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Show HN: Agentic interface for mainframes and COBOL

33 pointsby sai18today at 5:10 PM14 commentsview on HN

Hi HN, we’re Sai and Aayush, and we’re building Hypercubic (https://www.hypercubic.ai/), bringing AI tools to the mainframe and COBOL world. (We did a Launch HN last year: https://news.ycombinator.com/item?id=45877517.) Today we’re launching Hopper, an agentic development environment for mainframes.

You can download it here: https://www.hypercubic.ai/hopper, and you can also request access and immediately get a mainframe user account to play with.

There's also a video runthrough at https://www.youtube.com/watch?v=q81L5DcfBvE.

Mainframes still run a surprising amount of critical infrastructure: banking, payments, insurance, airlines, government programs, logistics, and core operations at large institutions. Many of these systems are decades old, but they continue to process enormous transaction volumes because they are reliable, secure, and deeply embedded into business operations.

A lot of that software is written in COBOL and runs on IBM z/OS. The development environment looks very different from modern cloud or Unix-style development. Instead of GitHub, shell commands, package managers, and CI pipelines, developers often work through TN3270 terminal sessions, ISPF panels, partitioned datasets, JCL, JES queues, spool output, return codes, VSAM files, CICS transactions, and shop-specific conventions.

TN3270 is the terminal interface used to interact with many IBM mainframe systems. ISPF is the menu and panel system developers use inside that terminal to browse datasets, edit source, submit jobs, and inspect output. It is powerful and reliable, but it was designed for expert humans navigating screens, function keys, and fixed-width workflows, not AI agents.

A simple COBOL change might require finding the right source member, checking copybooks, locating compile JCL, submitting a job, reading JES/SYSPRINT output, interpreting condition codes, patching fixed-width source, and resubmitting.

Much of this work is so well-defined and repetitive that it's a good fit for agentic AI. To get that working, however, a chatbot next to a terminal is not enough. The agent needs to operate inside the mainframe environment.

Hopper combines three things: (1) A real TN3270 terminal, (2) Mainframe-aware panels for datasets, members, jobs, and spool output, and (3) An AI agent that can operate across those z/OS surfaces.

For example, here is a tiny version of the kind of thing Hopper can help debug:

  COBOL:

   IDENTIFICATION DIVISION.
   PROGRAM-ID. PAYCALC.

   DATA DIVISION.
   WORKING-STORAGE SECTION.
   01  CUSTOMER-BALANCE     PIC 9(7)V99.

   PROCEDURE DIVISION.
       ADD 100.00 TO CUSTOMER-BALNCE
       DISPLAY "UPDATED BALANCE: " CUSTOMER-BALANCE
       STOP RUN.


  JCL:

    //PAYCOMP  JOB (ACCT),'COMPILE',CLASS=A,MSGCLASS=X
    
    //COBOL    EXEC IGYWCL
    
    [//COBOL.SYSIN](https://cobol.sysin/) DD DSN=USER1.APP.COBOL(PAYCALC),DISP=SHR
    
    [//LKED.SYSLMOD](https://lked.syslmod/) DD DSN=USER1.APP.LOAD(PAYCALC),DISP=SHR

A human would submit this job, inspect JES output, open `SYSPRINT`, find the undefined `CUSTOMER-BALNCE`, map it back to the source, patch the member, and resubmit. Hopper is designed to let an agent operate through that same loop autonomously.

Hopper is not trying to hide the mainframe behind a generic abstraction, and it's not a chatbot. The design principle is simple: preserve the fidelity of the mainframe environment, but make it accessible to AI agents.

Sensitive operations require approval, and the terminal remains visible at all times.

Once agents can operate inside the mainframe environment, new workflows become possible: faster job debugging, automated documentation, safer code changes, test generation, migration planning, traffic replay, and modernization verification.

We’re curious to hear your thoughts! especially from anyone who has worked with mainframes, COBOL or has done legacy enterprise modernization.


Comments

cube00today at 7:52 PM

Built by leading minds behind the world's most advanced AI and technology - Our team unites top researchers, engineers, and strategists from pioneering companies and institutions [...]

https://www.hypercubic.ai/company

It would be good to understand more background of the executive and heads of department on the about page to help understand who these top researchers, engineers, and strategists are.

There are currently no names on the about page, not even the co-founders are listed there.

It seems:

* Sai was a lead machine learning engineer at Apple for 17 months

* Aayush was a senior software engineer at Apple for 8 months.

sixtyjtoday at 6:52 PM

If it ain't broke, don't fix it. So letting an LLM loose on a mainframe is like letting a fox into a henhouse. :)

show 2 replies
ASalazarMXtoday at 6:14 PM

What was the training data? While there are open source projects for mainframes, most high-quality and battle-tested COBOL code bases are likely proprietary.

Also, will it be trained on the code base it sees? Most companies would be opposed to sharing their IP.

Edit: according to the website, the model won't be trained with your data.

650REDHAIRtoday at 7:00 PM

US banks and creditors desperately need this yesterday.

show 2 replies
happyPersonRtoday at 6:29 PM

Hopefully Llm while it may not allow immediately for like 100% ready to go financial services code

Maybe it gives us good tests ?

That alone for something on cobol might be worthwhile

schlauerfoxtoday at 5:31 PM

Is this available to install on Hercules emulator for hobbyists? For people unfamiliar with Mainframes, check out the moshix youtube channel.

show 1 reply
artem_amtoday at 8:47 PM

[dead]

squid-protocoltoday at 8:47 PM

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