[MorehouseJ09]

“If it takes longer to explain to the system all the things you want to do and all the details of what you want to do, then all you have is just programming by another name,”

I think this is going to make the difference between junior and senior engineers even more drastic than it is today. It's really hard to know what/how to even describe real problems to these tools, and the people who invest the most in their tooling now, are going to be most successful. It's hard for someone who hasn't designed a large codebase already to do this in an ai native way where they don't have the experience of abstracting at the right level and things like that.

Today's equivalent, I've often found some of the best engineers I know have insane setups with nvim or emacs. They invest in their tool chain, and are now bringing AI into.

[roxolotl]

That quote really perfectly encapsulates the challenge with these tools. There is an assumption that inherently code is hard to write and so if you could code in natural language it would save time. But code isn’t actually that hard to write. Sure some people are genuinely bad at it just like I’m genuinely bad at drawing but a bit of practice and most people can be perfectly competent at it.

The hard part is the engineering. Understanding and breaking down the problem, and then actually solving it. If all we gain out of these tools is that we don’t have to write code by hand anymore they are moderately useful but they won’t really be a step change in software development speed.

[elcritch]

It's not too different in my opinion from the skills need to build complicated machinery like Boeing 747s despite how much Wallstreet and PHBs want to believe it's fungible. Having competent experienced engineers on the ground level watching these processes and constantly revising and adapting to everything from personnel, material, or vendor changes is so far irreplaceable.

Maybe if we get super AGI one day. Even then I suspect that from a thermodynamics perspective that might not be cost effective as you often need localized on site intelligence.

It's an interesting question but I bet humans combined with AI tooling will remain cost competitive for a long time barring leaps in say quantum compute. After all organic brains operate at the atomic level already and were honed in an extremely competitive environment for billions of years. The calories and resources required to create highly efficient massively powerful neural compute had incredibly thin resource "margins" with huge advantages for species to utilize.

[anon7000]

You hit the nail on the head too. Coding itself is very easy for anyone halfway decent in this career — and yet there were a ton of people in CS101 and even in later courses who struggled with things like for loops. It was very hard for them to succeed in this career.

What’s hard is coming up with the algorithm/system design, making the right choices that will scale and won’t become a maintenance nightmare, etc. And yeah, after almost a decade, I have picked up enough I can at least write an outline of a solution that will work alright. But there are still so many tricky edge cases and scaling problems that make it hard to turn “alright” into “really good!”

Sure, AI can help… but it mostly helps with greenfield projects. It doesn’t know about the conversations on slack & jira from a year ago. It doesn’t know about the dozens of other systems and ways the project interacts with other parts of the business. It doesn’t know why whatever regurgitated approach won’t be a good fit for our specific use case. And elaborating all of that detail is not easy! Part of what makes you a good employee is the shit you picked up over the past several months & years that is joe ingrained in your mind when you start working on new projects.

[sublinear]

> some of the best engineers I know have insane setups with nvim or emacs. They invest in their tool chain, and are now bringing AI into.

I find this likely, but totally irrelevant to their success now and in the future. AI tools are as much of a trivial choice as any other text editor features. The resulting time spent and code quality are the same regardless of personal preferences.

[thunky]

> It's really hard to know what/how to even describe real problems to these tools

I would argue that if you can't describe the problem in plain language then you don't have a very good chance of solving it with code or otherwise.

Personally I find that the act of describing the problem will often reveal a good solution...then it's just a matter of seeing if the LLM agrees with me or if it has a difference idea (for better or worse).

[majormajor]

As software grows the problems go such that the effort to completely describe the necessary changes in plain language is often not all that much shorter than the code. Especially if you have a really really good autocomplete for the boilerplate parts of the code. So LLMs being really good at the tedious autocomplete makes LLMs have less marginal utility for the "write the whole thing" for certain types of work.

But the sneakier part of the problem is that as business rules get more complex it's usually harder to completely describe the problem in plain language than in a more formally specified language. For instance, plain-language "apply the user's promo code" doesn't capture the nasty if/else tree you might hit when you're deep in the codebase and see that there's already a bunch of restrictions on other types of promo codes and the product manager didn't think about which of those restrictions should apply to this new promo code. And at this point you're gonna need to use plain language to describe and refine the problem with the product manager - but if you instead were relying on an LLM to turn your short sentence into the right code, it might pick the wrong thing when it comes to modifying that existing code.

[thunky]

> For instance, plain-language "apply the user's promo code" doesn't capture the nasty if/else tree you might hit when you're deep in the codebase and see that there's already a bunch of restrictions on other types of promo codes and the product manager didn't think about which of those restrictions should apply to this new promo code

Sure, but you've already lost at this point. Your code is so jacked up that you can't even describe what it does in words.

Now imagine what happens when a customer calls customer service and asks why their promo code isn't working.

> And at this point you're gonna need to use plain language to describe and refine the problem with the product manager - but if you instead were relying on an LLM to turn your short sentence into the right code, it might pick the wrong thing when it comes to modifying that existing code.

I think you're agreeing with me here...

But TBH this all feels like the establishment trying to protect it's turf, which is understandable. But using the argument of "my code is so overcomplicated and confusing that nobody but me can understand it but me" probably isn't the best position to take.

[Verdex]

> ...describe the problem in plain language...

Oh, I get it. They're saying you should be able to write it in C.

[Jokes aside, I would be interested in hearing from bridge builders, aerospace engineers, or nuclear scientists. Pretty sure they're using math and not 'plain language'.]