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Duke: All right.

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Well, we almost blew all the
punch lines in the green room.

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So Corey, why don't you tell them
what we're actually, what we for

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sure are now going to talk about.

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CJ: All right, dude, today we've
got a very special guest with us,

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friend of the show, Jace Benson.

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Jace, man, it's always
good to have you here.

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Welcome to the show.

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Jace: Hey, thanks for inviting me back.

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I appreciate that.

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Duke: Jace is like the
friend of everyone, right?

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CJ: Yes.

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Duke: nobody's not friends with Jace.

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CJ: Dude, like to a person, right?

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Acknowledge.

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Whenever I saw Jace, they're like,
man, is that Jace guy awesome?

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Jace: Oh, man.

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I'm just another guy I put on, you
1 leg at a time like everybody else.

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So we can all be as good
or whoever we want to be.

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Right.

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CJ: Yeah, that's so magnanimous, but
still no, man,  you are pretty awesome.

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And so thanks  for taking the
time to chat with us today.

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Jace: no, I love it.

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I love an opportunity to
talk , with you fine folks.

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You guys always have great
insights and inspire me sometimes.

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I'm like, well, I really should
question how this works or question why

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we're doing this or what we're doing.

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What value does this add?

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Duke: Speaking about what we're
doing and value adding, , Jace

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just released AI in a box.

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Tell us about that.

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Jace: Yeah, so I really like owning
the things that I want, my blogs.

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My content,  I like having it as
mine and I think that corporations

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don't necessarily want to have their
data controlled by other people.

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Entities, And so I set off to make a
self hosted AI solution for service now.

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And that's what AI in a box is.

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That's like it's core
underpinning value that, and it

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doesn't cost an arm and a leg,

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CJ: so I'll, I'll leave the capitalist
angle,  for a bit later and figure

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out why it doesn't cost arm and a
leg when AI is like the number one

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through 20, trending items on Google.

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But yeah, , tell us a little bit
about what you mean in a box.

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That's the part of it that I feel like
it's really catchy marketing, , but I

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feel like there's something there too.

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Jace: Well, it was called
something else in a knowledge.

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Somebody said, Oh, so
it's like AI in a box.

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And I said, Oh, I'm going to
use that because really it's

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a self contained unit that.

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Does the artificial degenerative AI stuff.

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It's not the same as ServiceNavs
because it's obviously running on

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your own hardware and it's doing
its own, they call it inferences.

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It's only inferences of the text you
give it, but it's self contained.

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It doesn't make calls
outside to like open AI.

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you download the models,
you download the software.

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And then it becomes a server that you
can hit like any other integration you

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have internally within your network,

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CJ: Nice,

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Duke: that.

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I love the, in the box for that, right?

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Cause this is like a box you take
home and it's got your AI in it,

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Jace: right?

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And you can,

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Duke: to you at that point.

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It's like

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Jace: and, you know, it's
not sending stuff out, right?

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You know, it's not, getting
processed out of country.

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I've heard some, shared infrastructure
might be running cross country borders.

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I don't know what the official
stance on that stuff, but , , it

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gets weird, but if you have control
over it, you control where it is.

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When it's on.

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Who can access it what it does?

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CJ: Yeah, and I could tell you having
gone through, , the CTA training

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and such, there are definitely some
regulations about, like, where you

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can store data depending on what
country you're in and things of that

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nature and the type of data, right?

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And so, I don't think that that
changes because you're throwing it

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into a model and spreading across
whatever happens inside the A.

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I.

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black box, right?

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Like it's still data, And it still needs
to correspond to those regulations.

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So being able to control it, being
able to control where it is and

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also maybe even being able to
deploy it across your organization.

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But in ways that in discreetly, align
with those different regulations, I

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think it's also pretty cool, right?

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Because you could deploy.

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Several of these things, right?

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You can have, say, if there are
regulations where, I think Great

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Britain has one of these where the data
that's produced there needs to stay

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there or something like that, right?

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Like you can deploy your own AI
in the box for Great Britain,

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but then you can have another
ones , for the rest of the EU, right?

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Like that's something that you could do.

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Jace: I don't have it set up.

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So you can have it distributed.

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I have a couple of them at once right now.

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I'm still working on just a.

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Singular AI in a box per org but
that totally could be possible.

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Yeah.

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CJ: Look at me jumping ahead on you, man.

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So put that on one on your, uh,

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Duke: Uh, Bye bye.

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Jace: it makes a lot of sense, right?

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If you have a company that has, entities
in multiple countries, If you need

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to keep certain data ran against in
certain places, like you'd want to

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somehow devise a way to say, Oh, this
incident is for a United Kingdom.

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Resident it needs to be therefore be
processed on United Kingdom hardware,

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that's not possible today, but it
could be like, you could install

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it and then you could like, set up
the calls to use that mid server.

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CJ: Tell me what you get, I just
bought AI in the box, right?

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I got it set up.

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I assumed that this was like a Docker
container or something like that.

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And, you know, and I
got it up and running.

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Tell me how I get that connected to
service now and tell me what I get.

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Duke: a

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Jace: All right, so right now
it's, I'm not going to name the

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price because the price is going to

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CJ: No, no, no, no.

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You should never name pricing.

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Yeah,

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Jace: Right.

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but right now it's a very low static
price Price is just going to go up as

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a fixed amount, but when you purchase
it, you get an update set and you get

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a zip file and install instructions
to install the zip file as a server

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in your choosing where you are.

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you take the zip, Send it over to a
server, you SSH into the server, you

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extract the zip, and you run an install
file, and it installs it after it asks

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you a few questions, where it says give
me a username and password that will

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be used to connect to this machine.

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You'll want to note that down so
you can set it up in your instance.

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And then it'll start on its own
and then you can leave the server.

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You go into the update site after
you've imported into your instance.

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There's a settings page.

