Time to talk about AI

Good morning, LinkedIn friends, Value First Nation. Welcome to another episode of Value First AI Daily, your collaborative intelligence report. It is Thursday, March 12th, 2026, uh, day before George B. Thomas goes on vacation. How you doing, man?

I'm doing good, super excited to, uh, get through today and then, um, yeah, head out on vacation and spend some time with the wife. So looking, looking forward to it and, and in a relatively decent place today considering, um, all that has been going on and things that I have been trying to do.

But how about you? Oh man, uh, I feel you, I feel you. And that kind of ties into how I was gonna lead in, um, to this, like, constraints. Right, uh, the constraints of you going on vacation. It's all good now because we've got, uh, AI by our side. And, um, like, those constraints and the ability to just do whatever, uh, you know, put us in a place to make sure the value's getting done. And we're not putting it in our— we don't have to, you know, assign things to post-vacation George when he gets back as much, right? Knowing that we're going to come back to all the stuff we're behind on or, you know, whatever. So that's how I'm choosing to tie in to this lead-in. Um, because what I'm talking about is, uh, this presentation that I'm giving later today, uh, with Juan Ryan Ginsburg. Um, it's one of those moments when I first, uh, as I started making the presentation, I was like, okay, the Unified Customer View, the foundation of an AI-native revenue engine. I've never talked about those things together before. Hmm. But it's like always hard for me to disconnect, like, the whole system, right? Yeah. And, and definitely two very hot topics, I think, like that we're trying to help clients with. We're trying to help anybody with right now. And as I was given this constraint, I was like, okay, yeah, let's, let's go. Let's, let's get after it. So I'm gonna run through this. This is a presentation designed for 20, 25 minutes. I'm just gonna run through the slides with George here with this first one-shot pass after a 30-minute conversation., with, with V and the rest of the team. Um, uh, so we'll see how, how far we got. Uh, and so every AI tool you heard about today depends on one thing: none of them can give you a single complete picture of your customer. Uh, so from the annual kickoff, 2026 is all about AROPS today and having lots of discussions, me and Ryan talking about this, and this is stuff that we're doing every day, so we get to show a lot of practical examples along the way, speak from direct experience. So what is a unified customer view? Means every person who touches a customer relationship sees complete relationship context where they already work, enabling informed decisions without hunting across systems. Best case scenario for us, this is in HubSpot, but even in, even when it's not, wherever the leader wants to view the unified customer view, wherever the operations folks want to see it, we can, we can put it over there too. So that view is going to include who are they, where are they in their journey, and what do they need. We are trying to answer those questions for anybody in marketing, sales, service, support, success, leadership, anybody who's trying to answer that question in relationship to what they can do to help answer those questions. When we talk about AI native, we mean human judgment and AI capability working together in partnership, not AI bolted on, AI woven in. And value first, we're focused on relationships over transactions, empowerment over dependence, and to build everything so well that AI can just operate it and humans can focus on humans. So not as much as it could be considered a dashboard or a record view. This is really just a way to think about your system and everybody that works with it to make everything else easier. And why does it make it easier? I think before you can have your, your smooth operating AI-native system in place, everyone in your organization needs to speak the same language about customers. So language shapes how you name your properties, objects, stages, like everything in your processes. The data gets shaped by that language and it becomes structured and consistent when you're using a common language. A lot easier to use common language if you're using natural language. AI trained on that data, especially when it's also using natural language, can then make decisions that you actually trust. And then outcomes compound because everyone is building on the same foundation, everyone including AI. Okay, without common language, uh, sales calls them prospects, marketing calls them MQLs, got 5 different systems with 5 different definitions of the word engaged, and AI, uh, inherits that confusion and amplifies the hell out of it. And then you blame AI for not working well for you. But with common language, create one vocabulary, people, relationships, signals, readiness, humans, audience, researcher, like normal words to describe everyday aspects. Properties named the way humans think about customers and the way customers think about your business, and then it gets a lot easier for AI to speak the same language as you are. So this is where I'm going to show an example of a completed UCV inside of HubSpot, because again, we're trying to connect the dots between HubSpot, HubSpot AI, and AirOps and the AI initiative that every business has right now. And when you get your data model in order and you align your teams, which I should really emphasize this part more. When you can set this as a goal for the organization, all of a sudden marketing and sales Conversations get easier, it becomes less about the, the who's in charge of which system and how is that system paid for and who's gonna— it's like, nope, unified customer view is the, is the focus and we just need to find the data that's going to support it and bring it into view and everybody can get behind that goal. So that allows us to create these things in a place like HubSpot, which really, again, trying to create AI-ready context so that we can leverage AI in the way that everybody's saying we can. All right, we're going to show some examples of working with AI that leads you to, um, lead you to maintenance of that view and like answers a lot of the how of on the daily. We can't have all of our customer-facing teams spending 6 hours in the CRM just to make sure the data stays up to date for the unified customer view that everybody's agreed to. So we'll have some examples of 3 leaders here, uh, V, Sage, and Pax. COO, CCO, and CFO calling in some sub-agents. Sentinel monitoring relationship health signals. Herald preparing client session context. And Forge multiplying session insights. Into articles for internal and external use. So we've got 3 AI leaders and 50 specialist agents underneath. We've got one data foundation that is composed of the GitHub repo or the folders, the local folder structure and HubSpot data. That way humans can focus on the relationships. We get to have really good calls, ask really good questions, and then have those answers come into the system and continue to build a context foundation that leads to continued unification of context and data. We've got some tech stack and architecture we're going to talk about here. Um, our example, HubSpot CRM, Cloud Code Plus Agents, Astro Plus for Sales website, and VIP client portal is Sanity CMS. A lot of other stuff in there, um, but, uh, we're not going to dive too deep because we don't have a bunch of time. To go through all the details, but really talking about these, these layers of CRM, unified views, AI, AI layers, agents, AI like automation workflows, and then the interface that everybody needs to see. Here's an example of repo design that makes operations possible. So how contact flows from data to agents to decisions. We've got a client's example here. So these client folders, we have, you know, a configuration— who they are, what portal, what stage are they at, what's the context, business background, relationship history, which sessions have we had. So synthesized and indexed so that we're not always looking at full transcripts for everything. But then we do have access to our transcripts in there. And this is the part where there's a heavy syncing with HubSpot, and there's a balance to be had for every organization in terms of what's saved in HubSpot and what's saved you know, in your, in your repo here, right? Because then inside the repo we have, as an example of the intelligence layer, right, skills. So we've got some methodology skills like the value path and core beliefs and unified customer view, right? Enforcement language rules and platform context. So language rules, again, built by how your organization has, has reached a common language, how people refer to things in the organization. Because if you don't give AI that, it will use training data which might not match your organization's common language. And then we've got some HubSpot skills, making sure the way that we think about the data model and how we're using HubSpot and what property schemas are, right? All that's enforceable here, right? And then we've got agents that are using that, including a transcript processor agent, session brief agent, relationship Sentinel, and a bunch more that have skills built in, are called in at certain times, right? So for anybody, you know, I think the biggest takeaway and what you can do to take action on Monday morning is starting with conversations, right? Like pick a role in the org. What do they need to see? And they think about unified customer view, which I guarantee they do, right? If it's not in their CRM, they've got to create it in the moment, whether it's when they have to talk to that customer or when they're at the monthly board meeting describing what's happening with the customers in the org. Um, ask what do you need to see, and then we map it, map it out. How do we get there, right? Where does the data live today? Where do we need it to live? Properties, views, automation— like just getting everything on the table. Um, and with AI, trying not to worry about the how so much, Just tell us, just tell yourself what, get that under control and then repeat for every role, right? And again, when using a system like HubSpot with the help of AI, repeating for every role, like the hardest part is probably the conversation, right? Like just helping people feel safe to tell you what they need And then we can do some amazing things inside of a tool like HubSpot to, to clone and modularize views so that every single person on the team can have the view that they need at any given time. We've got some real client examples of what that conceptually looks like, right? Before we just go into HubSpot and start building it. Who owns it? Get this organization breakdown here, or operations org, customer org, and finance org, right? All play a role, but really in your organization, it's going to help to have an AI orchestrator or AI director or somebody who is responsible for the success of AI. In the org. A key thing here, if you're looking up how to do this, you're probably going to find a bunch of stuff of this is how you build AI, right? It's whether it's this person alone or they work closely with a chief people officer or somebody that's going to manage the humans, right? We need to manage how humans work with AI. Right, and that's the ownership that needs to be managed at this point, right? Uh, and if you need help getting started, we've got some free Value First office hours and the AI Native Shift program. Uh, what do you think, George?

