Yesterday, we had a fantastic mini-group retreat centered around AI. We had an engaging and thought-provoking day from start to finish - kicking things off with coffee and a panoramic view from the JenTower, setting the tone for open conversations and shared learning.
Throughout the day, we explored how AI is being used in practice across the team, from diverse real-world applications to the ways each of us integrates it into our daily research workflows. We exchanged perspectives on the platforms and tools we rely on, and what makes them effective in different contexts. Claude Code stood out to be the tool of the day - for building agents and tailored workflows and using Claude skills and projects effectively. NotebookLM sparked interesting discussions around idea development, building foundational understanding, and organizing ideas.
We also reflected on how AI is reshaping research workflows more broadly, covering literature organization, writing and synthesis, and ways to streamline repetitive or complex tasks. At the same time, we discussed practical considerations such as security, privacy, and cost, and how to balance efficiency with responsible and sustainable use.
The day got even more exciting when we had an impromptu mini hackathon. A buggy piece of code, 3 teams, and a mix of AI tools later, the problem was solved reminding us how debugging can be a collaborative experience between AI and humans.
We ended the day by reflecting on the broader impact of AI on research and beyond, and how to actively adapt to technological change rather than resist it. A key takeaway was the importance of being mindful of how much knowledge we internalize versus outsource. Ultimately, it’s not just about using AI effectively, but about continuing to learn, think critically, and grow alongside it.