If you’re a Salesforce architect your customers have probably started to ask you about generative AI. To maintain their trust, you’ll need to understand what the Einstein 1 Platform is, the unique advantages it provides, and how it’s different from other Salesforce products. This blog discusses five key concepts that architects need to know about Einstein now.
Host: Andy Whiteside
Co-host: Derek Cassese
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Andy Whiteside: Hello! Welcome to Episode 8 of Salesforce simplified. I’m your host, Andy Whiteside, and as always, I have Derek Cassis with me. Derek, let me get the commercial all the way real quick. So Zintegra is committed to helping people be successful with salesforce.
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Andy Whiteside: and that is not a small task. There is a lot to do. And we’re gonna talk about some stuff today that will be relevant to that topic. But, we believe that there is an opportunity to raise the bar as a salesforce partner for both. The customer who’s who has invested in the platform and salesforce who has developed the platform. I say that as a customer of salesforce and other partners, the the opportunity to do it better
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Andy Whiteside: is there because we’ve had to do it for ourselves. That’s what led to starting the practice and bring in Derek on Derek. What’s the most exciting thing that you talked to a customer about in the last I don’t know. Last 5 business days, 7 days.
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Derek Cassese: The most exciting thing, let’s see. So I’ve talked to a customer
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Derek Cassese: had to explain what change sets were to a customer and they didn’t really understand what that was, because
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Derek Cassese: they don’t typically do that. So I got to explain to them why the you know, the importance of sandboxes as it pertains to an org, and
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Derek Cassese: I went and just showed them, and then, you know, had an Aha like you could see the Aha moment happen. And they’re like, Oh, that’s what that is. Okay, cool.
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Derek Cassese: So. And they’ve had, I mean, multiple people in and out, and nobody’s ever taken the time to explain that to them. So it’s pretty.
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Andy Whiteside: You’re just proving my point right there, and I would know to change. Sets are either. But it I mean, kind of makes sense when you start talking about it. But
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Andy Whiteside: Not only is it an idea of knowing what it is, but also having some degree of holding yourself accountable to following.
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Derek Cassese: Yes.
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Derek Cassese: yeah, yeah, I mean.
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Derek Cassese: and that could be another. That’ll be a podcast. For a later date. Is getting into change sets and the new devops center, which is pretty cool.
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Derek Cassese: Yeah. So.
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Andy Whiteside: Let’s see. So the topic you brought for today
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Andy Whiteside: 5 things architects should know about Einstein.
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Andy Whiteside: written by Shoshone Poleski.
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Derek Cassese: Susannah.
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Andy Whiteside: Oops. Suzanne Susannah. Sorry.
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Derek Cassese: Believe it’s Suzanne Place, Dad.
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Andy Whiteside: And so, Derek, this is this is good cause. I’ve been waiting
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Andy Whiteside: well before you joined us.
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Andy Whiteside: and now, since you’ve been here. And I hear all this talk about generative AI. And I’m thinking that little salesforce Einstein guy is finally gonna be really relevant. And I think that’s kind of what we’re gonna cover today is how this Einstein thing which I love, that salesforce gives.
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Andy Whiteside: You know, these cartoon logo characters to these techniques, these topics. And I love that Einstein is the AI one that’s been around for a while, but now is gonna actually start doing stuff for me right.
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Derek Cassese: Yeah, a big time. Yeah, I’m I’m excited about it. It’s
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Derek Cassese: As we go through this, it’ll all start to make sense. But it’s it’s definitely, really powerful. And you know, it took me a little bit to to really
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Derek Cassese: have my Aha moment with this, because, you know, sometimes in what we do.
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Derek Cassese: Sometimes, you see, tech being done just to do it. And it’s not. It’s almost like, Okay, that’s cool. But I don’t really need that.
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Derek Cassese: But this is this is different. This is
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Derek Cassese: like the generative AI capabilities that it’s giving to the salesforce platform is pretty transformational. So I’m pretty excited about it.
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Andy Whiteside: Yeah. And and hopefully, the business is, gonna see that all these years we’ve been trying to get them into a platform is going to pay off, and it’s gonna pay off exponentially. And I can’t think of a better example than Einstein and salesforce.
