Pipeline Persistence

Pipeline persistence is the practice of saving the output from each step to disk (CSV, JSON, Markdown) instead of keeping it only in memory. This enables resuming after failure and debugging by inspecting what each step produced. It also enables auditing by tracing where results came from, and modularity by swapping one step without rerunning the rest.

In a semantic audit, each step saves its output: the first step saves keywords.csv, the second saves embeddings.csv, the third saves clusters.csv, and so on. If the pipeline crashes at step 4, steps 1–3 have their results on disk. Persistence is a fundamental pipeline engineering principle—without persistence, any pipeline failure means starting over from scratch.

For example: a 6-step pipeline crashes at step 5 after 4 hours. With persistence, you resume from step 5 in minutes. Without it, you restart from zero—another 4 hours lost.

In practice, use numbered file naming conventions like 01_keywords.csv, 02_embeddings.csv to ensure clear ordering.