[xwdv]

Spare me the shitty analogies. We write shell scripts because it’s cheap, fast, and the behavior is very predictable.

Like it or not, an AI’s behavior is a black box and can’t be “proven” to execute exactly the same every time for the scenarios you are targeting.

A shell script will do exactly what it has been written to do every time, unless tampered with. And if changes need to be made, it can be done quickly without need for retraining, god knows how long that would take for an AI to learn something new. God help you if you need to maintain “versions” of your AI, trained for different things.

Face it, AI are pointless and slow for certain classes of problems.

[com2kid]

> A shell script will do exactly what it has been written to do every time, unless tampered with.

Or unless some magic environment variable changes, or one of the runtime dependencies changes, or it is run on a different operating system, or permissions aren't setup right, or one of its tasks errors out.

Shell scripts are digital duct tape, the vast majority of shell scripts do not come close to being reliable software.

> god knows how long that would take for an AI to learn something new

Did you watch OpenAI's demo yesterday? They pasted in new versions of API docs and GPT4 updated its output code. When GPT forgot a parameter, the presenter fed back the error message and GPT added the parameter to the request.

[xwdv]

AI proponents are missing the point. Anything you write to make an AI produce something is basically code. Docs are code.

You don’t have to feed a developer code or docs, you can give them a high level idea and they’ll figure it out on their own if you want.

[echelon]

That code will eventually fall away.

The big thing everyone in this single thread is missing is that AI is a metaheuristic.

I wouldn't expect to use AI to run_script.py. That's easy. I'd expect it to look at the business signals and do the work of an intern. To look at metrics and adjust some parameters or notify some people. To quickly come up with and prototype novel ways to glue new things together. To solve brand new problems.

[xwdv]

To do the work of an intern an AI must go on Jira, read a ticket, then find the appropriate repositories where code needs to be modified, write tests for its modification, submit for code review, respond to feedback in code review, deploy its changes.

It’s not there yet.

[com2kid]

> To do the work of an intern an AI must go on Jira, read a ticket, then find the appropriate repositories where code needs to be modified,

The problem is Jira workflows are designed for reporting results to upper management.

If the cost savings / productivity benefits[1] are there, new workflows will appear.

[1] Then again there are huge productivity benefits to be gained by simplifying existing Jira workflows, yet such steps are not taken.

[echelon]

This feels achievable in five years.

[JohnFen]

It always feels achievable in five years. People were saying exactly this 30 years ago.

Sooner or later it may (or may not) be a true statement, but it's awfully hard for me to say that it's any different right now than it has been before.

[Analog24]

What developer working on anything meaningful does not rely on documentation? You certainly have to make the documentation available similar to how you would have to make it "available" to an LLM. I think you might be missing the point about what the potential use-cases for these systems are.

[qup]

> A shell script will do exactly what it has been written to do every time

I wish I lived in that universe.

[njarboe]

Correct. So are humans.