I felt the same, SWE with 20 years experience. Absolutely none of this is relevant to anything I’ve been paid to do for my whole career.

If someone on my team was doing things this unusually they’d probably be let go.

I use ChatGPT for similar. I can spend time looking into various languages/libraries I don't use often and figure it out. Or I can ask an LLM and have an answer I can validate in the same amount of time I start browsing search results.

You're missing the point. These LLM which are replacing "junior developers" aren't what's going to be used for "hard or even medium problems" because you don't just give junior developers "hard problems" to solve in isolation. Now try to give some thought as to the types of problems junior developers are suited to solve. Now apply ChatGPT to those scenarios.

I never said these problems were hard.

But... they're things that require research. Do you know how to loop through all of your Apple Notes using AppleScript off the top of your head?

That research isn't free: it takes time.

As someone who hasn't done much work with AppleScript before, I would guess it would take me about half an hour to figure out how to do this. But there's a risk that it might take longer.

So the sensible thing is probably not to take on that project at all! I don't care enough about solving it to invest the research time.

But the time taken to chuck a prompt through GPT-4 and then test the results to see if it works is less than a minute.

I wrote more about how this is encouraging me to be more ambitious with my projects here: https://simonwillison.net/2023/Mar/27/ai-enhanced-developmen...

100% agree with this. I used ChatGPT earlier today to give me networkx code for computing the connected components of a graph and visualizing the graph. This isn't hard to do, but I don't use networkx all that often and I forget the exact API. I could go to read documentation and piece together an example myself, or I could ask ChatGPT for an example, which tends to be much faster than doing the former.

I Googled "applescript loop through apple notes" and this was the first result: https://apple.stackexchange.com/questions/225938/notes-scrip.... Looks exactly like what ChatGPT came up with for you minus the dialog.

I then Googled "applescript print to console" and got this: https://stackoverflow.com/questions/13653358/how-to-log-obje... ; admittedly this answer took a few minutes to read through, but the second most upvoted answer recommended using log, which your ChatGPT-developed solution (eventually) used.

This all took me < 5 minutes.

Yeah, those StackOverflow posts are the perfect illustration of why I find ChatGPT so much useful for this kind of thing.

Compare them to my original transcript. They don't provide me with enough information: how do I actually run that code?

I got ChatGPT to split me out a zsh script, which caused it to show me how to use "osascript -e ".

I think Simon has plenty of experience solving hard problems: https://simonwillison.net/about/

That's irrelevant, we are taking about solving hard problems with ChatGPT none of the examples are even slightly complex.

Not sure where this idea that my post was about "hard problems" came from.

I'm excited about using ChatGPT/GPT-4 because it takes the time I need to figure out how to do something "easy" down from half an hour to sub-5-minutes.

Dude, simonw invented Django web framework

They’re probably not hard and medium problems but if you can take care of these easy and medium problems with chatgpt, that saves so much bandwidth to have time to tackle the fun and “hard” problems.

Also, take a look at the problems and projects simonw actually tackles.

You don't get the point.

I work in Deep Learning Research. I don't get any help at all from ChatGPT for my core job. Copilot spews gibberish, too.

I do get enough help about peripherals. Some weeks ago, I needed help with Flask and HTML deploying a model to show it to stakeholders. (I learned Flask some years ago, but not needing it regularly, I forgot enough.)

The data cleaning, preprocessing, model training, making it better than humans were the hard tasks.

Deploying a Flask app with a simple HTML frontend was the easy task. But easy != free. It would have required 2-3x more time researching how to do exactly what I needed, which I did with Copilot and ChatGPT in ~1 hr.