUDCon Fall 2026 Program announced

October 9, 2026

The program for MediaWiki Users and Developers Conference (MUDCon) Fall 2026 in Ljubljana, Slovenia (November 11–13, 2026) has now been announced.

It is compiled from more than 30 contributions, ranging from structured data and cultural heritage to AI and the development of MediaWiki. The keynotes will be held on November 11 by Marko Robnik-Šikonja of the University of Ljubljana, Faculty of Computer and Information Science, on AI in transition from LLMs to agents, and on November 12 by Simon Colnar of the University of Ljubljana, School of Economics and Business, on knowledge management as the foundation of economy and society. See all the details in the program.

To attend in person at the Jožef Stefan Institute, please buy a ticket on Luma. Places are limited to 120 participants. The conference will also be streamed live on YouTube, where no ticket is needed.

The conference is organised by the MediaWiki Stakeholders' Group, the ECHOLOT project and the Jožef Stefan Institute. It is kindly supported by gesinn.it, KM-A, MyWikis Europe, Professional Wiki, ArchiXL and Wikibase Solutions.

From technical skills and new leadership structures to institutional partnerships and Wikipedia milestones, the Language Diversity Hub Mentorship Programme is showing what sustained, community-centred support can make possible.

What does it take to build a thriving Wikimedia language community?

Creating articles is part of the answer. But communities also need technical skills, supportive leadership, institutional partnerships, funding opportunities, and the confidence to keep going when challenges arise.

These needs are at the heart of the Language Diversity Hub (LDH) Mentorship Programme, which supports language communities at different stages of developing and sustaining their Wikimedia projects.

The programme’s August 2026 report captures the progress of 13 language communities across Africa, Asia, and the Americas. After the first six months of the 12-month programme cycle, the results demonstrated the value of combining personalised mentorship with practical training, micro-grants, and opportunities for communities to learn from one another.

What has changed so far?

The programme has recorded encouraging progress across content creation, editor participation, technical capacity, and community governance.

By the midpoint, participating communities had:

• Trained and onboarded more than 1,500 new editors.
• Created more than 4,000 new articles.
• Added more than 2,500 Wikidata items and lexemes.
• Uploaded more than 700 media files to Wikimedia Commons.
• Established six institutional partnerships.
• Secured more than US$4,000 in micro-grants.
• Appointed five new administrators and strengthened community leadership structures.

Five communities had graduated, with another awaiting Language Committee approval at the time of reporting. The programme had also supported the development of community guidelines, leadership teams, technical workflows, and new approaches to outreach and volunteer retention.

These numbers matter because they represent more than an increase in Wikimedia content. They reflect growing capacity within communities to organise, contribute, and take greater ownership of their language projects.

Five stories that show what mentorship can make possible

1. Runyankore: From the Incubator to Language Committee approval

One of the programme’s significant milestones was Runyankore Wikipedia receiving Language Committee approval in July 2026.

During the reporting period, its article count grew from 621 to 1,174, while active editors increased from 54 to more than 134.

A micro-grant supported a university partnership with Mbarara University of Science and Technology (MUST). The initiative engaged 41 participants, including 24 new editors, who created 96 articles and uploaded 214 photographs.

The community also established a Core Organising Team and developed community guidelines.

The lesson: Small grants can unlock substantial opportunities when they support community-led activities, institutional relationships, and long-term leadership.

2. Fante: Building technical skills and shared leadership

The Fante community made progress in both content development and technical capacity, including translating Wikidata properties from English into Fante.

Its article count increased from 1,593 to 1,800, while active editors grew from two to five. The community also formalised leadership roles and established partnerships with the University of Education, Winneba, and Radio Windy Bay 98.3 FM.

These developments help create a foundation for continued outreach and more distributed responsibility within the community.

The lesson: Technical training has greater long-term value when it is accompanied by leadership development and relationships beyond Wikimedia.

3. Nupe: Connecting Wikimedia participation with organisational development

The Nupe community achieved legal registration in Nigeria during the reporting period. Its active editor count grew from approximately 12–13 to 29–31, while its article count increased from more than 500 to 930.

The community also developed partnerships with other organisations and began pursuing Wikimedia affiliate recognition through the Affiliations Committee (AffCom).

This progress illustrates how a language community’s development can extend beyond editing to organisational capacity, external partnerships, and formal recognition.

The lesson: Communities need support not only to establish a Wikimedia presence, but also to develop the structures that help sustain their work.

4. Tibetan: Reviving a dormant project

After a period of inactivity dating back to 2019, Tibetan Wikipedia began experiencing renewed activity. The report recorded an average of approximately 44 active editors per month and 1,065 new articles since January 2026.

The community also completed a Rapid Grant project reaching approximately 300 editors across seven venues, appointed four administrators, and expanded its Wikidata work.

Alongside Wikipedia contributions, the community proofread more than 700 Wikisource pages, demonstrating how mentorship can support work across multiple Wikimedia projects.

The lesson: With dedicated support, technical capacity building, and community engagement, even a dormant project can begin to regain momentum.

5. Maya Yucatec: Connecting language revitalisation with education

The Maya Yucatec community strengthened its relationship with the Yucatán Indigenous Education system. The report records 101 teachers trained and 25 active editors, alongside a government partnership extending through 2030.

The community is exploring ways to connect Wikimedia contributions with educational practice, while working to address infrastructure and localisation barriers.

The lesson: Partnerships with educational institutions can provide a pathway for integrating Wikimedia into wider language learning and revitalisation efforts.

What makes the mentorship model work?

The programme’s findings point to several practices that communities and movement organisations can build on.

