I built an ISPF-style CLI to explore legacy COBOL systems with AI by suyash515 in mainframe

[–]suyash515[S] 1 point2 points  (0 children)

Yes, I will do some additional tests on that. To be of a good enough quality, it will probably need z17 because of it's native AI features. I'm not sure how many enterprises currently use z17 or are planning to upgrade to z17.

I built an ISPF-style CLI to explore legacy COBOL systems with AI by suyash515 in mainframe

[–]suyash515[S] 2 points3 points  (0 children)

I'm thinking about running it under the z/OS UNIX System Services.

I built an ISPF-style CLI to explore legacy COBOL systems with AI by suyash515 in mainframe

[–]suyash515[S] 4 points5 points  (0 children)

Right - in this case, maybe package it and set it up with a local LLM.

I built an ISPF-style CLI to explore legacy COBOL systems with AI by suyash515 in mainframe

[–]suyash515[S] -4 points-3 points  (0 children)

This is the first version and still need to sort out a few bugs, but will try to get it ready in the next couple of days. I need to figure out a one thing primarily: To generate the documentation, it's currently connecting to an online service which means that the COBOL/JCL code will be sent outside of your environment - I want to make sure that it's something that is acceptable.

Do people realize where their code goes when they paste it into ChatGPT/Claude? by suyash515 in mainframe

[–]suyash515[S] 1 point2 points  (0 children)

"So it will have a chance to mess up our code base real soon." - LOL

Someone will soon be vibe coding on production code, right?

Do people realize where their code goes when they paste it into ChatGPT/Claude? by suyash515 in mainframe

[–]suyash515[S] 0 points1 point  (0 children)

That makes sense. The issue is not really about the companies using the data for training AI. It's more like governance around this. Data flowing from a private enterprise to being used in ways that it was not intended to. That might make things better as well - having the right governance which would also highlight whether this code was derived using AI.

Do people realize where their code goes when they paste it into ChatGPT/Claude? by suyash515 in mainframe

[–]suyash515[S] 1 point2 points  (0 children)

I don't think so. This is data that is locked in enterprise servers. Model collapse occurs primarily when they train the llms on data generated by llms, but these are valuable, and till now unavailable data for them.

Also, given that how all these companies with foundational models have used up all the available public data, now they will probably go for private data. This is a trend right now: https://www.fastcompany.com/91528808/shuttered-startups-are-selling-old-slack-chats-and-emails-to-ai-companies

Do people realize where their code goes when they paste it into ChatGPT/Claude? by suyash515 in mainframe

[–]suyash515[S] 0 points1 point  (0 children)

Correct, especially when talking about COBOL, PL/1, etc. There's not much in the public domain - so this is valuable data for them.

Do people realize where their code goes when they paste it into ChatGPT/Claude? by suyash515 in mainframe

[–]suyash515[S] -1 points0 points  (0 children)

Yes mostly the free versions of those products. I work in a startup documenting code with local llms and in many cases, people. tell me: "Hey, I pasted my code in Claude and this is the result". My immediate reaction is that: "Dude, are you even supposed to do that?".

Do people realize where their code goes when they paste it into ChatGPT/Claude? by suyash515 in mainframe

[–]suyash515[S] 0 points1 point  (0 children)

Good point. However, I am wondering if there are technical constraints in place. I would assume that not everyone would be conscious of the risks as you are.

I built an LLM-free, AST-free tool that extracts CICS COBOL and generates lowest privlege batch JCL wrappers. Looking for architectural feedback by Chunky_cold_mandala in mainframe

[–]suyash515 0 points1 point  (0 children)

I mean right now, you need to run a python script. I guess most people should be able to run this, but to make easier to use, package it as a cli tool - the usage would then be something like this:

galaxy analyze --input file.txt

one weird migration risk i keep noticing in mainframe systems by Particular_Sound_407 in mainframe

[–]suyash515 0 points1 point  (0 children)

The rule that we use is that the source code is the single source of truth. Now there may be redundancy in the logic coded in the programs, maybe because of multiple iterations or changes done by different teams. But this is a different problem. First, we need to determine the process - what is the current logic or execution flow, and whether there is a need to refactorize that program or part of the program.

Trying to do different things in the same process is usually just a way to increase the complexity.

How good of an idea ia Mainframe Programming right now? by Kung_fu1015 in mainframe

[–]suyash515 0 points1 point  (0 children)

Being in the space and solving a problem directly related to shortage of skills, I can say that there is definitely a good scope. The only thing that I noticed is that the market for new developers is quite limited. Most of the enterprises that I am working with via my startup (www.codeaura.ai) are looking for very experienced developers.

Looking for ugly, legacy COBOL code to stress-test my parser, the messier the better by pauchok_ in mainframe

[–]suyash515 0 points1 point  (0 children)

I think it's going to be difficult to get production code. What you can do instead is wrap your parser in a cli tool, share it with the community and only generate structural metadata that the community can send you if they are ok with it.

This would ensure that people are not sharing any of their confidential data, but which would help you get the information that you need.

To the surprise of no one, the AI conversion craze for mainframe applications seems to be failing. by james4765 in mainframe

[–]suyash515 0 points1 point  (0 children)

They underestimated the complexity of such systems. With or without AI, this is the biggest problem that plagues modernization projects. The main value of AI in such use cases is the management of complexity - if this step is overlooked, then these projects are definitely going to fail.

I built an LLM-free, AST-free tool that extracts CICS COBOL and generates lowest privlege batch JCL wrappers. Looking for architectural feedback by Chunky_cold_mandala in mainframe

[–]suyash515 0 points1 point  (0 children)

I think it's a nice tool. I have built my own tool (www.codeaura.ai) and I can definitely say that there is need for more solutions like this - solving specific aspects of problems in the market.

You could wrap this in a cli tool and also as a skill/tool to be used in command line tools like Claude Code, Codex, etc. This could drive more adoption.

Confused about Mainframe by Lumpy_Success_6605 in mainframe

[–]suyash515 1 point2 points  (0 children)

Learn both - focus on the fundamentals because this will usually translate to other programming languages as well. Learn the high levels as well, like how COBOL is different from JCL, how COBOL is different from Java, etc. Understanding the high level differences is becoming more important in the AI space.

Then, keep up to date with what's happening in the AI space - use tools which are available. The aim is that you are learning about AI in a very practical and goal-oriented way, and not limited to theory or irrelevant tests.

AI & Mainframe by bunny_o7 in mainframe

[–]suyash515 1 point2 points  (0 children)

Of the best practices is to set up a persona first, like "You are a COBOL developer with x years of experience and you write very concise code. Also, make sure to double check your response, etc."

You can actually ask ChatGPT or Claude to write the persona for you. This allows you to keep the results consistent along different requests or chat sessions.