5 ms·

Is anyone else getting more mentally exhausted by this? I get more done, but I also miss the relaxing code typing in the middle of the process.

by _cenw 9mo ago

simonw 9mo ago
Yes, absolutely, I can be mentally wiped out by lunch.
jghn 9mo ago
That's kind of the point here. Once a dev reached a certain level, they often weren't doing much "relaxing code typing" anyways before the AI movement. I don't find it to be much different than being a tech lead, architect, or similar role.
- remich 9mo ago
  As a former tech lead and now staff engineer, I definitely agree with this. I read a blog post a couple of months ago that theorized that the people that would adopt these technologies the best were people in the exact roles that you describe. I think because we were already used to having to rely on other people to execute on our plans and ideas because they were simply too big to accomplish by ourselves. Now that we have agents to do these things, it's not really all that different - although it is a different management style working around their limitations.
  - jghn 9mo ago
    Exactly. I've been a tech lead, have led large, cross-org projects, been an engineering manager, and similar roles. For years, when mentoring upcoming developers what I always to be the most challenging transition was the inflection point between "I deliver most of my value by coding" to "I deliver most of my value by empowering other people to deliver". I think that's what we're seeing here. People who have made this transition are already used to working this way. Both versions have their own quirks and challenges, but at a high level it abstracts.
    - 9rx 9mo ago
      LLMs are just a programming language/compiler/REPL, though, so there is nothing out of the ordinary for developers. Except what is different is the painfully slow compile time to code ratio. You write code for a few minutes... and then wait. Then spend a few more minutes writing code... and then wait. That is where the exhaustion comes from. At least in the olden days[1] you could write code for days before compiling, which reduced the pain. Long compilation times has always been awful, but it is less frustrating when you could defer it until the next blue moon. LLMs don't (yet) seem to be able to handle that. If you feed them more than small amounts of code at a time they quickly go off the rails. With that said, while you could write large amounts of code and defer it until the next blue moon, it is a skill to be able to do that. Even in C++, juniors seem to like to write a few lines of code and then turn to compiling the results to make sure they are on the right track. I expect that is the group of people who is most feeling at home with LLMs. Spending a few minutes writing code and then waiting on compilation isn't abnormal for them. But presumably the tooling will improve with time. [1] https://xkcd.com/303/ https://xkcd.com/303/
      - recursive 9mo ago
        Programming languages are structured and have specifications. It is possible to know what code will do just by reading it.
        9rx 9mo ago
        Well designed ones do, at least. LLMs, in their infancy, still bring a lot of undefined behaviour, which is you end up stuck in the code for a few minutes -> compile -> wait -> repeat cycle. But that is not a desirable property and won't remain acceptable as the technology matures.
        recursive 9mo ago
        I don't see any way this is changing, acceptable or not.
tikimcfee 9mo ago
Ya know, I have to admit feeling something like this. Normally, the amount of stuff I put together in a work day offers a sense of completion or even a bit of a dopamine bump because of a "job well done". With this recent work I've been doing, it's instead felt like I've been spending a multiplier more energy communicating intent instead of doing the work myself; that communication seems to be making me more tired than the work itself. Similar?
- whynotminot 9mo ago
  It feels like we all signed up to be ICs, but now we’re middle managers and our reports are bots.
  - senshan 9mo ago
    > and our reports are bots. With no gossip, rivalry or backstabbing. Super polite and patient, which is very inspiring. We also brutally churning them by "laying off" the previously latest model once the new latest is available.
  - MikeTheGreat 9mo ago
    I forget where I saw this (a Medium post, somewhere) but someone summed this up as "I didn't sign up for this just to be a tech priest for the machine god".
    - whstl 9mo ago
      Someone commented yesterday that managers and other higher-ups are "already ok with non-deterministic outputs", because that's what engineers give them. As a manager/tech-lead, I've kind of been a tech priest for some time.
      - danielbln 9mo ago
        Which is why it's so funny to hear seasoned engineers lament the probabilistic nature of AI systems, and how you have to be hand setting code to really think about the problem domain. They seem to all be ICs that forget that there are abstraction layers above them where all of that happens (and more).
teaearlgraycold 9mo ago
I like to alternate focusing on AI wrangling and writing code the old fashioned way.
bugglebeetle 9mo ago
Nah, I don’t miss at all typing all the tests, CLIs, and APIs I’ve created hundreds of times before. I dunno if I it’s because I do ML stuff, but it’s almost all “think a lot about something, do some math, and and then type thousands of lines of the same stuff around the interesting work.”
mupuff1234 9mo ago
For me it's the opposite, I'm wasting less energy over debugging silly bugs and fighting/figuring out some annoying config. But it does feel less fulfilling I suppose.
agumonkey 9mo ago
I think there are two groups of people emerging. deep / fast / craft-and-decomposition-loving vs black box / outcome-only. I've seen people unable to work at average speed on small features suddenly reach above average output through a llm cli and I could sense the pride in them. Which is at odds with my experience of work.. I love to dig down, know a lot, model and find abstractions on my own. There a llm will 1) not understand how my brain work 2) produce something workable but that requires me to stretch mentally.. and most of the time I leave numb. In the last month I've seen many people expressing similar views. ps: thanks everybody for the answers, interesting to read your pov
- sanufar 9mo ago
  I think for me, the difference really comes down to how much ownership I want to take in regards to the project. If it’s something like a custom kernel that I’m building, the real fun is in reading through docs, learning about systems, and trying to craft the perfect abstractions; but if it’s wiring up a simple pipeline that sends me a text whenever my bus arrives, I’m happy to let an LLM crank that out for me. I’ve realized that a lot of my coding is on this personal satisfaction vs utility matrix and llms let me focus a lot more energy onto high satisfaction projects
- remich 9mo ago
  I get what you're saying, but I would say that this does not match my own experience. For me, prior to the agentic coding era, the problem was always that I had way more ideas for features, tools, or projects than I had the capacity to build when I had to confront the work of building everything by hand, also dealing with the inevitable difficulties in procrastination and getting started. I am a very above-average engineer when it comes to speed at completing work well, whether that's typing speed or comprehension speed, and still these tools have felt like giving me a jetpack for my mind. I can get things done in weeks that would have taken me months before, and that opens up space to consider new areas that I wouldn't have even bothered exploring before because I would not have had the time to execute on them well.
  - jaapz 9mo ago
SJMG 9mo ago
I think it's the serial waiting game and inevitable context switching while you wait. Long iteration cycles are taxing
bccdee 9mo ago
So far what I've been doing is, I look for the parts that seem like they'd be rewarding to code and I do them myself with no input from the machine whatsoever. It's hard to really understand a codebase without spending time with the code, and when you're using a model, I think there's a risk of things changing more quickly than you can internalize them. Also, I worry I'll get too comfortable bossing chatbots around & I'll become reluctant to get my hands dirty and produce code directly. People talk about ruining their attention spans by spending all their time on TikTok until they can no longer read novels; I think it'd be a real mistake to let that happen to my professional skill set.
epolanski 9mo ago
Yes it's taxing and mentally draining, reading code and connecting dots is always harder than writing it. And if you let the AI too loose, as when you try to vibe code an entirely new program, I end up in the situation where in 1 day I have a good prototype and then I can spend easily 5 times as much sorting the many issues and refactoring in order to have it scale to the next features.

