Runcell operates inside Jupyter rather than beside it. It writes Python, runs cells, reads the output, debugs failures and explains results — working through the notebook the way an analyst does, instead of returning code to be pasted in.
Execution access is the difference that matters. An assistant that cannot run a cell cannot see a shape mismatch or a null-heavy column, so it guesses; an agent that executes iterates against real data and corrects itself.
Autonomous execution in a notebook connected to real data deserves care around destructive operations and credentials, so scope it to analysis environments first. A free tier covers evaluation with paid plans for heavier use.
