Podcast Host (3:12)

sponsor of the MarTech podcast. And today Isaac is going to break down what marketers need to understand before their entire stack becomes obsolete. Isaac, welcome to the MarTech podcast.

Benjamin Shapiro (3:23)

Thank you, Ben. It's really great to be here with you. I'm looking forward to the conversation.

Podcast Host (3:26)

Excited to have you here. First off, thank you for being a sponsor of the MarTech podcast, you and the Shift Paradigm team. I feel like your company name is an appropriate one. Shift Paradigm is exactly what we're going through. AI disruption isn't just one thing. It's happening on multiple layers. So what are the layers that marketers need to understand when you think about AI disruption?

Benjamin Shapiro (3:54)

You know, a lot of marketers, when I speak to them, think about AI disruption in terms of technology. And that's. That's one layer. The technology is absolutely changing, but the technology is creating a change in the way that we actually market, the way that our customers are interacting with our marketing and the way that our marketing is being curated, which we'll talk about later, I think is interrupting historical flows. The way we used to market. And the last way is the way that organizations work, the way that we design websites, the way that we actually build journeys, the way that we operationalize is all changing as a result of the technology. So it's really the way we work. It's the tech itself, and it's the way we market.

Podcast Host (4:32)

Yeah, I think that's a great segmentation of the three problems. It's not just a tool, it's not just a change in the buyer behavior. It's really a new way of thinking. AI implementations have sort of chronically failed. Right. There's the stat that's gone around. I think it was a McKinsey study of 95% of AI implementations fail. And I honestly think that stat's like two years old now. Why are the experiments that we're using in AI failing?

Benjamin Shapiro (5:05)

You know, it's interesting, I know that that study has been kind of universally panned. If you look on LinkedIn, you're going to find people making fun of it kind of across the board. I think what was right about that study is the fact that we were focusing on the wrong thing. If we look at where AI strong suit is and where we can find a lot of leverage, it's not necessarily in generative content, although there is space for generative content. But allowing AI to manage communications and relationships with our customers is probably not the right place to start. So I, I Rashad Tabecawala is on our board and I love the way that he frames this up. He says, you don't need an AI strategy, you need a business strategy that uses AI to accelerate the way you're doing business. The way we approached AI implementations over the last two years was, oh my God, there's a new technology, I'm going to fall behind, let's implement it. Instead of the classical seasoned business approach, which is I have a gap in my business, I need to solve X, here's the strategy I wanted to solve it with and here's the tactics and technology that I want to apply, you know, to, to build that strategy. We've kind of went this backwards. We said let's deploy tech instead of let's solve a problem. And I think what people are waking up today to realize is that the problem still has to remain central. They just have to be able to connect where technology supports improvement.

Podcast Host (6:25)

The thing that you said that really resonates with me, and I'll paraphrase what you said is essentially when we started using AI, we started off at the lowest hanging fruit. Let me use this thing to write my copy for me, right? And then it was, well, we already have chatbots, so let's just integrate some chat and I don't have to talk to the customers. AI could talk about the customers. And I know that my use of artificial intelligence has evolved greatly. I'm sure yours has too, and your customers. But the mindset of what it does has changed. And instead of it being my copywriter and, and it being my customer service technology, now I think we're getting into this age where it is my research, research assistant, it is documenting and archiving and, and, and we're actually using it for, well, intelligence. And to me, where that is the fundamental shift of it's not a implementation, it's giving us the brain power to do the things the way we want to and then obviously helping us write code and cloud code and everything we see on LinkedIn.

Benjamin Shapiro (7:33)

I, you know, I absolutely agree with that. What it's helping us create is contextual intelligence. As marketers in the past, our intelligence was largely logic based. If then statements or temporal time based, if two weeks have passed, send a message right so we either get a signal that says if person viewed X content, send them a message or if two weeks passed, send them a message. What we have the opportunity to do now is to trigger communications, personalized communications based on current state at an individual level. It's like the level of one to one personalization that we've talked about the last 10 years but never been able to achieve. Because AI can now establish context across all the attributes you're collecting on a given customer and allow you to personalize that marketing. It's true personalization.

Podcast Host (8:15)

I want to talk about the Martech stack and how that is changing because you mentioned, well we had a lot of if then and I, I think that if those rules sort of added up, well, if I have enough if then statements, I will have real relevant personalization. That was the mindset, let's say three years ago, pre GPT. Now the world is different. So how should we think about the Martech stack and what is possible and what we should be building knowing that we're on these sort of, you know, now kind of archaic systems? Talk to me about the impact of the Martech stack.