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Derek Cassese: Yeah. Yup.
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Derek Cassese: yeah. And and part of what we’re gonna talk about, too. So anybody that was at dreamforce in September of last year, you know. The big announcement was the Einstein one platform.
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Derek Cassese: So they’re going, you know. Salesforce is going full bore ahead with, you know, AI as kind of their leading
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Derek Cassese: message to customers, and it brings along with it a lot of topics that we’ll we’ll get into here.
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Derek Cassese: Yep.
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Andy Whiteside: Alright. The first topic is, Einstein is hyper focused on trust. Derek, what does this mean? Why is it relevant.
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Derek Cassese: Yeah. So
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Derek Cassese: the
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Derek Cassese: number one value for salesforce is trust. That’s why they have trust salesforce.com.
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Derek Cassese: By the way, in his books, you know, behind the cloud.
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Derek Cassese: Benny, off discusses how that was kind of groundbreaking at the time when they were like, you know what we’re gonna have outages. Why don’t we just put it up there and be totally transparent about it?
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Derek Cassese: And I found that really fascinating. So anybody at any time can go to trust at Salesforce com
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Derek Cassese: and see if there’s any issues with the platform. So trust is a very, very important piece
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Derek Cassese: to the relationship of salesforce and their customers. And
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Derek Cassese: it’s also really important. We get into like generative AI, because now we’re in a situation where you gotta understand all the moving pieces right? And so what this is talking about is how
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Derek Cassese: it it mentions that you know the core value is trust, but also that you’ve got this concept within the Einstein one platform which is a rebranding of the salesforce platform with a focus on AI
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Derek Cassese: it the
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Derek Cassese: and there’s this thing called the Einstein Trust layer, right? Which is a Comp. It’s a variety of apps and services that kinda come together that
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Derek Cassese: do things to protect the customer and their data and content.
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Derek Cassese: And you know from, you know, one of the things that it does is it can mask personally personal, identifiable information. Pi.
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Derek Cassese: So if it’s sending, you know, if you’re sending your salesforce data into a lm, large language,
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Derek Cassese: model the
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Derek Cassese: the specifics of me like Derek Cassis. And you know, anything that is personally identifiable can be masked
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Derek Cassese: so that it’s not actually being stored in that model.
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Derek Cassese: it’s also hosted on hyper force. So that is the relationship of Salesforce and
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Derek Cassese: Microsoft.
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Derek Cassese: and it allows
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Derek Cassese: the
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Derek Cassese: use of generative AI
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Derek Cassese: without leaving the infrastructure. Since salesforce has moved the majority of orgs over to hyperforce. So now you’re actually able to leverage AI without leaving that infrastructure from within, hyper force of which has already been vetted. Because that’s where you’re running your salesforce platform, anyway. So it’s it’s all kind of combined into this one single layer.
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Derek Cassese: And that’s you know. That’s what they’re calling the Einstein trust Layer. It’s a pretty important piece of this entire discussion.
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Derek Cassese: It says. Here, you know, it also supports the use of external models. And this is, this is really important, too. Right? So
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Derek Cassese: it only will. It’s the use of external models that have agreed to a 0 retention policy.
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Derek Cassese: So that’s important. Because what that means is companies like Openai
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Derek Cassese: that exist within the trust boundary of salesforce. They are not. Go they, if you’re using their model, if you choose, hey? I want to use Openai. They’re, you know, they have contracts and agreements that they’re not saving any of your data to help train their model
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Derek Cassese: right? So if they’re not retaining any of that, so you know where your data is going, how it’s being used. You know that Pi is being masked.
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Derek Cassese: And all this is kind of building that that trust that you’re giving salesforce
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Derek Cassese: so that you can then turn around and use this technology. They’re also soon going to support. Bring your own model.
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Derek Cassese: So
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Derek Cassese: you know there are customers out there that are building their large language models. And they could bring their own right. And that’s important. Because and I’ll just kinda go back a couple of years.