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You build a credential where you
put in that username and password.

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the mid server.

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in the IP address and port to access
this machine you just set up and it

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defaults to the tiny dolphin model,
but you can change that if you want to

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use a different model or bring your own
model in for the,  share of AI stuff.

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Once that's all set up right now, it just
has a summarize button to show that it

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does work, but because it's set up using
like the event system under the hood.

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You can call it from any back
end APIs you can think of.

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So I whipped together a subflow,
so you can just call a subflow

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and say, Hey, summarize this task
and it'll summarize that task.

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And you can choose to take the output
of that, write it to the work notes or

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send an email or whatever you want to do.

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Duke: can we dive deeper into
that because it's just , yes,

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I got this new, AI in a box.

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It's totally mine.

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It's affordable, but the really important
thing is what does it do for me?

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Jace: thinking about what value
does generative AI in general

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add to ServiceNow or any tools?

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And it's not necessarily that,
oh, it can just summarize text

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or do these things really.

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What are we after when we're looking
at this generative AI stuff, right?

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We're looking for either
feedback or direction or write.

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if we're summarizing something, hopefully
we're using that summary to save us

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time, but not reading the whole record.

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But really, maybe we should summarize
and reassign like that should be like

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the action that happens like only
really summarize it when it's going

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to get reassigned to the new group.

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So, the new group can just read the
summary instead of the whole spiel,

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CJ: Yeah.

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Duke: Maybe I'm getting ahead and
putting more on your to do list

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like Corey, but  can it summarize
more than 1 object at a time?

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Jace: Yeah.

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So.

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Duke: incident, can I say, give it a
list of incidents and have it summarize

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basically what's been going on this week?

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Jace: So right now, the only,
, functionality that it has is just, I'm

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calling it simple summarization, which
is you say, give it a specific task.

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You give it a template that kind of
looks like a mail script, and then you

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can use a  scripted notation inside
of it to give it related records.

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So you can't say like summarize
all these incidents, but you

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could write a background script.

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To like generate an event against
all those records and have

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it summarize all 10 of them.

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But I won't summarize them
as a collection right now.

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If you understand what I'm saying.

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Duke: Yeah, it's not 1
summary is 10 summaries.

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Jace: It's 10 summaries today.

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But  if, I need to add like
a general inference, option.

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So you could say like, Hey,
take these things and use

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this prompt and deal with it.

00:10:10.308 --> 00:10:10.658
Right.

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So you could say, Hey, here's 10
summaries, summarize these 10 incidents.

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In that case, you could do
it, but I like that idea.

00:10:18.215 --> 00:10:18.995
I need to add that.

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That's a very basic core, like
idea that I realized I don't have.

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CJ: So aside from Robert and I adding a
bunch of stuff to your like to do list,

00:10:31.855 --> 00:10:35.585
what I really like about
this concept, is the trust.

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With AI, there's a lot of,
conversation around trust.

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like we started off talking about,
like, where's the data going

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to be, who has control of it?

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Right?

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Like what am I shipping
my data off somewhere?

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That's not gonna be used to train a model.

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That's gonna be, you know, be, federated
out to a bunch of different people.

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And then, well, my data starts showing up
in their answers, when they ask questions

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of the eye with this situation, right?

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Like, I think the number 1
selling point of this is that you

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have the trust that your data,
stays inside of your protection.

00:11:04.127 --> 00:11:07.820
I think the number two thing for me
once I trust that, you know, okay, I

00:11:07.820 --> 00:11:10.834
can use this AI for whatever I want
it, to Robert's point, it's like, all

00:11:10.834 --> 00:11:14.084
right, so it's like, what next now,
what can I have it do for me now?

00:11:14.643 --> 00:11:18.566
So Jace, one of the things that,  I hear
a lot from my clients, Is that, when we go

00:11:18.566 --> 00:11:20.906
in and looking into like open AI, right.

00:11:20.906 --> 00:11:22.156
Like we kind of know what that does.

00:11:22.476 --> 00:11:24.926
Tell me what like AI in a box does.

00:11:24.926 --> 00:11:29.389
And then how we could inject some of
our data into  those AI models,  to

00:11:29.389 --> 00:11:33.179
make all of this work a little bit
better for us versus the generic in

00:11:33.179 --> 00:11:35.159
the sky solutions that exist currently.

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Jace: When you're asking a large
language model to do something.

00:11:39.286 --> 00:11:41.636
It's just guessing the next best thing.

00:11:41.656 --> 00:11:45.046
It's like the most expensive
autocomplete system you can buy.

00:11:45.156 --> 00:11:45.536
Right.

00:11:45.676 --> 00:11:46.286
CJ: All right.

00:11:46.486 --> 00:11:46.696
Jace: right.

00:11:46.716 --> 00:11:47.806
That's what, that's what AI is.

00:11:48.566 --> 00:11:53.555
But when you give it like 3 paragraphs
of suggested best thing, best next

00:11:53.555 --> 00:11:58.375
things to do based on the current text
that's given, it's going to give you

00:11:58.375 --> 00:12:03.325
like the best next answer, best next
thing because it has it right there in

00:12:03.325 --> 00:12:05.235
its context above the data you're doing.

00:12:05.792 --> 00:12:06.422
CJ: Gotcha.

00:12:06.562 --> 00:12:27.076
Right.

00:12:31.635 --> 00:12:34.892
Jace: a user is asking for a answer to.

00:12:35.184 --> 00:12:38.834
How should I, I'm trying to think
of like a good example here.

00:12:38.834 --> 00:12:38.849
Yeah.

00:12:39.816 --> 00:12:42.436
Say, like, you wanted to
add, , suggested resolution notes.

00:12:42.836 --> 00:12:43.356
Right?

00:12:43.462 --> 00:12:46.402
And you don't have it yet
because the instance not solved,

00:12:46.932 --> 00:12:48.562
or maybe you put it resolved.