Nice, very nice.

So that constraint, um, like, oh, and by the way, like, so next step, uh, is there's some, uh, there's some, some event template like Google Slides, you know, that, uh, that need to be used. Well, luckily I was able to, you know, start that process because I just— here's the API team, here's the template that we're supposed to use, and some quick, like, again, maybe an extra 10 minutes there, right? Then we got our Google Sites, and I'm going to document this, this specific case study too. I've been taking screenshots and, like, hasn't been all, like, you know, sunshine and rainbows. Uh, but, um, all of it is in view. And I think that's, uh, again, I think we mentioned this yesterday, just trying to help people see what's possible and whatever is gonna scratch that itch of like, oh yeah, I've been wanting to do something like that for a while, and it's really that easy. Let me click on that, see what happens. So, so I guess you're not going to stop hearing about Unified Customer View. I guess not.

I guess not. Oh man.

Um, uh, I tell you what though, we are seeing— and again, this The whole reason for it is like, this is not about HubSpot at all. It's like, we love HubSpot, we build for HubSpot, uh, everybody— we're in the HubSpot ecosystem, so it's always going to come out pretty orange, right? Right. But this framework was developed specifically so the leader could not say, oh, that's a HubSpot project. It's like, no. Everybody needs a unified customer view wherever they're at, whatever system they're in. They usually make it with like spreadsheets and email inboxes and slides. And it has been the clearest leadership responsibility I have found to be like, this is the part that you own and how you can help make change across the organization. Nice. Yep. Because these, um, like, it's so hard, especially with AI. Again, if you show up and say, well, how does AI work? Which tool should we use? Like, it— we could be in those conversations like for the rest of the year. Yeah, right. Um, if you can find use cases that everybody can align on, this happens to be one of them. All of a sudden the conversations just get a little bit safer, a little bit more productive, a little bit less conflict-y. And those are the stuff that I've seen get in the way of, you know, progress for years. So. What do you think, man?

I think it's a good presentation. I think hopefully people will get a ton of value out of it, and, um, and then they'll be able to, to rock and roll and do things a little bit easier, a little bit better.

And by the time you get back from vacation, everybody will be, you know, all AI native transformed. Oh yeah, everybody.

Everybody.

All right, folks. Well, thank you, George, for letting me, you know, present that in your direction. It's a practice run. Hope you have an enjoyable vacation. Thank you, sir. We'll see you back in a couple of Mondays. A couple.

Yep. Couple Mondays. All righty.

Until that time, you have a, a great trip, and we'll see everybody else tomorrow morning. Peace out, everybody.