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AI is automating all the easier tasks in people’s jobs, leaving them to spend 8 hours a day on the hardest problems which AIs cannot yet solve. Software engine

by chis 4mo ago

AI is automating all the easier tasks in people’s jobs, leaving them to spend 8 hours a day on the hardest problems which AIs cannot yet solve. Software engineers are probably already familiar with the feeling of burnout from thinking too hard. The reality is very few people can work on the hardest problems they’re capable of for 8 hours a day. Writing routine Python code for some system you know well is not that mentally taxing. Managing an agent that rapidly finishes tasks but needs careful review and big-picture planning is much more exhausting, and has higher returns on intelligence and deep careful thought. I think this points towards the opposite conclusion of the OP. It’s not realistic to expect 8 hours of hard work out of a knowledge worker. Remote work naturally allows this transition, as employees can work a bit less but still overachieve with AI. (I hate AI. Just observing the world we live in)

hnthrow10282910 4mo ago
Is this your reality? I’ve noticed that while the team is way more burned out people are also way less engaged and no longer critically think about edge cases or design reviews, etc anymore.
- jmalicki 4mo ago
  Then they get fired for poor performance and you hire new fresh people. Rinse, repeat.
  - kykat 4mo ago
    Fresh people meaning burned out from the previous job?
- icedchai 4mo ago
  Yep. Someone will copy-and-paste a Jira ticket into AI and blindly accept the output without thinking about the actual intent and context behind the request. It's frustrating. I use AI sparingly, mostly on personal projects where I am prototyping and the quality is not of the greatest concern.
  - Yiin 4mo ago
    your comment with "I use Ai" is as useful as saying "I eat food and it's not the best". Details matter
    - icedchai 4mo ago
      I use Claude Code. I bet that doesn’t help you much. Also, that was not the main point of my comment, which is why it didn't have much detail.
- leoqa 4mo ago
  Yeah this is true on my team for two archetypes: the new junior engineer and the old staff engineer that was too “busy” to ever actually write code. Now he’s just busy in a different superficial way.
tw04 4mo ago
> It’s not realistic to expect 8 hours of hard work out of a knowledge worker. It wasn’t really realistic to expect hard physical labor for 70 hours a week, and yet in the 1800s before unions were established to negotiate workers rights, that’s exactly what we had. What on earth makes you think non unionized IT workers aren’t going to be pushed to their breaking point and then pushed further? If AI truly starts eating all the knowledge work, there will be an endless supply of people lining up to work themselves to death.
- zombot 4mo ago
  > It wasn’t really realistic to expect hard physical labor for 70 hours a week That makes no sense at all. If it was common, it was obviously realistic.
  - port11 4mo ago
    People were, in a very literal sense, working themselves to death. The birth of the industrial age is documented as one of the worst periods in Humanity’s record for quality of life.
    - disgruntledphd2 4mo ago
      To be fair, the industrial revolution also produced more books and other records, so there's a bias there in that without the changes to technology, there might not be as many books written about that period remaining.
konovalov-nk 4mo ago
I had a few aha moments recently while thinking about this problem (automating easy parts and leaving "hard parts" unsolved). 1. Understanding the world is the bottleneck to thinking. 2. The world is an unbounded system with unpredictable behavior. Chaos. 3. An outcome is a possible state of a system. 4. Formulating an outcome means choosing a future state of the system. 5. That future state may be desired or undesired. 6. Therefore an outcome is not purely objective. It is a consensus problem. 7. Consensus is concentration around a shared outcome. 8. Consensus around an undesirable outcome is maladaptive consensus. 9. Intent is a decision that constrains future system states. 10. One outcome may relate to another. It may also relate to intents. 11. Related outcomes and intents form a problem domain. Or simply: a semantic graph. 12. A graph gives structure to otherwise ambiguous future states. 13. Structure reduces the number of possible interpretations. Or simply: reduces uncertainty. 14. High uncertainty prevents action. Low uncertainty makes action obvious. 15. A problem without structure requires thinking. 16. A structured problem can be acted upon. 17. A sufficiently structured problem becomes the solution to itself. 18. An insufficiently structured problem keeps producing chaos. 19. Problem solving is creating structure from chaos. 20. Therefore thinking is problem solving before the structure exists. We can automate action. Not understanding. Therefore we should optimize for it.
zombot 4mo ago
> overachieve with AI But only for bullshit criteria. If your work needs to be actually good to reach the goal posts, AI can have a supporting role in the background at best.