00:12:48.679 --> 00:12:51.479
But you don't know if it
should list a list of steps.

00:12:52.104 --> 00:12:55.651
Or just like, thank you, for letting
us know this issue is resolved.

00:12:56.311 --> 00:12:58.591
You may want to give it a
couple examples of hey, here's

00:12:58.591 --> 00:13:00.211
an incident that was resolved.

00:13:00.211 --> 00:13:03.194
And here was a resolution
note of user called and said,

00:13:03.194 --> 00:13:04.114
this isn't an issue anymore.

00:13:04.294 --> 00:13:07.867
And maybe you'll give it another one that
said, have the user reboot their computer.

00:13:08.341 --> 00:13:12.327
And then they rebooted it and they had
to install a patch, For the same thing.

00:13:12.647 --> 00:13:16.131
And if you give it that kind of
context, it may use that stuff.

00:13:16.151 --> 00:13:20.991
Those things become more likely as the
next best token to be included in your

00:13:21.001 --> 00:13:25.754
resolution notes, especially if you asked
it to, hey, take the last few resolution

00:13:25.754 --> 00:13:30.897
notes from the previous incidents and
give them as an example for the current

00:13:31.237 --> 00:13:33.597
short description and work notes given.

00:13:33.597 --> 00:13:37.032
Um, So then it's you're having
an inference against content

00:13:37.032 --> 00:13:38.182
that makes sense for it.

00:13:38.782 --> 00:13:42.972
But building those prompts like that is
complicated and hard to talk through.

00:13:43.552 --> 00:13:44.182
CJ: I follow you.

00:13:44.182 --> 00:13:48.412
Duke: is that the work that you were in
a box is taken out of the system doing

00:13:48.718 --> 00:13:51.338
Jace: I want to leave some of it
in the system to like build those

00:13:51.368 --> 00:13:55.598
prompts and then send it over to the
self hosted large language model and

00:13:55.608 --> 00:13:58.181
vector databases to, get those answers.

00:13:58.554 --> 00:13:58.894
So there's

00:13:59.129 --> 00:13:59.489
Duke: I see.

00:14:00.089 --> 00:14:03.169
So, the configuration of it
is still inside service now.

00:14:04.124 --> 00:14:05.944
Jace: the configurations
inside ServiceNow.

00:14:06.484 --> 00:14:09.074
I presented this a few months
ago to one of the partners,

00:14:09.144 --> 00:14:10.804
and their feedback was clear.

00:14:11.139 --> 00:14:13.049
Jace, this is way too complicated.

00:14:13.499 --> 00:14:17.169
And so I spent like two months before
knowledge, like simplifying it down.

00:14:17.394 --> 00:14:21.404
And it's really simple right now, but
I'm re enabling things that I had that

00:14:21.404 --> 00:14:23.534
were really complicated to set up.

00:14:23.942 --> 00:14:24.662
CJ: Yeah.

00:14:24.662 --> 00:14:25.642
Duke: been working on this?

00:14:26.264 --> 00:14:28.264
Jace: Well, do you remember ScribeMonster?

00:14:28.642 --> 00:14:29.352
Duke: Yeah.

00:14:29.572 --> 00:14:31.502
So like, you're talking
like a year, right?

00:14:31.707 --> 00:14:36.727
Jace: When I stopped working on that,
about three months later, somebody said

00:14:36.727 --> 00:14:40.022
something on Discord and I thought,
you know what, I'm going to try.

00:14:40.192 --> 00:14:42.712
And I started down this
path of a self hosted.

00:14:42.857 --> 00:14:45.777
Largely like a self hosted
solution for service now.

00:14:46.532 --> 00:14:48.992
Duke: Did you know AI before that?

00:14:49.492 --> 00:14:49.732
Or

00:14:49.837 --> 00:14:51.107
Jace: I knew what I learned.

00:14:51.202 --> 00:14:52.682
Duke: your, your masterwork in it?

00:14:53.237 --> 00:14:56.207
Jace: I knew what I learned from
building that scribe monster project,

00:14:56.437 --> 00:14:58.047
which I recently open source.

00:14:58.097 --> 00:15:01.147
I learned a ton from building that
And I'm using a lot of the things

00:15:01.147 --> 00:15:03.297
I learned from that going forward.

00:15:03.615 --> 00:15:04.545
Duke: It's a ton of energy, man.

00:15:05.215 --> 00:15:06.185
It's a lot of energy.

00:15:06.795 --> 00:15:10.945
, CJ: did you intend on scribe monster
to be like a learning project to

00:15:10.945 --> 00:15:14.665
eventually get to AI in the box
or did it just work out that way?

00:15:14.960 --> 00:15:17.910
Jace: I built scribe monster
to learn AI, that is true.

00:15:18.160 --> 00:15:21.890
I started that project and I
shipped in like a week, right.

00:15:21.910 --> 00:15:24.050
It had a bunch of
updates to it eventually.

00:15:24.283 --> 00:15:27.023
And then I just stopped updating
them because companies became

00:15:27.033 --> 00:15:30.357
like adverse to running anything
on anybody else's hardware.

00:15:30.822 --> 00:15:35.132
Duke: Can we just talk about the
appreciation for how much of his extra

00:15:35.142 --> 00:15:38.652
energy Jace has , spent on this whole
thing, , not only just scribe monster,

00:15:38.652 --> 00:15:40.152
but then getting to the AI in the box.

00:15:40.742 --> 00:15:45.322
And where do you find the time and
energy when you've got a full time job?

00:15:45.837 --> 00:15:49.147
We got to get Jace a sample
of MagicMind if we can.

00:15:49.437 --> 00:15:51.647
MagicMind is a channel sponsor of ours.

00:15:51.907 --> 00:15:54.777
It is the world's first
productivity drink.

