Ask HN: Has anybody built search on top of Anna's Archive?
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Ask HN: Are you using AI coding assistance?
9 cloudking 15 5/8/2025, 11:35:14 PM
Why or why not?
Granted, it is frustrating at times since I end up spending lot of time verifying and iterating.
But overall it is definitely efficient to use LLMs for developing software.
In my case, my baseline mood and motivation fluctuates - so I only. see a small increase in productivity overall - if at all.
I have also noticed excitement to build something new and exciting wore off a bit - because it is ‘just an LLM prompt or two away’.
I'd never vibe code a whole project, especially not in a language I don't know too well.
Mainly I use it like a coworker to bounce ideas off of, and that seems to work pretty well. Sometimes it will reveal some information, or do something in a way I hadn't thought of. The only problem is that it tends to veer into unnecessary territory if I'm not careful what enters into the context.
I also still just use Google because I find advice written by humans to be much more valuable.
My job is in operations at a marketing agency. Scripts that I used to code in an hour take seconds now. Scripts that used to take hours take minutes.
The fast turnaround means there is almost no “cost” to experimenting with some new script/automation.
It’s really amazing.
I tried supermaven, and llama.cpp, as autocomplete in steroids, but they got annoying pretty fast.
I now use ChatGPT and Claude to ask questions about thing I don’t know how to do, or ask them to rewrite/optimize a specific piece of code.
Also there are scenarios where wiring up exhaustive cases would be tedious or require clever use of a vim macro, that a call to AI tends to do in slightly less time but much less mental overhead - allowing me to move on with less fatigue. Overall I cover more ground this way.
It tends to excel when I’ve structured code in a way that’s easily copyable or extensible, such that I can ask the AI to replicate pattern A but for API B. Again this saves me dropping into a low level understanding of an API integration unless I absolutely need to. I tend to check if I need to based on test cases, observability, and performance monitoring —- all the same shit I’d usually use to determine whether or not I should edit the code manually anyway.
Overall, obvious net benefit when used prudently. I’ve seen juniors use AI to write messy code that’s challenging to debug, understand, and maintain. It really is just another tool. You can use it to make your life easier or you can use it to make your life harder.