Is anyone else getting more mentally exhausted by this? I get more done, but I also miss the relaxing code typing in the middle of the process.

by _cenw 9mo ago

Is anyone else getting more mentally exhausted by this? I get more done, but I also miss the relaxing code typing in the middle of the process.

simonw 9mo ago

Yes, absolutely, I can be mentally wiped out by lunch.

jghn 9mo ago

That's kind of the point here. Once a dev reached a certain level, they often weren't doing much "relaxing code typing" anyways before the AI movement. I don't find it to be much different than being a tech lead, architect, or similar role.

remich 9mo ago
As a former tech lead and now staff engineer, I definitely agree with this. I read a blog post a couple of months ago that theorized that the people that would adopt these technologies the best were people in the exact roles that you describe. I think because we were already used to having to rely on other people to execute on our plans and ideas because they were simply too big to accomplish by ourselves. Now that we have agents to do these things, it's not really all that different - although it is a different management style working around their limitations.
- jghn 9mo ago
  Exactly. I've been a tech lead, have led large, cross-org projects, been an engineering manager, and similar roles. For years, when mentoring upcoming developers what I always to be the most challenging transition was the inflection point between "I deliver most of my value by coding" to "I deliver most of my value by empowering other people to deliver". I think that's what we're seeing here. People who have made this transition are already used to working this way. Both versions have their own quirks and challenges, but at a high level it abstracts.
  - 9rx 9mo ago
    LLMs are just a programming language/compiler/REPL, though, so there is nothing out of the ordinary for developers. Except what is different is the painfully slow compile time to code ratio. You write code for a few minutes... and then wait. Then spend a few more minutes writing code... and then wait. That is where the exhaustion comes from. At least in the olden days[1] you could write code for days before compiling, which reduced the pain. Long compilation times has always been awful, but it is less frustrating when you could defer it until the next blue moon. LLMs don't (yet) seem to be able to handle that. If you feed them more than small amounts of code at a time they quickly go off the rails. With that said, while you could write large amounts of code and defer it until the next blue moon, it is a skill to be able to do that. Even in C++, juniors seem to like to write a few lines of code and then turn to compiling the results to make sure they are on the right track. I expect that is the group of people who is most feeling at home with LLMs. Spending a few minutes writing code and then waiting on compilation isn't abnormal for them. But presumably the tooling will improve with time. [1] https://xkcd.com/303/ https://xkcd.com/303/
    - recursive 9mo ago
      Programming languages are structured and have specifications. It is possible to know what code will do just by reading it.
      - 9rx 9mo ago
        Well designed ones do, at least. LLMs, in their infancy, still bring a lot of undefined behaviour, which is you end up stuck in the code for a few minutes -> compile -> wait -> repeat cycle. But that is not a desirable property and won't remain acceptable as the technology matures.
        recursive 9mo ago
        I don't see any way this is changing, acceptable or not.