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Derek Cassese: When I was at Salesforce I got the opportunity to work with the team on the blockchain product, which I thought was
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Derek Cassese: really really cool, very promising. But
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Derek Cassese: part of the issue was like, what chain do you use? You know there’s a lot of blockchains out there, and without going down that rabbit hole
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Derek Cassese: I felt like that was part of the issue and then, you know, it’s subsequently phased out. But I think that this is this is being done correctly. Where there you’re not locked into using one particular model when it comes to the Llm. That you want to use for these technologies. Right? And so
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Derek Cassese: all this allows you to
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Derek Cassese: use this AI right that’s being protected. And you’re and you’ve got a trust layer.
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Derek Cassese: But then they’re adding this one magical piece that I’ll see if this reminds you of anything, but it’s it’s
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Derek Cassese: the ability to keep the keep the people in the loop that they’re saying so. The ability to give your users the ability to
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Derek Cassese: give feedback on the responses from these models. So like a thumbs up thumbs down, was this, you know, a a good response, and that feeds back into the system and helps refine what’s being provided to the users of this of this.
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Andy Whiteside: It’s non intrusive. Real time feedback loop, feedback model.
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Derek Cassese: Yep.
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Andy Whiteside: Yeah, yeah, I think I’ve heard of that before.
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Andy Whiteside: That’s a joke inside joke. People listening don’t know we’re talking about zoom. Derek wanted to invent something similar about 10 years ago in the It space where it was just
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Andy Whiteside: this constant little button you could hit on the screen, saying, I’m I’m happy, I’m happy, I’m happy. Oh, I’m unhappy. I’m unhappy.
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Andy Whiteside: Yeah, something was worth, you know, adding comments to you could do it.
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Derek Cassese: Yeah, just you know, it’s a point in time, like, there.
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Derek Cassese: if you collect feedback at the time, the user experiences either a good experience or a bad experience, you’re gonna get really good feedback. But if you send a survey like 2 days later, it’s not gonna be that good. In my opinion, it’s gonna be people forget they may not even fill it out. So
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Andy Whiteside: They’ve moved on. They’re past the point of carrying. Whether it was good or bad at that point.
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Derek Cassese: Exactly. Yeah.
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Andy Whiteside: Derek. The next section yourself about Data cloud is crucial is a crucial part of the Einstein one platform, you know. I’ve I think I’ve heard of people talking about data lakes and data clouds several times over the past week, and how important it’s gonna be salesforce is offering up one that can be used certainly with its platforms, and beyond it seems like.
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Derek Cassese: Yeah. And you also hear, like a data lake house, that’s another term that it will be passed around here.
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Derek Cassese: I. And that that’s a much deeper conversation as far as like data. Lake, Dale Lake House.
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Derek Cassese: data lake being like very unstructured. I think I have that right.
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Derek Cassese: But anyway, what they’re saying is like data cloud. So again, another really big announcement, we were at sales at Dreamforce was that salesforce was giving all their customers on
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Derek Cassese: particular versions. And enough, I think it was like enterprise. And up they were giving them free data to cloud
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Derek Cassese: and so free data club means free a certain number of credits.
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Derek Cassese: But free data cloud to start
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Derek Cassese: digging into that technology because it’s a crucial aspect of this in that.
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Derek Cassese: you know all the data that you’re gonna be using for this generative, AI is going to be collected. And it’s going to be sitting in the data in in the data cloud platform, which is still part of the salesforce platform.
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Derek Cassese: But it allows like extremely large
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Derek Cassese: like database sizes right? And so
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Derek Cassese: you know, you can basically get the performance of this stuff. That you you typically wouldn’t been able to do without data cloud, you can get the performance that you need.
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Derek Cassese: But all the all what they’re saying here is that all their generative AI capabilities are built using data cloud infrastructure on hyper force.
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Derek Cassese: Right? And so that’s the again, you’re gonna keep here in this hyper force which allows for extreme
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Derek Cassese: like petabyte scale data.
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Derek Cassese: So you know, you can ingest, just an insane amount of data into data cloud. And then, you know, work with structured, unstructured data across this separate system. So for example.
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Derek Cassese: maybe you have data in service. Now, maybe you have data in salesforce. Maybe you have data in Microsoft. Maybe you have data in other areas which you probably all do
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Derek Cassese: you can. You can have all of that
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Derek Cassese: in data cloud, and then start, you know, generating these responses that know about all of that
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Derek Cassese: which is pretty.
