You don't, and as long as you're comfortable with that you keep prompting to dig yourself out of holes.
The problem is unless your ready to waste hours prompting to get something exactly how you want it, instead of spending those few minutes doing it yourself, you start to get complacent for whatever the LLM generated for you.
IMO it feels like being a geriatric handicap, there's literally nothing you can do because of the hundreds or thousands of lines of code that's been generated already, you run into the sunk cost fallacy really fast. No matter what people say about building "hundreds of versions" you're spending time doing so much shit either prompting or spec writing that it might not feel worth getting things exactly right in case it makes you start all over again.
It's literally not as if with the LLM things are literally instantaneous, it takes upwards or 20-30 minutes to "Ralph" through all of your requirements and build.
If you start some of it yourself first and you have an idea about where things are supposed to go it really helps you in your thinking process too, just letting it vibe fully in an empty directory leads to eventual sadness.
LLMs would not be popular if "spending those few minutes doing it yourself" part was true. In actuality it can be hours, days, or weeks depending on the feature and your pickiness. Everyone acts as if they are the greatest developer and that these tools are subpar, the truth is that most developers are just average, just like most drivers are average but think of themselves as above average. All of the sudden everyone that was piecing together code off of stackoverflow with no idea how to build the damn thing is actually a someone who can understand large code bases and find bugs and write flawless code? Give me a break.
To the degree that those same people are now writing 10-100x more code...that is scary, but the doom and gloom is pretty tiring.
LLMs are not reliable to fix bugs and when they do they often introduce new ones in my experience.
In fact, humans do targetted bug fixing reasonably well and knowing they did not change the structure of other code better than LLMs currently do in my experience.
I do not find them reliable enough TBH to leave such delicate tasks in a production system in their hands.
Yeah… I wonder how you write complex software without something that looks like a spec, other than slowly. It seems like the prep work is unavoidable, and this contrarian opinion you are offering is just that.
Same as any other software team? You keep an eye on all PRs, dive deep on areas you know to be sensitive, and in general mostly trust till there's a bug or it's proven itself to need more thorough review.
I've only ever joined teams with large, old codebases where most of the code was written by people who haven't been at the company in years, and my coworkers commit giant changes that would take me awhile to understand so genAI feels pretty standard to me.
I love using AI and find it greatly increases my productivity, but the dirty little secret is that you have to actually read what it writes. Both because it often makes mistakes both large and small that need to be corrected (or things that even if not outright wrong, do not match the style/architecture of the project), and because you have to be able to understand it for future maintenance. One other thing I've noticed through the years is that a surprising number of developers are "write only". Reading someone else's code and working out what it's doing and why is its own skillset. I am definitely concerned that the conflux of these two things is going to create a junk code mountain in the very near future. Humans willing to untangle it might find themselves in high demand.
And, as well as noticing actual semantic issues, it's worth noting where they've mixed up abstractions or just allowed a file to grow to an unsustainable size and needs refactoring. You can ask the AI agent to do the refactoring, with some guidance (e.g. split up this file into three files named x, y, z; put this sort of thing in x, ...). This helps you as a human to understand their changes, and also helps the AI. It also makes you feel in control of the overall code design, even though you're no longer writing all the details.
They'll often need a little final tuning afterwards (either by hand or ask the AI again) e.g. move this flag from x to y. As is often the case, it's just like you have an enthusiastic and very fast but quite junior dev working for you.
The trick is to separate your codebase into "code I care about that I give the AI a fixed API and rarely let the AI touch" and "throwaway code I don't give one iota of damn about and I let the AI regenerate--sometimes completely from scratch".
For me, GUI and Web code falls into "throwaway". I'm trying to do something else and the GUI code development is mostly in my way. GUI (especially phone) and Web programming knowledge has a half-life measured in months and, since I don't track them, my knowledge is always out-of-date. Any GUI framework is likely to have a paroxysm and completely rewrite itself in between points when I look at it, and an LLM will almost always beat me at that conversion. Generating my GUI by creating an English description and letting an AI convert that to "GUI Flavour of the Day(tm)" is my least friction path.
This should be completely unsurprising to everybody. GUI programming is such a pain in the ass that we have collectively adopted things like Electron and TUIs. The fact that most programmers hate GUI programming and will embrace anything to avoid that unwelcome task is pretty obvious application of AI.
written-beyond|18 days ago
The problem is unless your ready to waste hours prompting to get something exactly how you want it, instead of spending those few minutes doing it yourself, you start to get complacent for whatever the LLM generated for you.
IMO it feels like being a geriatric handicap, there's literally nothing you can do because of the hundreds or thousands of lines of code that's been generated already, you run into the sunk cost fallacy really fast. No matter what people say about building "hundreds of versions" you're spending time doing so much shit either prompting or spec writing that it might not feel worth getting things exactly right in case it makes you start all over again.
It's literally not as if with the LLM things are literally instantaneous, it takes upwards or 20-30 minutes to "Ralph" through all of your requirements and build.
If you start some of it yourself first and you have an idea about where things are supposed to go it really helps you in your thinking process too, just letting it vibe fully in an empty directory leads to eventual sadness.
u1hcw9nx|18 days ago
The way I use LLM's is that I design main data structures, function interfaces etc. and ask LLM's to fill them. Also test cases and assertions.
mym1990|18 days ago
To the degree that those same people are now writing 10-100x more code...that is scary, but the doom and gloom is pretty tiring.
germandiago|17 days ago
In fact, humans do targetted bug fixing reasonably well and knowing they did not change the structure of other code better than LLMs currently do in my experience.
I do not find them reliable enough TBH to leave such delicate tasks in a production system in their hands.
doctorpangloss|18 days ago
scottyah|18 days ago
I've only ever joined teams with large, old codebases where most of the code was written by people who haven't been at the company in years, and my coworkers commit giant changes that would take me awhile to understand so genAI feels pretty standard to me.
maweaver|18 days ago
quietbritishjim|17 days ago
And, as well as noticing actual semantic issues, it's worth noting where they've mixed up abstractions or just allowed a file to grow to an unsustainable size and needs refactoring. You can ask the AI agent to do the refactoring, with some guidance (e.g. split up this file into three files named x, y, z; put this sort of thing in x, ...). This helps you as a human to understand their changes, and also helps the AI. It also makes you feel in control of the overall code design, even though you're no longer writing all the details.
They'll often need a little final tuning afterwards (either by hand or ask the AI again) e.g. move this flag from x to y. As is often the case, it's just like you have an enthusiastic and very fast but quite junior dev working for you.
whynotmaybe|18 days ago
whynotmaybe|18 days ago
I've tried fixing some code manually and then reused an agent but it removed my fix.
Once you vibe code, you don't look at the code.
h4ch1|18 days ago
Truly one of the statements of all time. I hope you look at the code, even frontier agents make serious lapses in "judgement".
pschastain|18 days ago
And therein lies the problem
bsder|18 days ago
For me, GUI and Web code falls into "throwaway". I'm trying to do something else and the GUI code development is mostly in my way. GUI (especially phone) and Web programming knowledge has a half-life measured in months and, since I don't track them, my knowledge is always out-of-date. Any GUI framework is likely to have a paroxysm and completely rewrite itself in between points when I look at it, and an LLM will almost always beat me at that conversion. Generating my GUI by creating an English description and letting an AI convert that to "GUI Flavour of the Day(tm)" is my least friction path.
This should be completely unsurprising to everybody. GUI programming is such a pain in the ass that we have collectively adopted things like Electron and TUIs. The fact that most programmers hate GUI programming and will embrace anything to avoid that unwelcome task is pretty obvious application of AI.