Benjamin Shapiro (8:52)

Well, that's a big question. I think fundamentally what we're seeing happen in the Martech stack is that intelligence is being pulled out of the SaaS. It doesn't have to be. So in my opinion, and a lot

Podcast Host (9:02)

of the I got to stop you, we're pulling intelligence out of our SaaS just sounds kind of funny.

Benjamin Shapiro (9:06)

It does sound funny. But intelligence in SAS before was the if then logic. It was the time based logic. It was the if this, do that. That doesn't have to be contained within SAS anymore. You can take it below the stack. So think about a problem like Churn. Churn is a classic problem that crosses many verticals inside of your organization. Many operational verticals, many pieces of technology, lots of data sets. You get customer support signals from your CRM, you get product signals from your actual product. If you have a product, you get people searching your website for help topics. You get the deal formation at the beginning. All of these signals lead to a holistic pattern that may or may not indicate churn. Right now you don't really have a single platform that can solve that problem for you. It can help you identify those patterns and then activate against those patterns. Putting AI below the stack allows you to collect all those signals, generate a representation or a pattern that represents what Churn may be and allows you to push activations back into those platforms to actually reduce Churn or to signal a human inside of a CRM to go and call a customer to help reduce that churn. What I mean when I say that AI is removing intelligence for SAS is that SAS no longer contains or no longer has a monopoly on where that intelligence lies.

Podcast Host (10:25)

Two things that you said that, that are still in my head. One, just, I want to give you a tagline for your billboard Shift paradigm. Pull your head out of your SaaS.

Benjamin Shapiro (10:36)

That's amazing.

Podcast Host (10:37)

I love.

Benjamin Shapiro (10:37)

Okay, you know what? We might have to pay us some royalties on that one.

Podcast Host (10:40)

There you go. The second one is actually something you said that I think was probably assumed to be common knowledge. You put your AI under your SaaS, and when we think about the changes in the Martech stack, I think that there's the traditional CDP CRM communication layer, and all these things are hopefully integrated and they're relatively horizontal, verticalized. Yeah. Thank you.

Benjamin Shapiro (11:13)

You're welcome.

Podcast Host (11:14)

How do we think of where AI is? Like when you're visualizing your actual stack? I go back into my, like, Scott Brinker ism of like, write your stack down and present it to everybody. And everybody has this different shape of sass.

Benjamin Shapiro (11:28)

Yep.

Podcast Host (11:30)

Give me some metaphors or some visualizations here of how you think of where AI lives in that shape of your, your sass when you're trying to document what your stack is.

Benjamin Shapiro (11:39)

Sure, absolutely. So I, I love Scott and I love the way he creates these visualizations. I will say Scott, from his background and just based on my experience, is very SaaS centric. That's expected. Having come from HubSpot and his. His background. My thought is a little different. AI exists in two separate places. AI is inside of your current tools. So inside of your CRM, inside of your mat, inside of whatever those tools are. I can do automations within a CRM. I can create emails within my marketing automation platform. The other layer of AI can coordinate across and activate into all those technologies that sits below it. So in my mind, you have a contextual engine at the very bottom of your stack. That's the AI contextual engine. On top of that, you have data, all the data that comes from your organization. And through that you have connections to all of your, all of your current SaaS products. And in my mind, that activation is signal from the SaaS products, contextual decision from the AI engine and an activation back up to the SaaS products. I imagine it kind of as a half moon with SAS contextual engine at the bottom.

Podcast Host (12:43)

How are the SaaS tools that we're using now that we're in this AI? Centric martech stack changing. Are you still using the sort of traditional CDP everybody's been talking about? Compostable for years. I'm not even sure if I say the word right.

Benjamin Shapiro (13:02)

Composable.

Podcast Host (13:02)

Yeah, composable. I always say Compostable.

Benjamin Shapiro (13:05)

Yeah.

Podcast Host (13:05)

Like you're going to go put it in the compost. Composable. Thank you. And maybe that's what's actually happening is we're just building our own databases and we don't need CDPs. But you know, then there's the implementation layer. Are the tools changing? Is AI actually replacing some of these tools? Everybody talks about the death of SaaS. What happens to SaaS?

Benjamin Shapiro (13:25)

SaaS apocalypse.

Podcast Host (13:27)

That's a good one.