00:15:55.187 --> 00:15:56.317
It's got matcha.

00:15:56.317 --> 00:15:56.607
It's got nootropics.

00:15:57.617 --> 00:15:59.247
It's got all kinds of good stuff.

00:15:59.737 --> 00:16:03.647
Sometimes I'll have it with my coffee in
the morning, in the afternoons around this

00:16:03.657 --> 00:16:09.637
time where I usually have my three o'clock
crash, take my magic mind, boom, I'm back

00:16:09.637 --> 00:16:11.357
into flow state for the rest of the day.

00:16:11.387 --> 00:16:15.112
So Jace, thanks so much for, taking
all that extra mental energy and

00:16:15.122 --> 00:16:16.402
building these things for us.

00:16:16.432 --> 00:16:18.952
And we'll see if we can get
you a sample of magic mind.

00:16:19.102 --> 00:16:22.252
If you're interested in magic mind, just
go ahead into the description below.

00:16:22.462 --> 00:16:23.662
You'll see that there's a link.

00:16:23.712 --> 00:16:28.412
Use the promo code CJ and the Duke 20,
give you 20 percent off your first order.

00:16:28.797 --> 00:16:30.017
Jace: I'll definitely
have to give it a try.

00:16:30.117 --> 00:16:31.647
That sounds like something I could use.

00:16:35.202 --> 00:16:38.602
CJ: Piggybacking off of that, I think
it is a really good point that you

00:16:38.602 --> 00:16:44.099
have used a significant amount of
your mental, capacity, to enhance the

00:16:44.099 --> 00:16:49.133
ServiceNow ecosystem as a whole,  it's
not lost on me how much you give back.

00:16:49.191 --> 00:16:52.780
To the community,  And as I know, it's
not lost on a lot of folks out there

00:16:52.780 --> 00:16:56.072
because they're the folks that you're
giving back to, everywhere I go on

00:16:56.072 --> 00:16:59.642
LinkedIn, I see, you know, folks, you
know, mentioning your name about just

00:16:59.642 --> 00:17:04.002
something really cool that you've built
that they've gotten value out of or.

00:17:04.232 --> 00:17:06.930
A conversation that you've
had with someone or, some help

00:17:06.940 --> 00:17:07.940
that you've given someone.

00:17:07.940 --> 00:17:10.966
So I just wanted to, pick it back into
what, what the Duke was just saying,

00:17:11.016 --> 00:17:14.236
express that appreciation on behalf of
the community, . For all the work that

00:17:14.236 --> 00:17:16.176
you do, you know, that's number one.

00:17:16.316 --> 00:17:20.240
and then number two, I do actually want
an answer,  , where do you find, where

00:17:20.240 --> 00:17:22.690
do you find all the time and effort, man?

00:17:24.363 --> 00:17:29.433
Jace: when I get into a phase of building,
I drop a bunch of other hobbies that I do.

00:17:29.735 --> 00:17:34.101
I don't play video games, I don't do other
things,  I want to see a thing finished.

00:17:34.671 --> 00:17:36.051
I want to get it done.

00:17:36.385 --> 00:17:40.185
So I spend the time after I could
put the kids to bed until I go to bed

00:17:40.205 --> 00:17:43.615
working on this kind of stuff, which
gives me a couple hours every night,

00:17:43.855 --> 00:17:45.205
Some nights I don't get anything done.

00:17:45.435 --> 00:17:46.705
Other nights I do.

00:17:47.305 --> 00:17:52.095
I wish I got up earlier so I was a more
morning routine person, but I'm just not.

00:17:52.195 --> 00:17:53.335
I'm not wired that way yet.

00:17:53.655 --> 00:17:54.785
But that's where I find the time.

00:17:54.805 --> 00:17:56.805
It's before bed, generally.

00:17:57.435 --> 00:18:00.955
And then I think about when I'm not
working, because it excites me because

00:18:00.955 --> 00:18:04.275
these are the passion projects that
I, the things that I care about.

00:18:04.713 --> 00:18:09.763
Duke: if somebody was interested in AI in
a box,  tell us roughly how it deploys,

00:18:09.823 --> 00:18:14.396
how long that takes and the first things
that they would do with it, to make

00:18:14.396 --> 00:18:15.856
sure that that money was well spent.

00:18:16.901 --> 00:18:17.571
Jace: Very simple.

00:18:17.571 --> 00:18:21.801
I've been re simplifying that over
and over again, running through it

00:18:21.851 --> 00:18:25.660
with different folks, , who I've had
trying this thing now, you, you pay

00:18:25.660 --> 00:18:29.670
a fixed flat fee, and then you're
given that zip file and XML, you

00:18:29.670 --> 00:18:32.364
download those two files, you push the.

00:18:33.124 --> 00:18:37.984
Zip file to a server with like SCP
or our sink or magic wormhole or

00:18:37.994 --> 00:18:41.738
however, you want to bring that file
to that server, you deploy it, you

00:18:41.738 --> 00:18:45.405
install it, like I said before, and
then you connect it with the instance.

00:18:45.405 --> 00:18:48.195
Once you install the update set
and run through the install page.

00:18:48.305 --> 00:18:53.375
And right now, the immediate value is, you
have a sub flow that can summarize a task.

00:18:53.745 --> 00:18:58.012
So you could say when an incident
gets reassigned, you could have a

00:18:58.012 --> 00:19:01.385
work note written that says, Hey,
summarize this for that new group.

00:19:01.549 --> 00:19:03.749
That'd probably be the
most value add today.

00:19:04.329 --> 00:19:07.779
I have it presenting on the form when you
load a form, if there's a summary that

00:19:07.779 --> 00:19:10.139
exists, that's newer than the last update.

00:19:10.409 --> 00:19:12.309
And that's useful for presentations,

00:19:12.895 --> 00:19:16.165
, 
Duke: one thing I'm really curious about
is when you say it summarizes a task.

