Post by @ivan@piefed.social

2026-10-27 07:57 UTC

I teached embedded programming for a while and students were to find out that AI often failed miserably at our tasks. And the funny thing is that when I tried it myself to see if it’s that bad at given tasks - I explained the task like I would explain to a student, and actually got a decent result. It all simply comes down to the fact that AI won’t really help you if you can’t do without it. So I double that making the guy pass some guidelines on styling the code to Claude should at least make the code less shit to debug.

Replies (2)

@squaresinger@lemmy.world 2026-10-27 09:28

This here. It makes a huge differenche which AI you use and what you do with it. “Free ChatGPT, make me an app” is going to result in pretty bad code. “Claude Opus 5.5, here’s a project with a well-defined agents.md, coding guidelines, tests, …, please analyze this well-defined ticket and grill it. Together we knock out the remaining kinks in the ticket. Then put the analysis into .md files, and I review that you actually understood what you are supposed to do. Then in a new session read the .md files and start the implementation, always stopping and asking if something’s unclear. Then in a new session let’s review the result together, before I send it on to the next developer to do a pull request review.” This results in actually pretty good code that often catches issues that a human dev alone wouldn’t.

Open ##5268347
@cass1312@piefed.blahaj.zone 2026-10-27 13:39

I took an arduino class after already having programmed for years, and at one point the teacher wanted everyone to use chatgpt to write code for an assignment that was basically “run a motor while a button is pressed and stop it when it’s released”. The code for that is an extremely simple one liner, and if phrased correctly an llm could definitely spit out that single line, but everyone seemed to have it generate like 10+ line blocks with a bunch of if statements and stuff.

Open ##5270960