The previous articles each closed one leak. A real Streamlit + pandas dashboard leaks through five at once. This is the whole session — obfuscate, run, prompt, apply — with every channel accounted for.
Why a dashboard is the hard case
The earlier articles in this series each took one surface: the runtime workspace and .env, the transparent proxy, pandas column names.
A data dashboard is where all of them collide, because a Streamlit app is the rare Python project that is simultaneously:
Code the AI reads and edits (business logic, service classes).
