From SQL Copilot to Autonomous Data Scientist: The L0–L5 Reality Check
A dashboard fails. The sales team says the numbers changed overnight. The data engineer checks the pipeline. The analyst checks the SQL. The BI vendor says its “agent” can help. The executive hears “agent” and imagines a small autonomous data scientist quietly fixing the mess before breakfast. Usually, no. Usually it is a chatbot with access to SQL, a tool wrapper with better manners, or a workflow assistant that still depends on human supervision at the awkward parts. Useful, yes. Autonomous, no. The distinction is not academic hair-splitting; it determines who owns the error when the agent rewrites a query, changes a pipeline, or confidently explains a metric built on dirty data. ...