This is what I've never understood about vibe coding. Every attempt I've made (and quite a lot) makes me feel faster but in reality is slower.
When traditional coding >50% of the debugging is done while writing lines. If all you are measuring is lines out then you're discounting more than half the work.
I already have a strategy to optimize this. I work mostly in Python but it translates even when I work in compiled languages.
I write code 3 times.
Step 1: hack in an ipython terminal where I can load the program modules. This is actually where AI can help the most imo. Doesn't matter how messy, your first iteration is always garbage.
Step 2: translate that into a function in the codebase. Use Unix philosophy, keeping functions minimal. This helps you move fast now but more importantly you move fast later. Do minimal cleanup so everything is coherent. Any values should be translated into variables that the function can take as arguments. No hard coding! I guarantee even though you don't know it now you'll want to turn those knobs later. This is your MVP.
Step 3: this is a deceptively critical step! Write quick documentation. Explain your function signature. What is every variable's purpose and expected type. Ditto for the output. Add a short explanation of what the function does. Then you write developer comments (I typically do this outside the docstring). What are the limits? When does it work? When does it fail? What needs to be improved? What are the bottlenecks? Could some abstraction help? Is it too abstract? What tests do you need? What do they show or don't show? Big or small, add it. You add it now because you won't remember any of this after lunch, let alone tomorrow or in a year. This might sound time consuming but if your functions are simple then this entire step takes no more than 5 minutes. If you're taking more than 30 then your function is probably too complex. Either fix that now (goto step 1) or add that to your developer notes and move on.
Step 4: triage and address your notes. If there's low hanging fruit, get it now. A small issue now is a big issue tomorrow, so get it when it's small. If there's critical issues, address now. No code is perfect and you can't nor shouldn't address every issue. You triage! But because you have the notes if they become bigger issues or things change (they always do!) then you or someone else can much more easily jump in and address them.
This sounds complicated but it moves surprisingly fast when you get the habit. Steps 2-4 is where all the debugging happens. Step 2 gives you time to breath and sets you up to be able to think clearly. Step 3 makes you think and sets you up for success in the future even you'll inevitably come back. (Ironically the most common use I see is agents is either creating this documentation or being a substitution for it. But the best docs come from those who wrote the code and understand the intent, not just what it does). Step 4 is the execution, squashing those bugs. The steps aren't always clear cut and procedural, but more like a guide of what you need to do.
And no, I've never been able to get the to AI to do this end to end. I have found it helpful in parts but I find it best to have it run parallel to me, not in the foreground. It might catch mistakes I didn't see but it also tends to create new ones. Importantly it almost always misses big picture things. I agree with others, work in smaller chunks, but that's good advice when working with agents or not. Code is abstraction and abstraction isn't easy. Code isn't self documenting, no matter how long or descriptive your variable names are. I can't believe documentation is even a contentious subject considering how much time we waste on analyzing to just figure out what it even does (let alone if it does it well).
When traditional coding >50% of the debugging is done while writing lines. If all you are measuring is lines out then you're discounting more than half the work.
I already have a strategy to optimize this. I work mostly in Python but it translates even when I work in compiled languages.
I write code 3 times.
Step 1: hack in an ipython terminal where I can load the program modules. This is actually where AI can help the most imo. Doesn't matter how messy, your first iteration is always garbage.
Step 2: translate that into a function in the codebase. Use Unix philosophy, keeping functions minimal. This helps you move fast now but more importantly you move fast later. Do minimal cleanup so everything is coherent. Any values should be translated into variables that the function can take as arguments. No hard coding! I guarantee even though you don't know it now you'll want to turn those knobs later. This is your MVP.
Step 3: this is a deceptively critical step! Write quick documentation. Explain your function signature. What is every variable's purpose and expected type. Ditto for the output. Add a short explanation of what the function does. Then you write developer comments (I typically do this outside the docstring). What are the limits? When does it work? When does it fail? What needs to be improved? What are the bottlenecks? Could some abstraction help? Is it too abstract? What tests do you need? What do they show or don't show? Big or small, add it. You add it now because you won't remember any of this after lunch, let alone tomorrow or in a year. This might sound time consuming but if your functions are simple then this entire step takes no more than 5 minutes. If you're taking more than 30 then your function is probably too complex. Either fix that now (goto step 1) or add that to your developer notes and move on.
Step 4: triage and address your notes. If there's low hanging fruit, get it now. A small issue now is a big issue tomorrow, so get it when it's small. If there's critical issues, address now. No code is perfect and you can't nor shouldn't address every issue. You triage! But because you have the notes if they become bigger issues or things change (they always do!) then you or someone else can much more easily jump in and address them.
This sounds complicated but it moves surprisingly fast when you get the habit. Steps 2-4 is where all the debugging happens. Step 2 gives you time to breath and sets you up to be able to think clearly. Step 3 makes you think and sets you up for success in the future even you'll inevitably come back. (Ironically the most common use I see is agents is either creating this documentation or being a substitution for it. But the best docs come from those who wrote the code and understand the intent, not just what it does). Step 4 is the execution, squashing those bugs. The steps aren't always clear cut and procedural, but more like a guide of what you need to do.
And no, I've never been able to get the to AI to do this end to end. I have found it helpful in parts but I find it best to have it run parallel to me, not in the foreground. It might catch mistakes I didn't see but it also tends to create new ones. Importantly it almost always misses big picture things. I agree with others, work in smaller chunks, but that's good advice when working with agents or not. Code is abstraction and abstraction isn't easy. Code isn't self documenting, no matter how long or descriptive your variable names are. I can't believe documentation is even a contentious subject considering how much time we waste on analyzing to just figure out what it even does (let alone if it does it well).