The Executive Revenue Lab with Michael and Lara How today's revenue leaders are rebuilding GTM for t

So if you could let real people in, that'd be great.

This meeting is being recorded.

We're gonna get started here pretty soon, everybody. Just letting everybody in. Hey, Martin.

Recording in progress.

Oh, hello.

I think I'll let a couple of note-takers in, Michael. How about that for a start?

Sorry.

I'm declining them.

All right.

We don't have 50 note-takers in here, but leave mine in. Mine's Fireflies.

You got it.

Well, we'll get started here in a little bit. We got a special guest here, uh, or co-host, I would say, um, Lara from Hawksmoor.

AI.

So, Laura, why don't you make some small talk while we're letting people in?

Hi, everyone. Thank you for joining us today. What I'd love to see—

What are we going to talk about today?

Should we talk about AI? I don't know. It's overhyped a little bit. Maybe we should just change the subject. By the way, so fun to see friends in the audience. So I love the friendly faces, people I've been wanting to connect, connect with for a while, and new faces also, of course. But hi, Emily. Hi, Keith. And, uh, I know there are others.

But if you guys want to put your information in chat, again, this, this is a roundtable definitely about AI solutions and tips and tactics. And, you know, it's, it's, it's really what it says, the Revenue Lab, right? How do we increase revenue? What's some tips and tactics around that? What's Michael and Laura's background and help? And then we wanna touch on your background too, as, as well. But what we don't want is sales pitch, pitch slapping, any of that stuff. Here's what I do, here's how I help. Even if you make it sound like you're, you're giving us advice, it's sales pitchy.

Mm-hmm.

It's gonna get way too much into that and people are gonna never come back to these things. And I'm not, I'm not doing it or saying this because I'm trying to be a jerk, but no one's going to want to hear 50 sales pitches today. So if you want to pitch what you do because you want to connect and make partners, this is why we do it. But do that in chat so you guys can do a one-on-one in chat. You guys could do a one-on-one there. You guys could say, here's my Calendly. Feel free to go crazy there. Um, but today we're gonna really be about What's working, what's not, strategy, tips, tactics. If you talk about things, think about TEDx, right? I know someone that went through this, that did that, and they got there. The storytelling is what makes it interesting versus here's what our feature does, which is pitch slapping, or here's how I help somebody.

And also, Liza—

Laura, do you want to kind of add to that just so we make sure that we kind of hit on a certain approach on this roundtable?

Yeah, I mean, one of my favorite— one thing I like the most in these situations is examples, right? What's really working and failures are— it's one of our topics for today, but they're as important as anything else. But I love the real stories. Like there's someone who is invested in a business with 2 close friends from college that I know and is working with someone on building AI agents because this is their side job. And they're figuring out how do they build agents so that they can make, you know, get better traction in this business that they've invested in. And, you know, those are the stories that I love to hear, the human side of it, and how are we using AI to really, you know, improve areas of our lives or business in unique ways.

And here's the agenda that we put into the invite, and I'll put it in chat here. It's one AI win, maybe AI failure, one GTM lesson, one prediction. I'm gonna start off because this is Laura and my roundtable. And so we're gonna not pitch, we're gonna give you why we're doing this and who we are. Because obviously, if you control the event, you can be a little bit of self-promo. But, um, I do these things for a living. I do roundtables and masterminds and podcasts. And intent data, go-to-market strategies, building a whole cloud co-work around your CRM and your GTM, and just really developing how do you build your top of funnel. So I'm Michael Filotta. I've been doing this for 25 years in sales and marketing, AI over the last 5 years, and my information will be in chat. But would love to work with you. Love referrals. Love to work all together as far as. One big happy family. I see people putting their LinkedIn in the chat. Great, but who are you? What do you do? Why are you here? What's something you want to gain? Like, I'm trying to figure this out, or I want to let people know I do this. So put more than just your LinkedIn, you know, put your deck, put your Calendly link, put stuff that's going to say, oh, I want— I would love to connect with Matthew or Steve or Lee. And Laura, tell us who, what your background. You have a big background in what you do and you just built your own company. So tell us a little bit about what you do. And then we're gonna go into, I wanna go into the, we'll each start with one failure or one, one failure or one, what's what I'm trying to think. I just lost my brain thought. One success, go ahead.

