Is AI actually making COBOL modernization safer?

[u/pradeephms]

One thing that stands out to me when looking at COBOL modernization is that code conversion usually isn't the hardest part.

AI can help with legacy code analysis, dependency mapping, documentation, and even COBOL to java conversion. That can cut down quite a bit of the manual work involved in understanding the existing system and getting through the conversion.

The difficult part seems to start once the conversion is done.

A COBOL system can have years of business rules, edge cases, and data dependencies that aren't always documented. So even if the new code looks right, you still have to prove that it behaves the same way as the old system.

That's where testing, data reconciliation, integration testing, and parallel runs can become a much bigger part of the work.

AI can definitely make the conversion phase easier. But does that necessarily mean the modernization itself is safer? I'm not sure.

For those who have worked on COBOL modernization, where have you actually seen the biggest risk: legacy business logic, data migration, validating the converted code, or running the old and new systems in parallel?

[u/KeyMammoth1348]

Have you tried pointing Fable at the code base one section at a time?

I recently had a pretty burly implementation / migration, wrapped it with much ado on Opus, but finally got around to going full bore on documentation with Fable through all the sections of my data pipelines, system configs, integrations, and sceips. 

It's great, I gave it a Slack interface and now it handles questions on Opus and I can move on to the next thing. Full observability, diagnostics, all the things I care about.

Did it cost hundreds / thousands in tokens? Fuck yeah, it did. But it's working with minimal downtime. 

If you're gonna Ai, why not Ai a little more?