00:19:16.385 --> 00:19:20.215
. what all is it summarizing about a
task and does it do as good a job

00:19:20.215 --> 00:19:22.395
on custom task types as out of box?

00:19:22.884 --> 00:19:23.264
Jace: Right.

00:19:23.274 --> 00:19:24.294
So I made it.

00:19:24.414 --> 00:19:28.514
So the update set includes a
table, which consists of a.

00:19:28.735 --> 00:19:33.891
The table field, and then it consists of
a record template where you say, this is

00:19:33.891 --> 00:19:37.751
the template I'm going to use to present
the data to the large linked model.

00:19:38.241 --> 00:19:42.221
And then you're given a few other
fields to build out the few shot.

00:19:42.281 --> 00:19:43.781
You can put in like a record.

00:19:44.251 --> 00:19:46.671
It'll build out what that
data would look like.

00:19:46.923 --> 00:19:48.503
And then you can modify that data.

00:19:48.533 --> 00:19:52.403
So if you wanted to like, I don't know,
scrub something or add some other thing

00:19:52.433 --> 00:19:56.560
to the example data, you could do that
for the two records that it gets included.

00:19:56.933 --> 00:20:01.263
And you can use any custom fields that
you'd want within that, just like you

00:20:01.263 --> 00:20:03.223
could a mail script and a notification,

00:20:03.663 --> 00:20:07.406
Duke: One use case I see you can
go right away is,  in projects,

00:20:07.486 --> 00:20:08.946
there's the project status report.

00:20:08.946 --> 00:20:09.226
Right.

00:20:09.403 --> 00:20:10.483
CJ: Oh my God.

00:20:10.963 --> 00:20:15.113
Duke: And also projects and
demand just have slews of.

00:20:15.155 --> 00:20:16.135
big text fields

00:20:16.610 --> 00:20:16.970
CJ: Yep.

00:20:17.385 --> 00:20:20.215
Duke: demands, especially  I mean, for
crying out loud at vivid charts, we

00:20:20.215 --> 00:20:23.845
built something that we didn't like
build a summarizer, but we built a report

00:20:23.855 --> 00:20:26.135
to present as a slideshow of demands.

00:20:26.171 --> 00:20:29.531
imagine going to the demand and just
seeing the summary rather than the essay

00:20:29.531 --> 00:20:31.111
somebody's written in every single field.

00:20:31.463 --> 00:20:31.723
Jace: right?

00:20:31.723 --> 00:20:33.003
Or that on a change.

00:20:33.033 --> 00:20:35.343
I mean, I cannot believe how
much data is in a change,

00:20:35.343 --> 00:20:35.983
Duke: Oh, yeah.

00:20:36.123 --> 00:20:38.633
Or just, or just like, or the projects

00:20:38.906 --> 00:20:42.026
CJ: hold on, hold on, dude,
dude, like change, right?

00:20:42.066 --> 00:20:45.463
think about the people who approved
changes, typically management, often

00:20:45.483 --> 00:20:47.753
upper management in some places, right?

00:20:47.753 --> 00:20:49.623
Like they don't have time
to read  all of that crap.

00:20:49.633 --> 00:20:50.613
That's on the change record.

00:20:50.613 --> 00:20:50.803
Right.

00:20:50.803 --> 00:20:52.653
But you need all the crap
that's on a change record.

00:20:52.687 --> 00:20:56.547
that approval record should
have a summary, right?

00:20:56.552 --> 00:20:57.582
Duke: bingo, man.

00:20:57.582 --> 00:20:59.062
Yeah.

00:20:59.138 --> 00:21:02.598
Jace: I know the folks on listening
to this can't see, but can I

00:21:02.608 --> 00:21:05.898
share a visual with you guys
and you guys can describe it?

00:21:06.858 --> 00:21:07.128
Duke: you why.

00:21:07.128 --> 00:21:09.408
Well, I will, I will get
you on the YouTube channel

00:21:09.438 --> 00:21:11.298
and we will get you a video.

00:21:12.203 --> 00:21:12.973
Jace: Well, here, I'll, I'll,

00:21:13.063 --> 00:21:14.343
Duke: I don't know, I don't want to be

00:21:14.513 --> 00:21:18.413
Jace: I'll, I'll throw this thing up and
we can, talk about it and cause then,

00:21:18.483 --> 00:21:21.003
Duke: like an episode of some cooking
show where they're just eating in front of

00:21:21.003 --> 00:21:22.973
you and you're like, damn, it's so good.

00:21:23.163 --> 00:21:24.673
I wish you guys were here.

00:21:27.693 --> 00:21:31.013
Jace: Can you guys, can you guys
see this AI summarizers table?

00:21:31.343 --> 00:21:31.753
CJ: Yep.

00:21:31.753 --> 00:21:32.643
I just put it on the stage.

00:21:32.913 --> 00:21:33.103
Duke: Yeah,

00:21:33.213 --> 00:21:35.133
Jace: Very, very simple table, right?

00:21:35.133 --> 00:21:38.933
So let's just take a look at change
requests just because it has a little

00:21:38.933 --> 00:21:43.317
complicated caveat, So in here you define
the prompt of what it's going to do.

00:21:43.507 --> 00:21:45.707
You define the record template.

00:21:45.990 --> 00:21:47.600
Duke: So the record template
is just, it looks like a bunch

00:21:47.600 --> 00:21:50.010
of labels and field names.

00:21:50.075 --> 00:21:53.425
Jace: yep, so it literally just
reads it out like current dot

00:21:53.465 --> 00:21:56.285
when it does the evaluation,
It just reads out those values.

00:21:56.295 --> 00:21:58.625
It gets the display
value, which is critical.