• Personalised, practical support matters. Community members valued having someone they could approach with questions and receive guidance tailored to their needs. As one participant, Tsewang Jamling from the Tibetan community, explained: “We were stressed out about the technical stuff in Wikidata but it’s now an easy subject for us.”
• Technical capacity remains essential. Templates, infoboxes, Wikidata, interface localisation, and mobile editing workflows are among the areas where communities need continued support. Training helps contributors move from wanting to participate to having the practical skills to do so.
• Leadership should be shared. Community organising teams, guidelines, and clearer responsibilities can help distribute work and reduce the risk of volunteer burnout.
• Peer learning creates opportunities for exchange. Communities working in different languages and contexts can share approaches, troubleshoot problems, and learn from one another rather than having to solve every challenge independently.
• Support should not end at graduation. Moving from the Incubator to an approved Wikipedia is a major achievement, but it also brings new responsibilities. Communities need opportunities to maintain momentum, develop partnerships, strengthen governance, and continue learning after graduation.

The challenges ahead

This report also highlights persistent barriers: limited funding, connectivity and device constraints, technical skills gaps, volunteer retention, leadership burnout, and difficulties with language identity and naming recognition.

For some communities, interface localisation remains a significant obstacle to participation. Others need additional support with administrative skills, institutional relationships, and the practicalities of editing from mobile devices.

The communities’ recommendations for the next phase are clear: continue micro-grant support, increase technical training, facilitate more peer-learning opportunities, improve access to French and English interpretation, and provide sustained support beyond mentorship.

These priorities are not simply requests for more activities. They point to the conditions communities need to become more resilient and self-sustaining.

Looking towards the next phase

The LDH Mentorship Programme will continue working with participating communities, with a focus on graduation readiness for Incubator projects, sustainability for communities that have already received approval, and stronger peer-learning opportunities.

These results offer an important reminder for the Wikimedia movement: language diversity requires more than the availability of an editing platform. It requires investment in the people, relationships, skills, and community structures that make participation possible.

When language communities receive support shaped around their actual needs, they can create content, develop technical expertise, strengthen leadership, build partnerships, and determine their own priorities for the future.

The next milestone is not just how much more content these communities create. It is how well equipped they are to continue building their Wikimedia projects on their own terms.

This article is based on the Language Diversity Hub Mentorship Programme: 2025–2026 Midpoint Report, prepared in August 2026.

Photos

References

1. Runyankore Community Diff post: https://diff.wikimedia.org/2026/07/19/from-incubator-to-approval-how-mentorship-helped-the-runyankore-wikipedia-community-grow/
2. Maayat‘aan Community Diff Post: https://diff.wikimedia.org/es/2026/07/24/wikipedia-ich-maayataan-la-wikipedia-en-maya-para-el-mundo/
3. Nahuat Community Diff Post: https://diff.wikimedia.org/es/2026/07/30/de-la-incubadora-a-la-autonomia-como-la-mentoria-y-el-liderazgo-comunitario-estan-construyendo-el-futuro-de-los-proyectos-wikimedia-en-nahuat/
4. Fulfulde Community Diff Post: https://diff.wikimedia.org/2026/07/27/six-months-of-growth-how-the-language-and-diversity-hub-mentorship-is-strengthening-the-fulfulde-wikimedia-community/
5. Kinyarwanda Diff Post: https://diff.wikimedia.org/2026/08/20/strengthening-kinyarwanda-through-mentorship-community/
6. Tibetan community report: https://docs.google.com/document/d/15ErtovShrlRixBARpjp7yZl60Ha3UY6H8HvYo9bvcFc/edit?usp=sharing
7. https://meta.wikimedia.org/wiki/Wikimedia_Language_Diversity_Hub/Mentorship_Programme:_2025%E2%80%932026_Report

Wikipedia’s neutral point of view (NPOV) is one of its founding principles, and editors enforce it in part with maintenance templates, the {{POV}} banner and its relatives that flag an article (or a section) as disputed. A natural question follows: could a tool watch articles and catch one sliding away from neutrality before an editor has to flag it? That was the premise we set out to test. The answer turned out to be more interesting than a yes or no.

Most of the work was getting the ground truth right. Dating an NPOV dispute is harder than it looks:

• Bots backdate templates. About 26% of dated maintenance templates were last touched by a bot stamping them with a month. If you date the dispute by the template alone, you’re measuring the bot’s run, not when a human actually raised the concern.
• Edit summaries miss half the story. Searching edit summaries for tag additions recovers only about 53% of the human edits that really added a template.
• Controls can be dormant. If you compare a tagged article to a “similar” article matched only on lifetime totals, the comparison article is often inactive in the exact window your detector looks at, which quietly flatters the results.

So we built NPOV-Onset: roughly 2,000 English NPOV-dispute events, each pinned by binary search over the page history to the exact revision that introduced the tag, and each paired with a never-tagged article matched on topic and on edit activity, so the comparison is honest. Everything comes from public revisions collected read-only through the MediaWiki Action API, the code never logs in and never edits.

The dataset is openly released (CC BY-SA 4.0), with a full datasheet documenting every field and limitation.

The surprise: flagged articles don’t drift, they start different

We then tested one signal at a time against this benchmark, always asking the same thing: does the signal rise in the year before the tag?

It doesn’t. An article that later receives an NPOV tag already reads as more subjective than its matched, never-tagged twin a full year before any human flags it and that gap stays flat right up to the tag. We checked a second, independent notion of bias too: not tone, but one-sidedness (whether an article gives due weight to the relevant viewpoints, judged while explicitly ignoring how the prose sounds). Same result, a standing gap, no drift toward the tag.

In other words, the textual signs of a neutrality problem look like a static property of dispute-prone articles, not a warning sign that develops over time. What actually changes around the time of a dispute is editor activity, not the prose.

The one thing that does drift, and it’s shallow

There is a single real exception, and naming it precisely matters. When we trained a detector on this task rather than borrowing one, a small pre-onset drift did appear and survived every check we could throw at it. But a plain bag-of-words model reproduced the same drift, and giving a larger neural model more data made its drift vanish while the word-level signal held. So the one genuine pre-onset change is lexical: dispute-era vocabulary slowly accumulating, not a drift in the article’s deeper meaning.

