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I resonate with that. I also find writing code super pleasurable. It's immediate stress relief for me, I love the focus and the flow. I end long hands-on coding

by sho_hn 8mo ago

I resonate with that. I also find writing code super pleasurable. It's immediate stress relief for me, I love the focus and the flow. I end long hands-on coding sessions with a giddy high. What I'm finding is that it's possible to integrate AI tools into your workflow in a big way without giving up on doing that, and I think there's a lot to say for a hybrid approach. The result of a fully-engaged brain (which still requires being right in there with the problem) using AI tools is better than the fully-hands-off way touted by some. Stay confident in your abilities and find your mix/work loop. It's also possible to get a certain version of the rewards of coding from instrumenting AI tools. E.g. slicing up and sizing tasks to give to background agents that you can intuit from experience they'll be able to actually hand in a decent result on is similar to structuring/modularization exercises (e.g. with the goal to be readable or maintainable) in writing code, feelings-wise.

bearfox 8mo ago
I'm in the enjoy writing code camp and do see merits of the hybrid approach, but I also worry about the (mental) costs. I feel that for using AI effectively I need to be fully engaged with both the problem itself and an additional problem of communicating with the LLM - which is more taxing than pre-LLM coding. And if I'm not fully engaged those outcomes usually aren't that great and bring frustration. In isolation, the shift might be acceptable, but in reality I'm still left with a lot of ineffective meetings - only now without coding sessions to clear my brain.
- marginalia_nu 8mo ago
  I think an additional big part of why LLM-aided coding is so draining is that it has you constantly refreshing your mental model of the code. Making sense of new or significantly changed code is very taxing. Writing new code is less taxing as you're incrementally updating the model as you go, at a pretty modest pace. LLMs can produce code at a much higher rate than humans can make sense of it, and assisted coding introduces something akin to cache thrashing, where you constantly need to build mental models of the system to keep up with the changes. Your bandwidth for comprehending code is as limited as it always was, and taxing this ability to its limits is pretty unpleasant, and in my experience, comes at a cost of other mental capabilities.
  - bearfox 8mo ago
    It rings true. Then we have a question in front of use - when you're doing the changes yourself you are also building and adapting the mental model of the system - which approach needs less effort in total?
kelvinjps10 8mo ago
I get a dopamine hit with AI by being able to accomplish tasks fast, mostly in frontent or using a dynamic language like python because you see the changes in real time
duskdozer 8mo ago
I'll use some small code completion but that's it. And only when I can do it locally with non-proprietary software.

by sho_hn 8mo ago

bearfox 8mo ago

I'm in the enjoy writing code camp and do see merits of the hybrid approach, but I also worry about the (mental) costs. I feel that for using AI effectively I need to be fully engaged with both the problem itself and an additional problem of communicating with the LLM - which is more taxing than pre-LLM coding. And if I'm not fully engaged those outcomes usually aren't that great and bring frustration. In isolation, the shift might be acceptable, but in reality I'm still left with a lot of ineffective meetings - only now without coding sessions to clear my brain.

marginalia_nu 8mo ago
I think an additional big part of why LLM-aided coding is so draining is that it has you constantly refreshing your mental model of the code. Making sense of new or significantly changed code is very taxing. Writing new code is less taxing as you're incrementally updating the model as you go, at a pretty modest pace. LLMs can produce code at a much higher rate than humans can make sense of it, and assisted coding introduces something akin to cache thrashing, where you constantly need to build mental models of the system to keep up with the changes. Your bandwidth for comprehending code is as limited as it always was, and taxing this ability to its limits is pretty unpleasant, and in my experience, comes at a cost of other mental capabilities.
- bearfox 8mo ago
  It rings true. Then we have a question in front of use - when you're doing the changes yourself you are also building and adapting the mental model of the system - which approach needs less effort in total?

kelvinjps10 8mo ago

I get a dopamine hit with AI by being able to accomplish tasks fast, mostly in frontent or using a dynamic language like python because you see the changes in real time

duskdozer 8mo ago

I'll use some small code completion but that's it. And only when I can do it locally with non-proprietary software.