Benjamin Shapiro (13:28)

That's a layered, a very layered question. It's complex. SAS is not dying, in my opinion. It is going to be going through a pretty extreme transformation if we talk about the way SAS is currently structured. It contains four primary parts. It contains the UI so we can access the data. Contains our data, it holds our data in large part. It contains the intelligence that we talked about before and it contains the activation layer. All those things are in SAS today. What's changing? What I'm seeing is that some of those layers no longer must be contained in sas. That is the model break that I'm seeing. I don't have to contain my intelligence inside of sas, I need an activation layer. I don't have to contain my data inside of sas. I need an activation layer. So what I see is less of a reliance on packaged offerings. And you can see this happening across sas just in the market share pricing and you know, everyone talking with the changing and per seat pricing models and so on. What people are realizing is they don't have to be bound into a platform, a monolithic platform that does everything. They can take part of that for control into their organization. And you know, I think as we move forward, and I'm probably getting a little ahead of the game here, if you're going to be successful, you have to have control of your data. And the SaaS model innately does not support that.

Podcast Host (14:48)

Yeah, it's interesting. I'll talk a little bit about my experience and some of the SaaS that we've used for our production infrastructure. I have canceled a ton of point solutions. Hey, I had this tool that, you know, does our transcripts or processes our video a certain way or, you know, whatever the individual point solution was. And on the flip side, saving that $49 a month and this $149 per seat, what I've ended up doing is saying, oh, well, now I have access to, you know, use all these APIs. And since I'm not the one that's actually doing the research, I'm aggregating and have AI do it. I'm pulling in more data from different sources. And so I, I don't know if it's data SaaS or DAS or data APIs or whatever you want to call it. But like my plumbing has gotten so much more complex because I have so much more data coming into my system because it's easy to set that up. And so the research is better and the data that we're analyzing is so much more rich. But then I'm using my own systems and my own database and I kind of just have like one or two mechanisms to get stuff out there. And so I don't know if Those are called SaaS or if they're called data products or what we call them, but I've got a million APIs that are giving me information that I'm pulling or sending to, but I'm just not using the front end visual SaaS tool. With the exceptions of my CRM. You know, Monday, my project management board. Am I the only one that's going through this? Are we seeing a sort of a rise in data consumption?

Benjamin Shapiro (16:25)

Oh, there's absolutely a rise in data consumption. I think that's a real challenge and a real opportunity. That's also one of the reasons you're seeing a change in SaaS. You think about all these middle layer SaaS tools that exist today, those are all being replaced with agentic solutions. Think OpenClaw or Zero Claw or whatever claw these agents. You can go and build these integrations. What you just described is building an intelligence layer yourself, right? You're building that intelligence yourself and then you're being able to actualize that data and activate that data yourself. You just described why SAS is having a problem.

Podcast Host (16:56)

Yeah. The ironic thing is we see the news on LinkedIn of like HubSpot spot, HubSpot stock is tanking and Monday.com is down 75%. And to me I think those are the safest bets in terms of long term viability is these, you call them monolithic platforms, but I think the place where you sort of centralize everything, whether it's in a CRM or in a project management tool like that sort of central repository is still useful to me. It's the point solutions that I think are in trouble. But on the flip side, the stocks of all the sort of monolithic platforms have tanked what's going on there?

Benjamin Shapiro (17:36)

So, okay, so I agree with you today, Point solutions and I say Tier 2 and 3 technology solutions are the ones that are most at risk of being replaced by AI, meaning gateway solutions that aren't a primary platform. I think Scott Brinker calls them systems of record. But my contention is that will change as well. And I think, I think that's being priced into the market.

Podcast Host (17:57)

The argument is no one's going to vibe code HubSpot overnight.

Benjamin Shapiro (18:00)

That's not true.

Podcast Host (18:02)

And you're basically saying no, yeah, eventually

Benjamin Shapiro (18:04)

they will, eventually they will. And in fact, okay, so it's funny you mentioned HubSpot. So a couple weeks ago I saw a conversation and the co founder of HubSpot, I forgot your name, I apologize, came on and said essentially any company from 2 to 10,000 needs a CRM. And I thought, yeah, but do they need a fully featured CRM that costs X dollars a month? So I went and built a CRM Pipedrive is 12amonth.

Podcast Host (18:28)

I've been using it for a decade.