Hi everyone. So I'm Laura Shackelford. I spent 25+ years in leading go-to-market growth marketing for CMO for startups, but mostly large enterprises. I was a part of the Global Demand Center at Microsoft. I ran the Americas. It was an AI-native go-to-market system before we were calling those things AI-native. And I started at Microsoft actually decades ago doing demand in the old-fashioned way in spreadsheets. And so I've seen it all and I love it. I love the place that we're in with AI. I love the possibilities. And I also know I'm getting some incredible wins and I'm making all, you know, making the mistakes along the way too. And so anyway, my, what I wanna do is help people through that. I do run a Women in AI group just as a community that I really care about making sure there's a place for people to come together. We meet every other Friday. And just as an example, we're meeting this Friday to figure out how people can build agents and bring them into other organizations with, you know, enterprise, with security. how do they roll them out to other companies, things like that. So anyway, those are the— that's actually my community that's doing it, but those are the kinds of problems that my company and I solve is, you know, we'll go in and build strategy orchestration and build agents for companies. We work with everyone from $20 million to $6 billion companies. And in fact, one of the largest financial services firms, companies in Asia Pacific. So we're, We work with companies at all sizes right now. We'll see where we, where we focus. And that's me. And like I said, I just think this is interesting. I want to help you. I want us to help each other through it.

What's your, what's your, your one go-to-market? I know we just, you and I decided to do LinkedIn automation around this whole invite process for you with me. I would, I would love to focus in on how to make a partner like you and me grow together and how we did this. And we have 100 people registered for today. So talk, tell us, tell us what your opinion was on, on building these roundtables as a part of a way to connect with people, build your business, and also help other people versus just you.

Yeah, well, I think what's really nice is Michael and I come to this with complementary skills. Michael is really good at, you know, LinkedIn automation, getting, you know, doing outreach, bringing these roundtables together. I've spent a lot of time in my career both at scale but at enterprise companies where we're trying to get to, you know, focused audiences. And I just see the future of B2B completely changing in terms of how marketing engagement happens. I don't think, you know, we all know this personalization that we've been experiencing is terrible and it persists. I still get the awful emails all day long in LinkedIn.

Oh, yeah.

Right. And so, yeah, the one yesterday that I find— I don't respond, I ignore them. But yesterday I got the one that said, Laura, question mark, question mark, question mark, that like I owed someone something, right?

Yeah.

And I, I don't think that is definitely not the future. It's not this. I think it's being focused and being even more personalized. Like every lead I've gotten has come to me. And this is, this is, that's, this is the non-scalable version of it. They've all come to me inbound through relationships that I've built and me reaching out and connecting with people one-on-one because I genuinely care about them. And meeting those people in roundtables or CMO dinners. And so I think, you know, take that and figure out how you, you know, how you manufacture that and be an individual in how you engage with people. Laura, that's key to be—

Laura just connected with someone because of our outreach that I did for her and us to someone that she hasn't talked to in years. Because a lot of people have— I have 30,000 connections. I don't talk to all these people for 10 years sometimes. But if you do something where you're opening the door, cracking it open, saying, I want to put you on the roundtable or podcast, or I want to see if you're going to inbound or this conference, and you're not pitching, you're just saying, hey, what's going on? And not just saying, how are you doing? But asking an opinion question or giving them a compliment to do something with you. Laura, dude, who was that you just connected? You don't have to say who it was, but it was someone that was something that you want to connect with again.

Yeah.

Yeah, it was someone— I'm not saying this because you're here, Keith. The first 8 years of my career were at Oracle, and it always will hold a special place in my heart. And there was this female executive there that was just known for running part of the sales organization like a machine, and we all just worshiped her. I remember going to her office to see her dashboards, and she's of course soared throughout her career and now is one of the most important female VCs you can probably easily trace back and figure out who this is. But anyway, I would not have reached out to her on my own, even though we had a relationship and she's helped me along the way over the years, because I probably thought now that she's this VC partner, a really important VC, she's too busy for me, right? And she was like, hey, I really can't make this one. I'm off that day, but I'd love to come to future. You know, will you add me on the list? And also, how are you doing? And that simple thing where I would— that took me out of my comfort zone to reach out to her on it. It happened because Michael added her to the list and I agreed to it. And, you know, those are the conversations, but that's, it's, you know, that more personalized outreach. And I think taking that risk.

Being very careful how you use AI is very important. You wanna make it so that you're not pitchy or not taking something with AI and go, oh, I see that you worked at Oracle. You know, it might be someone that went to Oracle group and just had Oracle on their LinkedIn, but didn't work at Oracle. They just had it listed a certain way and it makes you look like you don't care. So, Keith, were you raising your hand?

Yeah, just because Lara name-checked me. Can you hear me okay?

Yeah, we can hear you.

That's good. Yeah, so just very briefly, I'm a GVP at Oracle. I run the CX Center of Excellence here, so I'm in the sales marketing service domain. I'm not a salesperson. I'm actually in kind of the development organization. And my sales kind of responsibilities around retention and upsell more than new business, which is obviously probably more important than anything else. The thing I want to say is the reason why I was interested in this call is I live in a bit of a fishbowl at Oracle. I speak to lots of customers all the time, but it's all about Oracle, large company AI rollout strategy. What I don't know is what the rest of the world is like. And the reason I say that is if you're a big vendor, I think Salesforce is the same, ServiceNow, everybody, you know, we are selling an AI strategy and it makes sense. It's good. We're being effective at it. There's a huge appetite, but it's all going enterprise-centric outwards. And what I'm interested in, you know, having made a few mistakes as well, which, you know, I can talk about You know, on a personal level, not on an Oracle level. I'm interested in that.

