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ajrouvoet

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Do you mean that specifically those models perform badly without guidance or do all models need specific instructions for technical writing?

We have observed that it is a loss for teamwork that the sparring with AI is entirely lost when only the technical conclusion is recorded. I write to recover that for my team and an AI can use it to its advantage as a side effect.

It would be cool to have good tool support for this process, but I’d bet on support, not delegation in that case.

Although I’d like this to work, I have not seen evidence that AIs extract good reusable knowledge from sessions without strong guidance.

I do R&D work in comp sci and usually write software and reports or papers in parallel. I have been using Opus in a controlled human-in-the-loop fashion to (significantly) speed up the work. While I’m at times surprised how high-level input steers output the right way, no high level ideas emerge from the AIs output. Many attempts to abstract from the concrete are wrong.

As a consequence, most writing is poor on content and form. It writes about the wrong things and crosses abstraction levels all the time. It cannot keep implementation details and conceptual leaps apart.

I don’t know what this means for the aim of this project to maintain important info for agents. Perhaps there are enough low-hanging fruits. That said, I’m skeptical that the resulting wiki is good documentation for human contributors.

I think that just highlights how “empowerment” through tech is biased towards producers, which makes sense because that aligns with the usual business propositions.

For consumers, YT is not empowering. It fulfills a need, well enough to tie them to the platform. But it is obviously not set up to hand them any more power than to serve that goal. You want to shield yourself from wasting time here? Sorry, not sorry, our goal is to steal your attention and entertain you just enough that you keep scrolling.