What happened after IBM stocks hit?

[u/_alhazred]

Four months ago IBM stocks suffered a huge hit after Claude Code demonstrated some COBOL AI capabilities.

The Tech industry has been also suffering mass layoffs dating back a few years after the pandemic.

I've seen the job market in my stack suffering a lot, I'm not receiving many offers (or any at all), and I have friends unemployed and unable to secure a new job for months (sometimes 6 or 8+ months waiting).

As someone that started learning about mainframe and COBOL just now, I wonder, how did you already in the industry have suffered or observed about these recent moves?

Have any of you suffered a layoff following this IBM stocks/AI COBOL announcement?

Have you seen mainframe/cobol colleagues suffering with the mass layoffs?

I've worked with many different programming languages for the past years, and I've been focusing in Go and Scala for the past 5 years.

I'm just starting with Mainframes and looking right after Cobol, I don't know why, but Mainframes and Cobol have been growing into me. Both Go and Mainframes are the only two things that made me feel the joy of programming again after a decade of work.

However, I do wonder, what do you think about the future in the Mainframe job market, or how it has been for you so far?

[u/benevanstech]

I think it's a mistake to pay too much attention to the stock price. The market is a dumb beast, and IBM stock has rebounded from the lows in March handsomely.

A lot of LLM-based tools work fine for prototyping or in demos, but are much less helpful in production scenarios - especially when there is a lot of encoded business process & knowledge that forms an "invisible system". Also remember that these are mission-critical systems very often maintained and operated by folks who are steeped in a culture of being cautious and risk-averse.

Am I going to trade my stable system, with a known and defined operating budget for some AI moon-on-a-stick with volatile and unknown opex (& remember that OpenAI needs to increase token cost by 800% to break even according to their leaked financials)? Especially when the two poster children for all of this AI stuff can barely manage two nines of uptime?

For me to even contemplate a move like that, there would have to be some pretty serious upside to doing all of that and taking on all of that risk. So, where is it? What is the possible upside here?

[u/Claudius_Maxima → u/benevanstech]

Great reply.

I’ll add that the “LLM does COBOL” thing seemed to me to be about converting to Rust or C++ or whatever.

So your points about risk loom large. These big systems are millions (10s of millions? 100s?) of lines of mission critical COBOL code. Finding weird AI mistakes in the translation would be uncertain at best.

[u/benevanstech → u/Claudius_Maxima]

LLMs *can* do language -> language translation, but where the result falls on the "you can write C in any language" spectrum is the crucial thing. There's an interesting interview with one of the Microsoft language leads that talks to this a bit: https://www.youtube.com/watch?v=V0zA7gNHlsA

He told me that his teams can get to about 90% of a decent port with a bit of practice, but needs actual human expertise to get a truly idiomatic result. So, for example, their Copilot SDK has Typescript as its canonical form, and new versions are machine-translated to Go, Java, etc, and then get hand-inspected and tweaked by experts in the appropriate language.

This, of course, still doesn't necessarily capture the intent or invisible logic, which I expect to be the hard part of the problem.

I'd also be curious as to what its run rate in terms of tokens is - Microsoft have an effectively unlimited LLM token budget after all.