Oracle level.

Yeah, exactly. So, so I'm interested in other people's perspective rather than to get out of my own every day and see what other people are doing. Yeah, I'll kick this off. You know, mistake I think Oracle made, say, 3 years ago in my area is very early on when we paid AI apps. As a vendor to roll them out. I don't think they were that effective, but it was kind of like an early step. It was a good attempt to kind of get some interest levels on. There was a huge appetite, but especially in large companies, you have to have a very kind of integrated, organized, signed-off kind of big corporate strategy and so on, which I think we now have under what we call Fusion AI. Agent Studio. And, but that was a mistake early on, I think, didn't work very well, wasn't very functional. It was also too hardwired. And you think about what's happened in the last 18 months in particular, the whole industry has transformed itself, like the tooling and general availability is totally different. So from a large vendor point of view, what I'm trying to say is, Mistakes were made on early product rollout and adoption. A couple of mistakes later, I think there's a good machine. Now it's an execution challenge to roll out, and that's what I'm in the middle of. So happy to talk more about that with anybody.

What would you say your biggest revolution that you saw, like it could be a tactic or strategy or a piece of AI tool, not saying it has to be Oracle-based, but What's something that was taught to you, either it was a mistake or it was a success, that you can almost do a TEDx talk to us about?

Well, there's a lot of noise and very little signal in all of this, obviously. And I can self-criticize the Oracle position. We've got something like 1,000 agents that have been rolled out in the last year. Very, very few of them make sense, which sounds like a bad kind of admission here. But there are lots of automation agents, which I think are probably going to go nowhere. The ones that are going to make a difference are the cross-company ones. So anything to do with procurement, where a company is in with another company, and you can compress times and actually save cash money. Anything to do with things like, in my field, quoting, bidding, things like that. You bring money in faster if you bid more accurately sooner and bill sooner. So in this massive amount of noise about AI agents over a massive landscape, very quickly it's a hit business.

Yeah.

So that hit business for me is gonna cluster around the cross-company B2B kind of exchanges because that's where the cash money changes hands. Everything else is pushing money around an organization from budget to budget and doesn't count.

Well, sorry, I'm just—

it sounds to me like what you're saying with all the ones that aren't going anywhere, that companies are not starting from the standpoint of, you know, where do we want to be in 3 years? What is it going to take to get there?

And what do we need from systems and tools to help us get there?

It sounds like they're just throwing AI at stuff to see what sticks. Are they not being more strategic about it?

No. Well, I can't speak to everybody, obviously. The point I was trying to make is that when I said there's a hit business, lots and lots of applications, the agents is the way I think of them, something like generative AI for HR job reviews, for example.

Yeah.

Yeah.

That is a useful function. That's a little agent that we've got, for example. We use it all the time. The novelty value wears out after about 2 days.

Yeah.

Then everybody's using it just like LinkedIn email and so on. So the arms race suddenly becomes, it's in a different area. So a lot of these things, they're not gonna endure is what I'm saying. They're useful. They're internal productivity tools. But I think the real end goal on internal productivity is to get rid of the people doing the increasingly productive things. Where the long-term value lies is in the intercompany exchanges. So we do ERP, for example. In ERP, you're closing books, you're paying vendors, you're chasing receivables, and so on. The really valuable things are the intercompany experience points. Anything that's to do with internal automation is an arms race that's gonna quickly resolve in jobs being eliminated, is my view. That's my view. It's not Oracle's view.

You know, I definitely think for me as a sales guy or a guy that's doing a business, my own business for 5 years, the note-taker has been monumental to my approach in doing things. As far as recapping meetings, following up on next items, throwing that stuff into my HubSpot instance. So one of the things that, that I was horrible at is had 15— I mean, all these people had 15,000 notebooks with handwritten notes. And how do you even go through that stuff? And the note-taker part of AI and what it's doing and how it's turning that into automated tasks, uh, task automation on Next steps, help me write messages that I don't really never like doing, recapping the whole conversation I just did. That's one of the things that I thought was amazing for me on success.

Yeah, we got— yeah, I want to add to that an example of a company that does the random acts of AI and how we're trying to change, how we're working to change that. But I know I want to make sure, Keith, that we make sure you finish your thought and that we get to Diane.

Yeah, just, just one last thing on your point, Michael. You know, I think there's always a— the question is always, so what, right?

Yes.

