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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

#51

I've been forcing myself to "pure vibe-code" on a few projects, where I don't read a single line of code (even the diffs in codex/claude code). Candidly, it's awful. There are countless situations where it would be faster for me to edit the file directly (CSS, I'm looking at you!). With that said, I've been surprised at how far the coding agents are able to go[0], and a lot less surprised about where I need to step i…

    Always create a plan/debug markdown file
Very much necessary. Especially with Claude I find. It auto-compacts so often (Sonnet 4.5) and it instantly goes a-wall stupid after that. I then make it re-read the markdown file, so we can actually continue without it forgetting about 90% of what we just did/talked about.

    Prompt the agent to ask questions/present multiple solutions
I find that only helps marginally. They all output so much text it's not even funny. And that's with one "solution".

I don't get how people can stand reading all that nonsense they spew, especially Claude. Everything is insta-ready to deploy, problem solved, root cause found, go hit the big red button that might destroy the earth in a mushroom cloud. I learned real fast to only skim what it says and ignore all that crap (as in I never tried to "change its personality" for real - I did try to tell it to always use the scientific method and prove its assumptions but just like a junior dev it never does and just tells me stupid things it believes to be true and I have to question it. Again, just like a junior dev, but it's my junior dev that's always on and available when I have time and it does things while I do other stuff. And instead of me having to ask the junior after and hour or two what rabbit hole it went down and get them out of there, Claude and Codex usually visually ping the terminal before I even have time to notice. That's for when I don't have full time focus on what I'm trying to do with the agents, which is why I do like using them.

The times when I am fully attentive, they're just soooo slow. And many many times I could do what they're doing faster or just as fast but without spending extra money and "environment". I've been trying to "only use AI agents for coding" for like a month or two now to see its positives and limitations and form my own opinion(s).

    Prompting the agent to ask questions/present multiple solutions allows me to stay "in control" over the how something is built.
I find Claude's "Plan mode" is actually ideal. I just enable it and I don't have to tell it anything. While Codex "breaks out" from time to time and just starts coding even when I just ask it a question. If these machines ever take over, there's probably some record of me swearing at them and I will get a hitman on me. Unlike junior devs, I have no qualms about telling a model that it again ignored everything I told it.

    Ideally a 3rd party "agent" would handle this.
With sub-agents you can. Simple git interactions are perfect for subagents because not much can get lost in translation in the interface between the main agent and the sub agent. Then again, I'm not sure how you loose that much context. I rather use a sub agent for things like running the tests and linter on the whole project in the final steps, which spew a lot of unnecessary output.

Personally, I had a rather bad set of experiences with it controlling git without oversight, so I do that myself, since doing it myself is less taxing than approving everything it wants to do (I automatically allow Claude certain commands that are read only for investigations and reviewing things).

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

#53
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 think you're right, the roles will exist for some time. But I think we'll start to see more and more overlap between engineering, product management and design.

In a lot of ways I think that will lead to stronger delivery teams. As a designer—the best performing teams I've been on have individuals with a core competency, but a lot of overlap in other areas. Product managers with strong engineering instincts, engineers with strong design instincts, etc. When there is less ambiguity in communication, teams deliver better software.

Longer-term I'm unsure. Maybe there is some sort of fusion into all-purpose product people able to do everything?

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

#54
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 take feedback (talking to people is the key major things LLMs have solved).

They can iterate (see: codex) deploy and they can absolutely write copy.

What do you really think in this list they can’t do?

For simplicity reduce it to a relatively basic crud app. We know that they can make these over several steps. We know they can manage the ui pretty well, do incremental work etc. What’s missing?

I think something huge here is that some of the software engineering roles and management become exceptionally fast and cheap. That means you don’t need to have as many users to be worthwhile writing code to solve a problem. Entirely personal software becomes economically viable. I don’t need to communicate value for the problem my app has solved because it’s solved it for me.

Frankly most of the “AI can’t ever do my thing” comments come across as the same as “nobody can estimate my tasks they’re so unique” we see every time something comes up about planning. Most business relevant SE isn’t complex logically, interestingly unique or frankly hard. It’s just a different language to speak.

Disclaimer: a client of mine is working on making software simpler to build and I’m looking at the AI side, but I have these views regardless.

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

#55
post #29
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'm paying much less attention for quality now. After all, why bother when AI produce working code? I hear this so much. It's almost like people think code quality is unrelated to how well the product works. As though you can have 1 without the other. If your code quality is bad, your product will be bad. It may be good enough for a demo right now, but that doesn't mean it really "works".

> If your code quality is bad, your product will be bad.

Why? Modern hardware power allow for extremely inefficient code, so even if some code runs a thousand times slower because it's badly programmed it will still be so fast that it seems instant.

For the rest of the stuff, it has no relevance for the user of the software what the code is doing inside of the chip, as long as the inputs and outputs function as they should. User wants to give input and receive output, nothing else has any significance at all for her.

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

#56
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…

> The people saying LLM can code are hard for me to understand. Just today, I spent an hour documenting a function that performs a set of complex scientific simulations. Defined the function input structure, the outputs, and put a bunch of references in the body to function calls it would use. I then spent 15 minutes explaining to the free version of ChatGPT what the function needs to do both in scientific terms and…

> documenting a function that performs a set of complex scientific simulations.

The example you gave sounds like the problem is deterministic, even if composed of many moving parts. That's one way of looking at complexity.

When I talk about complex problems I'm not just talking about intricate problems. I'm talking about problems where the "problem" is design, not just implementing a design, and that is where LLMs struggle a lot.

Example, I want to design a strongly typed fluent API interface to some functionality. Even knowing how to shape the fluent interface so that is powerful, intuitive, well/strongly typed, and maintainable is a deep art.

The intuitive design constraints that I'm designing under would be hard to even explain to an LLM.

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

#57
I feel you can apply this to all roles. When models passed highschool exam benchmarks, some people talked as if that made the model equivalent to a person passing highschool. I may be wrong, but I bet even an state of the art LLM couldn't complete high school. You have to do things like attending classes at the right time/place, take initiative, keep track of different classes. All of the bigger picture thinking and soft skills that aren't in a pure exam.

Improving this is what everyone's looking into now. Even larger models, context windows, adding reasoning, or something else might improve this one day.

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

#58
post #44
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.

Converting an algorithm implementation from recursive to iterative: it got the concept broadly right, but was quite bad at making the logic actually match up, often refusing to fix mistakes or reverting fixes two edits later. Still a positive experience though, since it was fixable issues and reduced the amount of tedious copies I had to type

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

#59

Many human devs can code, but few can build software.

It's the ultimate irony that I cling to the stance that humans are capable of nuance and creativity that machines will never match, yet the human-written defenses of AI are so repetitive and shallow and cliched that they don't even require the sophistication of LLMs to produce.

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

#60
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…

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.

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