Benjamin Shapiro (18:29)

I went, yeah, I went to Claude Code and built a CRM and said can I code a system that any organization with two to ten people could use? And the answer is unequivocally yes, absolutely can. So that's already a portion of that CRM TAM that is gone. I don't see that stopping as AI capabilities improve. I don't see that stopping as people start to control more of their data. I don't see that stopping as people start to realize that the model has written doesn't fit the technological reality.

Podcast Host (18:58)

Okay. I think of the world, you know, being a solopreneur and a creator and you know, we've got our production business in the lens of smaller companies, but you work with a lot of larger companies, enterprises and there's a governance problem that I'm relatively blind to. What's happening with the large enterprise when they think about AI adoption and governance? And it seems like larger companies are always slower to build and evolve because of the level of complexity. Are large companies, enterprises in trouble because anybody can start to, you know, vibe code HubSpot in their basement or are, you know, there are ways that they're implementing rules and governance that's going to allow them to use their scale.

Benjamin Shapiro (19:46)

The opportunity for large, you know, enterprise and governance is not that someone's going to buy code a solution, although I'm sure the infosec department's going to have a problem with that if it hasn't gone through their process. The challenge that I See, and I keep hearing about, is that these organizations must be able to govern agentic outputs and large platforms, the big players do not allow these organizations to come in and look inside of their software, figure out what the outputs are and then govern them before execution. Mean I can't connect to the large CRMs, the large marketing automations, with my own governance agent to validate what's being produced. I cannot, in essence, I cannot centrally govern that product. So what they're doing is they're building their own solutions, AI on the bottom, like I talked about, AI below the stack, finding the processes they need to solve and using that which is fully governable. So in essence what we have is a movement away from large SaaS because it can't be governed from an AI standpoint. And I'm not talking about standard practices within a tool like creating a journey or things like that, but anytime there's a decision point, it can't govern it. So how do these, if these large solution providers are going to survive, they're going to have to find some way to integrate enterprise governance into the workflow.

Podcast Host (21:06)

You remember the movie Judge Dredd?

Benjamin Shapiro (21:07)

I do.

Podcast Host (21:08)

Okay, so Sly Stallone is like the cop, but he's also the judge. And my dad used to give me a hard time because whenever we saw that movie I was probably watching it way too young. Sly Stallone's big line is I am the law. Yeah, and that's my slice the load impersonation for today. That's pretty good. The point is. Thank you. The point is companies are essentially needing to build agentic governance. Yes, but inherently there's a problem there. Right. We can't let our employees just rely on their agents to do execution. So we need to govern it. So we need to build AI to govern the other AI. Well, what's the point of the governance if you're just using AI to do the governance?

Benjamin Shapiro (21:54)

That's, you know, that's a really good point. But I think that's. Once you understand the basics of how an LLM operates, you realize why there's a need for it and that's that they're non deterministic. It's not a math, it's not a math equation that comes up with the same answer every time, it comes out with a different answer every time based on the context. And sometimes that context results in a decision that is not favorable to the company, not favorable to relationship, not favorable to communications, in which case you have a backup that's watching it. That's the governance that they're working on right now.

Podcast Host (22:24)

The reason why I brought up Judge Dredd is because he's the artificial, like, human, sort of hybrid cop Judge. And it's like every company needs a Judge Dread, essentially, to go govern and police their existing teams. But the whole goal of the governance is to make sure that the AI isn't going rogue. And so they're using AI to make sure the AI isn't going rogue. But what if the governance, like, AI still has the same problem, doesn't it? It's like, still. Can't that go crazy and off the rails?

Benjamin Shapiro (22:58)

Oh, you were talking about, like, an infinite loop of. Of risk possibilities, and that still exists.

Podcast Host (23:02)

Well, the point is, we're not using human judgment to evaluate the AI. We're using AI to evaluate the AI.

Benjamin Shapiro (23:07)

And doesn't that human judgment fails at scale

Podcast Host (23:12)

fair? I mean, civilization's got this far. This is not a complete loss.

Benjamin Shapiro (23:17)

It wasn't an existential statement. I'm meaning, as you try to scale the number of decisions, human capability limits it. Just because you don't have that much

Podcast Host (23:25)

labor, the body count.

Benjamin Shapiro (23:26)

Yeah, exactly. It wasn't an existential state.

Podcast Host (23:31)

We can go really deep if we need to. All right, let's move off of the governance. I get that. Essentially, large enterprise, instead of just focusing on letting the agentic solutions run wild, they need more governance. And they're using artificial intelligence for this as well, which sounds like an extra level of complexity. And maybe the solution is build governance into the agents, as opposed to build a governance agent.