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Derek Cassese: but that’s pretty. That’s pretty impressive, right? And it’s very useful. Useful information.
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Derek Cassese: To be able to just have a conversation right with
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Derek Cassese: this type of AI and the fact that
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Derek Cassese: you know fact, the data cloud is this crucial part is what they’re saying in this article is a key differentiator
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Derek Cassese: to what Salesforce is doing with AI as opposed to some of these other companies.
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Derek Cassese: Up
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Derek Cassese: might not you know that might be, hey, go, go use Snowflake, go use something else. But this is kind of an all-encompassing solution
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Derek Cassese: for customers to really start embracing this
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Derek Cassese: and so you know, and data cloud.
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Derek Cassese: It’s interesting because we’ve already done. We’ve already done a podcast on that right went through all the names that that that’s had.
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Derek Cassese: So you if you’re listening, and you haven’t heard that and go back and listen to that one where we discuss the fact that it’s not necessarily a brand new product. It’s had a bunch of names, but it’s evolved significantly
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Derek Cassese: from a use case and our reach perspective.
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Andy Whiteside: Derek. The next section is Einstein supports multiple models, and it’s multi module model module model modal. Sorry start try again.
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Andy Whiteside: Mine. So supports multiple models. And it’s multi
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Andy Whiteside: modal.
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Derek Cassese: Yeah, that’s kind of a weird thing. And real quick. Also, before I jump into that one thing I didn’t mention as well is that one of the other features of Data Cloud. And this is really important. Is the grounding piece of it
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Derek Cassese: so? And what that means is, you can ask. You can ask a generative
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Derek Cassese: AI a question.
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Derek Cassese: and it may be very ambiguous when it comes back a response. But if you’ve grounded it with like company name, like the data that you already have in salesforce. Right? You can. You can feed it that information because it already has that information, and it can get a really really refined response.
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Derek Cassese: So that’s also another benefit of data cloud. But as far as what you’re saying here, right? And it’s multiple models
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Derek Cassese: and multimodal right? And what we talked about in the beginning was how
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Derek Cassese: they’re not just locking you into a single.
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Derek Cassese: you know, a single Ll. LMLL. M. Right. It’s not just
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Derek Cassese: the salesforce hosted like code. Gen. I know that. Anthropic, I think anthropic. I would say that wrong. I think it’s anthropic or cohere. There’s a lot of them out. There’s a ton of them. But
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Derek Cassese: they, you know, if they’ve established the trust with salesforce like Openai has. Then you can. You can leverage them within this type of an arrangement.
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Derek Cassese: They also said that if you developed your own, then you’ll be able to connect it to salesforce with your bring your own model capability. So
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Derek Cassese: you know.
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Derek Cassese: But you know, supporting multiple models
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Derek Cassese: is their core approach for AI,
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Derek Cassese: and that what that allows you to do is use what you want. Use the best of breed model. Share them across.
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Derek Cassese: You know your solutions and then
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Derek Cassese: use those and what you know when you build your prompts.
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Derek Cassese: And that’s a whole nother discussion about prompt engineering. Which is this new role that’s been birthed, that objective. AI.
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Derek Cassese: But it’s the art of creating
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Derek Cassese: the prompts that you send to a generative AI model.
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Derek Cassese: And
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Derek Cassese: the more specific and the more information that you put into a prompt, the better the response is going to be for the user. And what salesforce has is prompt studio and different models will work with that
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Derek Cassese: that make sense.
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Andy Whiteside: That’s I just keep thinking every time here someone say that that’s where the whole prompt engineering skill sets gonna come in.
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Andy Whiteside: But yeah, it depends on what’s behind the curtain as well.
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Derek Cassese: Yet.
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Derek Cassese: Yeah, and it’s. And the other thing is is that it’s like it’s not even, you know. He, he! I was reading this. I was like, this is, this is kind of crazy, right? So it it doesn’t just support one modality of content generation. Right? So when they say multi modal.
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Derek Cassese: It’s not just generating text for an email. And that was something I was joking with you when we were so I was like every demo I saw seemed to be like just generating an email. And and then all of a sudden, I saw them generate code in vs. You know, in visual studio code for developers. Which kind of blew my mind as a developer that
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Derek Cassese: can’t stand having to come up with test classes
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Derek Cassese: like the ability to have this generate a test class is just.
