COBOL Job Analysis and Business Logic Extraction - Individual Record Matching

From there, I iterated with the AI chat to perform an exhaustive search across the codebase. I double checked that the search results were actually complete and not missing entire sections of logic, since everything downstream depended on that being correct. Once I was confident in the coverage, I put together a rough plan for how to turn the raw search results into structured documentation instead of jumping straight into writing. I then worked through each of the five modules one at a time, using the search results as input to build out business analysis documentation. During each iteration, I actively checked that nothing was being hallucinated or inferred beyond what the code actually supported. The goal was to document what the system does and why, not to redesign it or add assumptions. After consolidating everything into a final Markdown document, I shared it with a business analyst for verification to make sure the documented behavior matched business expectations.

I started by skimming through the COBOL code myself to get some baseline context before involving any tooling. I didn’t try to understand every detail, but I wanted a rough sense of how the five modules fit together and how data flowed through the pipeline. That upfront pass made it easier to reason about what I was looking at later and helped me avoid blindly trusting any generated output. Once I had that context, I set up a Windsurf Cascade AI chat and was very intentional about the background I gave it. I explained what the system was doing at a high level, what kind of analysis I needed, and what the final deliverables were expected to look like. The more precise I was up front, the better the responses got.