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I’m not a full-time COBOL dev, but I’ve worked adjacent to mainframe systems
(bank integrations, legacy batch jobs, and data pipelines). From what I’ve seen, LLMs aren’t really a threat to COBOL roles right now.
They can help explain unfamiliar code, summarize programs, or assist with
documentation, but they struggle with the things that actually matter most:
institution-specific conventions, decades of undocumented business logic,
and the operational context around jobs, datasets, and JCL. In practice, the hardest part isn’t writing COBOL syntax, it’s understanding
why a program exists, what assumptions it encodes, and what will break if
you change it. That knowledge tends to live in people, not in code comments. So AI feels more like a force multiplier for experienced engineers rather
than a replacement. If anything, it might reduce the barrier for newer
engineers to approach these systems, which could be a net positive given
how thin the talent pool already is. |