How, when and why to use agentic AI in our neuroscience labs
A neuroscience researcher discusses the rapid integration of agentic AI tools like Claude Code into laboratory workflows. The author emphasizes the need for formal lab policies to manage how these tools impact research methodology, skill development, and scientific norms.
Why it matters
As AI agents become capable of performing complex coding and analytical tasks, scientific institutions must adapt their operational frameworks to maintain research integrity and educational standards.
It dawned on me in early March this year, on the Caribbean island of Barbados, of all places. Konrad Kording, in swimming trunks, stood in front of about 30 PIs with backgrounds mostly in neuroscience and machine learning and live-demoed Claude Code, using a projector hardly visible in the broad daylight. He asked Claude to build a web app, and within minutes it was ready to test. The demo—designed to show how independently agentic AI could now solve tasks—presented the perfect picture: human in swimming trunks, machine working hard.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in