Why this matters for the movement

The honest framing changes what a tool like this is for. It is not a real-time drift alarm, and it should not be one. It is a triage aid: because the signal is static and already present a year ahead, ranking articles by it concentrates the ones that will later be tagged at roughly 4–5× the base rate at the top of the list. That’s a way to help maintenance work focus attention earlier, a prioritisation hint for editors, not an automated judge of neutrality.

Two principles guided the work and should guide any use of it:

• It supports editors; it doesn’t replace their judgment. The label here is “an editor flagged this,” a human signal, not a machine’s verdict on what is neutral.
• It respects editors’ privacy. The data describes articles and public revisions; it is not a tool for profiling the people who edit them, and we ask that it not be used that way.

Try it, and build on it

• Dataset (browsable): huggingface.co/datasets/MahimaSinghal/npov-onset
• Citable archive (DOI): zenodo.org/records/23633608
• Code + datasheet: github.com/mahi01agarwal/npov-drift-detector
• Tracking task: phabricator.wikimedia.org/T428896

The measurement lessons: bot backdating, edit-summary recall, dormant controls, apply to any study that uses maintenance templates as ground truth, so we hope the dataset is useful well beyond this one question. If you work on NPOV, content integrity, or Wikipedia research and want to extend it (other templates, other language editions), we’d love to collaborate.

This work is independent research, led by Mahima Agarwal and Dev, connected to the Wikimedia Research community. The dataset is derived from English Wikipedia and shared under CC BY-SA 4.0.

I read an article by Professor Danah Boyd about recently released discovery materials indicating that Meta directly targeted Jonathan Haidt by trying to stir up academics to oppose him. Read the article and honestly Meta deserves all the bad press that it royally deserves.

Professor Boyd was particularly upset for the targeting of Professor Candice L. Odgers so much so that she used "wtaf", an acronym I did not know.

So what to do. Given that Scholia is more or less functional, I did the Wikidata thing; I added a few awards, several recent publications and attributed known publications to the people involved. When you consider the sum of all knowledge, it is what AI systems including the one by Meta use for their training material, it introduces a dilemma. Will it include info in its systems critical of its operations and objectives? If not why trust its systems as a neutral source of intelligence?

Thanks,

       GerardM

Are you passionate about minority communities, languages, cultures, cultural heritage, religious minorities, disability communities, and other underrepresented voices across Wikimedia projects?

Wiki for Minorities (WfMin) is pleased to announce the opening of applications for Cohort 1 of the WfMin Mentorship Program. The program is designed to support Wikimedia contributors and community members who are working to strengthen the visibility and representation of minority and minoritized languages, people with disabilities, religious minorities, cultural communities, and other underrepresented groups across Wikimedia projects,

You can apply as either a Mentor or Mentee:

🔹 Mentors: Share your knowledge, experience, and skills with emerging contributors.

🔹 Mentees: Learn from experienced Wikimedians, develop new skills, and receive guidance for your Wikimedia journey.

Application Period: 25th October 2026 – 5th November 2026.

📝 Apply here (Google Form)

We look forward to welcoming passionate contributors from across the Wikimedia movement and building a stronger network for minority communities together.

Come learn. Come share. Come contribute. Let’s make minority voices more visible through free knowledge.🌍

October 30, 2026. The Wikimedia Foundation, the nonprofit that hosts Wikipedia and other open knowledge projects, today filed an amicus brief — or friend of the court opinion — with the Southern District Court of New York in In re: OpenAI, Inc. Copyright Infringement Litigation (12 combined lawsuits against OpenAI, the most well-known of them being The New York Times Co. v Microsoft and OpenAI) urging the court to protect the open knowledge ecosystem in its decision. In the key case, the court will rule on whether the use of copyrighted content by artificial intelligence (AI) companies to develop large language models (LLMs) constitutes fair use. 

Because of the significance of the jurisdiction and the parties involved, and because only a few cases have addressed this issue already, the ruling here will be highly influential as more courts grapple with interpreting the law in light of new technological uses. “We are taking a position in this case to defend the free and open human knowledge that Wikipedia depends on. Expanding access to knowledge through AI is a powerful goal, but it must respect the people, contributors, and communities that make reliable knowledge possible. Finding this balance is both a mutual benefit and a shared responsibility for the entire information ecosystem,” said CEO Bernadette Meehan. 

The lawsuit, originally filed by The New York Times in 2023, alleges that OpenAI and Microsoft’s use of The New York Times owned content for any purpose — including AI model training — is a direct violation of copyright law. On the other hand, OpenAI and Microsoft assert that training and deploying models based on publicly available data constitutes technological development, and falls within the definition of fair use. Wikimedia Foundation’s amicus brief argues that a ruling for a too restrictive version of fair use could inhibit technological innovation, which would limit the availability of tools that benefit open source projects like Wikipedia; while a ruling in favor of blanket fair use could lead to a more closed web where knowledge online is weakened due to a lack of available secondary source materials.

The Wikimedia Foundation’s court filing offers an alternative position that applies fair use to two specific cases: model training, and retrieval-augmented generation (RAG) and newer techniques that serve a similar “grounding” purpose. For model training, the Wikimedia Foundation argues that using copyrighted content should be considered fair if it is being used for training LLMs that are something new and different from the original sources. In this case, there would not be a requirement to meet any copyright licensing terms. 

