Jeff Dean
speaker
343 appearances
1 recordings
1 series
first heard Aug 2026
last heard 1 Aug
Jeff Dean’s voice in public audio — every appearance, attributed to the second.
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Appearances
It's a very specific one.
And there are other, I think, domains where that kind of approach can work really well, maybe in material science or chip design or things like that.
that will enable you to leverage the capabilities of a very accurate but niche model to do things that are hard today.
Yeah, I mean, I think you'll have a lot more success when working with your virtual agents if you can clearly specify what it is you want.
And the clearer you are on what it is you want, the more the agent will have sort of guidelines and sort of rules of, you know, an outline of what it is trying to accomplish.
Whereas if you don't specify very much stuff, the agent has to sort of infer what it is you meant.
And in many cases, it might infer things that are different than what you imagined.
So we've always told computer scientists from the very beginning that it's really important to specify what the software that you're writing is trying to accomplish.
before then going and writing it.
And so now we actually have agent-based systems that can do the writing, but the importance of specifying what it is you want has actually gone up.
Because before, you'd be handing it off to a very intelligent human who maybe has context or can ask you follow-up questions.
And agents can sometimes do that, but I think clear specifications is a really good idea.
And to give you an example of a...
a use of a coding agent that works extremely well is you can ask today's models to translate software from one computer language to another very effectively.
Because in that case, you actually have a incredibly detailed specification.
You have the whole software.
that says what the system is supposed to do.
And so if you have a Python implementation of something and you want a Go implementation of it, that is something that the models seem incredibly capable of doing these days because it can sort of take all the tests that are in Python, make sure they pass in the Go version, translate the test to Go, compare behavioral differences between the implementations until there aren't any.
and be highly effective because that spec is so clear.
Yeah, I mean, I think it's really...
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