# GitHub Copilot session at Cédille (with GitHub & Arctiq)

> Cédille hosted GitHub and Arctiq for Copilot Chat, /createNotebook, and GitHub Next — expanded recap with photos and student takeaways.

- HTML page: https://antoineboucher.info/CV/blog/posts/github-copilot-cedille-session/
- Language: en
- Translation (fr): https://antoineboucher.info/CV/blog/fr/posts/github-copilot-cedille-session/index.md
- Published: 2022-09-06
- Updated: 2026-05-22
- Tags: GitHub Copilot, Conference, Cédille, Arctiq, AI
- Author: Antoine Boucher (https://antoineboucher.info/CV/index-en.html)**Cédille** (ÉTS consulting club) hosted **GitHub** and **Arctiq** for a session on **Copilot** and the AI tooling around modern dev workflows — fall 2022, when “AI pair programmer” still felt novel in a university room.

## Why Cédille hosted it

**Cédille** is the ÉTS consulting club — students ship real projects for external clients and need credible tooling opinions, not TikTok hot takes. Fall 2022 was peak “is Copilot cheating?” energy on campus. We invited **GitHub** and **Arctiq** so the room could hear licensing, privacy, and roadmap from people who actually ship the product.

## Why we ran it

Student teams wanted to know if Copilot was allowed on internships, useful for data labs, or a shortcut that gets you failed on code review. Bringing vendor voices in cut through rumor: here is what the tool is, here is what GitHub ships today, here is where experiments live on **GitHub Next**.

## Advice I still give students

| Question | Short answer |
|----------|----------------|
| Can I use it on assignments? | Follow your course policy; assume you must cite and understand every line you submit. |
| Does it replace tests? | No — run the code, read the diff, reproduce the bug without AI once. |
| Best first win? | Explain unfamiliar code + generate test scaffolding, not “write my entire lab.” |

## What we saw live

| Topic | Why it mattered |
|-------|-----------------|
| **Copilot Chat** | Explanations and refactors in-editor, not only tab completions |
| **`/createNotebook`** | Bootstrap a Jupyter notebook from existing repo code — huge for courses and EDA |
| **[GitHub Next](https://githubnext.com)** | Sandbox for features that may never ship as-is — worth bookmarking |

The **`/createNotebook`** demo was the crowd reaction moment. You point Chat at a module, ask for a notebook that imports and demonstrates it, and you get a first draft faster than copy-pasting cells by hand. Not magic — you still verify paths and versions — but it lowers the “blank notebook” barrier.

## Session photos

Room was full — mix of software, data, and curious management folks.

![GitHub Copilot session at Cédille — room view](https://antoineboucher.info/CV/blog/posts/github-copilot-cedille-session/images/1695948465024.jpeg)

Wide shot of the room — ÉTS students up front, laptops open. The energy was “show me something I can try Monday,” not passive keynote mode.

![Copilot session — presentation](https://antoineboucher.info/CV/blog/posts/github-copilot-cedille-session/images/1695948465037.jpeg)

Presenters walked through **Chat** flows on a real repo, not slideware only. The memorable beat was refactoring a messy function in-place: accept suggestion, run tests mentally, tweak. That rhythm is what I still recommend to juniors — Copilot as a fast draft, not an oracle.

![Copilot session — audience](https://antoineboucher.info/CV/blog/posts/github-copilot-cedille-session/images/1695948466072.jpeg)

Audience questions were practical: **privacy** (what leaves the machine), **license** on generated code (still your responsibility to comply with project policy), and whether Copilot works offline (it does not — plan demos with Wi‑Fi).

Thanks to **Thierry Madkaud** and **Eldrick Wega** for presenting, and to everyone who showed up.

## What I took home

- **Copilot is a accelerator, not an author** — review still belongs to the human who commits.
- **Notebooks are first-class** — data curricula should teach Chat + notebooks together, not as an afterthought.
- **Next vs product** — GitHub Next is where you look for preview features without betting your thesis on beta APIs.

I later built diagram tooling in the ChatGPT plugin era — see **[D2C OpenAI diagram plugin](https://antoineboucher.info/CV/blog/posts/d2c-openai-diagram-plugin/)** and **[Diagram prompts with AIPRM](https://antoineboucher.info/CV/blog/posts/chatgpt-airprm-sequence-diagrams/)**.

## Related posts

- [Run:ai on AWS — webinar notes](https://antoineboucher.info/CV/blog/posts/runai-aws-inference-webinar/) — another 2022 industry session recap
- [Software engineering journey](https://antoineboucher.info/CV/blog/posts/software-engineering-journey/) — where school and industry threads meet