When you've got 15,000, when you've got 15,000 notes in HubSpot and something like everybody else, what difference does that make? The point I'm trying to make is, you know, what are some of these killer applications that will endure? We don't know what they are yet. It's a bit of a hit business and you can't predict the hit business by definition. They're very likely to be in certain functional areas, and everything else is going to become part of the fabric. And it'd be interesting for a while, then the world will move on. Some things will endure about sales and buying in particular, making and bidding, proposing, prototyping, all that kind of stuff. That's really where the value is. So just my personal view.

Okay.

Sorry, Laura.

No, we love having you. Yeah, thank you. Diane.

Thanks. I— good to see everybody here. I sent you a note, Keith. I'm happy to talk to you. We see a lot of mid-market, so I can share with you some of what we see. I'm in the experience management space, so I work with a lot of organizations who are trying to helicopter up and take a look at everything they have going on. One of the things that we see all the time is that they're really forgetting about what you're truly after. It's typically, what are we trying to accomplish, and not, What is the customer trying to accomplish? What do our employees need to be able to do? And how can we take those things away from them and have them do things that are better for the organization? So I think we're treating AI as a thing we're going to go build when really it's an enabler to achieve those things that we need to go achieve. So I think about customer onboarding, right? It's a mess for every company. I can't tell you one company we've worked with where it hasn't been. How do you automate that? How do you make the contract process better? How do you get them the right content at the right time? Those are the things that are going to drive value.

What's a good customer onboarding solution?

Well, I mean, that depends. I'm not looking for a solution. The problems are there. We have to help organizations really figure out how to work that. If it's a contract that gets stuck in legal, if it's they don't understand who they need to contact, there's no handoff internally in the organization. A lot of times it's internal processes.

Nobody owns it.

So it depends on the organization, but helping that and saying, if we're able to get time to value by getting somebody onboarded quicker and they don't have the, you had me at, you didn't have me at hello experience.

Yeah.

Then they're probably going to stay longer. So we're focused more on how do we apply AI to those situations where we know it's going to provide value to the customer and in turn the brand. Or the employee and in turn the brand.

I was using this perspective.

We're missing a little bit about building apps and building AI when really we're just— we need to be leveraging it to achieve that value. That's my soapbox.

There's a digital twin thing called delfi.ai I started using. And I had my daughter start helping me, and she was asking me questions every 2 hours about what should I say here, or how should I answer this? And I just had a light bulb come like, why don't I have her talk to my digital twin at Delphi.ai and ask them, ask my digital twin questions for the onboarding for employee? So that was something I kind of stumbled on. I don't know if anybody else has done anything like that where your onboarding of employees becomes a very time-consuming OJT stuff. So anyways, Emily, how you doing? I saw you on the last call, but You, uh, you had your hand raised and then you disappeared. You must have had to leave.

Yeah, I had to jump early. Um, I just wanted to jump onto the conversation about the importance of onboarding clients correctly and using AI for that as well as—

Uh-oh, we lost her.

Having a backend that is basically automating, you know, this is who you call Emily, you're—

we're losing you when you're walking around, I think. Laura, do you want to fill in while we get her back?

Sure, Emily, jump in anytime. So, so I did want to go back to your point, Ted, about the random acts of AI. Because I've seen that and it's still happening. One, I'm still seeing— is that Emily?

Yeah, Emily.

Oh, yes.

You're walking around. We lost you 3 times.

So sorry. Okay, I, I'll try to say it here and then my— the— yeah, I'm actually in the office and the internet's wonky. But, um, just want to say about using— I'm now proposing using AI for our client onboarding because, you know, if the main client partner is on vacation for a week, there are important onboarding emails. It can be as simple as like, we're delighted to partner with you. Here's who you contact if an emergency. Here's what we do. That doesn't go out. You know, in addition to that, they need someplace where their— all of their information and conversations is being aggregated that they've had with your company. And when that's not done well, it's the difference between a relationship ending. I mean, those first 6 weeks are everything. And I understand the idea of like building yourself a digital twin, and that's a great start, but you, you have to realize you have to keep on updating that digital twin. It's not a build it and forget it.

Oh yeah.

But it's, it's a powerful tool, and I'd say for client retention and building that relationship, that's a great place to start.

Yeah, I would love— I, I've been using Claude Cowork for some of that stuff, but I would love, Emily, like if you, if you found a Really good way for client onboarding. I think people that sign contracts and then you wait a week to get say, "Hey, congrats on being a client." Blah blah blah. My whole thing is sense of urgency. If if I I gotta think about like if I just signed a contract for whatever it is, I want immediate attention. What what's your Razorfish has been something I've known about for 25 years. You want to give a little overview of what Razorfish is doing today? Just because. It's a pretty big name in the space. I would love to kind of hear.

Yeah.

Yeah, absolutely. So we do end-to-end marketing and we've just been around for 30 years last year. So really what we do is work with new technologies integrated into our client system, but it's always external marketing. So for example, we'll do end-to-end media, social brand reputation for like Samsung, who I'm sitting in their section now. So anything that's on digital and usually emerging tech.

