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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

#71

Post by simonw »

IanCal wrote: post #54
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…

I disagree. Unless you’re focussed on right now, in which case case… maybe? Depends on scale. I have a few scattered thoughts here but I think you’re caught up on how things are done now. A human expert in a field is the customer. Do you think, say, gpt5 pro can’t talk to them about a problem and what’s reasonable to try and build in software? It can build a thing, with tests, run stuff and return to a user. It can t…

I expect that customers who have those needs would much rather hire somebody to be the intermediary with the LLM writing the code than take on that role themselves.

You'll get the occasional high agency non-technical customer who decides to learn how to get these things done with LLMs but they'll be a pretty rare breed.

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

#72

Post by simonw »

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…

Funny you should use role/permissions as an example here, I spent the weekend using Claude Code to rewrite my own permissions engine to a new design that uses SQL queries to solve the problem "list all of the resources that this actor can perform this action on".

My previous design required looping through all known resources asking "can actor X action Y on this?". The new design gets to generate a very complex by thoroughly tested SQL query instead.

Applying that new design and updating the hundred of related tests would have taken me weeks. I got it done in two days.

Here's a diff that captures most of the work: https://github.com/simonw/datasette/compare/e951f7e81f038e43...

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

#73

Post by YZF »

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…

What % of the total amount of software (lessay lines of code or time invested) in the world is like that?

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

#74

Post by kujjerl7 »

echelon wrote: post #60
roxolotl wrote: post #13

Earlier quoted context omitted.

One of the interesting corollaries of the title is that this can also be true of humans. Being able to code is not the same as being a software engineer. It never has been.

We're also finding this true with media generation. AI video is an incredible tool, but it can't make movies. It's almost as if all of these models are an exoskeleton for people that already know what they're doing. But you still need an expert in the loop.

>it can't make movies

Humans are sharply declining in this ability at the same time. Most of what Hollywood churns out now is superhero slop, forced-diversity spin-offs, awful remakes of classics, and awkward comebacks for yesteryear's leading men.

I know it's not a movie but I could've happily watched "Nothing, Forever" for the rest of my life. That was creative, chaotic, hilarious, and wildly entertaining.

Meanwhile I watched the human-created War Of The Worlds (2025) last weekend... The less said, the better.

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

#75

Post by phyzome »

hamasho wrote: post #22

The problem with vibe coding is it demoralizes experienced software engineers. I'm developing a MVP with vibes and Claude Code and Codex output work in many cases for this relatively new project. But the quality of code is bad. There is already duplicated or unused logic, a lot of code is unnecessarily complex (especially React and JSX). And there's little PR reviews so that "we can keep velocity". I'm paying much le…

I find it fascinating that your reaction to that situation is to double down while my reaction would be to kill it with fire.

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

#76

Post by phyzome »

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.

I've been hearing "they'll be better in a few months/years" for a few years now.

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

#77

Post by IanCal »

simonw wrote: post #71
IanCal wrote: post #54

Earlier quoted context omitted.

I disagree. Unless you’re focussed on right now, in which case case… maybe? Depends on scale. I have a few scattered thoughts here but I think you’re caught up on how things are done now. A human expert in a field is the customer. Do you think, say, gpt5 pro can’t talk to them about a problem and what’s reasonable to try and build in software? It can build a thing, with tests, run stuff and return to a user. It can t…

I expect that customers who have those needs would much rather hire somebody to be the intermediary with the LLM writing the code than take on that role themselves. You'll get the occasional high agency non-technical customer who decides to learn how to get these things done with LLMs but they'll be a pretty rare breed.

This may be a timeframe issue but I sincerely doubt anyone wants to hire someone to be an intermediary. They just want the thing done.

I know that right now few want to sit in front of claude code, but it's just not that big of a leap to move this up a layer. Workflows do this even without the models getting better.

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

#78

Post by aussieguy1234 »

I'm of the opinion that not a single software engineer has yet lost their job to AI.

Any company claiming they've replaced engineers with AI has done so in an attempt to cover up the real reasons they've gotten rid of a few engineers. "AI automating our work" sounds much better to investors than "We overhired and have to downsize".

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

#79

Post by NicoJuicy »

CjHuber wrote: post #44
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…

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.

There are severe edge cases. Here are some of the last days.

Eg. Just updating bootstrap to angular bootstrap. It didn't transfer how I placed the dropdowns ( basically using dropdown-end). So everything was out of view in desktop and mobile.

It forgot the transloco I used everywhere and just used default English ( happens a lot).

Suggested code that fixed 1 bug ( expression property recursion), but now linq to SQL was broken.

Upgrade to angular 17 in a asp.net core app. I knew it used vite now. But it also required a browser folder to deploy. 20 changes down the road, I noticed something on my ui wasn't updated in dev ( fast commits for my side project, I don't build locally), it didn't deploy anything related to angular no more...

I had 2 files named ApplicationDbContext and it took the one from wrong monolith module.

It adds files in the wrong directory sometimes. Eg. Some modules were made with feature folders.

It sometimes forgets to update my ocelot gateway or updates the compressed version. ...

Note: I documented my architecture in eg. cline. But I use multiple agents to experiment with.

Tldr: it's an expert beginner programmer.

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

#80

Post by Esophagus4 »

phyzome wrote: post #76
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.

I've been hearing "they'll be better in a few months/years" for a few years now.

But hasn’t the ecosystem as a whole been getting better? Maybe or maybe not on the models specifically, but ChatGPT came out and it could do some simple coding stuff. Then came Claude which could do some more coding stuff. Then Cursor and Cline, then reasoning models, then Claude Code, then MCPs, then agents, then…

If we’re simply measuring model benchmarks, I don’t know if they’re much better than a few years ago… but if we’re looking at how applicable the tools are, I would say we’re leaps and bounds beyond where we were.

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