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Derek Cassese: you know, it’s like Christmas morning
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Derek Cassese: and then you can even have it. Generate configurations and flow in salesforce. So like, it’s not just like, Hey, so and so I want to have a meeting with you. It’s it’s a different context within everything that’s being done in the salesforce platform, which is pretty impressive.
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Derek Cassese: And then here, here’s where. Here’s where this gets really interesting. So
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Derek Cassese: the article goes in and says that it’s, you know, all this becomes even more relevant
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Derek Cassese: when we prepare for autonomous agents.
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Derek Cassese: And that, I was like, oh, this is really cool, right? It’s the next wave of AI autonomous agents that leverage these Lms. Llms.
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Derek Cassese: I always say Lmmm Lms but not to predict the next word right or sentence, but to predict the next action.
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Derek Cassese: So just like that sink in for a minute. So let’s just say you’re having a conversation with salesforce Einstein co-pilot. Everybody seems to be using co-pilot
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Derek Cassese: and you’re you’re talking about.
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Derek Cassese: you know the example they say, you know. Let’s just say we’re talking about you. You want to get this opportunity closed.
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Derek Cassese: Well, it may actually understand, based on historical trending. And all this it may know what to do next.
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Derek Cassese: Right? It may automatically set up tasks
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Derek Cassese: or create a campaign
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Derek Cassese: for you? But
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Derek Cassese: they keep they they, they basically say, you know.
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Derek Cassese: so long as you’ve trained the agent on the types of tasks. You need to reach your goal. Then the AI will orchestrate.
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Derek Cassese: you know, getting that done right. There’s always going to be the like the human in the middle.
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Andy Whiteside: Yeah.
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Derek Cassese: So they they kind of address the whole like this isn’t gonna replace people. But it’s gonna augment significantly.
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Andy Whiteside: Yeah, I I know you said the the word copilots mean. And I I hate the fact that it’s being used earlier. But it’s the most applicable world word where it’s not in charge. It’s this there to help and assist you.
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Derek Cassese: Yep, and it’s and they can’t use assistant, because that’s been used everywhere. Right? So
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Derek Cassese: I guess you know that we’ll probably see many name changes.
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Andy Whiteside: I actually like Coppili, because it really can fly the plane for you.
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Andy Whiteside: But in general you’re gonna fly the plane and you’re gonna give. Make sure the co pilots doing it right. You’re not just, you know. It’s not just there to help you. It could actually do it. But
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Andy Whiteside: you’re
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Andy Whiteside: You’re gonna make sure it’s doing it right, or you’re gonna take over as needed.
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Derek Cassese: Yeah, yeah. And they should. And in here they reference another article.
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Derek Cassese: cause it says, you know again. Like I said, Einstein Copeland isn’t fully autonomous. There’s still going to be humans in the loop. But to go deeper on it. There’s another article about about that which links off of this blog, which is located on mediumcom.
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Derek Cassese: so.
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Andy Whiteside: Alright next topic here is Einstein will change the way we think about application, lifecycle management.
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Derek Cassese: Yup, yeah. So
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Derek Cassese: you know. And this one.
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Derek Cassese: this is, this is kind of an interesting one, too. So as a architect or somebody designing a system.
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Derek Cassese: And I’m like this a lot, too. Right? I’m used to writing code and then creating tests like I just mentioned. But I’m expecting a a particular response.
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Derek Cassese: and if it’s not that response, then the desk fails.
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Derek Cassese: But
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Derek Cassese: with.
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Derek Cassese: you know, and that’s a predictable result, right? And that’s kind of why you test it, you need to have predictable result based on inputs and all that good stuff. What they’re saying here is that with generative AI, it’s non deterministic. So the response could be different
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Derek Cassese: every time the prompt is sent. It could just be a different
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Derek Cassese: answer.
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Derek Cassese: which is a reason why we can’t guarantee that that answer is actually gonna be what you want. It could be totally irrelevant, based on how the system is set up.