And you're— are you still in Seattle that you guys are based in?

Uh, we, we have an office in Seattle, but we are across the US. I'm based in New York.

And what do you— what, what have you found on the onboarding side that is— whether it's a really cool topic that you've integrated or a really cool platform that has helped you with the onboarding for the client?

Yeah, it's not going to be one platform. It's not going to be optimizing Claude, it's gonna be a bot, a destination they can go to. They have to be able to log into something. They can see everything aggregated. It has to be a cadence of emails that go out. And on the backend, do you see that those emails were opened and received? A lot of times we'll put in, hey, and to welcome you aboard, if you'd like to fill this out with your address, we'll send you, you know, a welcome client starter kit. That way, you know, we don't retain their address, but, you know, that way we know they've been through it, they've read it, they have something. But it's so important to give that experience. But it's a series of tools. It's setting up an automated system that's smart and interconnected more than just one tool.

It's probably hitting the client with certain questions, but also reminding the internal client team, do A, B, and C, otherwise it's not going to go well, right?

Exactly. Do A, B, and C. In fact, it's almost like taking off A, B, and C from the client partner's plate. It's like we're automating A, B, and C. You know, now the stakes are you just have to, you know, make sure you get the answers back from A, B, and C in a timely manner. You're CC'd on everything. So I think when we first started doing this, the idea was, oh, I don't want— you know, I know my client, I don't want it taken out of my hands. But this is just a tool to make sure they have the most updated information. It's really almost like a comforting way to onboard someone to a company, and it continues for about 6 weeks. But that was in response to directly not having a good onboarding experience.

Awesome. Well, thanks for— nice to meet you. I've been dying to talk to you. So thanks for joining.

It's not fully rolled out. We've rolled it out to some clients, but we're looking to roll it out fully in 2027. Just so I don't want everyone to think we're that, you know, That's slick.

That's slick. Okay, Sean.

Yeah, this topic, and Emily being at Razorfish, I used to run film sets for old Razorfish campaigns for their clients back in a previous life. Onboarding is such a great topic when it comes to this AI thing. I tend to focus more on the human side of it though, and I'm wondering, and Emily, you might be able to speak to this, There's a ton of studies and research out there about things like trust and what it takes to forge connection, and that AI really misses the mark in terms of forging actual connections. So the case, Emily, that you just brought up sounds like, man, to have all those resources at my fingertips and just know that I've got some of those basics, that seems to be really Valuable. But I'm wondering if anybody's having experiences about where they thought they were making gains and they did it at the cost of human connection and where that— if they've found any— here's where it's okay, here's where it actually ends up becoming a challenge or even worse, a deficit.

Sean, I'll weigh back in here. That's exactly the whole point I was trying to make. Onboarding was just an example. If you don't understand where and how your customer wants that onboarding experience to be, they might want it to be all automated and just be informed. But you, you might lose some ways that you are building that relationship and making the transition from typically sales teams to whoever's gonna take it on.

Right.

The whole point is we need to think about the experience we're creating and what value it is, and then we enable it with AI. Because I think putting a solution in place, that's what we're seeing being the problem. We'll just go AI it like we did digital and we'll just put AI against it. It'll be fine.

I have— Some study and I'm gonna butcher this, but it was something like they tried to do therapy with people through a few different means. There was person to person, online texting, but it was a real person and AI. And surprisingly, there were somewhat decent results if people actually knew that somebody was texting. But once they knew it was AI, a lot of the bioindicators for trust, well-being, connection just went off a cliff. And that's one of those things when it comes to, you know, I think on the organizational side, we deal with the fact that a lot of times the company gets their insights at the exit interview and not enough care is being put into the actual employee experience and robust onboarding. So this is where I know I have like Yeah, where's the line between doing some really practical things and where you might be shooting yourself in the foot?

If you design for trust, I think that's an important part.

Lead with that.

If anybody's interested in that, I've got some stuff that I think we came up the other day was everybody loves, but nobody wanted to buy.

But yeah.

Matthew.

Hey, Michael. Yeah, no, I, on the issue of trust, one of the things that we found, and by the way, I work with a startup called Personize and we're building Trying to build that trust layer. What we found in our research over the last year and a half that we've been building this over the last 5 years is that AI agents that don't have a shared memory or don't have a continuous memory is what breaks this. So I'm sure we've all been on our, you know, sessions with Claude or ChatGPT, and it forgets what's in the context or outside the context window from the day prior or even the hour prior. just had this happen earlier this morning. So one of the things that we're building is, is a, is a shared memory, a governed memory that basically treats the AI agents as if they're employees and assumes that you're not going to follow the rules all the time. So we're going to make you follow the rules by enforcing governance. And we're going to share all the memory that's resident in the enterprise. So think of a large enterprise with, you know, tens of billions of data points, whether it's customer records or phone calls or transcriptions, what have you, uh, make that available to every agent in, in a system where any agent can pull up that, that memory, that recall, such that you're not having to retrain those agents every single time. And you don't have those situations, Sean, as you were just mentioning, of, um, as soon as you kind of detect or smell the AI, your, your trust layer level goes down pretty significantly. So one of the things that we're solving for is, is, is that memory.

