| ▲ | klodolph 3 days ago |
| I’ve tried the second path at work and it’s grueling. “Almost certainly succeed” requires that you mostly plan out the implementation for it, and then monitor the LLM to ensure that it doesn’t get off track and do something awful. It’s hard to get much other work done in the meantime. I feel like I’m unlocking, like, 10% or 20% productivity gains. Maybe. |
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| ▲ | bluefirebrand 3 days ago | parent | next [-] |
| 10-20% productivity gains at the expense of making it grueling sounds like a recipe for burnout |
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| ▲ | chain030 2 days ago | parent | next [-] | | The smart ones saw this early on. The rest are just catching up to the reality now. | |
| ▲ | dvfjsdhgfv 3 days ago | parent | prev [-] | | And that's how many people feel now. | | |
| ▲ | bluefirebrand 2 days ago | parent [-] | | I think it's a bad strategy Burning out a substantial portion of the workforce for short term gains is going to cause way more long term decline than the short term gains are worth | | |
| ▲ | krapp 2 days ago | parent [-] | | I think the long term assumption is that the first path mentioned by trjordan mentioned above, where AI does all the work, is the goal. The second path is a necessary evil until the first path, which requires as yet unachieved improvements in AI (maybe approaching AGI, maybe not) becomes feasible. Burning out employees doesn't matter since they're still creating more value than they otherwise would, and they'll be replaced by AI anyway. |
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| ▲ | fluoridation 3 days ago | parent | prev | next [-] |
| Agreed. Either that, or the task has really, really broad success parameters. |
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| ▲ | BinaryIgor 3 days ago | parent | prev | next [-] |
| Exactly, same for me |
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| ▲ | 3 days ago | parent | prev [-] |
| [deleted] |