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Derek Cassese: Which is why all these tools are like with grounding and all that good stuff you’re trying to get it to be as close to relevant. And what you’re asking for. But it’s
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Derek Cassese: it’s not like as predictable as
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Derek Cassese: what we’re used to right? And so
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Derek Cassese: and you know, when you think about application, life, cycle.
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Derek Cassese: and unit testing.
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Derek Cassese: there’s a whole concept of what they bring up here. Which is this ethical review
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Derek Cassese: to make sure that.
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Derek Cassese: like you understand to me, like to to look at the used cases so that you understand what you’re building and how the A how the AI is going to be used.
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Derek Cassese: and then you build your templates with the prompts, and you’ve tested them in the sandbox.
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Derek Cassese: Yeah, you still need to think about the response, because this is not like
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Derek Cassese: a A B equals C every time a B equals C every time it’s it’s.
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Derek Cassese: you know, not deterministic. So what the the rollout plan has to be such that
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Derek Cassese: you know you have. You have a review, you develop, and then you roll it out to a pilot group. You get feedback, you fine tune, you roll it back out, you fine tune, and then you roll it out to the masses, which may not be the traditional way that you’re doing. You know, lifecycle management.
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Derek Cassese: And they have, like, you know, they have this
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Derek Cassese: janitor today. I release plan diagram in here.
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Derek Cassese: Which, by the way, is in the format of well architected. So anybody that doesn’t know about that go to salesforce architects and read up on well architected. It’s very interesting.
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Derek Cassese: but I digress. This is, it talks about project definition.
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Derek Cassese: configure, a test pilot review.
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Derek Cassese: Beta, review that type of stuff. Right? So it’s it is going to change the way you think about rolling out.
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Derek Cassese: you know, net new applications and stuff like that.
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Andy Whiteside: Dirk section 5 here talks about has a consumption based model of, I hear a lot about how much is gonna cost and how much power is gonna be used? How do people
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Andy Whiteside: financially justify? Yeah.
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Derek Cassese: Yeah, so this is a, this is a different one, too, especially
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Derek Cassese: because, you know, salesforce has not been a consumption based.
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Derek Cassese: Solution
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Derek Cassese: never has been until now. And so the way that Salesforce is doing it, which is kind of following
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Derek Cassese: following along with the majority of the providers is, they use what they call credits, and they’re consumed on the the length of the prompts
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Derek Cassese: sent into the Llm. The outputs generated back so, depending on how complex or not complex, and how complex the answer is or not.
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Derek Cassese: you’ll be using a certain number of credits, and that’s exact. That’s what salesforce has given to the to all customers to play with. They’ve given them
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Derek Cassese: so like a certain number of credits
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Derek Cassese: to just kind of get used to it. And
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Derek Cassese: you know, it’s it’s really
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Derek Cassese: that’s that’s real high level, as far as like. So you would buy a certain number of credits based on what you want to do.
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Derek Cassese: But that is a conversation I have with, you know, like with a partner like us, and in conjunction with the salesforce team.
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Derek Cassese: to really dig into what you’re trying to do, so that you size that appropriately, because I know that there are.
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Derek Cassese: There are things you can do that use up a lot of credits.
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Derek Cassese: and then there are, you know, simple like imports that don’t. And so it’s a really important to understand that kind of out of scope for this discussion cause that gets really into the weeds on the licensing of it. But I think the takeaway here is that.
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Derek Cassese: unlike everything else, this is. This is a consumption based setup when it comes to data cloud. And it’s something to be aware of.
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Andy Whiteside: And then there the bring it all together. Right? The conclusion of
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Andy Whiteside: why people should be interested in AI
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Andy Whiteside: specifically, as it relates to salesforce to.
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Andy Whiteside: I was kind of teeted up from my perspective. It’s it’s super easy, because well, maybe I’m just been living in the sales and marketing world too long, but there’s so much we could do more efficiently and better in both marketing and sales that salesforce to me the platform that
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Andy Whiteside: that there’s a lot to be accomplished because you can never. You can never come close to doing it all AI is gonna get us a chance to do more, better.
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Derek Cassese: And yeah, and faster and more efficiently. And
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Derek Cassese: yeah, I mean the, the.
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Derek Cassese: the overall takeaways of this are, you know, those 5 points. Right? It’s it’s built on a trusted framework
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Derek Cassese: with data cloud in the middle.