You need to Let people know this is an AI chatbot or AI response, then you won't do that. But if you try to pretend like it's a human and you get caught, it makes you look like somebody you can't trust, the company and yourself.

Yeah, yeah. One of the practical applications is personalization. So we have some customers working with us to deliver very, very personalized experiences. Think, you know, emails and landing pages that are personalized for the for the target contact that are highly personalized because we have all that context. We have all that memory on the individual contacts themselves, which is, again, raises that level of trust. Conversions are better. So if you're thinking go-to-market, that's a much better way to achieve performance than trying to force-fit an AI bot to do something that it's just not structured to do from an infrastructure standpoint.

Laura?

I was— yes, I was just on a call with a roundtable actually on this topic with McKinsey. And it was all about how you create psychological safety for your for your team members as you bring in AI. And such an important part of it is having the team feel like they're a part of the journey. And this brings it back to the point Ted made earlier that I wanted to say that I still see companies doing random acts of AI. So one company, a $3 billion tech company I'm working with, they've got an AI leader who sits in tech who has a use case application. If you want to have— bring up, you know, if you want to use Claude or ChatGPT Enterprise, submit a use case and it'll say, you know, does it help with revenue? Does it help, you know, with internal efficiency? Things like that. And then suddenly, you know, if the use case is approved, suddenly it's rolled out to this department, but it's not part of a bigger strategy. It's not, you know, you're not bringing your team along when you do that. And what we're doing is going back, like, that's fine, we'll let the, you know, we'll continue to— let people request their use cases. And at the same time, we're going back to put together a strategy that, you know, the teams have a part in developing. And whatever, you know, there are lots of ways to get at your AI strategy, but it's really thinking about your moat, where you are today, what it's going to be in the future. And I think a lot of companies, like I said, they default to this idea of either the random acts of AI— I heard some of that earlier in a couple of examples you all gave— Or it's just, you know, it's just kind of loose and uncontrolled rather than giving people that structure. And some of that structure is what people need. They need to feel that they're brought along on the journey.

All right. Let's go to Pete Matthews.

Pete, you there?

Let's go down. Jane Sorsen Hirthel, is that it?

Hirthel, yes. Hi, how are you?

How you doing?

Listening. I'm fine, thank you very much. Um, I love the dialogue here. It's interesting. I, I have a number of early-stage clients that are all struggling with the noise and how to obtain leads, and it's been fascinating. I've reached out to some of my former colleagues that are CROs and leading different sales organizations to kind of see what's been going on, because I don't know about you all, but I feel like the last 6 months has been flipping everything on its side about what worked before to kind of navigate these leads generation in this complex B2B environment. So listening earlier about what someone said about memory and kind of making sure that You know, these agents are smart and have context and can be consistent, I think is important, especially when you look at the lead generation process. And so I'm curious to hear about what other people are doing around in that area.

Well, that's kind of my realm, so I'll kind of chime in about a lot of other people, but on the lead gen side is, is creating value and giving before you're asking. And like Laura and I, it's like, you know, we have our own business, probably. I think you do too, it looks like. Is don't pitch slap, don't say let's grab a virtual cup of coffee. The whole idea is like, hey, we're doing around like this roundtable. We would never get to meet you if I didn't— we didn't offer you. You probably came from Laura or me or someone else. And the whole idea is to get the engagement, build a relationship. What I call dating is business dating. And In this world, right? So you gotta get to know somebody before you sit there and throw up everything you do for them. So by doing things like podcasts or roundtables, or hey, you're going to the conference and inbound for HubSpot in June—that's just asking them a question and having a normal conversation. You would, but everybody's so hyper about here's what I do, here's how I help, here's what I sell, and that no one wants to be sold to. So you really need to sell the people. Well, if you're gonna understand their disc profile, understand how they buy, understand what they do, and don't hurry up the whole the whole approach because if you look at doctors and lawyers, they'll ask you a bunch of qualifying questions to understand at least the good ones how they can help you. I think we as business people forget that or we want to do everything ourselves. Like I I try to help people like well doing this. I'm doing it. I'm like, what's your business? Because if you're doing lead generation, top of funnel, roundtables and masterminds and podcasts, then you're not focusing on what you do. So does that help?

Yeah, no, for sure. Yeah. And the value. And I think the value that you provide and making sure that you can really provide a service that's of value that the customer really feels like they can get something from. Right. And so I think finding that match is critical. And being able to really service them, right? Do something good for them.

