[zby]

This report lists failures of some AI systems. They look consequential - but the company does not seem to care. This is very strange - how can it be? I really like AI products they help me all the time - but I know I need to take into account their failure modes and be careful. But lots of organisations don't seem to do that calculation. Will competition root them out? I don't know - I am so enthusiastic about AI - but ever after the LangChain situation I can see that what is adopted is always something that has a lot of flows. The more careful developers that notice the flaws and try to find true workarounds fail because it takes time to do the design well. It is not new thing - there were Betamax mourners for decades - but it seems that the hype machine is now more and more powerful.

[Paul-Craft]

Which "LangChain situation" are you talking about? Anything specific, or just everything that's happened in the past year or so?

[zby]

What I meant was how LangChain dominated the llm frameworks scene because it loaded VC money. It was just at the beginning - now it has normalised - but I believe it did a lot of damage at that early stage by sucking all oxygen.