Regular doors with handles don’t fail open, there is just an Intuitive and common way to manually open them, which seems like the short coming here.

You know it’s funny how many times I’ve heard that “it’s just predictive text algorithms!” As a dismissal that I’m beginning to think we’re just predictive text algorithms.

but for beginners? They will have a lot of bugs in their code.

Everyone has lots of bugs in their code, especially beginners. This is why we have testing and qa and processes to minimize the risk of bugs. As the saying goes, “the good news about computers is that they do what you tell them to do. The bad n was is that they do what you tell them to do.”

Programming is an iterative process where you do something, it doesn’t work, and then you give it another go. It’s not something that senior devs get right on the first try, while beginners have to try many times. It’s just that senior devs have seen a lot more so have a better understanding of why it probably went wrong, and maybe can avoid some more common pitfalls the first time around. But if you are writing bug free code in your first pass, well you’re a way better programmer than anyone I’ve met.

Ai is just another tool to make this happen. Sure, it’s not always the tool for the job, just like IoC is not always the right tool for the job. But it’s nice to have it and sometimes it makes things much easier.

Like just now I was debugging a large SQL query. I popped it into copilot, asked if to break it into parts so I could debug. It gave a series of smaller queries that I then used to find the point where it fell apart. This is something that would have taken me at least a half hour of tedious boring work, fixed in 5 minutes.

Also for writing scripts. I want some data formatted so it was easier to read? No problem, it will spit out a script that gets me 90% of the way there in seconds. Do I have to refine it? Absolutely. But if I wrote it myself, not being super prolific with python, it would have taken me a half hour to get the structure in place, and then I still would have had to refine it because I don’t produce perfect code the first time around. And it comments the scripts, which I rarely do.

What also amazes me is that sometimes it will spit out code and I’ll be like “woah I didn’t even know you could do that” and so I learned a new technique. It has a very deep “understanding” of the syntax and fundamentals of the language.

Again, I find it shocking that experienced devs don’t find it useful. Not living up to the hype I get. But not seeing it as a productivity boosting tool is a real head scratcher to me. Granted, I’m no rockstar dev, and maybe you are, but I’ve seen a lot of shit in my day and understand that I’m legitimately a senior dev.

And before stack overflow, we used books. Did we need it? No. But stack overflow was an improvement so we moved to that.

In many ways, ai is an improvement on stack overflow. I feel bad for people who refuse to see it, because they’re missing out on a useful and powerful tool.

Which is, of course, true for every source of information that can point you in a direction.

I’m a senior dev, and copilot as a productivity tool usually pays for the monthly license multiple times per week.

Whenever I hear someone say it’s useless, that tells me they are either some godlike dev who knows everything already (lol), they haven’t actually used it, they are not good at integrating new tools into their workflow, or they simply haven’t learned how to use it yet.

If I sort this community by top for the week, this is the top post.

The second post hilariously concludes “All work is degrading.”

The other poster is either speaking from a place of ignorance, as they’ve never really used it, of they just aren’t smart enough to learn how to use a new tool.

As much as middle management sucks, devs blaming management for their own inability to learn is almost on the same level.

I was lucky enough to get in on my company’s beta test for copilot.

When I hear people say it’s bad, all that tells me is that they are either completely ignorant and have never really used it, or they aren’t good at learning how to use new tools.

I’ve worked in a few places, all with senior engineers, including myself as a senior engineer, all of which the senior engineers spent most of their time actually engineering. If I went somewhere as a senior and was told I was going to be in meetings all day, I would quit because that’s management, not engineering.

We do standups twice a week. At worst they run a half hour for my team of about 10 people. Usually we’re done in 15-20 minutes. Please tell me it’s just an absolutely made up joke that you have an hour and 15 minutes of stand up meetings every day. I would shoot myself.

My 100 year old house has marks on the floor that look like it was worn from a door swinging. Very distinctive arc pattern. Like it was there for many years and was under frequent use.

The problem is that there’s no door there, just a wall, which is also the edge of a dormer…so if there were a door there it would just open out onto a sloping roof.

Every time I register it I contemplate why it’s there and wtf happened.

A crowd of 10,000 people means fuck all compared to 158,429,631.

I agree that it would be a bad data set, but not because it is too small. That size would actually give you a pretty good result if it was sufficiently random. Which is, of course, the problem.

But you’re missing the point: just because something is obvious to you does not mean it’s actually true. The model could be trained in a way to not be biased by our number choice, but to actually be pseudo-random. Is it surprising that it would turn out this way? No. But to think your assumption doesn’t need to be proven, in such a case, is almost equivalent to thinking a Trump rally is a good data sample for determining the opinion of the general public.

“we don’t need to prove the 2020 election was stolen, it’s implied because trump had bigger crowds at his rallies!” -90% of trump supporters

Another good example is the Monty Hall “paradox” where 99% of people are going to incorrectly tell you the chance is 50% because they took math and that’s how it works.

Just because something seems obvious to you doesn’t mean it is correct. Always a good idea to test your hypothesis.

Windows bad, ai bad. Upvote. Thought isn’t a big consideration here.

People are able to tell apart BS, though.

Please help me be optimistic. Why do you think this is the case? No matter where I go I see mostly confirmation bias and the lack of even the most basic level of critical thought.

I was going to joke “wow, a whole 4 years?”

These threads drive home the point that a GUI of some sort is far superior for most users. I use git kraken, but in the past I’ve used git extensions as well, and I take advantage of so much more git has to offer than pretty much everyone here.

I swear people just want the cli to be better so they claim it is, but I really don’t get how. Especially for quickly scanning the repo, doing diffs, commiting partial files, history, blame, etc.

Yeah, I was lucky that I snuck into my company’s pilot program for it.

I’m impressed at how often it predicts what I’m about to do. The code almost always needs a slight bit of editing, but it almost always at least shaves a bit of time off of whatever task I was doing.

I no longer go straight to stackoverflow, I always ask the copilot first. Sometimes even just phrasing the question in natural language, something I wouldn’t do it trying to find it via search or stackoverflow, is kind of like rubber duck debugging, and I’ll come up with the answer while writing it out.

I was originally a chip designer. Then I shifted into embedded development. Now I’m mainly a C# guy.

But when I shifted into embedded development, I also shifted into doing power engineering. I grabbed a couple of books on the topic at hand, taught myself a lot, and designed the electronics to meet the need. We sold the product to city utilities.

I remember one time I was in a room with probably 10 engineers from one of the utilities. After having described the product to them, and went through a lot of our settings and stuff, I was explaining the difference between two of algorithms we put in (because different utilities use different algorithms, and I just wanted one device that could do both). At some point I was like “which of the two algorithms do you use?” and one responded “well, which do you recommend?” So I talked about why I thought one was better than the other.

They all started looking at each other and nodding and saying “Yeah, that’s the one were going to use.” I realize I could have said anything at that point and they would have agreed. They thought I was expert. And that was my “last two frames” of this comic moment.

Now as a senior dev, I’ve seen enough shit to realize that most people have no idea what is going on, and are flying by the seat of their pants. So I figure my ignorance is a little less than theirs, and that gives me a lot of confidence, but I also realize that I can learn a lot from most people.