RAG is a process that finds and copies news content or other works of human knowledge from the web and then delivers that same content back to users through a chatbot interface. It’s one of several techniques to help ground the answers of a chatbot in reality using the most current sources from the internet. For RAG and newer techniques that serve a similar “grounding” purpose, the Wikimedia Foundation argues that the use of copyrighted works should not be considered fair, and companies offering this feature should respect each content platform or publisher’s licensing requirements to avoid copyright infringement. In Wikipedia’s case that license is Creative Commons CC BY-SA 4.0, which requires credit to be given to the original creators of the work and that any remix or adaptations remain under the same CC license.

Wikipedia is one of the most popular and trusted open knowledge websites in the world, with more than 67 million articles across 300 languages. Every month, nearly 250,000 volunteers contribute their time to create and improve information on Wikipedia, using reliable sources, such as well-researched news articles. It is one of the highest-quality datasets used to train LLMs and the backbone of information on the internet, powering AI chatbots, search engines, and voice assistants. 

“Any conversation around fair use and copyright in the age of AI cannot be limited to for-profit organizations: it must include stakeholders across the entire online information ecosystem,” the Wikimedia Foundation’s General Counsel Stephen LaPorte notes. 

“A ruling that does not apply fair use principles carefully could threaten the sustainability of free knowledge, and stifle the development of open source technologies, ultimately impacting access to information for everyone in both cases. The court needs to understand that Wikipedia is created through a collaborative process that requires a strong foundation of open and accessible human knowledge to thrive.”

We will continue advocating for a copyright position that strikes a fair balance. One that takes into consideration the importance of protecting the fair use of copyrighted content to develop open source technologies in the public interest, along with the sustainability of the sources and humans who create that content. 

For the Wikimedia projects that means ensuring that uncredited use of the content we host is limited to model training, and that any use of the content for RAG and newer techniques that serve a similar “grounding” purpose must result in proper attribution under our Creative Commons CC BY-SA 4.0 license. As importantly, regardless of the use case, scraping of our projects must be done sustainably and in line with our public API rate limits or through our Enterprise API offerings. 

Learn more details about our amicus brief on our blog post here. 

About the Wikimedia Foundation 

The Wikimedia Foundation is the nonprofit that operates Wikipedia and other Wikimedia projects. We support the people, technology, and policies that enable reliable information to be shared with the world. The Wikimedia Foundation is a United States 501(c)(3) tax-exempt organization with offices in San Francisco, California, USA.

The post The Wikimedia Foundation files to protect open knowledge in New York Times v OpenAI case appeared first on Wikimedia Foundation.

The Wikimedia Foundation has filed an amicus brief, a “friend of the court” submission, with the Southern District Court of New York in In re: OpenAI, Inc. Copyright Infringement Litigation, a major copyright case involving OpenAI and Microsoft. The Foundation’s goal is to help protect the open, accessible knowledge that Wikipedia, and millions of people, depend on.

The case brings together 12 lawsuits, the most well-known of them being The New York Times Co. v Microsoft and OpenAI. At its heart is an important question: When AI companies use copyrighted information does it qualify as fair use?

For the Wikimedia Foundation, the answer needs to leave room for innovation while supporting the people and organizations that make access to knowledge possible, including Wikimedia volunteers. The Foundation is not taking the side of either OpenAI or The New York Times in this case. It is asking the court to protect open knowledge, something that matters to everyone who uses the internet.

Wikimedia has a stake in this fight

More than 67 million Wikipedia articles, across 300 languages, are built and improved by nearly 250,000 volunteer editors. This work relies on access to trustworthy sources, including journalism, and other published research.

AI systems, in turn, rely on Wikipedia. It is one of the largest and most high-quality datasets for large language models, in addition to powering search engines and voice assistants. 

A copyright ruling that disrupts either side of that relationship could affect how everyone finds and uses information.

Making sure that fair use supports the knowledge commons

The New York Times filed its lawsuit in 2023, arguing that OpenAI and Microsoft used its copyrighted content without permission. OpenAI and Microsoft argue that using publicly available material to develop their AI systems qualifies as fair use.

Fair use allows certain uses of copyrighted material without the copyright holder’s permission. The question here is how it should apply to AI.

The Wikimedia Foundation sees risks in overly broad answers in either direction.

A ruling that interprets fair use too restrictively could make it more difficult to access publicly available content that is critical to developing open source AI technologies that benefit everyone. It would also inhibit many valuable ways that people gather and share public knowledge online. 

The New York Times and other publishers argue that the way AI companies have acquired copyrighted works for training AI, use those copyrighted works to train AI, and later use those copyrighted works in their consumer services to answer people’s questions should not be considered fair use. OpenAI is arguing that all of the ways that they use copyrighted works to develop and operate their LLM systems should be considered fair. 

Our arguments focus on preserving an appropriate place for fair use in the process, while protecting copyrighted content when it can be replaced by AI. If the training step is not considered fair use, AI technology development would likely only become possible for either the largest corporations who can afford to pay for the content, or the most well-funded developers who can purchase their proprietary models. Many open-source developers would be unable to afford or even access the technology. 

This outcome would directly harm the ability for Wikimedia volunteers to access relevant knowledge and to build and experiment with new open-source technologies which help them add, maintain, and improve the knowledge on Wikipedia. 

But a ruling that gives AI companies a blanket right to avoid existing copyright rules and license requirements would encourage publishers to lock more information behind barriers. That would leave fewer sources available to the volunteers who build Wikipedia.

If courts agree with this blanket interpretation of fair use, AI developers would no longer be beholden to existing copyright licensing terms that require proper attribution and additional licensing terms that underpin open human knowledge online and support the communities that produce it. 

This outcome would harm open knowledge and Wikimedia projects by further reducing visibility that we, and many publishers, depend on for readership and to attract the new volunteers that sustain our projects. 

The Foundation’s position is straightforward: the court should consider how material is being used, rather than treat every AI use as the same.

Respecting licensing while opening the door for innovation 

The Foundation’s brief draws an important distinction between training an AI model and using source material to answer a particular question.