by chis 4mo ago

hnthrow10282910 4mo ago

Is this your reality? I’ve noticed that while the team is way more burned out people are also way less engaged and no longer critically think about edge cases or design reviews, etc anymore.

jmalicki 4mo ago
Then they get fired for poor performance and you hire new fresh people. Rinse, repeat.
- kykat 4mo ago
  Fresh people meaning burned out from the previous job?
icedchai 4mo ago
Yep. Someone will copy-and-paste a Jira ticket into AI and blindly accept the output without thinking about the actual intent and context behind the request. It's frustrating. I use AI sparingly, mostly on personal projects where I am prototyping and the quality is not of the greatest concern.
- Yiin 4mo ago
  your comment with "I use Ai" is as useful as saying "I eat food and it's not the best". Details matter
  - icedchai 4mo ago
    I use Claude Code. I bet that doesn’t help you much. Also, that was not the main point of my comment, which is why it didn't have much detail.
leoqa 4mo ago
Yeah this is true on my team for two archetypes: the new junior engineer and the old staff engineer that was too “busy” to ever actually write code. Now he’s just busy in a different superficial way.

tw04 4mo ago

> It’s not realistic to expect 8 hours of hard work out of a knowledge worker. It wasn’t really realistic to expect hard physical labor for 70 hours a week, and yet in the 1800s before unions were established to negotiate workers rights, that’s exactly what we had. What on earth makes you think non unionized IT workers aren’t going to be pushed to their breaking point and then pushed further? If AI truly starts eating all the knowledge work, there will be an endless supply of people lining up to work themselves to death.

zombot 4mo ago
> It wasn’t really realistic to expect hard physical labor for 70 hours a week That makes no sense at all. If it was common, it was obviously realistic.
- port11 4mo ago
  People were, in a very literal sense, working themselves to death. The birth of the industrial age is documented as one of the worst periods in Humanity’s record for quality of life.
  - disgruntledphd2 4mo ago
    To be fair, the industrial revolution also produced more books and other records, so there's a bias there in that without the changes to technology, there might not be as many books written about that period remaining.

konovalov-nk 4mo ago

I had a few aha moments recently while thinking about this problem (automating easy parts and leaving "hard parts" unsolved). 1. Understanding the world is the bottleneck to thinking. 2. The world is an unbounded system with unpredictable behavior. Chaos. 3. An outcome is a possible state of a system. 4. Formulating an outcome means choosing a future state of the system. 5. That future state may be desired or undesired. 6. Therefore an outcome is not purely objective. It is a consensus problem. 7. Consensus is concentration around a shared outcome. 8. Consensus around an undesirable outcome is maladaptive consensus. 9. Intent is a decision that constrains future system states. 10. One outcome may relate to another. It may also relate to intents. 11. Related outcomes and intents form a problem domain. Or simply: a semantic graph. 12. A graph gives structure to otherwise ambiguous future states. 13. Structure reduces the number of possible interpretations. Or simply: reduces uncertainty. 14. High uncertainty prevents action. Low uncertainty makes action obvious. 15. A problem without structure requires thinking. 16. A structured problem can be acted upon. 17. A sufficiently structured problem becomes the solution to itself. 18. An insufficiently structured problem keeps producing chaos. 19. Problem solving is creating structure from chaos. 20. Therefore thinking is problem solving before the structure exists. We can automate action. Not understanding. Therefore we should optimize for it.

zombot 4mo ago

> overachieve with AI But only for bullshit criteria. If your work needs to be actually good to reach the goal posts, AI can have a supporting role in the background at best.