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The growing problem with this and many other AI offerings is the asymmetry of effort. All of them take my notes, meeting transcripts, jira tickets, code, websi

The growing problem with this and many other AI offerings is the asymmetry of effort. All of them take my notes, meeting transcripts, jira tickets, code, websites, and give me more to read. Then everyone else in the org is doing the same, to give me more to read. At the end of the day there is too much to read. AI is supposed to be reducing toil, but it's just making more.

booi 3mo ago
Have you tried having AI read it for you? /s
- stevenally 3mo ago
  The AI should be doing the reading, then deciding what to do, then doing it, right? While you are at the beach, or unemployed. That's what Sam says.
  - segmenta 3mo ago
    I would like to be on the beach. But seems like people are working more and not less with AI. Somebody needs to care enough.
    - rglullis 3mo ago
      > But seems like people are working more and not less with AI. Overall productivity hasn't increased, has it? At best there are cases of increased per productivity due to layoffs, at worst it's just busywork. > Somebody needs to care enough. Why?
      - segmenta 3mo ago
        On productivity: I feel the baseline for productivity has moved up. As a personal anecdote, I had a startup before with 25+ engineers. Now we are a startup of 2 co-founders and a couple of interns, and if I step back, I feel we can produce a surprising amount of stuff. But producing is just the input side, which brings me to 'care'. On somebody needs to care enough: I meant that AI agents by design have no intrinsic motivations, so (stating the obvious) they do not really care if the product works or actually solves the user's problem. This puts the onus on the human to care for the problem to really solve it, vs just building something. With increased AI output there are too many things to care about which the AI won't, and I believe that's why people might be working more and not less
        rglullis 3mo ago
        I think we are talking about the same thing and reaching wildly different conclusions. If "producing is just the input side" and you still need people to check if the product really solves the user's problems, then I get to conclude that the bottleneck has never been the "generating the code" part of the work, and actual productivity - i.e, delivering things that actually solves the customer's problem - is pretty much the same.
        segmenta 3mo ago
        I think we agree on the diagnosis: generating code was never the whole bottleneck. Where we differ is the conclusion. Work is implementation plus verification (specing, testing, checking it actually solves the problem). Pre-AI, implementation was so slow that verification hid inside its schedule - you verified while the next thing was being built. AI collapsed implementation time, so verification is now the exposed bottleneck - and the cheapest way teams absorb that today is more human hours. So: output per person is up, hours up too, and the delivered-value gain is real but smaller than the raw output gain suggests. Which I think explains both our observations.
segmenta 3mo ago
Fair point. But our goal with Rowboat is to do the opposite, to distill down only the parts you care about. For instance, you are not expected to read meeting notes, the important parts from it are added to your knowledge graph. That way next time you want to know something like 'where are we on x', you can find exactly that without having to wade through irrelevant information to get there.
StackOptimist 3mo ago
[flagged]

booi 3mo ago

Have you tried having AI read it for you? /s

stevenally 3mo ago
The AI should be doing the reading, then deciding what to do, then doing it, right? While you are at the beach, or unemployed. That's what Sam says.
- segmenta 3mo ago
  I would like to be on the beach. But seems like people are working more and not less with AI. Somebody needs to care enough.
  - rglullis 3mo ago
    > But seems like people are working more and not less with AI. Overall productivity hasn't increased, has it? At best there are cases of increased per productivity due to layoffs, at worst it's just busywork. > Somebody needs to care enough. Why?
    - segmenta 3mo ago
      On productivity: I feel the baseline for productivity has moved up. As a personal anecdote, I had a startup before with 25+ engineers. Now we are a startup of 2 co-founders and a couple of interns, and if I step back, I feel we can produce a surprising amount of stuff. But producing is just the input side, which brings me to 'care'. On somebody needs to care enough: I meant that AI agents by design have no intrinsic motivations, so (stating the obvious) they do not really care if the product works or actually solves the user's problem. This puts the onus on the human to care for the problem to really solve it, vs just building something. With increased AI output there are too many things to care about which the AI won't, and I believe that's why people might be working more and not less
      - rglullis 3mo ago
        I think we are talking about the same thing and reaching wildly different conclusions. If "producing is just the input side" and you still need people to check if the product really solves the user's problems, then I get to conclude that the bottleneck has never been the "generating the code" part of the work, and actual productivity - i.e, delivering things that actually solves the customer's problem - is pretty much the same.
        segmenta 3mo ago
        I think we agree on the diagnosis: generating code was never the whole bottleneck. Where we differ is the conclusion. Work is implementation plus verification (specing, testing, checking it actually solves the problem). Pre-AI, implementation was so slow that verification hid inside its schedule - you verified while the next thing was being built. AI collapsed implementation time, so verification is now the exposed bottleneck - and the cheapest way teams absorb that today is more human hours. So: output per person is up, hours up too, and the delivered-value gain is real but smaller than the raw output gain suggests. Which I think explains both our observations.

segmenta 3mo ago

Fair point. But our goal with Rowboat is to do the opposite, to distill down only the parts you care about. For instance, you are not expected to read meeting notes, the important parts from it are added to your knowledge graph. That way next time you want to know something like 'where are we on x', you can find exactly that without having to wade through irrelevant information to get there.

StackOptimist 3mo ago

[flagged]