tikimcfee 9mo ago

Ya know, I have to admit feeling something like this. Normally, the amount of stuff I put together in a work day offers a sense of completion or even a bit of a dopamine bump because of a "job well done". With this recent work I've been doing, it's instead felt like I've been spending a multiplier more energy communicating intent instead of doing the work myself; that communication seems to be making me more tired than the work itself. Similar?

whynotminot 9mo ago
It feels like we all signed up to be ICs, but now we’re middle managers and our reports are bots.
- senshan 9mo ago
  > and our reports are bots. With no gossip, rivalry or backstabbing. Super polite and patient, which is very inspiring. We also brutally churning them by "laying off" the previously latest model once the new latest is available.
- MikeTheGreat 9mo ago
  I forget where I saw this (a Medium post, somewhere) but someone summed this up as "I didn't sign up for this just to be a tech priest for the machine god".
  - whstl 9mo ago
    Someone commented yesterday that managers and other higher-ups are "already ok with non-deterministic outputs", because that's what engineers give them. As a manager/tech-lead, I've kind of been a tech priest for some time.
    - danielbln 9mo ago
      Which is why it's so funny to hear seasoned engineers lament the probabilistic nature of AI systems, and how you have to be hand setting code to really think about the problem domain. They seem to all be ICs that forget that there are abstraction layers above them where all of that happens (and more).

teaearlgraycold 9mo ago

I like to alternate focusing on AI wrangling and writing code the old fashioned way.

bugglebeetle 9mo ago

Nah, I don’t miss at all typing all the tests, CLIs, and APIs I’ve created hundreds of times before. I dunno if I it’s because I do ML stuff, but it’s almost all “think a lot about something, do some math, and and then type thousands of lines of the same stuff around the interesting work.”

mupuff1234 9mo ago

For me it's the opposite, I'm wasting less energy over debugging silly bugs and fighting/figuring out some annoying config. But it does feel less fulfilling I suppose.

agumonkey 9mo ago

I think there are two groups of people emerging. deep / fast / craft-and-decomposition-loving vs black box / outcome-only. I've seen people unable to work at average speed on small features suddenly reach above average output through a llm cli and I could sense the pride in them. Which is at odds with my experience of work.. I love to dig down, know a lot, model and find abstractions on my own. There a llm will 1) not understand how my brain work 2) produce something workable but that requires me to stretch mentally.. and most of the time I leave numb. In the last month I've seen many people expressing similar views. ps: thanks everybody for the answers, interesting to read your pov

sanufar 9mo ago
I think for me, the difference really comes down to how much ownership I want to take in regards to the project. If it’s something like a custom kernel that I’m building, the real fun is in reading through docs, learning about systems, and trying to craft the perfect abstractions; but if it’s wiring up a simple pipeline that sends me a text whenever my bus arrives, I’m happy to let an LLM crank that out for me. I’ve realized that a lot of my coding is on this personal satisfaction vs utility matrix and llms let me focus a lot more energy onto high satisfaction projects
remich 9mo ago
I get what you're saying, but I would say that this does not match my own experience. For me, prior to the agentic coding era, the problem was always that I had way more ideas for features, tools, or projects than I had the capacity to build when I had to confront the work of building everything by hand, also dealing with the inevitable difficulties in procrastination and getting started. I am a very above-average engineer when it comes to speed at completing work well, whether that's typing speed or comprehension speed, and still these tools have felt like giving me a jetpack for my mind. I can get things done in weeks that would have taken me months before, and that opens up space to consider new areas that I wouldn't have even bothered exploring before because I would not have had the time to execute on them well.
- jaapz 9mo ago

SJMG 9mo ago

I think it's the serial waiting game and inevitable context switching while you wait. Long iteration cycles are taxing

bccdee 9mo ago

So far what I've been doing is, I look for the parts that seem like they'd be rewarding to code and I do them myself with no input from the machine whatsoever. It's hard to really understand a codebase without spending time with the code, and when you're using a model, I think there's a risk of things changing more quickly than you can internalize them. Also, I worry I'll get too comfortable bossing chatbots around & I'll become reluctant to get my hands dirty and produce code directly. People talk about ruining their attention spans by spending all their time on TikTok until they can no longer read novels; I think it'd be a real mistake to let that happen to my professional skill set.

epolanski 9mo ago

Yes it's taxing and mentally draining, reading code and connecting dots is always harder than writing it. And if you let the AI too loose, as when you try to vibe code an entirely new program, I end up in the situation where in 1 day I have a good prototype and then I can spend easily 5 times as much sorting the many issues and refactoring in order to have it scale to the next features.