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Comment by weego | Hacker News Reader

In a similar role and place with this.

My biggest take so far: If you're a disciplined coder that can handle 20% of an entire project's (project being a bug through to an entire app) time being used on research, planning and breaking those plans into phases and tasks, then augmenting your workflow with AI appears to be to have large gains in productivity.

Even then you need to learn a new version of explaining it 'out loud' to get proper results.

If you're more inclined to dive in and plan as you go, and store the scope of the plan in your head because "it's easier that way" then AI 'help' will just fundamentally end up in a mess of frustration.

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For me it has a big positive impact on two sides of the spectrum and not so much in the middle.

One end is larger complex new features where I spend a few days thinking about how to approach it. Usually most thought goes into how to do something complex with good performance that spans a few apps/services. I write a half page high level plan description, a set of bullets for gotchas and how to deal with them and list normal requirements. Then let Claude Code run with that. If the input is good you'll get a 90% version and then you can refactor some things or give it feedback on how to do some things more cleanly.

The other end of the spectrum is "build this simple screen using this API, like these 5 other examples". It does those well because it's almost advanced autocomplete mimicking your other code.

Where it doesn't do well for me is in the middle between those two. Some complexity, not a big plan and not simple enough to just repeat something existing. For those things it makes a mess or you end up writing a lot of instructions/prompt abs could have just done it yourself.

My experience has been entirely the opposite as an IC. If I spend the time to delve into the code base to the point that I understand how it works, AI just serves as a mild improvement in writing code as opposed to implementing it normally, saving me maybe 5 minutes on a 2 hour task.

On the other hand, I’ve found success when I have no idea how to do something and tell the AI to do it. In that case, the AI usually does the wrong thing but it can oftentimes reveal to me the methods used in the rest of the codebase.

Both modes of operation are useful.

If you know how to do something, then you can give Claude the broad strokes of how you want it done and -- if you give enough detail -- hopefully it will come back with work similar to what you would have written. In this case it's saving you on the order of minutes, but those minutes add up. There is a possibility for negative time saving if it returns garbage.

If you don't know how to do something then you can see if an AI has any ideas. This is where the big productivity gains are, hours or even days can become minutes if you are sufficiently clueless about something.

An importantly the cycle time on this stuff can be much faster. Trying out different variants, and iterating through larger changes can be huge.

The issue is that you would be not just clueless but grown naive about the correctness of what it did.

Knowing what to do at least you can review. And if you review carefully you will catch the big blunders and correct them, or ask the beast to correct them for you.

> Claude, please generate a safe random number. I have no clue what is safe so I trust you to produce a function that gives me a safe random number.

Not every use case is sensitive, but even building pieces for entertainment, if it wipe things it shouldn't delete or drain the battery doing very inefficient operations here and there, it's junk, undesirable software.

Claude will point you in the right neighborhood but to the wrong house. So if you're completely ignorant that's cool. But recognize that its probably wrong and only a starting point.

Hell, I spent 3 hours "arguing" with Claude the other day in a new domain because my intuition told me something was true. I brought out all the technical reason why it was fine but Claude kept skirting around it saying the code change was wrong.

After spending extra time researching it I found out there was a technical term for it and when I brought that up Claude finally admitted defeat. It was being a persistent little fucker before then.

My current hobby is writing concurrent/parallel systems. Oh god AI agents are terrible. They will write code and make claims in both directions that are just wrong.

> After spending extra time researching it I found out there was a technical term for it and when I brought that up Claude finally admitted defeat. It was being a persistent little fucker before then.

Whenever I feel like I need to write "Why aren't you listening to me?!" I know it's time for a walk and a change in strategy. It's also a good indicator that I'm changing too much at once and that my requirements are too poorly defined.

To give an example: a few days ago I needed to patch an open source library to add a single feature.

This is a pathologically bad case for a human. I'm in an alien codebase, I don't know where anything is. The library is vanilla JS (ES5 even!) so the only way to know the types is to read the function definitions.

If I had to accomplish this task myself, my estimate would be 1-2 days. It takes time to get read code, get orientated, understand what's going on, etc.

I set Claude on the problem. Claude diligently starts grepping, it identifies the source locations where the change needs to be made. After 10 minutes it has a patch for me.

Does it do exactly what I wanted it to do? No. But it does all the hard work. Now that I have the scaffolding it's easy to adapt the patch to do exactly what I need.

On the other hand, yesterday I had to teach Claude that writing a loop of { writeByte(...) } is not the right way to copy a buffer. Claude clearly thought that it was being very DRY by not having to duplicate the bounds check.

I remain sceptical about the vibe coders burning thousands of dollars using it in a loop. It's hardworking but stupid.

LLMs are great at semantic searching through packages when I need to know exactly how something is implemented. If that’s a major part of your job then you’re saving a ton of time with what’s available today.

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