basicagent.org

BasicAgent

When Jupyter Notebooks Fall Apart

Jupyter works for short experiments but breaks down for long-running, stateful workflows.

Published: 2026-01-04 · Last updated: 2026-01-04

Jupyter notebooks are great for experiments. They struggle with long-running, stateful workflows that need continuity across time and reconnects.

Where the notebook model breaks

  • session limits cut off work,
  • output history becomes fragile,
  • state drifts without a durable workspace.

What to use when that happens

A persistent terminal workspace keeps the session alive and lets you resume work without re-running the entire notebook state.