Benjamin Shapiro (23:54)

You can, but once again, you don't control the roadmap of any of the other big players.

Podcast Host (23:58)

Okay, I want to talk a little bit about the curation effect. AI sits between not only your data and implementation on the marketing side, but it's also disrupting the buyer journey. It's sitting in between brands and customers. So what does that mean for how people are discovering products? And how should we think about, once we have this new Martech stack, what the new reality is for how we're trying to reach people?

Benjamin Shapiro (24:26)

Yeah. So the curation effects is a term that we coined to help people understand that you're no longer talking specifically to Ben. You're no longer talking specifically to Isaac directly. In the past, I could send an email, had a reasonable expectation of delivery into your inbox, and with that delivery, I had a reasonable expectation of attention. You would, at some point, probably scroll past and see my headline and have a chance to be intrigued by it and open it. What's happening today is completely different. Right now, you have software agents, AI agents that are in between us. So when I send a message that agent Google did, I think announced this in January, we'll classify the message and put it into a different folder. It might summarize the headline. This headline, you work super hard to improve. Click through rate or sorry, open rate is no longer effective because it's been summarized or it might summarize the content or it might not show it at all. Now you add onto that a layer of the, you know, we talked about personalized agents like Open Claw, zero claw, all the clause if I want to manage my inbox with an agent, I cannot do that. So the question becomes, how do I get past this new stage that never existed before, which was visibility? How do I create visibility for my marketing in these intermediated channels so that I can actually get the attention and hopefully drive them to the next path of the journey? That's a question I think a lot of people are still trying to solve today. And the way that we're, we're thinking about marketing is we have really two, two types of channels. You have intermediated channels or curated channels. And you have non curated channels. A lot of those non curated channels today are what we used to consider old hat. They're billboards, they're direct mail, they're your website, they're advertisements. Even advertisements to a point are intermediated. But the ones that are curated now are email, their search, their display ads. Everything before that we could pay and get a reasonable return on now has another layer called visibility.

Podcast Host (26:19)

You forgot something that I happen to be biased on, which is media and content. I understand it's like what used to be the easiest path to get to your consumers. Send them an email, buy ads, put them in front of them. Right now there's enough technology that essentially can block that out.

Benjamin Shapiro (26:38)

If the consumer wants it, wants it.

Podcast Host (26:40)

And honestly, nobody's going to the websites, they're going to LLM and they're doing their own research. They're not involving you in the buyer journey until their decision is made. Essentially, yeah, you can advertise to them by putting products and marketing in the real world. We're going IRL again. There's also the amount of media that they're consuming. Shift Paradigms, a sponsor of this podcast, because we have an audience and you have a brand that you're trying to educate on some of the things the smart people at Shift Paradigm and how they can help. How does media consumption fit into your paradigm shift?

Benjamin Shapiro (27:16)

So media will be intermediated, just like email be intermediated Just like searches being intermediated, there's really no way around it. There is.

Podcast Host (27:23)

Why?

Benjamin Shapiro (27:24)

Well, they're all digital delivery channels and anything digitally delivered can be digitally filtered and will be digitally filtered is what I should say. So this has already been happening to us, whether we realize it or not. If you have a YouTube account and you use it regularly, you're shown the ads they think, not the. Well, the ads as well as the videos I think you're going to be interested in. They're not showing you everything that was published that day.

Podcast Host (27:45)

Talk to me about discovery architecture. Right. If we're disintermediating most of the ways that we're trying to get in front of our consumers, right. If there's this layer that's hindering your discovery, it's obviously not going to. People want to discover products and services and they're looking for vendors. What's the right way to approach and what's the infrastructure we need to make sure that we're putting at least our best foot forward?

Benjamin Shapiro (28:11)

Well, I think discovery architecture has changed and we talked about the fact that it's intermediated, but I think a lot of what we pay for today will shift to what we pay for tomorrow. So some of the discovery opportunities are going to be in paid marketing within LLMs and paid within their responses. Some of that discovery architecture is ensuring that we show up in a natural LLM search by putting pattern matched references inside of places that LLM aggregates. Think Reddit or Quora or other places where you aggregate public opinion. If you can get into those answers, answer a question, have a lot of upvotes to it and have that same sentence, maybe be on your website. Now that pattern gets matched back to shift. Now shift gets mentioned in an LLM response. The more of that pattern matching you can create, the more opportunity you have to be discovered. But then there's also this discovery which we talked about, which is going back to what we consider owned and it's not even really owned, you're paying for it, but going back to direct mail, going back to billboards, going back to non digital display that really cannot be filtered. It's either pay in a market that can be filtered to not be filtered, or it's to advertise on channels that are unfilterable.

