[yawnxyz]

I've been able to use phind + Co-pilot to learn python, build and deploy a FastAPI service on the OpenAPI spec, without really knowing any of those things. Just ask GPT-4 how FastAPI works, how OpenAPI works, and ask it to format and write your YAML for you.

It's an amazing TA — better than any I've had in undergrad, and way better than office hours, where your prof don't really care and wants to go back to their research.

I don't have to read through docs for hours and build a mental model — that stuff is taken care of by asking Chat.

Now I'm learning how to deploy my own pytorch model for a real-life use case, by using a combination of SAM and Roboflow. I have absolutely no background in any of these, I just ask it dumb questions until I get it. It's also helping me understand how and when to use hashing and merkle trees for a related project.

For me this is xInfinite because I'm doing stuff I'd been too lazy to learn and understand (e.g. vision).

And I'm at the core a UX / product designer and absolutely not an engineer.

[darkteflon]

This has been my experience too. I’ve seen a few responses in here comparing time-to-write x lines of code alone vs with GPT, but imo it’s not that stuff that makes the biggest difference (although I do like that stuff too).

If creating something complex and novel (for you, at least) is to be constantly pushing at the edges of what you know, your ability to progress that work is gated by a constant flow of challenges that are - to you - insurmountable without the right knowledge. Whether it’s an incantation or a mental model or whatever: you need that key to open that gate.

ChatGPT - and I want to confine my claims to GPT4 because I have found it much better than Turbo3.5 in this regard - is a tool that has the potential to take each of those gates, and tell you - converse with you until you understand - what you need to, to progress. That feels incredibly powerful, and I wouldn’t hesitate to call that a 10x improvement for those - very common - scenarios.

As a result, I have found the same thing happening that Simon Willison has been talking about - and that parent also mentioned: you’re in a position to tackle a much wider array of challenges than before. Stuff you would’ve written off as too time-consuming is suddenly a few minutes work.

I dunno, to me, this whole experience is completely magical. Honestly can’t understand how people remain underwhelmed by what’s happening. I always want to say “hey, look over here! This is _amazing_!”

I think we’re still in the stage where people are figuring out how to use a powerful new tool, and there’s quite a bit of “trying to drill holes with a hammer”. For the types of job at which this particular tool excels, until now we’ve largely had to do it by hand.

[mk89]

If you have no experience whatsoever, how do you know what to avoid? I can tell that phind is a great educational tool, but without the proper knowledge it can give you answers you might not know how to cope with, and you need to ask and ask again and again until you get half a convincing answer.

It's like reading exclusively the accepted answer on stackoverflow. There are many reasons why that's wrong: it can be outdated, it might have been upvoted simply by the "wrong" people, etc.

I am honestly very scared by the amount of people that never wrote one line of code and suddenly can "deploy" things. Not because I am afraid for my job, but simply because in any language and framework there are implicit things to learn which take years to master, and suddenly everyone knows how to build a product -> why does it take our engineers so long! Look, here is the code!

Yeah, that kind of "mindset", I am afraid of. Wrong tool in the wrong hands.

As long as you do it for hobby, I wish you all the fun of the world.

[MrJohz]

That's an interesting review of the technology, because to me what you've described raises a lot of red flags. I've read - and written! - plenty of code where the author clearly hasn't taken the time to learn the tools that they're using, and just hacked around in circles until they've got everything to work. And that code is usually bad - difficult to extend or change, poorly abstracted, difficult to understand, etc. It has its place, and I understand why people (including myself) write like that sometimes, but I wouldn't want it to become the norm.

It sounds like these sorts of tools are making it easier to get started with new ideas, but I'm intrigued to see what long-term maintenance is going to look like.

[kaba0]

> It's an amazing TA — better than any I've had in undergrad, and way better than office hours, where your prof don't really care and wants to go back to their research

It may be for trivial things (under which I mean that there is basically a verbatim answer on the internet that it had in its training data), but I don’t think it’s a good idea in general — if you talk with it on any topic that you are knowledgeable on, you notice it spews a bunch of nonsense and it is really hard to recognize that otherwise. And I’m not talking about just hard questions, something as basic as Java medior interview questions have sometimes glaring inconsistencies - it sounds techy and detailed, but ultimately wrong.

[Planktonne]

> I've been able to use phind + Co-pilot to learn python

> I don't have to [...] build a mental model

You are not actually learning.