00:21:58.775 --> 00:22:01.095
But here, I'm going to make a
change to this just so it triggers

00:22:01.095 --> 00:22:02.275
a change to everything else.

00:22:02.698 --> 00:22:07.008
so you can see it updated
this record a data and you can

00:22:07.008 --> 00:22:09.308
see it builds out this with

00:22:09.333 --> 00:22:10.893
Duke: It's just like a
sample record, right?

00:22:11.488 --> 00:22:13.618
Jace: well, this is an actual
record in the instance.

00:22:14.588 --> 00:22:14.868
Right?

00:22:14.868 --> 00:22:16.628
So it read change 56.

00:22:16.778 --> 00:22:19.248
it went ahead and got all
of the related approvals.

00:22:20.437 --> 00:22:22.017
CJ: dude, dude, okay,

00:22:22.242 --> 00:22:23.812
Duke: Yeah, I'm with you.

00:22:26.897 --> 00:22:30.397
Jace: But it uses this as the
context when it makes that call

00:22:30.397 --> 00:22:32.467
to summarize another change.

00:22:32.627 --> 00:22:36.467
CJ: There are people at home, dude,
there are going to be people at home

00:22:36.467 --> 00:22:39.067
listening to this like, what are
they talking about, but listen, man,

00:22:39.067 --> 00:22:49.417
like the seasonings Jace, oh my god.

00:22:51.107 --> 00:22:51.347
Duke: Okay.

00:22:51.347 --> 00:22:54.657
So basically like, can it collect
data about sub records too?

00:22:54.657 --> 00:23:03.222
Yes.

00:23:03.262 --> 00:23:06.595
Jace: but I realized, oh, I probably
should include , The tasks has like,

00:23:06.595 --> 00:23:11.165
well, I'm going to want to do this for
other tables, like approvals for changes.

00:23:11.905 --> 00:23:13.585
And so I added this syntax.

00:23:13.642 --> 00:23:17.722
but effectively anything that's in
this double bracket is evaluated.

00:23:17.870 --> 00:23:22.430
And if you prefix it with
related, it'll do a query against

00:23:22.570 --> 00:23:25.000
this table with this query.

00:23:25.040 --> 00:23:28.940
And these square brackets are
different because it is Evaluating

00:23:28.980 --> 00:23:29.180
Duke: management.

00:23:29.830 --> 00:23:30.910
It's a spaceman stuff to me, but

00:23:31.270 --> 00:23:32.890
Jace: but it, but it
reads the current CIS ID.

00:23:32.900 --> 00:23:34.570
It says, Hey, give me all the approvals

00:23:35.350 --> 00:23:35.900
Duke: right.

00:23:36.140 --> 00:23:39.870
Jace: to like with this CIS ID
and then return these two fields.

00:23:40.960 --> 00:23:44.665
Duke: So, Even if you're not a pro dev,
if somebody just explained, listen,

00:23:44.665 --> 00:23:47.115
you just put these symbols around
it and it's going to work, like you

00:23:47.115 --> 00:23:50.651
could totally get by it reminds me a
little bit about the squiggly braces,

00:23:50.651 --> 00:23:52.571
dollar sign stuff with notifications.

00:23:52.751 --> 00:23:54.241
Like I want to put the
number in the field.

00:23:54.401 --> 00:23:55.641
That's what it reminds me of.

00:23:55.951 --> 00:23:56.801
But again,

00:23:56.836 --> 00:23:57.416
Jace: right there.

00:23:57.902 --> 00:23:59.082
Duke: think about change.

00:23:59.112 --> 00:24:03.022
I'm telling you, SPM  we'll be kick
ass for this because everybody hates

00:24:03.022 --> 00:24:04.562
writing their project status reports,

00:24:05.367 --> 00:24:05.787
Jace: Yeah.

00:24:05.877 --> 00:24:07.167
If you, if you'd like,

00:24:07.222 --> 00:24:07.582
Duke: stats,

00:24:08.517 --> 00:24:12.527
Jace: if you'd like, I'd like to
build an SPM summarizer for you and

00:24:12.527 --> 00:24:14.117
project just so we can walk through it.

00:24:14.137 --> 00:24:15.657
Not right now, but if

00:24:15.792 --> 00:24:16.942
Duke: Yeah, absolutely.

00:24:16.942 --> 00:24:19.052
Let's let's do it on video, but

00:24:19.067 --> 00:24:19.417
Jace: yeah,

00:24:19.564 --> 00:24:20.334
I would love to.

00:24:21.529 --> 00:24:26.822
Duke: you can almost get it to just full
on automate the project status reports.

00:24:27.041 --> 00:24:27.581
Jace: Right.

00:24:35.073 --> 00:24:46.852
Okay.

00:24:46.912 --> 00:24:49.502
CJ: that summary of , what's
going on in real time.

00:24:49.682 --> 00:24:51.542
All just condensed into.

00:24:51.578 --> 00:24:55.025
The relevant details,   some people
don't need to know like what port

00:24:55.035 --> 00:24:57.435
and switch that you're moving
the cord from, they don't care,

00:24:57.715 --> 00:24:59.315
we're getting rid of that stuff.

00:24:59.325 --> 00:25:02.305
We're bringing all the stuff that
matters, put it in front of people and

00:25:02.315 --> 00:25:05.635
like a concise, this is what we're doing.

00:25:05.775 --> 00:25:09.463
These are the people who have
already, weighed in on this, you

00:25:09.463 --> 00:25:11.373
know, here's your decision maker pick.

00:25:11.653 --> 00:25:14.515
, dude, you have no idea,
how much I am seeing

00:25:14.593 --> 00:25:15.394
Duke: first

00:25:15.436 --> 00:25:18.736
CJ: the analysis paralysis, of,
working with the ServiceNow platform.

00:25:19.105 --> 00:25:20.135
so much data.

00:25:20.295 --> 00:25:21.875
so many different interfaces.