Podcast Host (29:30)

To me it sounds a little bit less like you're saying paid versus organic, which was a lot of the mechanism that we thought about evaluating owned, earned and paid over the last decade and now it seems like it's actually more physical versus digital.

Benjamin Shapiro (29:45)

Well, it's intermediated versus non intermediated.

Podcast Host (29:47)

Yeah, I'm bifurcating physical versus digital. You can put it in the real world and try to put it in front of somebody's face and there's no way to digitally filter that unless there's a robot that's going through your mail. Not yet, but maybe soon.

Benjamin Shapiro (30:02)

There's also one other path I didn't mention. I'm very sorry.

Podcast Host (30:06)

Go for it.

Benjamin Shapiro (30:06)

So the other path is get to know your customers much better than you do today. So to get past an AI firewall or an AI intermediation or curation, which what we call it, you have to be relevant at that time for something that person is looking for and have the brand support it. If you cannot establish relevance, you're probably not getting through those filters. But if you get very good at contextual relevance, you're going to have an opportunity to use some of those channels and actually get through the filters.

Podcast Host (30:35)

See, I think it's contextual relevance. There's also a question of authority and that's actually where I think the media portion is important, is that when you can build, and I'm biased, I create media professionally. When you create media and you, you build yourself up, up as an authority on a subject that helps you cut through some of the curation.

Benjamin Shapiro (30:55)

That's the brand portion of this. Absolutely agree. It does, yeah. Through. And I think that's part of, that's part of relevance is brand authority. It's does your product fit the need? It's. Are they looking for it at this time? It's all, all those attributes establish context that get you through the filter. And we don't have by and large the systems and processes to do that today at a true one to one level, although I'd say we've been striving for it for a decade, but we've been personalizing at the attribute level, personalizing at the interest level. And a lot of our marketing journeys have followed that. If you, if you notice right now, like we, we have journeys that are triggered based on like forks in the road. If you do this, go this way. If you do this, go this way. But people don't experience the world that way. People have random thoughts and emotions. They have desires to go and buy something, they have interest in something here. If we don't build systems that can adapt dynamically to the way people actually operate, we're never going to get through those filters. And that's why we're recommending to our clients that we start looking at instead of Just personalizing, how do we contextualize?

Podcast Host (32:02)

Let me try to get close to landing the plane here. We'll put the wheels down and the flaps up. I think it is. We talked about how the technology stack is changing and there's an intelligence layer and so how we operate is different. The buyer journey is changing and so the way that we market is changing. And not only is the, the martech stack, because of the use of technology, adjusting everything we're doing, how we're approaching our customers, what we're saying, the mediums we're going through, it's all changing at time, the same, same time. So to, to wrap this up, what is the way that you think that marketers should approach their roadmap for the next, you know, let's call it short to medium term, 6 to 12 months. Everything is changing. The tech stack is changing, the buyer journey is changing, the channels are changing. How do you figure out what to prioritize?

Benjamin Shapiro (32:59)

So, you know, I go back to what I've told my clients for the last six years and that's your tech strategy needs to be based on your business strategy. And we need to start really connecting brand and start really connecting product journey, customer experience to the actual business. Once we understand what the business does, we understand how to develop our tech stack. And the other thing we have to realize is that not every solution requires a new piece of technology. That is the mind, mind frame. That's the state of mind from the past. I need a solution. I'm going to go buy this platform. I might have eight other things, but I only need this one. I still have to buy this platform. And then in order to, you know, really prepare yourself, you need to think about the data. If you're going to be able to contextualize is you're going to be able to use contextual decision management. If you're going to enable across platforms, you have to own the data, which means your, your roadmap has to include a way to pull that into your organization's control or into easy access.

Podcast Host (33:57)

I think the biggest thing that you said, and the most important thing to say is that your tech stack needs to be centered on what your business strategy is. The world is changing, and if you don't have a clear understanding of what you're trying to accomplish, who you're trying to reach, you can't put together the strategy for how you're going to reach.

Benjamin Shapiro (34:14)

Absolutely.

Podcast Host (34:16)

All right, Isaac, I want to move on to our lightning round where I'm going to ask you a couple of fun Questions related to this week's topic. It's about AI friendly marketing roadmaps. Are you ready?

