Corey Knowles
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You know, it's one of those things that's a struggle to teach people, but they learn it real quick if they learn it the hard way.
You really, you only once have to accidentally embarrass yourself because you rushed, because you overtrust.
And that's
You know, I think what you're talking about, about continuing education with attorneys and making sure they understand this, understand the tool and what it can do, I think that's very valuable.
You know, something just last week was we saw this that I think could have implications for you all moving forward, especially is that, you know, there was one of the biggest advancements in GPT-5 that no one was talking about is that this way lower hallucination rate.
And which leads me to believe we'll start seeing that follow in other tools as, you know, research comes about.
Is that something you keep an eye on in like, you know, model selection you're working with or is it fully proprietary inside?
If you don't mind me asking.
You know, you're working with frontier AI models in a highly regulated industry.
What do you feel like it takes to make
cutting edge AI enterprise ready for legal professionals, like actually in the workplace.
I know you've talked about, you know, bringing in experts, but I'm also kind of curious about, you know, what you can share of maybe the technical end a little bit in terms of like, you know, how big a team you're dealing with and how long it took to build this out, stuff like that.
They disappear as fast as they show up sometimes.
I was going to say a thing about, and MVP is such an interesting subject because it kind of gets contorted a little bit.
And I really feel like a lot of people don't spend enough time on the viable.
Quite often you see the minimum.
What's the minimum we can shove out the door?
And then things have a tendency to stall.
And I think it's important that if you're going to subscribe to the MVP idea that you have to understand it's not MVP and move on.
It's MVP and finish building it in public.