00:25:21.968 --> 00:25:23.698
The data is not nearly concise enough.

00:25:23.728 --> 00:25:26.908
It's not presented in a way to
make it easy for folks who don't

00:25:26.908 --> 00:25:29.798
have a lot of time to engage with
the system to make good decisions.

00:25:29.858 --> 00:25:30.668
All of this stuff.

00:25:30.731 --> 00:25:35.841
I'm seeing this thing that this AI
in the box, that you built answer

00:25:35.891 --> 00:25:37.421
all of those questions for me.

00:25:37.703 --> 00:25:39.463
I got my credit card out, dude.

00:25:41.618 --> 00:25:43.938
Jace: Well, it's, money well spent, right?

00:25:44.218 --> 00:25:46.648
The pricing model is
kind of different than a.

00:25:47.028 --> 00:25:50.145
Regular pricing model we've
seen, cause I'm, I'm tired of the

00:25:50.865 --> 00:25:52.315
sasses, just how they're priced.

00:25:52.385 --> 00:25:53.365
It's so hard.

00:25:53.521 --> 00:25:57.321
Did you guys hear about the
new Adobe, like Congress

00:25:57.386 --> 00:25:58.246
Duke: insane.

00:25:58.276 --> 00:25:58.576
That's

00:25:58.781 --> 00:25:59.431
Jace: Adobe?

00:25:59.763 --> 00:26:00.603
Duke: yes, I did.

00:26:00.643 --> 00:26:01.143
And it's.

00:26:02.023 --> 00:26:02.733
CJ: Catch me up.

00:26:03.706 --> 00:26:06.226
Duke: from what, from my reading
of it,  Adobe's new terms and

00:26:06.226 --> 00:26:11.196
services is basically you give them
an unrestricted license to anything

00:26:11.196 --> 00:26:14.616
you create, they can reproduce it
and use it in any way they want.

00:26:15.201 --> 00:26:16.661
Jace: Oh, that's not
what I'm talking about.

00:26:17.236 --> 00:26:17.876
Duke: Oh, really?

00:26:18.161 --> 00:26:21.061
Jace: I mean, that, that's
important too, right?

00:26:21.441 --> 00:26:23.621
But , the way that they
charge for it, right.

00:26:23.621 --> 00:26:26.651
They charge every month for
it, but you buy it annually.

00:26:26.651 --> 00:26:29.641
So you pay 700, 60 bucks a month.

00:26:29.791 --> 00:26:33.541
But if you cancel mid contract,
you have to still pay half

00:26:33.541 --> 00:26:34.621
of the remaining contract,

00:26:34.872 --> 00:26:35.882
Duke: That's cheesy.

00:26:36.337 --> 00:26:36.807
Jace: right?

00:26:37.017 --> 00:26:40.397
But like, my whole point is these
software as a service solutions,

00:26:40.397 --> 00:26:45.437
, they're fantastic to get paid from,
but they suck as a consumer as a

00:26:45.437 --> 00:26:47.217
company needs to pay for these things.

00:26:47.411 --> 00:26:50.581
So there's this company I
follow called 37 signals.

00:26:50.631 --> 00:26:52.031
They're the guys behind Ruby on rails.

00:26:52.127 --> 00:26:53.637
and they started this thing called once.

00:26:53.947 --> 00:26:57.757
com and they're like, there's
something broken in the system and

00:26:57.757 --> 00:26:59.727
it's how we sell some software.

00:26:59.767 --> 00:27:01.277
Not everything needs to be a SAS.

00:27:01.904 --> 00:27:05.584
Let's sell some things  and let people
own them where they don't have to

00:27:05.584 --> 00:27:07.254
keep paying a recurring fee every day.

00:27:08.214 --> 00:27:12.064
And so they came up with Campfire
as a competition to like Slack and

00:27:12.064 --> 00:27:14.727
Microsoft teams, As a chat thing.

00:27:14.807 --> 00:27:17.327
Cause like, it doesn't necessarily
need to be up all the time.

00:27:17.337 --> 00:27:20.177
It will be up all the time, but
it doesn't need to be persistently

00:27:20.187 --> 00:27:21.127
everywhere all the time.

00:27:21.457 --> 00:27:25.817
Like ServiceNow makes sense as
a SaaS, But does the generative

00:27:25.817 --> 00:27:27.417
AI functionality make sense?

00:27:27.727 --> 00:27:34.497
And so it's like a recurring fee that you
pay every month for on top of service.

00:27:34.497 --> 00:27:37.637
Now, I don't know, I think you
should be able to own that stuff.

00:27:37.637 --> 00:27:40.527
And so, because of that, I'm
selling this at a fixed price.

00:27:40.527 --> 00:27:44.661
You pay once you get access to it
forever because it's your code at

00:27:44.661 --> 00:27:48.861
that point, and I'm going to support
it until I get the version 2.

00:27:48.861 --> 00:27:49.011
0

00:27:49.776 --> 00:27:54.246
Duke: You might want to consider
Camtasia's model, which is super awesome.

00:27:54.269 --> 00:27:56.149
you buy whatever version you buy

00:27:56.180 --> 00:27:57.120
CJ: get this

00:27:57.209 --> 00:27:58.689
Duke: and then it's not a monthly fee.

00:27:58.689 --> 00:28:00.896
It's  200 bucks or something for Camtasia.

00:28:01.166 --> 00:28:04.936
But then they keep on developing
it and putting out new versions and

00:28:04.936 --> 00:28:06.576
then you buy the next version, right?

00:28:06.706 --> 00:28:06.746
Just.

00:28:07.061 --> 00:28:07.611
Jace: Right.

00:28:07.771 --> 00:28:07.801
CJ: Right.

00:28:07.935 --> 00:28:10.622
Second.

