[fc417fc802]

Someone at some point had a working mental model of the code and a reputation to protect and decided that it was good enough to merge. Someone vetted and hired that person. There's a level of familiarity and history that leads others to extend trust.

[eddd-ddde]

The way I see it is that LLMs and humans are not inherently different. They are simply on different segments of a very complex spectrum of sensory input and physical output. Over time this position on the spectrum changes, for both LLMs and humans too.

With this in mind, it's all matter of what are your metrics for "trust". If you are placing trust on a human employee because it was hired, does this mean the trust comes from the hiring process? What if the LLM passed went through that too?

About familiarity and history: we are at the point were many people will start working at a new place were the strangers are the humans, you will actually be more familiar and history with LLM tools than actual humans, so how do you take that into consideration?

Obviously this is a massive simplification and reduction of the problem, but I'm still not convinced humans get a green checkmark of quality and trust just because they are humans and were hired by a company.

[KronisLV]

> Someone at some point had a working mental model of the code and a reputation to protect

This isn’t always true in absolute terms. In many places and projects it’s about doing a good enough job to be able to ship whatever the boss said and getting paid. That might not even involve understanding everything properly either.

Plenty of people view software development as just a stepping stone to management as well.

With reading enough code it becomes apparent that the code quality that AI generates will often be similar or better to human developers, even if the details and design are sometimes demented.

[ygritte]

You could never have the same amount of trust in LLM-generated code as in a human developer, even if you wrote a large amount of tests for it. There will always be one more thing that you didn't think to test. But the many reports of massive security holes in AI coding tools and their products show that nobody even bothers with testing. Neither the vendors nor the users.