Yeah. Find a repeatable and scalable approach too. I mean, I do that as a repeatable and scalable approach. It's like, I don't want to have 5 clients. I want to have 20 clients that pay me $5,000 to $10,000. So if you don't have repeatable and scalable things you could do behind the scenes, then you're going to basically sell your time as a consultant. And that's great, but then you're at a limit and that's so that's okay too. But make sure then if you have a— if you're on the limit, maybe there's other partners that you could farm that out to that could be behind the scenes or sister company is my opinion. I don't know if we have other consultants on here that can definitely give their opinions too. And you're welcome to reach out to any of these folks.

I want to comment on this too because Jane, it's great to see you too. We have worked on this so much in terms of I don't know, consultants, but also like what I've purchased throughout my career. I've managed and spent big budgets. And so often it was not just the technology side, but when you're paying a consultant, it would be, here's the retainer and it's going to cost this much for 3 months or 6 months. And you're signing up for something where you're trying to— in the past, it was you're planning for things to move and happen, but it was still more of a retainer model. And today, Like, I sell outcomes to people. I don't sell retainers to people. And if someone I worked with tried to sign up for a retainer, I don't think that I would do it because it'd be a disservice to them. So I think the world has shifted so quickly in that way, and it's pure goodness for all of us.

Well, I totally agree, Laura.

I mean, I think, first of all, it's great to see you. I know you and I have worked together in the past, so thank you for the invite. I really appreciate it. My business as well too is outcome-only based. I only align on the upside. I do go through a process fairly regimented and then actually feed that into AI. So it is structured and it does have memory. So there's some consistency with that. And some of the clients, my clients that are leveraging it have found value just because it does have the consistency and the team can have a shared memory of what's gone on and what's transpired with the particular account that they interact with. So it really truly acts as kind of like the brains of their go-to-market process. And it's codified, so it creates alignment consistently over time, and then also, you know, throughout their team. So it's kind of an interesting way to use AI and combine it with some of the go-to-market bespoke knowledge that maybe each company has.

I've seen someone I haven't met yet, Natalia. Or is that how I pronounce it?

Yes, indeed. You got it right. And no one does. Thank you. It's Natalia. Nice to meet you guys.

Nice to meet you. What brought you to the roundtable today? What's a tip, tactic, or strategy that you loved or that just completely failed and you want to warn us?

Yeah, I mean, I think someone said it earlier in the conversation about getting the team rallied around it versus this random acts of AI. The challenge I'm facing today and why this was an interesting topic. I've joined mostly full-time with a new startup, very basic concept, selling coffee out of a barista-quality kiosk. But we're rebuilding a business, a whole infrastructure, and the team's not necessarily on board. I'm sort of the only one, like, kind of— and I shouldn't say only, but like kind of kicking and screaming, dragging the organization into it. For example, even You know, CRMs, things like that. We, we've got to organize very quickly. And part of that is the, the trust and reluctance. I was the same way, very slowly dipping my toe in the water. Just started using Claude Code. Didn't think that it was, you know, for me. I'm blown away.

Yeah. Awesome.

Yeah. How much you can get done. I am trying to, you know, soak up, eat up as much information, understanding, and learning courses, cohorts, the, the whole nine yards to figure it out because it, it is scary. We, there, I've had some things go not, not well.

Mm-hmm.

And I also came from highly regulated industries in the financial sector, like, you know, Laura's experience. And so, yeah, there, it's, it's, it's, it's just a, it's a lot to sort of organize and rally around. That's, That's the simplest way to put it, my experience. Some very pleasant surprises, but also some really, you know, terrifying moments.

One of the lines I—

oh, Michael, just let me— I'll throw it in. One of the lines I use most often, I love Claude Code too. I'm a Claude ambassador, like I'm all in on it. And at the same time, I often tell people just because you can doesn't mean you should. Yeah. If there are any startup CMOs on the call, right, the number of CMO friends I have who've said, I can't make dinner next week after all, or tonight, because my CEO redid our website over the weekend and now everything's broken, right? So there's so much that we can do, but I guess that I keep coming back to the idea that we need to be, to make up a word, we need to be planful in what we're doing and not just do it because we can.

Yeah, you nailed it, Laurel. Thank you.

Um, let's see who— oh, Pete, when I was— are you back? Oh, is he frozen? Pete, you there? I don't think he could hear us. How about Jerry?

Thanks, Michael. Great conversation and great context from everyone. Um, I think that the The only addition I would add to this, just in listening to a lot of the commentary, is 3 things. The first of which is start with AI is not a tool, it's an intelligence layer. Okay? Now, when you apply a, a tool that links to AI or utilizes AI, that's great. Recognize it as an intelligence layer. So if you, you're not feeding it new information, it only gives you the last information.

Mm-hmm.

It also needs to be trained.