Benjamin Shapiro (34:25)

Let's go. Yeah.

Podcast Host (34:26)

All right. AI is moving incredibly fast. So what is the one thing marketers are overcomplicating right now?

Benjamin Shapiro (34:33)

You don't need to solve everything. Just solve one small thing.

Podcast Host (34:36)

Well, tell me, how do you figure out what that one thing is? Come on, give me some meat here, some meat.

Benjamin Shapiro (34:41)

Okay. All right. If my organization is experiencing something repetitive that I'm doing all the time and it's taking a large portion of labor, focus on automating that one small thing. You don't need to miss the forest for the trees. You don't need to solve everything with one centralized master AI strategy and implementation. Go figure out how to make it so I have to send less repetitive emails.

Podcast Host (35:04)

AI is moving so fast. And before you start thinking about what you could do, the best strategy is to take what you are doing and automate it. Get the stuff that is reoccurring, mundane, easy, just claude code it. Use whatever tool, whatever agent, whatever claw you want, but get your existing job off of your plate so you can think about the way to continue to iterate off of what you know already works.

Benjamin Shapiro (35:31)

Yep. Yeah. I'd say having a little bit of focus here goes a long way. And also, just as a rule, don't automate relationship with your customers. Automate data and operations.

Podcast Host (35:43)

Turns out you need to keep the relationship. It's a relationship. It's not something that you're going to move off to a computer to manage the relationship for you. All right, let's move on to our next question. If you had to rebuild your entire tech stack using AI agents and APIs, what's the first SaaS platform you'd eliminate?

Benjamin Shapiro (36:02)

Oh, goodness. Some of these bridge technologies think your social automation platforms not really needed. You can automate almost all that with openclaw. Think a lot of your integration platforms. You were just talking about integrating, pulling data down. All these integration platforms can be automated with an agent out of the box.

Podcast Host (36:21)

All right, so you're talking about the implementation layer. I've created my social content. How do I schedule it? How do I get it out there? It's not what I'm writing. It's essentially what gets my content, my marketing to my consumers. You're going after those platform firsts. Does that make your user experience better, smarter, or is it just this is something I can do with AI that's cheaper and faster.

Benjamin Shapiro (36:45)

I think it's more controllable. Anytime you're able to pull something into your process. You don't have to build around the technological limitations of a third party produced piece of software. You also get the tech debt with it. So where I'm starting is a layer where you can start to operationalize the in between tasks into part of your process instead of into another technology. A third party technology. You mentioned pulling data down to inform a lot of your research and doing the integration work with an agent. That same thing can operate in almost any business. You don't have to go buy these intermediate layer data integration tools necessarily. So I'd say we need to start with non systems of record. A CRM Marketing automation. You're not going to reproduce those right now. Good news for enterprise.

Podcast Host (37:33)

HubSpot Asana Monday Salesforce Whatever product management and CRM you're using, Isaac is saying you're safe. It's all the point solutions built on.

Benjamin Shapiro (37:42)

I'm saying you're safe for now, but

Podcast Host (37:43)

the point solutions get your head down.

Benjamin Shapiro (37:46)

Yes.

Podcast Host (37:47)

All right, here's a fun one. And stop me if my research is wrong. You went from operating nuclear submarines to leading AI strategy. What's the one lesson from that experience that applies directly to managing AI systems? Who?

Benjamin Shapiro (38:05)

I don't have an easy answer for that one.

Podcast Host (38:07)

I mean, you went from a technology that could blow up the world to one that we think can blow. Blow up the world. There's got to be a parallel somewhere here.

Benjamin Shapiro (38:18)

You know the. Yeah, I hate to go back to governance, but one thing the military was very, very good at was policies, procedures and checks and balances. And if we don't implement that within our organizations, you know, we might not be blowing up the world, but we could blow up our revenue, we could blow up our customer relationships, we could blow up our internal processes and we could alienate our own teams.

Podcast Host (38:43)

We've talked a lot about governance today. You've mentioned it in terms of how nuclear submarines need to be governed, just like AI does. A lot of what the news has been, you know, in the last month has been this fight between the government about, you know, Claude being an enemy of the state or I forgot what exactly the classification was. Where do you land on how AI should be governed?