During training, an AI model learns patterns from large collections of material. The Foundation argues that using copyrighted works for this purpose may qualify as fair use when the resulting model is something new and different from those works. 

Answering a user’s question with retrieved material is different. Some chatbots search for information and use what they find to build a response. One such approach is called retrieval-augmented generation, or RAG. These techniques help connect an answer to outside sources rather than relying only on what a model learned during training.

The Foundation argues that when AI products retrieve and reproduce copyrighted content this way, they should respect the source’s licensing requirements rather than treat the use as fair.

Open knowledge comes with responsibilities

Wikipedia’s content is available for others to use; we want free knowledge to thrive. That openness is central to its mission, but it does not mean there are no conditions.

Wikipedia uses the Creative Commons CC BY-SA 4.0 license. It requires credit to the original creators and requires adaptations to remain available under the same license.

The Foundation argues that AI companies using Wikipedia content through RAG or similar techniques must honor those requirements. Giving credit preserves a connection between the information people receive and the contributors who made it available.

Collecting content should not put an unsustainable burden on the systems that keep Wikipedia running. Regardless of whether companies are gathering material for training or retrieving it for answers, they must respect its public API rate limits or use its Wikimedia Enterprise API offerings.

Protecting human knowledge 

This case is about more than who wins a dispute between publishers and technology companies. The question at the heart of this case can affect whether the next generation of information tools will help sustain the human work they’re built on.

The Foundation is advocating for a balanced position that considers each stage of use when considering AI technology. This will protect fair use that enables valuable new technologies, while respecting the rights of people, publishers, and communities that make reliable knowledge possible.

For everyone who has ever turned to Wikipedia to understand the world, that balance matters.

To read more about the details of our legal argument, see the post on our Policy on Medium. You can also review the amicus brief in its entirety on Commons.

We thank Angela Chung, WMF’s Tech Law and Policy Fellow for her support in drafting, Rossella Gabriele, Fellow-in-Residence at Yale Law School Information Society Project (ISP) for her support in research and editing, and Rhett Millsaps of Lex Lumina LLP for his support in the filing process.

What if sharing an interesting Wikimedia fact did not require a design tool, a QR-code generator and a separate caption? Wiki DYK Share Tool (wiki-dyk.toolforge.org) turns content from supported Wikimedia pages into ready-to-share images with QR codes, captions and customizable hashtags. It can also help communities promote campaigns, events and initiatives without requiring graphic-design skills.

Knowledge deserves to travel further

In October 2025, the Wikimedia Foundation reported that human pageviews on Wikipedia had declined by approximately 8% compared with the same months in 2024. The Foundation pointed to changing online habits, including AI-generated answers in search engines and younger audiences increasingly turning to social video platforms for information. Read the Wikimedia Foundation’s update.

For those of us who contribute to Wikimedia projects, this raises an important question: how can we help more people discover the knowledge our communities create?

Every day, volunteers write articles, upload photographs, improve dictionaries, digitize historical documents, contribute structured data and organize community events. Yet much of this work remains unfamiliar to people outside our communities.

An interesting fact, a remarkable photograph or a little-known historical document could catch someone’s attention on social media. It might encourage them to visit a Wikimedia project, explore a subject or even make their first edit.

But sharing something well takes effort. We often need to find an image, arrange the text, create a QR code, prepare a caption and choose relevant hashtags. For volunteers organizing an event or campaign, repeating these tasks can become an unnecessary distraction.

I wanted to make that process simpler.

Enter the sloth

I develop lightweight tools under Wiki’s Lazy Coders, a volunteer initiative focused on simplifying repetitive work across Wikipedia and the wider Wikimedia ecosystem.

The philosophy behind the name is simple: being lazy does not mean being careless. It means asking, “Why should we repeat this task manually when a small tool could do it for us?”

Our latest project is the Wiki DYK Share Tool. DYK stands for “Did you know?”, a familiar way of introducing an interesting fact. The tool makes it easier to turn content from a supported Wikimedia page into an attractive, shareable graphic.

From a page to a shareable image

The process is straightforward:

1. Paste a link to a supported Wikimedia page.
2. Select a sentence from the loaded page, or write your own text.
3. Choose a background image from the page or use a plain background.
4. Adjust the layout, select an image format and customize the hashtags.
5. Preview the result, then download it, copy it or share it using the available options.

The generated image includes the source project’s identity, the article title, a readable link and a QR code that takes readers back to the original page.

The aim is to give volunteers a useful starting point without requiring them to learn graphic-design software.

Beyond Wikipedia: supporting the wider Wikimedia movement

Despite its name, the Wiki DYK Share Tool is not limited to Wikipedia. It also supports other Wikimedia projects, including Meta-Wiki, Wikimedia Commons, Wiktionary, Wikisource, Wikidata and several other Wikimedia projects.

This opens up possibilities beyond sharing individual facts.

A photography community could highlight an interesting Commons image. A Wiktionary community could introduce an unusual word. Wikisource volunteers could draw attention to a historical text, while Wikidata contributors could share an interesting discovery.

Affiliate groups, campaign organizers and local communities could use the same workflow to publicize events, introduce new initiatives, highlight competitions and invite people to participate.

Imagine preparing a graphic for a photography campaign, adding campaign-specific hashtags, including a QR code to the relevant page and sharing the result with participants. The same approach could be used for an edit-a-thon, a community meeting, a language initiative or a Wikimedia outreach programme.

The tool can help create consistent graphics for multiple posts by changing the text, background, format and hashtags to suit different topics and audiences. Browser-saved preferences and custom hashtags can also make repeated work quicker.

It is not a campaign-management platform. Rather, it is a reusable outreach tool that can help make the work of different Wikimedia communities more visible.

Small details that make a difference

I wanted the tool to offer more flexibility than a single fixed template.

