As Brian Granger said in his keynote: "The Jupyter notebook format is the ideal document for AI."

And if we're going to add AI to computational workflows, we need to preserve the transparency that makes science trustworthy.

Full analysis on LinkedIn:
www.linkedin.com/feed/update/...

Current multi-agent frameworks (LangChain, AutoGen) orchestrate agents in the background.
User prompts → agents debate invisibly → result appears.
Jupyter AI makes agent coordination transparent. Human-in-the-loop, all the way down.

This respects what #Jupyter actually is: a medium for dialogue. Not a REPL with a GUI. Not an IDE with a chatbot bolted on. A conversational space where humans negotiate truth through computing.

Here's the genius: they're using @jupyter.org's Real-Time Collaboration (RTC) protocol—originally designed for humans—as the rail for AI interaction.

AI agents get cursors and chat privileges, just like human collaborators. They just "enter the chat" when needed.

In the demo: a Code-Cell-Editor agent encountered a statistics problem. It knows its limitations, so it @-mentioned a Statistician persona. The handoff happened visibly in the notebook—not in some hidden backend.

The model is agents are teammates, not black boxes.

If you use AI daily, you know "chat fatigue":
prompt ➡ wait ➡ read ➡ re-prompt ➡ repeat

Constantly context-switching between your work and a chat sidebar. Jupyter AI's new direction avoids this entirely.

The serious conversations about pedagogical approaches that harness AI productively rather than making human learning obsolete 𝘢𝘳𝘦 𝘯𝘰𝘵 𝘺𝘦𝘵 𝘩𝘢𝘱𝘱𝘦𝘯𝘪𝘯𝘨! How are other educators navigating this?

🎥 Check out this short video demo—and I'm curious to hear your thoughts:
youtu.be/6q5CtXD5koY

We're facing a 𝘄𝗶𝗰𝗸𝗲𝗱 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: motivating genuine learning when the tools have become this capable. Assignments should help critical thinking rather than just testing procedural knowledge. But the pace and the scale of the changes required are 𝘮𝘰𝘯𝘴𝘵𝘳𝘰𝘶𝘴.

What I witnessed:

– The AI assistant analyzed the entire Jupyter notebook
– Executed code cells autonomously
– Wrote proper NumPy functions
– Solved exercises completely
– Even explained its reasoning

All faster than students could read the problem statement.

This raises a critical question: Are certain genres of scholarly work—especially simple literature reviews or trend summaries—no longer valuable as original scholarship? It's time for academia to rethink what we consider "original."

What do you think? #PeerReview

The paper's abstract promised a "review of key trends" in AI for engineering education.
My reasoning for immediate rejection: anyone can generate this with a single, well-crafted prompt. I tested it in Gemini 2.5 Pro, and the results were stunningly good and likely similar to the submitted article.

Bonus:
In support of my statement in highlight 1), above, you need to see this video by Prof. Giordano Scarciotti of Imperial College London (posted May 10, 2025):
youtu.be/lSbnMBb6INA

7) Beware wearables: Smart glasses can photograph exam questions and get live AI answers. Your syllabus needs wearables policies NOW.

Bottom line: Students will use AI anyway. Let's redesign courses to help them thrive with it.

Full piece: doi.org/10.6084/m9.f...
8/8

6) The AI polarity: It can amplify learning OR create cognitive laziness. The difference is in how we design assignments and teach usage. How might you design for active AI use and promote user patterns that result in positive outcomes?
7/8

5) AI is much more than chat. It's autonomous agents doing research, filling forms, completing coursework. One prompt = entire literature review. Will you change expectations of what students do in your class?
6/8

4) Entry-level jobs were down 15% in 2024, and unemployment for new grads hit 4-year high this year. Meanwhile, companies now require AI use in their teams, and are conducting AI-enabled job interviews. Are we preparing students for this?
5/8

3) Students perceive that they know AI better than faculty (they're probably right). This gap is creating stress and missed opportunities for everyone. What are you going to do about this?
4/8

2) ChatGPT now has "Study Mode" and Gemini has "Guided Learning"—both promise Socratic tutoring versus immediate answers. But will students choose the hard path when instant answers are a click away? (They can turn Study mode on/off!) 🤔
3/8

1) Google just gave all US college students free access to Gemini Pro. They just need an .edu email for verification. This means validity of your take-home assignments is cooked: Gemini can do complex work for students and they don't need to think…
2/8