Akhil Verghese

And then at some point it became clear that this was a viable business and we both left Google in June of last year.

Yeah, so I'm probably at risk of reinforcing a lot of Indian stereotypes here, but most of my friends in school wanted to be engineers or doctors.

And I feel like it was interesting because I felt like one of the very fundamental differences that played a role in weighing which choice they went with was their love of...

being able to understand the system fully and being comfortable with ambiguity and uncertainty and the fact that answers are very rarely yes or no, but it could be this, could be that.

And so I found that engineers in general are very uncomfortable with that.

And it's sort of built in.

It's one of the reasons they became engineers.

And what I found is that when applying these systems that work really well in demos to enterprise environments, you really have to figure out ways to separate out the magic of LLMs into chunks that are predictable, reliable, and most importantly, testable.

so that you can bring in the level of oversight and everything else that you need to ensure that people actually feel comfortable deploying these systems.

And so this is really the gap that I found is that engineers aren't really wired to think this way.

And it kind of requires us to take a step back

re-evaluate the sort of risks we're comfortable with and where we're comfortable with taking them and then identifying the areas we're not comfortable with risk and finding workarounds, whether that's human oversight or human in the loop to kind of ensure that those areas remain not just predictable, but also accountable.

Because at the end of the day, you can never hold an LLM accountable for a mistake.

And you can't punish an LLM.

Right.

And so there is no, there are certain elements that even if the LM did it perfectly, you need accountability there for legal liability reasons and things like that.

And it's about breaking up that system in a way that all of this works well together.

So I think the best way to understand this is with an example, right?

And I think the gap here, again, comes into this engineering mindset.

If something works, it works.