Layouts for different platforms. You can position the text at the top, middle or bottom, and place the QR code in any of the four corners. Six image formats are available: Facebook (1200 × 630 pixels), Facebook Wide (1200 × 675), LinkedIn (1200 × 627), Instagram Portrait (1080 × 1350), Square (1080 × 1080) for Instagram, Telegram and WhatsApp, and Story / Status (1080 × 1920) for Instagram, WhatsApp and Telegram.

Text that remains readable. A dark overlay is applied to the background, with its strength adjusted according to the photograph’s brightness. The text size adapts to the available space, helping keep the fact legible.

Automatic and customizable hashtags. The tool suggests hashtags based on the page title, source project and article categories. You can switch individual suggestions on or off, add your own hashtags and remove custom ones. Custom hashtags are saved in the browser for future use.

There are separate controls for hashtags in the caption and on the image. You can include them in both places, only one, or neither—useful when different campaigns and social platforms have different requirements.

Captions without starting from scratch. A caption is generated automatically, beginning with “Did you know…” by default and including a link to the source page. You can copy the caption independently or use the sharing options for Telegram, WhatsApp, Facebook and X.

A QR code that brings readers back. The code is generated automatically and links to the original page. Someone who sees the image on another device, in a presentation or at an outreach event can scan it to continue reading.

The tool also remembers layout and display preferences in the browser, making repeated use quicker.

Works in your language and shows links the way they should look

Wikimedia is multilingual, and the tools we build should accommodate that diversity. A fact from Awadhi or Hindi Wikipedia deserves the same care in presentation as one from English Wikipedia.

One small detail has bothered me for years: the way links to articles with non-Latin titles can look when shared online.

Consider a link to the Awadhi Wikipedia article about Tulsidas. In encoded form, it looks like this:

https://awa.wikipedia.org/wiki/%E0%A4%A4%E0%A5%81%E0%A4%B2%E0%A4%B8%E0%A5%80%E0%A4%A6%E0%A4%BE%E0%A4%B8

That long string of percent signs and numbers is difficult to read and can look like a technical error.

But the title is simply तुलसीदास. Displayed naturally, the link looks like this:

awa.wikipedia.org/wiki/तुलसीदास

The tool displays the decoded, human-readable link on the image and in the caption. Behind the scenes, the QR code and sharing functions retain the properly encoded URL, so the link remains usable.

It may seem like a small improvement, but presentation matters. For communities working in Hindi, Awadhi and other languages that use scripts beyond the Latin alphabet, seeing their article titles displayed naturally makes a shared post feel more welcoming.

The tool also uses Unicode-aware hashtag generation, allowing characters from non-Latin scripts to be retained in hashtags. Its interface is currently in English, but the content being shared can come from different language editions and supported Wikimedia projects.

The goal is not simply to reproduce an English-language workflow. It is to make sharing more inclusive of the languages in which Wikimedia communities create and preserve knowledge.

There is always room to improve

The tool is a work in progress, and feedback from the community will help determine what comes next.

There are limitations I already know about. Some social platforms ignore captions when an image is shared, meaning users may need to paste the prepared caption separately. The tool currently creates static images rather than videos or animations.

It also does not verify the accuracy of a selected passage or publish posts directly to social-media accounts. Users should ensure that the content they share is supported by the source and presented in context.

I would particularly welcome feedback from language communities, campaign organizers, educators, GLAM partners, affiliate groups and volunteers who run Wikimedia events.

Which image formats would help your campaign? Are there language-specific display issues I should address? What would make the tool more useful for promoting events, outreach programmes or Wikimedia initiatives?

Try it at wiki-dyk.toolforge.org and share your suggestions on my Meta-Wiki user page or through Wiki’s Lazy Coders.

The tool is intended to make sharing knowledge easier, not to replace the people who create it. If a small improvement helps one more person discover a Wikimedia project, learn something new or become a contributor, that is a worthwhile step forward.

Wikimedia Tunisia organized GLAM Wiki Days Tunisia 2026 on October 20th and 21st, 2026, in collaboration with the Association Culture et Sciences de Métlaoui, bringing together representatives from cultural heritage institutions, documentation professionals, university teachers, students, Wikimedia contributors, and experts to explore opportunities for collaboration between Wikimedia projects and Tunisia’s memory institutions.

The two-day event aimed to strengthen cooperation between Wikimedia and institutions preserving Tunisia’s documentary and cultural heritage, promote open access to knowledge, and to explore new ways to make historical documents, archival collections, and cultural resources more accessible to the public through Wikimedia projects.

Day 1 – GLAM Wiki Day at the National Library of Tunisia

The first day took place on October 20th, 2026 at the National Library of Tunisia in Tunis. It brought together representatives of several major Tunisian institutions responsible for preserving and promoting the country’s documentary and cultural heritage, including:

• The National Library of Tunisia
• The National Archives of Tunisia
• The National Center for Documentation
• The Centre for Arab and Mediterranean Music, Ennejma Ezzahra
• The Higher Institute of Documentation of Tunis

Representatives of these institutions introduced their organisations, presenting their missions, collections, and the documentary resources available to researchers and the wider public. Their presentations highlighted the importance of preserving Tunisia’s documentary heritage, advancing the digitisation of collections, and developing open-access approaches that can facilitate access to knowledge.

The discussions also provided an opportunity to identify potential areas of cooperation between these institutions and Wikimedia projects, particularly in making digitised documents, historical photographs, archival materials, and other cultural resources available to a wider audience.

Wikimedia projects and the importance of GLAM collaboration

The Wikimedia Foundation was represented by Farida El-Gueretly, who presented the Foundation’s role in supporting the Wikimedia movement, the importance of Wikimedia projects in sharing free knowledge worldwide, and the opportunities offered by partnerships with galleries, libraries, archives, and museums (GLAM).