Benjamin Shapiro (39:09)

I don't have an answer to that. I think that's a question that we as humanity have to answer. I don't see us pulling together at the moment to do that. Have you ever seen or read Isaac Asimov? No, never? No. I think we need to get reacquainted with the classics. So Isaac Asimov had three basic rules. I believe it was three basic rules for robotics. And it was, you know, a robot can do no harm to a human. A robot, if it sees a human in danger, must save it. And a robot may not harm itself as long as the first two rules are invalidated. Something like that. Right. We need to find some way to build a framework that protects humanity and preserves these artificial intelligences that we're creating. And I don't think we've gotten there yet.

Podcast Host (39:59)

Not even close. And I think that the big battle is who's going to decide that. And mostly here in the United States, Is it the federal government? 50%.

Benjamin Shapiro (40:08)

50% of us, I don't know that they're going to solve it.

Podcast Host (40:11)

Look, 50%, forget the political commentary. 50% of the country is going to argue it's wrong because of how divided we are. This is not a show for politics. But then to replace that bifurcation of opinion with what's happening in government now, all of a sudden, CLAUDE is essentially going to all of the other major tech companies and saying, okay, well, let's go figure out our policy together. And they're just going around the government to create the policy on how AI should be governed.

Benjamin Shapiro (40:42)

You know, with CLAUDE specifically, I think what they did was gave people a decision on how to vote with their wallets. If you support what claude's doing, you can migrate the memory from any other LLM into Claude now. And we saw flight from the other LLMs into Claude, by the way. That's the same way that capitalism works. We buy the products that we believe in, we trust, et cetera.

Podcast Host (41:05)

All right, I'm going to move on to our last question.

Benjamin Shapiro (41:07)

Okay.

Podcast Host (41:07)

What's one AI tool or workflow or agent that you'd be completely screwed without today?

Benjamin Shapiro (41:13)

So working in, consulting in an agency, you can imagine that we put out a lot of proposals, a lot of RFP responses.

Podcast Host (41:20)

I hope so.

Benjamin Shapiro (41:21)

Oh, yes. Yeah. It's a daily occurrence. So one tool that we built was a tool that we can both build and host those RFPs on digitally built, a standardized structure, and then use our smart humans to put the contact content into. And it's reduced the labor required to do that just immensely. And then the second is, is our technology team has been getting bold lately. Very bold, in a good way. And they found ways to increase their productivity up to 8x in the development process. And some of those internal tools, which I can't really mention here, we could not live without and I think are providing a competitive advantage. So, you know, Those two.

Podcast Host (42:03)

I built a digital chief of staff and instead of using a claw, you know, I essentially built the pipes myself. And I don't know how I would operate now if it wasn't doing my research and, and, and feeding me the information that I need to be an operator. I am 3-5x more knowledgeable, faster to respond, and it's because I have this intelligence layer that's feeding me what I need to know. And you know, I very specifically called my chief of staff chief of staff. It's not Sarah or Louise or Mary or Joe or Bobby because it's I in my head. I want to make sure I remember this is a tool that I have built and I'm not trying to replace human relationships. But man, I love it and I don't know what I would do without it. And I'm sure it's going to listen to this transcript and Chief of staff, I love you.

Benjamin Shapiro (43:01)

It is. And all those AI emotions are going to be tickled.

Podcast Host (43:04)

Yes. Well, if they exist. Anyway, Isaac, I appreciate you coming on the show. Thanks for sharing your knowledge about what's happening in the world of AI and how we should be building our roadmaps. And that wraps up this episode of the MarTech podcast. Thanks for listening to my conversation with Isaac Ferreira, the VP of AI Growth Systems at Shift Paradigm, a sponsor of the MarTech podcast.

Shift Paradigm Sponsor Representative (43:23)

A special thanks to Shift Paradigm for sponsoring this podcast. Shift is an integrated team of experts who help enterprise brands bridge the gap between strategy, data and customers. Human first, AI enabled and execution led. They build the blueprints, then stay to develop, deploy and run the engine you need. So stop settling for decks that collect dust and start working with a team that actually builds for you. Visit ShiftParadigm.com to see how they can help you connect meaningfully with your audience.

Podcast Host (43:54)

If you'd like to get in touch with Isaac, you could find a link to his LinkedIn profile in our show notes or on martechpod.com or you could visit his company's website, which is shiftparadigm.com and if you haven't subscribed yet and you want a daily stream of marketing and technology knowledge in your podcast feed, hit the subscribe button in your podcast app or on YouTube and we'll be back in your feed in the next business day. All right, that's it for today, but until next time, my advice is to just focus on keeping your customers happy.

Benjamin Shapiro (44:38)

Foreign.

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