To be fair though, moving personal to institutional knowledge was always a challenge and rarely works really well. While I value apprenticeship a lot (I do science in Central Europe where that is pivotal) I wonder whether it is also a way to move personal knowledge from person to person without ever becoming institutional knowledge. Management didn’t just bury the legacy of Ben, they missed making sure that Ben and Sarah were leaving a manual which cannot burn. We know similar problems because we, as in the scientific endeavour, keep telling people that doing core developments and writing papers about it on half-year contracts in different institutions half a globe apart for a decade is about excellence and learning to become senior rather than a lack of commitment. And we have done so for a long time. But at least juniors, dreaming of becoming a sailor on the research vessel, keep coming.
And after watching ML is exacerbating existing problems in other fields for some years, we start (!) debating whether it might be slowly replacing us, too. But rather than challenging LLMs writing papers so that other LLMs can summarize them for us, we are still thinking about the next paper and how it will be cited most because that is how it always was and will always be.
So it is not just about greed. It is the idea of ever performing better to death and the way we define success. The same reason we self-optimize and love that fitness watch and the paid subscription so much because it helps us building habits and being strong and fit and better rested so that we can work even better. In the end, we must acknowledge that we have been part of it all along and the rest is a mirror of what societies’ rules have become.








With one difference. After merging with text.com they switched to a model with on-device bridges so that the decryption on their servers is no longer needed. Ofc it’s similar if the matrix instance and the bridges run on the own server.