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# AI Team

The Artificial Intelligence Team encourages thoughtful adoption of Artificial Intelligence by Django users and developers.

## Scope of responsibilities

The scope of the AI Team includes:
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Could this team become a point of expertise within the community for other Teams/WG's to contact for advice?

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I think yes? Do you think this should be written as an explicit responsibility?

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I would say yes, so that other there is an expectation and possibly some coordination between teams. While this likely happen naturally, to me we would benefit from more being written explicitly rather than assumed.


- Making it easier to build AI/ML products with Django without compromising on ethical, safety, social responsibility fundamentals
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I have concerns around the phrase "Making it easier to build AI/ML products with Django". Using this phrase in the charter of a team implies that changes to Django are within the scope of the team.

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I wonder if it could be rephrased to remove that implication? E.g. I think the AI team could serve this goal via documentation, tutorials, etc. without having to make any changes to DJango.

- Improvements to AI coding capabilities for developers, that meet responsible AI guidelines on security, copyright
- Considering how AI tools can be used and mis-used for Django core and in the Django ecosystem

We coordinate AI enthusiasts and skeptics who want to support the Django project and community. We encourage experimentation that is compatible with responsible use of AI (ethics, safety features, guardrails, environmental footprint).

---

The scope of the AI Team is expected to change over time, and is to be decided by consensus of the team, with input from the Steering Council as required.

Many of these activities can be undertaken by any contributor. The AI Team coordinates this work. It can step in where contributors are not available and support those who lack the knowledge to do so themselves.

## Membership

- Chair: Thibaud Colas
- Co-Chair: Sheena
- Steering Council Liaison: TBC (optional)
- Board Liaison: TBC (optional)
- Other members:
- Jan Gondol
- Jeff Triplett
- Paolo Melchiorre
- Tom Carrick
- Lilian
- You?

### Alumni

## Future membership

The team does not have a fixed size. The team decides when new members are needed. New members are chosen from a list of volunteers. If there are no qualified volunteers the team will place an advertisement on the Django website.

If you are interested in joining, please use our form: [Apply to join the AI team](https://forms.gle/s6xUcaZ17QHQfhxJA).

Priority will be given to volunteers who:

- Have expertise with AI.
- Have a record of contributing to Django.

Members must opt-in to remain on the team on an annual basis. They may also leave for any reason.

Members can also be removed by:

- Becoming disqualified by the Code of Conduct working group
- A vote of the Steering Council
- The vote of a 50% + 1 majority of the rest of the AI Team

## Budget

No budget is required at this time. This will be reviewed at least annually. Any changes to the budget may be requested from the board.

## Communication channels

The AI team operates in several areas:

- Public #ai channel on [Django Discord server](https://chat.djangoproject.com/)
- TBC Forum category
- Private #ai-team channel on [Django Discord server](https://chat.djangoproject.com/) or on the DSF Slack workspace
- A private Google Drive folder and Group in the DSF Google workspace

The AI team can be tagged specifically in the following areas:

- `@django/ai` team in the Django organization
- Other options TBC

The team meets online once per month.

## Reporting

The team posts public meeting notes to the forum. These serve as reports to the DSF Board and Steering Council.

The team produces an annual report that is shared with the Django community.

## Appendix

### Group activities

As an illustration of the group’s remit, here are possible activities members could take part in.

- Marketing: Django as the go-to for AI apps
- Django guidelines for LLMs
- Automated code review
- Understanding how to deal with AI-led contributions (AI slop and other contributions with little human involvement)
- Dynamic learning quiz or tutor for Django learners
- Boilerplate code generation with prompts for `startproject` / `startapp`
- Improved support for using the Django docs with AI, potentially including on-site vector search and llm-friendly docs formats (e.g. markdown files or `llms.txt`)
- Exploring modern agent-based workflows
- Reviewing the energy use of AI
- Adding context-aware chatbots to the Django docs site or Discord