00:28:10.622 --> 00:28:10.652
I am

00:28:11.072 --> 00:28:15.262
Jace: set for version one and then when I
get the version two, if I want to add more

00:28:15.262 --> 00:28:16.902
features, I'll sell that as version two.

00:28:17.256 --> 00:28:19.436
CJ: And then you'll probably do
something like a support contract,

00:28:19.436 --> 00:28:23.606
because since you're going to be selling
this enterprises where they can, opt

00:28:23.606 --> 00:28:26.936
into like upgrades and, , certain
hours of support, they get you on

00:28:26.946 --> 00:28:28.056
the phone and that sort of thing.

00:28:28.056 --> 00:28:28.326
Right.

00:28:28.776 --> 00:28:31.066
Jace: That's not on the website,
but that's planned to be there.

00:28:31.066 --> 00:28:35.816
So you pay for a bucket of hours or you
pay per hour for support and then also

00:28:35.816 --> 00:28:40.776
workshops to help people understand like
how this works and how ANN gen works.

00:28:41.751 --> 00:28:42.021
CJ: Yeah.

00:28:42.021 --> 00:28:45.381
So this is a labor, not, not just a
labor of love from the , the standpoint

00:28:45.381 --> 00:28:49.671
of doing a technology, but also a
philosophical perspective on how we're

00:28:49.671 --> 00:28:53.391
selling software and how you feel like
it should be done in a different way,

00:28:53.641 --> 00:28:58.154
Jace: Yeah, not everything needs to
be so difficult to buy I struggle with

00:28:58.164 --> 00:29:00.274
the value when everything is a SAS,

00:29:00.642 --> 00:29:01.432
CJ: now, for sure.

00:29:01.614 --> 00:29:03.984
Duke: It's a great capstone
for the whole show.

00:29:05.649 --> 00:29:06.059
CJ: Absolutely.

00:29:06.594 --> 00:29:08.304
Jace, man, this has been great.

00:29:08.355 --> 00:29:09.715
incredibly informative.

00:29:09.715 --> 00:29:13.325
I learned so much today and I'm
super, super stoked for this.

00:29:13.437 --> 00:29:17.097
Duke: The click point for me was once
you figure out that the related records

00:29:17.597 --> 00:29:20.647
can be part of the summary, there's
so many modules that are like that.

00:29:20.925 --> 00:29:24.765
I mean, GRC, like, imagine again,
summarizing all your control tests,

00:29:25.845 --> 00:29:26.335
Jace: right.

00:29:26.515 --> 00:29:28.165
Duke: of them, thousands of them.

00:29:31.710 --> 00:29:35.030
CJ: Oh my God, CMDB, CSDM, right?

00:29:35.030 --> 00:29:38.280
Like summarizing all of those
relationships and giving me like a

00:29:38.280 --> 00:29:42.314
quick overview of what happens if this
goes down, like, can you build, can

00:29:42.379 --> 00:29:42.769
Jace: I mean,

00:29:42.874 --> 00:29:44.394
CJ: summarize impact management?

00:29:44.404 --> 00:29:46.694
Like what happens if
this switch goes down?

00:29:46.809 --> 00:29:47.119
Duke: we go.

00:29:47.169 --> 00:29:48.269
Another 40 minutes.

00:29:49.939 --> 00:29:53.522
Jace: Well, so like, you have to
realize it's only going to know

00:29:53.522 --> 00:29:55.242
to do what you've told it to do.

00:29:55.292 --> 00:29:56.972
Because it's, it's  like a spell checker.

00:29:57.072 --> 00:29:57.402
Right?

00:29:58.132 --> 00:30:02.865
So, right now, if you were to , include
like a CMDB summarizer to say  like,

00:30:02.865 --> 00:30:04.355
say you added UI action that said

00:30:10.438 --> 00:30:13.791
give you like an impact analysis if
something went down and then you pick

00:30:13.791 --> 00:30:19.474
a CI in its chain of records, you'd
want to give it examples of how that

00:30:19.504 --> 00:30:21.534
actually would work with  real things.

00:30:21.824 --> 00:30:26.164
So it could infer, how the response
should look and what it's looking for.

00:30:26.438 --> 00:30:27.738
like I said, it's just guessing,

00:30:27.918 --> 00:30:28.443
CJ: I got you.

00:30:28.443 --> 00:30:30.743
So the answer is yes, but I'll take it.

00:30:31.848 --> 00:30:32.088
Jace: Right.

00:30:32.098 --> 00:30:34.664
It might get you close, It
might give you a starting point.

00:30:34.674 --> 00:30:38.001
Like, Oh yeah, this, actually would
have this problem or the problem

00:30:38.001 --> 00:30:41.104
would happen here, but maybe it would
still be available on this port and

00:30:41.104 --> 00:30:42.264
not that port, you know what I mean?

00:30:42.264 --> 00:30:43.634
Like there may be redundancies.

00:30:43.644 --> 00:30:45.974
It may not like suggest.

00:30:46.004 --> 00:30:47.184
Cause it's simple.

00:30:47.441 --> 00:30:50.818
Duke: The thing is,  on this show,
we've, come up with, 3 or 4 just.

00:30:51.096 --> 00:30:55.496
Fantastic good use cases for this and
that's with , a little less than 40

00:30:55.496 --> 00:30:59.846
minutes of thinking so we are going
to get you the links to get in contact

00:30:59.846 --> 00:31:04.346
with chase if you want to see AI in
a box and Man, thanks for watching

00:31:04.346 --> 00:31:05.466
and we will see you on the next one.

00:31:05.714 --> 00:31:06.694
Jace: Thanks again for having me.

00:31:06.764 --> 00:31:09.694
I really appreciate this time
of yours, , Robert and CJ.

00:31:10.529 --> 00:31:11.089
Duke: You're welcome

00:31:12.114 --> 00:31:12.384
CJ: Thanks Jane's.