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Derek Cassese: supporting multiple models
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Derek Cassese: in different areas of what you do. Right? That’s that multimodal setup.
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Derek Cassese: And
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Derek Cassese: it’s different. So it needs to be. It needs to be thought of as different. So it with the application lifecycle stuff that’s different. And the licensing is different. So that you know, all this stuff needs to be taken into account. But it’s it’s important to understand these things, because
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Derek Cassese: this is gonna be.
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Derek Cassese: In. In my opinion, this is going to be the differentiator between the the customers that are able to move quickly and get ahead of their competition.
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Derek Cassese: Faster and sell more and build bit more pipeline and be successful.
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Derek Cassese: Because if you think about it.
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Derek Cassese: and if you’ve ever written or wrote a report in salesforce.
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Derek Cassese: What do you? You’re not. You’re not. You’re not sitting there staring at your screen because you want to write a report.
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Derek Cassese: You’re sitting there spending time doing that because you want an answer to something.
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Derek Cassese: whatever that may be.
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Andy Whiteside: Yep.
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Derek Cassese: Imagine if you just literally like, if if you had somebody that knew all the answers knew everything in your salesforce environment, and you could just say, Hey, you know
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Derek Cassese: how many customers have done this in the past 90 days versus last year.
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Derek Cassese: and they were able to give you that answer in like literally
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Derek Cassese: 30 s or 10 s. Imagine what you could do like that right? And that’s an easy example.
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Derek Cassese: imagine just saying, hey.
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Derek Cassese: you know, create a create, a.
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Derek Cassese: a funny email from my bet, from my focused customers about last week’s event
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Derek Cassese: and send it in a week.
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Derek Cassese: That just stuff like that right? I mean, and I mean, it’s you could think of all these different
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Derek Cassese: use cases.
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Derek Cassese: And that’s really just making one individual more efficient. And so and that. And those are just really high level. I mean, there’s a lot of other use cases for this, the ability to
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Derek Cassese: just have conversations with the data, I think, is really fascinating. We do that a little bit.
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Derek Cassese: In in analytics, we’re but not to this level.
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Derek Cassese: And then when you bring in other other systems, you know, gets really, really interesting. So
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Derek Cassese: you know, you could talk about, hey? You know.
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Derek Cassese: how’s that? You know? Let’s just say you have projects going on that are stored in service now and assets, but yet you also have open opportunities, and you could just say, You know
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Derek Cassese: what is the status of Company ABC’s project, and is that gonna potentially cause issues with any open opportunities? Boom. And then it gives you all those answers and correlates what’s happening
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Derek Cassese: right? And all those. The way that you ask those questions are the prompts and those prompts are grounded with your data
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Derek Cassese: like nobody else’s data isn’t coming from some.
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Derek Cassese: you know, manufactured set of artificial data. It’s coming from your actual data that you created in salesforce.
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Derek Cassese: So it’s it’s fascinating stuff. It’s, I think, going to. It’s gonna change the way that these tools are used.
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Derek Cassese: There are going to be those that embrace it. They’re going to be those that don’t, and time will tell who gets left behind on some of this stuff. But
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Derek Cassese: you know this, this stuff is here. It’s here to stay.
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Andy Whiteside: Yeah, this is my third podcast of the day every single one of them talked about. You know, AI and where it’s going it. This, this has to be so applicable you. We talked about crypto and things like that. They weren’t. We’re we’re really real, they are. They are real, but they’re not as applicable. This is applicable everywhere. You you helped me out immensely just now with the idea that I’m gonna be able to just tell salesforce what I want for a report, instead of having to go through and figure out all the filters myself
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Andy Whiteside: and then have to go back days and days afterwards. Oh, I should have made the filter like this! Not that, at least at the minimum. Get me a good starting point.
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Derek Cassese: Yeah, just have a conversation with it. Right? I mean.
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Derek Cassese: reports are just a tool, because you want to get an answer to something. That’s the only reason you run. You have a report, and then filters are just because you know you want that in different ways
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Derek Cassese: that that those things are going to. I mean, this is a much, much better user interface to the same data that those reports are running on.
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Derek Cassese: Yeah, right?
