One of the best bosses I ever had was an electronics engineer (I’m software). There are a lot of shared concepts between engineering disciplines. I enjoyed working with hardware engineers and getting to see how they approach problems.

It’s more like:

Start with some AI generated code.

AI code fails to compile immediately, if you’re lucky.

If not, spend three days trying to find some really stupid bug.

Delete the AI code and write it yourself.

This is a Repost

Big Beautiful Code

Management: “We’re only going to hire ‘full stack’ devs from now on.”

Also Management: “Why is this page taking 37 seconds to load?”

There comes a point, somewhere late in the evening after my ADHD meds have worn off, where it’s more productive to not do any coding. If I do, I’m just going to end up throwing most of it out tomorrow because it’s a bunch of bug littered spaghetti.

Unfortunately, I also solve most of my big problems when I’m not staring at a screen. After which I have to resist the temptation to go work on it so I don’t make a big mess. It’s some kind of cruel irony.

QA: “Yeah, Hi. Can you look at this defect ticket?”

Reading ticket details…

Me: “Let me guess. Is [whatshisname] responsible for this?”

QA: “Yeah.”

Me: “Get him to fix it.”

QA: “I tried. Like four times.”

Me: Sigh “I’ll take care of it.”

QA: “Thank you!”

Remember when “The Cloud” was going to put everyone in IT out of a job?

Database performance tuning is its own little world and there are lots of complexities and caveats depending on the database system.

With MSSQL, the first thing you should check is your indexes. You should have indexes on commonly queried fields and any foreign keys. It’s the best place to start because indexing alone can often make or break database performance.

“Full Stack Dev” AKA Backend Dev who knows just enough about CSS to be dangerous.

Real talk: I wish more orgs place a high value on QA. A good QA team is worth it’s weight in gold and helps prevent a lot of stupid mistakes.

No good deed goes unpunished.

One time I worked on a team that had a ridiculously high defect rate. Stuff was constantly getting kicked back from QA. Management kept piling on all kinds of convoluted processes to try to reduce the number of defects which only made things worse.

I started really hammering the need for doing a root cause analysis as part of bug/defect tickets. Don’t just fix the bug. Make sure you understand what caused it and link the bug ticket to the ticket that caused it.

Big surprise (not really), 90% of the bugs and defects were being caused by like 3 people.

Your comment made me think of some of the PM’s whining about adding one story point for doing an RCA because apparently it’s better to just ignore the problem and keep pumping out shitty broken code as fast as possible.

Yes. Because they’ll store everything in MongoDB.

PO: “Why does it seem like it takes a really long time to develop new features?”

Dev: “I’m glad you asked! We’ve got this piece of code (points at smoldering pile of spaghetti) that literally has to be changed every time we do anything. The person who wrote it has been gone for like four years. No one knows how it works and it’s central to the entire application. I would estimate that this easily doubles the time it takes to work each ticket. I’ve created a set of stories to rewrite this code. We just need your approval to bring it into an upcoming sprint.”

PO: “Can’t… Hear… Breaking… Up… Bad connection…”

Dev: “Uhhh… This isn’t a Teams meeting. You’re sitting in the room with us right now.”

PO: …

Dev: “We know you’re still here even if you’re not moving.”

PO: …

Bet you $1,000 the credentials are stored in plain text.

My first thought when reading the OP was “Who the hell touches anything on a Friday evening? That sounds like a good way to end up working the entire weekend.”

Nearly every time I ask ChatGPT a question about a well established tech stack, it’s responses are erroneous to the point of being useless. It frequently provides examples using fabricated, non-existent functionality and the code samples are awful.

What’s the point in getting AI to write code that I’m just going to have to completely rewrite?

Don’t worry. We’ll totally fix all of them soon. Promise. Hand to God. They definitely will not be here five years from now.

So basically the same as a discard in C#?