Any team running an agentic pipeline on a periodically-reloaded dataset caches the output of inputs that repeat across periods to save cost. How you store that cache matters. Storing it in the same table as the data is safe, but makes you unable to wipe the data from the previous period before ...
Source: [Dev.to](https://dev.to/wondadav/architecting-lean-llm-caching-how-to-drop-a-20m-row-table-without-losing-your-ai-memory-3g2n)