The Higher Institute of Documentation of Tunis also presented its academic and professional activities, its experience with Wikimedia initiatives, and the opportunities for collaboration between the institute, its teachers and students, and the Wikimedia community in Tunisia and beyond. The presentations and discussions explored the role of open access and open data in facilitating research, education, and the dissemination of cultural heritage.

Camille Françoise, a GLAM expert from Wikimedia France, delivered an important presentation explaining why cultural institutions should engage with Wikimedia projects. Drawing on the experience of Wikimedia France and its collaboration with the National Archives of France, she demonstrated how partnerships between Wikimedia communities and memory institutions can increase the visibility of collections, improve access to historical resources, and encourage public participation in documenting and sharing heritage.

The programme also included a presentation by Winkie Williamson, historian at Ennejma Ezzahra Palace, who highlighted the importance of contributing to Wikipedia and the value of sharing historical knowledge with a wider audience. Her contribution reinforced the idea that historians, researchers, cultural professionals, and other knowledgeable individuals can all play a role in improving free online knowledge.

The first day concluded with discussions on possible partnerships, the development of open-access resources, and practical ways to strengthen collaboration between Wikimedia Tunisia and the participating institutions.

Day 2 – Institutional visit and practical workshops at the Higher Institute of Documentation of Tunis

On October 21st 2026, the program continued at the Higher Institute of Documentation of Tunis, with the participation of representatives of Wikimedia Tunisia, the Wikimedia Foundation, and the GLAM expert from Wikimedia France.

The day began with a guided tour of the institute led by Dr Aida Chebbi. Participants discovered the institute’s facilities, library, and different laboratories, gaining a better understanding of its educational environment and its role in documentation, information management, and the preservation and organization of documentary resources.

Following the visit, a meeting was held with several teachers and representatives of the institute to discuss potential areas of cooperation and the development of a future partnership with Wikimedia Tunisia. These exchanges helped identify opportunities to involve students and academic staff in Wikimedia activities and to connect documentation studies with practical open-knowledge initiatives.

A practical introduction to Wikimedia projects

The second part of the day focused on a hands-on workshop attended by a large number of students and teachers from the institute.

Camille Françoise introduced participants to the different Wikimedia projects, explaining their complementary roles in building and sharing free knowledge. The presentation included an introduction to Wikipedia and Wikimedia Commons, as well as the principles of contributing to these platforms and respecting copyright and open licences.

Participants then took part in a practical workshop on Wikidata, the Wikimedia project’s free and collaborative knowledge base. Through guided exercises, they explored how documentary resources and information about works, authors, institutions, and historical subjects can be represented and connected using structured data.

The workshop demonstrated how students and documentation professionals can contribute directly to Wikimedia projects while developing practical skills in digital documentation, data organisation, and open knowledge.

Looking ahead: A new phase of GLAM collaboration in Tunisia

GLAM Wiki Days Tunisia 2026 represents an important step towards establishing stronger and more sustainable partnerships between Wikimedia Tunisia and the institutions responsible for preserving Tunisia’s cultural and documentary heritage.

Building on the discussions and activities of these two days, Wikimedia Tunisia aims to develop a larger GLAM programme in 2027, in cooperation with the Higher Institute of Documentation of Tunis and other interested institutions.

One of the main objectives is to prepare a group of students to participate in a Wikimedia in Residence initiative, working with different GLAM institutions across Tunisia. Under this approach, trained participants would help institutions identify suitable collections, improve the documentation of their resources, contribute to Wikimedia projects, and promote the sharing of knowledge under free licences wherever legally possible.

The initiative could provide new opportunities for students to apply their academic skills in real-world projects while helping cultural institutions increase the visibility and accessibility of their collections.

By bringing together cultural institutions, universities, Wikimedia contributors, and international experts, GLAM Wiki Days Tunisia 2026 laid the foundations for a collaborative approach to digital heritage, open access, and free knowledge.

The shared ambition is clear: to make Tunisia’s documentary and cultural heritage more visible, accessible, and reusable, while connecting the country’s memory institutions with the global Wikimedia movement.

Wikimedia Tunisia warmly thanks all participating institutions, speakers, experts, teachers, and students for their contributions and commitment to this initiative.

This semester, I have a couple of students who will not or cannot complete work without AI. They have already turned in sloppy AI-generated work: they lost points, and I spoke with them, warned them, and told them that subsequent work would be checked via Pangram. (In this way I feel like I am almost coaching them to be dishonest.) Even so, they persist in turning in lazy AI slop. One student did appear to edit the AI prose to pass Pangram detection, but the prose still had the AI phrase “this is more than a X—it is their Y”—an inappropriate tone for a Wikipedia contribution in any case.

At the same time, my exhortations for students to use AI for learning, instead of shirking, haven’t had much (or any?) traction yet. Claude Opus 5.5 can build an amazing dynamically updating, spaced-repetition quiz deck with an embedded tutor chat box from a prompt that is fewer than one hundred words and points the agent at my class handouts folder.

Build an interactive space-repetitive learning quiz app as a published artifact, using the handouts at https://reagle.org/joseph/2026/cda/handouts/. Each (~10 minute) module should have:

• 6–-8 multiple-choice questions that test understanding, not just recall; prioritizing the content appearing the review slide
• a revealable non-giveaway hint
• a solution with link to the correct section of the slide handout
• a Claude tutor “discuss” box where I can ask questions.

Adopt new content and create new questions based on our discussions and as added new handouts are added to the folder.

Accelerationists enthuse “this is the worst AI will ever be,” yet for traditional education, I believe “this is not good, and not likely to get better soon.”

In 2016, Wiki Education dropped a pebble in the waters of science content on Wikipedia with our Year of Science initiative. The ripples from that pebble grew into our Communicating Science Initiative, and over the last ten years we have supported over 70,000 students and scholars in improving almost 70,000 Wikipedia articles and adding 635,000 references to STEM content.

