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AI can code, but it can't build software

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Re: AI can code, but it can't build software

#111

Post by aitchnyu »

latentsea wrote: post #96
prmph wrote: post #27

Earlier quoted context omitted.

> LLMs are remarkably good at writing code. Just this past weekend, I've designed and written code (in Typescript) that I don't think LLMs can even come close to writing in years. I have a subscription to a frontier LLM, but lately I find myself using like 25% of the time. At a certain level the software architecture problems I'm solving, drawing upon decades of understanding about maintainable, performant, and verif…

I think C# is really going to shine in the LLM coding era. You can write Roslyn Analyzers to fail the build on arbitrary conditions after inspecting the AST. LLMs are great at helping you write these too. If you get a solid architecture well defined you can then use these as guardrails to constrain development to only happen in the manner you intend. You can then get LLMs to implement features and guarantee the code…

I'm looking at AST based tools in Python to lint, enforce modularity, ban certain patterns. LLMs allow me to write scripts to find recursive function calls, calling super().method() in overrides etc.

https://pypi.org/project/import-linter/ https://github.com/hchasestevens/astpath

Re: AI can code, but it can't build software

#112

Post by ratatougi »

prmph wrote: post #27
simonw wrote: post #4

This is a good headline. LLMs are remarkably good at writing code. Writing code isn't the same thing as delivering working software. A human expert needs to identify the need for software, decide what the software should do, figure out what's feasible to deliver, build the first version (AI can help a bunch here), evaluate what they've built, show it to users, talk to them about whether it's fit for purpose, iterate…

> LLMs are remarkably good at writing code. Just this past weekend, I've designed and written code (in Typescript) that I don't think LLMs can even come close to writing in years. I have a subscription to a frontier LLM, but lately I find myself using like 25% of the time. At a certain level the software architecture problems I'm solving, drawing upon decades of understanding about maintainable, performant, and verif…

Agreed-I often use it when I need to brainstorm which appoarch I should take for my task, or when I need a refactor or generate a large set of mock data.

Re: AI can code, but it can't build software

#113

Post by jongjong »

Software development is one of these things which often seems really easy from the outside but can be insanely complicated.

I had this experience with my co-founder where I was shipping features quickly and he got used to a certain pace of progress. Then we ended up with like 6 different ways to perform a particular process with some differences between them; I had reused as much code as possible; all passing through the same function but without tests, it became challenging to avoid bugs/regressions... My co-founder could not understand why I was pushing back on implementing a particular feature which seemed very simple to him at a glance.

He could not believe me why I was pushing back. Thought I was just being stubborn. I explained to him all the technical challenges involved and it took me like 30 minutes to explain (at a high level) all the technical considerations and trade-offs and how much complexity would be introduced by adding this new feature and he agreed with my point of view.

People who aren't used to building software cannot grasp the complexity. Beyond a certain point, it's like every time my co-founder asked me to do something related to a particular part of the code, I'd spend several minutes pointing out the logical contradictions in his own requirements. The non-technical person thinks about software development in a kind of magical way. They don't really understand what they're asking. This isn't even getting into the issue of technical constraints which is another layer.

Re: AI can code, but it can't build software

#114

Post by sothatsit »

I like to think of it like AI can code, but it is terrible at making design decisions.

Vibe-coded apps eventually fall over as they are overwhelmed by 101 bad architectural decisions stacked on top of one another. You need someone technical to make those decisions to avoid this fate.

Re: AI can code, but it can't build software

#116

Post by gitaarik »

preommr wrote: post #9

These discussions are so tiring. Yes, they're bad now, but they'll get better in a year. If the generative ability is good enough for small snippets of code, it's good enough for larger software that's better organized. Maybe the models don't have enough of the right kind of training data, or the agents don't have the right reasoning algorithms. But it is there.

So what's your point exactly? That LLMs cán write software, just not yet?

Re: AI can code, but it can't build software

#118

Post by belZaah »

simonw wrote: post #4

This is a good headline. LLMs are remarkably good at writing code. Writing code isn't the same thing as delivering working software. A human expert needs to identify the need for software, decide what the software should do, figure out what's feasible to deliver, build the first version (AI can help a bunch here), evaluate what they've built, show it to users, talk to them about whether it's fit for purpose, iterate…

Yeah, no. Had Claude 4.5 generate a mock implementation of an OpenAPI spec. Trivial interaction, just a post of a json object. And Claude invented new fields to check for and failed to check for required ones.

It is helpful in reducing the number of keys I have to press and the amount of documentation-diving I need to do. But saying that’s writing code is like saying StackOverflow is writing code along with autocomplete.

Re: AI can code, but it can't build software

#120

Post by realusername »

prmph wrote: post #63
CjHuber wrote: post #44

Earlier quoted context omitted.

Can you maybe give an example you’ve encountered of an algorithm or a data structure that LLMs cannot handle well? In my experience implementing algorithms from a good comprehensive description and keeping track of data models is where they shine the most.

Example (expanding on [1]): I want to design a strongly typed fluent API interface to some role/permissions based authorization engine functionality. Even knowing how to shape the fluent interface so that is powerful but intuitive, as strongly typed as possible but also and maintainable, is a deep art. One reason I know LLM can't come close to my design is this: I've written something that works (that a typical senio…

Working on permissions for a large saas app, I can also confirm that the best LLM of the market have maybe a 10% success rate writing code in this area.
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