Aider: AI pair programming in your terminal

I do agree though, these basic examples do seem quite pointless, if you already know what you’re doing. It’s just as pointless as telling another developer to “add a name param to ‘greeting’ function, add all types”, which you’d then have to review.

I think it comes down to your level of experience though. If you have years and years of experience and have honed your search skills and are perfectly comfortable, then I suspect there isn’t a lot that an LLM is going to do when it comes to writing chunks of code. That’s how I’ve felt about all these “write a chunk of code” tools.

In my case, apart from automating the kind of repetitive, mindless work I mentioned, it’s just been a glorified autocomplete. It works -really- well for that, especially with comments. Oftentimes I find myself adding a little comment that explains what I’m about to do, and then boop, I’ve got the next few lines autocompleted with no surprises.

I had to work without an internet connection a few days ago and it really, really hit me how much I’ve come to use that autocomplete - I barely ever type anything to completion anymore, it was jarring, having to type everything by hand. I didn’t realise how lazy my typing had become.

Can you explain more how "checking everything is right takes just a few seconds as well? A code review can't happen in "just a few seconds" so maybe I don't understand what the process your describing really is

We live in a world with everything from macro systems and code generation to higher-order functions and types... if you find yourself writing the same "boilerplate" enough times that you find it annoying, just automate it, the same way you can automate anything else we do using software. I have found myself writing very little "boilerplate" in my decades of software development, as I'd rather at the extreme (and it almost never comes to this) throw together a custom compiler than litter my code with a bunch of hopefully-the-same-every-time difficult-to-adjust-later "boilerplate".

There's zero technical challenge, almost no logic, super tedious for a human to do, not quite automatable since there could be any kind of code in those views, and it's very very unlikely that the LLM gets it wrong. I give it a quick look over, it looks right, the tests pass, it's not really a big deal.

And one nice thing I did as well was ask it to "move all logic to the top of the file", which makes it -very- easy to clean up all the "quick fix" cruft that's built up over years that needs to be cleaned up or refactored out.

In those cases the file might indeed need more time dedicated to it, but it would've needed it either way.

I paste the table definition into a comment, and let the LLM generate the model (if the ORM doesn't automate it), the list of validation rules, custom type casts, whatever specifics your project has. None of it is new or technically challenging, it's just autocompleting stuff I was going to write anyway.

It's not that you're writing "too much" boilerplate; this is a tiny part of my work as well. This is just the one part where I've actually found an LLM useful. Any time I feel like "yeah this doesn't require thought, just needs doing", I chuck it over to an LLM to do.

I have trouble understanding the "boilerplate" thing because avoiding writing boilerplate is

1) already a solved "problem" long before AI

2) is it really a "problem"?

The first point: * If you find yourself writing the same piece of code over and over again in the same code it's the indication that you should abstract it away as a function / class / library.

* IDEs have had snippets / code completion for a long time to save you from writing the same pieces of code.

* Large piece of recycled functionalities are generally abstracted away in libraries of frameworks.

* Things like "writing similar static websites a million times" are the reason why solutions like WordPress exist: to take away the boilerplate part of writing websites. This of course applies to solutions / technologies / services that make "avoid writing boilerplate code" their core business

* The only type of real boilerplate that comes to my mind are things like "start a new React application" but that is a thing you do once per project and it's the reason why boostrappers exist so that you only really have to type "npx create-react-app my-app" once and the boilerplate part is taken care of.

The second point: Some mundane refactoring / translations of pieces of code from one technology to the other can actually be automated by AI (I think it's what you're talking about here, but how often does one really do such tasks?), but... Do you really want to? Automate, it, I mean?

I mean, yes "let AI do the boring staff so that I can concentrate on the most interesting parts" make sense, but it's not something I want to do. Maybe it's because I'm aging, but I don't have it in me to be concentrated on demanding, difficult, tiring tasks 8 hour straight a day. It's not something that I can and it's also something that I don't want to.

I much prefer alternating hard stuff that require 100% of my attention with lighter tasks that I can do while listening to a podcast and steam off in order to rest by brain before going back to a harder task. Honestly I don't think anyone is supposed to be concentrated on demanding stuff all day long all week long. That's the recipe for a burnout.

how can you check it in a few seconds if it'd take you hours to change it manually?

- create migration files locally, run statements against containerized local postgres instance - use a custom data extractor script in IntelliJ's data tool to generate r2dbc DAO files with a commented out CSV table containing column_name, data_type, kotlin_type, is_nullable as headers - let AI assistant handle the rest

The LLM output is also extremely prone to error, so it’s not like the second part of your sentence is a valid argument.