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Derek Cassese: So it’s, you know, and the other the other interesting piece of this is that
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Derek Cassese: you know, salesforce. But this is.
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Derek Cassese: you could be
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Derek Cassese: 5, you know, 5 employee customer on salesforce with sales cloud. And you could use the same AI capabilities that
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Derek Cassese: you know a hundred 1,000 employee company is using. And so it’s getting this technology in the hands of anybody that wants to use it
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Derek Cassese: level in the playing field. And I think that that’s you know you just not like, Hey, you need 2.3 million dollars to use this stuff. You know you don’t.
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Andy Whiteside: Why, yeah, funny, you said lay level in the playing field, my my visual, that I was coming up my head is, it’s like that show, you know. Are you smarter than a fifth grader, and having the ability to have phone a friend for every single question they ask, and how much the likelihood of getting it right would be so if you’re not phoning a friend, you’re phoning your most intelligent friend you could ever have.
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Derek Cassese: Yeah.
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Andy Whiteside: Oh!
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Derek Cassese: Yeah, and and you know, and that’s just the again. That’s just the like where you have a question. And you didn’t answer use case right? It’s not the
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Derek Cassese: you know, the the harder ones where it’s like, hey? Make sure that we don’t have any duplicates in here, and if we do have duplicates, let me know why and when was it created, and who you know all that stuff? There’s just. There’s so much you can do. That.
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Derek Cassese: you know, it is kind of like. The sky’s the limit. But there are limits right now.
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Derek Cassese: So and there’s limits. Just you know, it’s it’s still evolving. It’s still new. You know, some of the stuff is new, like pilot, you know, like the prompting and all that stuff is new. But
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Derek Cassese: you know the idea is to embrace this and not be afraid of it. Be educated on it. Understand that there’s trust behind the way Salesforce is doing it?
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Derek Cassese: And
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Derek Cassese: you know, underneath it all, though, is the data
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Derek Cassese: really important?
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Derek Cassese: People start thinking now about their data.
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Derek Cassese: and data integrity might you know. And maybe this is a
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Derek Cassese: a little sneak, peek. But data integrity might be a topic of another discussion.
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Andy Whiteside: Well, it’s the it’s core to the whole thing.
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Andy Whiteside: Yep.
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Andy Whiteside: Derek, I I appreciate it. What did we not cover that? You would want to add, maybe, to this topic, if anything.
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Derek Cassese: Justin, if anybody’s listening to this, that is a salesforce customer that didn’t realize they
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Derek Cassese: have some data cloud. If they are on like enterprise, or up
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Derek Cassese: to reach out because you do, and we can help you do a quick pilot, or understand what you’ve got.
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Andy Whiteside: Yeah. Me going back to my previous commercial I talked about in the very beginning. We need to help you. I don’t. I don’t care who you are. There’s opportunities have a discussion to at least discuss where a value added partner who’s in it for the right reasons, might be able to help with your salesforce current and future implementations, including
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Andy Whiteside: data cloud and AI related technologies that are they’re coming period. They’re coming. And as Derek pointed out, you’ve gotta be you’ve gotta be prepared and get your team prepared to use them. Because if you don’t, you’re gonna be getting behind instantly.
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Derek Cassese: Yeah. And also I will say, this is all this, a lot of this stuff is new, right? And
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Derek Cassese: so if you’re if you’re listening, and I said something that may not be that you don’t agree with. I’d love to hear that, too, because we’re all learning here. Right? And so, Ca, further conversations on these topics are welcome. I I would enjoy that, because you know, as these things evolve
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Derek Cassese: it’s hard to keep up with, and that’s, you know, part, why we do these podcasts to help people. Just, you know, in the car where we are, listen to stuff and just get get some of it.
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Derek Cassese: But again, we’re, you know, a lot of this stuff is new and coming out as we as we go about our day throughout these years to. It’s 2024 right now. So it’d be interesting to listen to this in 5 years and see how much it’s changed.
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Andy Whiteside: And it will, we’ll we’ll get it wrong. But it won’t be for lack of trying to connect the dots.
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Derek Cassese: Absolutely.
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Andy Whiteside: Alright, sir, thank you, and we’ll do this again in 2 weeks.
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Derek Cassese: And ready.