`marimo pair`: Put Agents Inside Reactive Python Notebooks

Agents can attach to a live marimo notebook, use it as persistent working memory, run scratch code, and rewrite the notebook itself. That turns the notebook into both an execution trace and a human-agent workspace, so it's worth testing for research-heavy workflows now.

[ KEY POINTS ]

A single command, /marimo-pair pair with me on my_notebook.py, binds an agent to a running notebook and exposes the full session state.
Agents can probe state in an ephemeral scratchpad, then persist useful work by adding cells, deleting cells, or installing packages into the notebook file.
marimo's reactive graph removes hidden state: rerunning propagates to dependents, and deleting a cell scrubs its variables from memory.
The team positions code mode as a REPL that extends context windows, but unlike throwaway scripts it incrementally builds a reproducible Python program.
Early uses center on data exploration, hypothesis testing, executable answer traces, and even self-hosted debugging of marimo pair and marimo itself.

Originalgithub.com/marimo-team/marimo-pairRead original →

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`marimo pair`: Put Agents Inside Reactive Python Notebooks

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