Thibaud Colas

The Django community is at a pivotal moment in its relationship with generative AI. From code generation tools reshaping developer workflows to ethical questions about training data and environmental impact, there's no shortage of opinions, but limited space for structured, collective sense-making. This workshop proposes a facilitated Open Space-style discussion that brings the Django community together to surface, explore, and document the key themes, concerns and opportunities around Django and AI. Rather than prescribing answers, we want to harness the room's collective expertise to map the landscape as practitioners experience it. The session, hosted by Thibaud Colas and Laura Gates, will use a participatory format drawn from Open Space Technology, where attendees propose and lead breakout discussions around the sub-topics that matter most to them – whether that's AI-assisted development, ethical frameworks for Django projects integrating LLMs, the Django Software Foundation's approach to AI policy, or something we haven't anticipated. Thibaud brings deep technical leadership and a long-standing commitment to ethical open-source practice as product lead for the Wagtail CMS, while Laura brings experience facilitating open space and participatory events across academic, charity and corporate settings. Together, we'll synthesise the session's outputs into a documented resource for the wider Django community. This workshop is for anyone in the Django ecosystem – whether you're enthusiastic about AI, cautious, or still figuring out where you stand. No prior AI expertise is needed; the goal is an inclusive, grounded conversation that reflects the full range of community perspectives and produces something genuinely useful beyond the room.

The llms.txt format is an emerging standard to structure information for Large Language Models. It’s a desirable addition to the docs of Python packages. We have been busy adopting it for Wagtail, and can now share how it all went. Let’s review how to adopt it! We’ll discuss the fundamentals of the format and its benefits as a user of the docs, and as a maintainer. How to produce and consume those files across different tools (Sphinx, mkdocs, Django). How to optimize them for different LLMs with an eval suite. Tools and techniques you should be able to reuse through other engineering tasks with LLMs.