[thunky]

> But it doesn't work for reasoning and abstraction, so it fails to synthesise and propose novel views

I disagree. Have a conversation with it about your problem and work through design decisions with it. When I do that, I find it gives me a lot of good ideas.

Disclaimer: I'm not working on anything groundbreaking (like most people)

[sublinear]

Yes, but "good ideas" compared to what? If you were aware of the better alternatives, you probably wouldn't be discussing those details with an LLM. You'd find that it just randomly gave you one. It might work, but you don't know how well until you're already entrenched.

Nobody knows everything, so of course LLMs can be useful sometimes. More useful than plain old search, books, or even discussion with real humans? Maybe.

Search can offer a much broader context than an LLM hyperfocused on just generating text. Books may lead you to realize you were asking the wrong questions. Discussions will provide an overall "vibe" of the topic.

These are not competing options. We can and should be using all of them when possible.

[thunky]

> Yes, but "good ideas" compared to what? If you were aware of the better alternatives, you probably wouldn't be discussing those details with an LLM

Even when I already have a good idea of how I plan to do something, I may still ask AI and then find it gave me better idea for some particular thing.

I liken it to using GPS even when you know the route like the back of your hand. It can still steer you around an accident.

To do this effectively I have to drop the idea that I always know better than it does.

[sublinear]

If we are going to use the GPS analogy, not every trip is a route or even paved. GPS is notoriously unreliable when on a hike. You have to be a lot more careful than that.

Most real world software tends to be exactly that kind of situation. You need the rest of the business to help decide every detail of a service that will be in production long term. You are not just on a hike. Business is conquest. You are setting up camp with the lofty goal of scaling to a settlement, then a town, etc.

This sounds dramatic, but I think many are too easily impressed/jaded. Some people can't believe it, but this is still very early days for software. We're barely at the point where, maybe, the layperson can just about build small trivial gadgets for themselves. Meanwhile, there are people out there sailing the seas and beyond.

[thunky]

Sure, if you're one of the few that is building something truly novel, I agree AI will not be as useful to you.

That's why I added the disclaimer above: I'm not working on anything groundbreaking (like most people).

And I disagree with your premise overall, because I think the overwhelming majority of software development is much more like driving on a paved highway than it is like hiking through unmarked forest. Which is exactly why AI works so well: it's trained on thousands of examples of very similar solutions to very similar problems.

All of the hard work has already been done by people before us. We have the luxury of sitting down in front of incredible hardware, operating systems, fully designed languages, optimizing compilers, IDEs to fill in the blanks for us, and now AI to write up entire programs for us - none of which we had anything to do with the creation of. All we need to do is hook things together and slap on a layer of paint.

[sublinear]

> the overwhelming majority of software development is much more like driving on a paved highway than it is like hiking through unmarked forest

The difficulty comes from meeting the exact requirements and providing a reliable result. Would you be so sure of this opinion if the requirement was to write "a simple CRUD app", but it had to integrate with a poorly documented legacy system and was for a big client with an SLA that could sink the business? Many devs find themselves in that exact situation all the time. What you end up writing, with AI no less, is tomorrow's poorly documented legacy system.

You don't know what you don't know. I'm reminded of stories where people from Europe traveled to America and underestimated how massive it is. They thought "just a few 5 hour roadtrips" sounded relaxing. They overlooked the details and found themselves falling asleep at the wheel, thirsty/hungry, and backtracking for hours.

[thunky]

> Would you be so sure of this opinion if the requirement was to write "a simple CRUD app", but it had to integrate with a poorly documented legacy system and was for a big client with an SLA that could sink the business?

Yes, because I think the underlying patterns are the same. Get data, move it around, serialize/deserialize it, store, query, present. It's very unlikely I'm going to run into some new pattern that's never been seen in code before. This is exactly where I think devs are giving themselves too much credit.

I'm not saying AI can do it without my help either, I'm just saying is that it can help me do it better and faster than I could have done without it.

[altmanaltman]

Sure but you can also google your problem and check what is industry standard/what is the correct way to do things (imo in less time than it takes to go through a conversation).

But the problem is that when you ask ai to solve a problem on its own, its default plan can suck. You can mitigate that by research and context but it doesn't mean the initial problem is solved. But even that requires skill and human judgement (both ai conversation research or traditional research) and a lot of people want to skip that entirely.

[appplication]

I find I don’t necessarily need or want AI to give me ideas, but I would agree having a conversational back and forth generally yields decent results.

I have found being Socratic in my questions, and trying to get the AI to arrive at my intended design via such conversations supplies the right level of context for properly solving the problem. It’s token intensive, without a doubt, but I find the result is the AI tends to be better equipped to handle the many micro decisions that need to be made along the way.

The contrast to this is I give it a detailed prompt where it then asks questions of me, which also generally works but I find the AI tends to not be as well equipped for decisions it needs to make mid implementation.

It’s not perfect, and maybe not even a good fit for some. I also never know what to think when people tell me their idiosyncratic ways of using AI. Ultimately I think the most effective way is whatever lets you translate the vision in your head into the end result.

[oulipo2]

When I say "novel ideas" it means something groundbreaking, indeed, not rehashing common "this is the best practice for a simple CRUD backend"