On October 8, the Wiki Education Speaker Series celebrated those achievements. The conversation included four veterans of our programs — Cecelia Musselman, Teaching Professor at Northeastern University, Michael Benjamin, Teaching Professor at the University of North Carolina at Charlotte, Glenn Dolphin, Associate Professor at the University of Calgary, and Alexandra Lau, Senior Program Manager at the American Physical Society — and was hosted by Ian Ramjohn, Wiki Education’s Senior Wikipedia Expert.

High-quality sources are the backbone on which all good Wikipedia content is built, and was what drew Cecelia Musselman to the Wikipedia assignment. Musselman teaches advanced writing for the sciences, a graduation requirement for science majors. When she first began teaching the course, she struggled to get her students to understand the idea of a reference article. 

In a passing conversation with her director, Musselman mentioned that “the only encyclopedia they know is Wikipedia”, to which he replied “have them write Wikipedia articles”. Musselman took that idea and ran with it, and created a Wikipedia assignment for her writing class. After doing a “rogue” Wikipedia assignment for several years, she discovered Wiki Education shortly before we launched the Year of Science. Fifty-five classes later (including three in progress this fall), Musselman has brought 862 students to Wikipedia who’ve improved over 1,100 articles and added over 9,300 references. 

“One of the really profound impacts on my students has been [that] they take citation really seriously. It doesn’t matter what else I do with them, it’s not until we get to the Wikipedia part of the semester when they start getting really serious about sources and source quality and where they come from,” Musselman observed.

While the main focus of the Communicating Science Initiative has been in the Wikipedia Student Program, participants in our Scholars & Scientists program have also made significant contributions to science content over the years. Much of this work has come through a partnership between Wiki Education and the American Physical Society, which sponsors Wiki Scientists courses. These courses primarily bring graduate students and early career researchers to Wikipedia to work in their area of expertise.

When speaking about the impacts of APS members on the encyclopedia, Alexandra Lau struck a similar chord as Musselman. “Verifiability is a key pillar of Wikipedia…and one of the things that I think makes me particularly proud is seeing the references that are added, bringing the connection to the scientific literature…and so making sure that it’s more accessible and available, feels really important…I always like to see how many references are added by our editors.”

Communicating Science isn’t just about improving science articles, it’s also about improving articles about scientists, especially those from historically excluded groups. 

“When I first started the Wikipedia project, I had met a professor from the West Coast, and she had a list of women geologists. There were 150 women on this list,” recounted Glenn Dolphin. He explained that when the professor learned that he was doing a Wikipedia project focussed on women geologists, she passed the list on to him.

“Probably 5 years after I had started this project, “Dolphin continued, “she wrote me an email, and she said, I’ve taught this geology course for the first time in a couple of years, and when I went to look at this list, I noticed that there are so many more women geologists on Wikipedia now.”

Wikipedia, of course, isn’t just in English. There are active Wikipedia projects in 348 languages. And these different language Wikipedias aren’t simply translations of the articles on the English Wikipedia, although translation can help fill gaps in different language versions.

In Michael Benjamin’s classes, translation has opened a door for his students. “We have a lot of international students, and one option that I’ve given the international students is that if they want to translate an article into their first language, they can. I think we’ve had a lot of motivation for the students to do that, because there might not have ever been an article about that topic in their first language.”

And as Benjamin’s classes have learned, there’s also scope for translating articles into English. “The last time a student of mine was working on something like this, we found out that in geometry, the Mandarin Wikipedia has incredible coverage in various places that simply doesn’t exist in English.”

Not every contribution to Wikipedia needs to be big to make a difference. Sometimes just changing a few words can have a major impact. Students in any given class or setting can bring unique perspectives to topics based on their education and experience. 

Benjamin observed, “Sometimes my students think that they have to recreate everything, or redo everything…[but] sometimes, if you’re gradually improving that article, it’ll make a difference in the end. It might [just] be uploading a picture.”

From students, to early career scientists, to the occasional Nobel laureate, our Communicating Science participants bring a unique set of skills to Wikipedia. 

Both Wikipedia and the world have changed a lot since 2016. Back then no one had heard of COVID-19 or ChatGPT, and few would have imagined the impacts that mRNA vaccines and CRISPR gene editing would have on science and medicine. New discoveries in STEM will always need to be added to Wikipedia, like the tilcayo, the first new living cat species discovered since 1923, while the contributions of excluded or overlooked scientists will continue to modify our understanding of how science has progressed. 

Despite all the contributions of both students and the amazing work of the volunteer community, a decade after the Year of Science, Wikipedia continues to need more and better STEM content. Your contributions and those of your students are always needed.

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Wiki Education’s Speaker Series is a monthly, Zoom-based panel discussion that brings together experts in Wikipedia and open knowledge to examine topics relevant to our communities. Each session is moderated by a Wiki Education staff member, includes a live audience Q&A, and is recorded for Wiki Education’s YouTube channel.

Visit our website to learn more and receive our next Speaker Series invitation.

Learn more about teaching with Wikipedia at teach.wikiedu.org, or explore editing yourself at learn.wikiedu.org.

Oct 28, 15:10 UTC
Completed - The scheduled maintenance has been completed.

Oct 28, 15:00 UTC
In progress - Scheduled maintenance is currently in progress. We will provide updates as necessary.

Oct 22, 06:42 UTC
Scheduled - The SRE team will run a planned data center switchover, moving all wikis from our data center in Virginia to the data center in Teaxs. This is an important periodic test of our tools and procedures, to ensure the wikis will continue to be available even in the event of major technical issues.

The switchover process requires a brief read-only period for all Foundation-hosted wikis, which will start at 15:00 UTC on Wednesday October 28th and will last for a few minutes while we execute the migration as efficiently as possible. All our public and private wikis will be continuously available for reading as usual, but no one will be able to save edits during the process.