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How I write software with LLMs
301–310 of 544 posts
Re: How I write software with LLMs
#302Earlier quoted context omitted.
I don't see a world where a motivated soul can build a business from a laptop and a token service as a problem. I see it as opportunity. I feel similarly about Hollywood and the creation of media. We're not there in either case yet, but we will be. That's pretty clear. and when I look at the feudal society that is the entertainment industry here, I don't understand why so many of the serfs are trying to perpetuate it…
That depends on how fast that change happens. If 45% of jobs evaporate in a a 5 year period, a complete societal collapse is the likely outcome.
Sounds like influencer nonsense to me. Touch grass. If the people are fed and housed, there's no collapse. And if the billionaire class lets them starve, they will finally go through some things just like the aristocracy in France once did. And I think even Peter Thiel is smarter than that. You can feed yourself for OTOH if what you're really talking about is the long-term collapse in our ludicrous carbon footprint when we finally run out of fossil fuels and we didn't invest in renewables or nuclear to replace them, well, I'm with you there.
Re: How I write software with LLMs
#303> On projects where I have no understanding of the underlying technology (e.g. mobile apps), the code still quickly becomes a mess of bad choices. However, on projects where I know the technologies used well (e.g. backend apps, though not necessarily in Python), this hasn’t happened yet, even at tens of thousands of SLoC. Most of that must be because the models are getting better, but I think that a lot of it is also because I’ve improved my way of working with the models.
I wonder whether at some point we'll get a translation model, that translates relatively vague requests into sound architectural decisions, with some embedded knowledge of the environment you're building in, and that can ask clarifying questions when there are multiple options with different tradeoffs.
Re: How I write software with LLMs
#304I randomly clicked and scrolled through the source code of Stavrobot - The largest thing I’ve built lately is an alternative to OpenClaw that focuses on security. [1] and that is not great code. I have not used any AI to write code yet but considered trying it out - is this the kind of code I should expect? Or maybe the other way around, has someone an example of some non-trivial code - in size and complexity - writt…
> is this the kind of code I should expect? Sadly yes. But it "works", for some definition of working. We all know it's going to be a maintenance nightmare seen the gigantic amount of code and projects now being generated ad infinitum. As someone commented in this thread: it can one-shot an app showing restaurant locations on a map and put a green icon if they're open. But don't except good code, secure code, perform…
What I find interesting is how AI enthusiasts will recursively offer AI itself as the solution to any of the issues you mention.
Since AI can read and generate code, it can surely fix code, or find bugs, or address security flaws. And if this all turns into a hot mess, AI can just refactor the whole thing anyway. And so forth.
Personally, I think we'll be some years off before the whole software loop is closed by AI (if it even happens anyway).
Re: How I write software with LLMs
#305Earlier quoted context omitted.
As human developers, I think we're struggling with "letting go" of the code. The code we write (or agents write) is really just an intermediate representation (IR) of the solution. For instance, GCC will inline functions, unroll loops, and myriad other optimizations that we don't care about (and actually want!). But when we review the ASM that GCC generates we are not concerned with the "spaghetti" and the "high coup…
You are comparing compilers to a completely non deterministic code generation tool that often does not take observable behavior into account at all and will happily screw a part of your system without you noticing, because you misworded a single prompt. No amount of unit/integration tests cover every single use case in sufficiently complex software, so you cannot rely on that alone.
I just rewrote a utility for the third time - the first two were before AI.
Short version, when someone designs a call center with Amazon Connect, they use a GUI flowchart tool and create “contact flows”. You can export the flow to JSON. But it isn’t portable to other environments without some remapping. I created a tool before that used the API to export it and create a portable CloudFormation template.
I always miss some nuance that can half be caught by calling the official CloudFormation linter and the other half by actually deploying it and seeing what errors you get
This time, I did with Claude code, ironically enough, it knew some of the complexity because it had been trained on one of my older open source implementations I did while at AWS. But I told it to read the official CloudFormation spec, after every change test it with the linter, try to deploy it and fix it.
Again, I didn’t care about the code - I cared about results. The output of the script either passes the deployment or it doesn’t. Claude iterated until it got it right based on “observable behavior”. Claude has tested whether my deployments were working as expected plenty of times by calling the appropriate AWS CLI command and fixed things or reading from a dev database based on integration tests I defined.
Re: How I write software with LLMs
#306I randomly clicked and scrolled through the source code of Stavrobot - The largest thing I’ve built lately is an alternative to OpenClaw that focuses on security. [1] and that is not great code. I have not used any AI to write code yet but considered trying it out - is this the kind of code I should expect? Or maybe the other way around, has someone an example of some non-trivial code - in size and complexity - writt…
You can make it better by investing a lot of time playing around with the tooling so that it produces something more akin to what you're looking for. Good luck convincing your boss that this ungodly amount of time spent messing around with your tooling for an immeasurable improvement in your delivery is the time well spent as opposed to using that same amount of time delivering results by hand.
You literally have it backwards. It's the bosses that are pulling engineers aside and requiring adoption of a tooling that they're not even sure justifies the increase in productivity versus the cost of setting up the new workflows. At least anecdotally, that's the case.
Re: How I write software with LLMs
#307> On projects where I have no understanding of the underlying technology (e.g. mobile apps), the code still quickly becomes a mess of bad choices. However, on projects where I know the technologies used well (e.g. backend apps, though not necessarily in Python), this hasn’t happened yet, even at tens of thousands of SLoC. Most of that must be because the models are getting better, but I think that a lot of it is also…
Is that not already possible with Markdown spec files and planning mode?
Re: How I write software with LLMs
#308In my experience an LLM does 2 things:
1. Bring you up to some average-LLM level when you don’t have the skills/knowledge to actually do what you want.
2. Work at 80-90% of your capacity but WAY faster than you physically could depending on how much context you provide it. If you don’t provide it sufficient context to do what/how you want it to do, of course it might default to something you don’t want.
Re: How I write software with LLMs
#309> One thing I’ve noticed is that different people get wildly different results with LLMs, so I suspect there’s some element of how you’re talking to them that affects the results. It's always easier to blame the prompt and convince yourself that you have some sort of talent in how you talk to LLMs that other's don't. In my experience the differences are mostly in how the code produced by the LLM is reviewed. Develope…
> Developers who have experience reviewing code are more likely to find problems immediately and complain they aren't getting great results without a lot of hand holding this makes me feel better about the amount of disdain I've been feeling about the output from these llms. sometimes it popsout exactly what I need but I can never count on it to not go offrails and require a lot of manual editing.
Exactly my experience. Sometimes it's brilliant, sometimes it produces crap, often it produces something that's a step in the right direction but requires extra work, and often it switches between these different results, producing great results at first until it gets stuck and desperately starts spewing out increasingly weird garbage.
As a developer, you always have to check the code, and recognise when it's just being stupid.
Re: How I write software with LLMs
#310Earlier quoted context omitted.
I also managed to find a 1000 line .cpp file in one of the projects. The article's content doesn't match his apps quality. They don't bring any value. His clock looks completely AI generated.
Remember you're grinding your anti-LLM axe against something a real person made, and that person read your comment.
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