And what I mean by that in listening to this conversation is trained is, and this is one of the things that I've run into on the sales side of things is I've often found all of the platforms will lend to business solutions and not to human solutions. That doesn't mean you can't train this intelligence layer to look for and feel more human emotional components to things. And it takes training because you can't derive that from just text, right? It's, it's difficult to do that. So you have to give it context to the text in order to train it. But I have found over time it gets better and better at that. So when we talk about, I think Sean, you were talking about personalization or someone was talking about Matthew, you might have been talking about personalization and getting more personalized in communications. That's one aspect of it. But if you're also adding the human context and that human operations layer on top of the actual transcript, you can start to train it to understand what those person's needs, interests, likes are, how they like to be talked to, what they like to talk about. So that's the second component of it. And the third is that these are all systems. So utilizing these in a systematic way and building systems that are sustainable. And Mike, you used the term And it's only the second time I've heard you say it, which is great, is repeatable systems. And what repeatable means is that you can do it over and over again, but doing the same thing that doesn't work over and over again is also wrong. So using the intelligence layer to make sure it's getting better and better and better. Jane, you were talking about this process that you have. You know, my question to you would be is, do you have your AI evaluating the performance of that? And any enhancements or tweaks to that in a real-time basis, because that's the intelligence layer really being optimized. So those are the 3 things that I would add to the conversation from what I've heard. Just— I came on 15 minutes late, I apologize. But those are the 3 things I would add that I've experienced and continue to experience, and ways to utilize this new technology in a unique way.

Um, Joe, I, I haven't heard like what you do and what's something that you could, you could spread some, uh, sunlight on for us.

Everyone, uh, so, uh, happy to be here, listen to you guys. This is my second time, uh, uh, second call.

Can you turn the mic, your mic up on your Zoom there a little?

Sure, sure, one second. Um, uh, can you guys You there? I'm here. I think it— I have a problem with the mic, maybe. So you guys can hear me or no?

Yeah, we can hear you. It's just low, but go ahead.

Okay, I'm gonna raise up the volume as high as I can.

Let's see.

Yeah, thanks for having me. Actually, this is a new microphone, so thanks for having me on the call. Amazing discussion. My Uh, focus. I'm, I'm a startup, uh, CRO, uh, CEO, founder. Um, we had a couple of exits in the past. I focus actually on helping, uh, startups, uh, similar to what I did in the past, uh, get through the, uh, go-to-market barriers. And now with AI, this is the, the very interesting conversation here, um, is, is what, what, what you can do more with less. Basically, that's, that's kind of the idea. And the biggest thing I always face with a lot of the startups that I work with is just because they have a friend that has a startup that does something in some way works really well for them, we want to copy what they're doing to make things work for us. And I always tell them it's not always true that that's gonna happen. You will have some unique workflows that work for you really well and ones that are really bad. That didn't work. So ideally, what works for you, even if it's on closing one sale or getting one lead in the system, and let's see how we can get this automated. Let's see if we can deploy AI. And the problem is, you know, most of my work has been B2B. I haven't done a lot of B2C. So B2B, you know, as you guys know, there's product-led growth and there is, you know, tops-down kind of marketing. And I tell them, look, Some things work for technical audience and some do not. And so you gotta find like the balance between quantity and quality with AI. I know with AI you can do a lot more. You can have one go-to-market engineer probably do the work of 6 SDRs potentially, but then that's pumping thousands of messages. Are these gonna all work really? I mean, and Michael, to your point earlier, it's good to let people know that this is actually an AI-generated message. It's fine to let people know that, but then If it's really super personalized to them and, you know, talks about their background, what they did before, etc., I like those messages. I know they are generated by AI, but, and sometimes I read them and there are ones that are really, you know, sorry, crappy messages that come in. I just delete. And so, and that's what I just advise people that I work with is like, you know, focus on what works really well for you and let's figure out how to automate that and how to build it. And now, of course, with Claude Code and others, even if there's no such tool, you can basically white code a tool that works to your, you know, kind of— so that's what I do.

Yeah, I actually took Claude and said, look at all my Fireflies notes, my email inbox, my HubSpot, and any Google Drive SOWs. Where am I? Where have I left something hanging that should be on my top 200 list and put it as a task in HubSpot. There's tons of ways to kind of use— you know, you gotta know how to talk to your cloud or to your AI, and then you can get what you want. But make sure you just make it so simple that a 2-year-old can understand it, because then they'll understand most of the time what you want. But if you, if you make it too generic, you're kind of sometimes rolling the dice. Um, Keith, uh, Keith, Keith, and then go Matthew. Go ahead. Go Keith.

It's just, I mean, this might reveal my lack of knowledge as well about Claude and so on because I've been a Codex user. So, but when you do all that aggregation, what happens to your data? What's the leakage? Where does it go?

I'm going to have someone that I can give you a little bit of background, but I'm not an engineer or I don't want to spread knowledge I don't have. Anyone want to answer that? Emily, you look like you're shaking your head yes.

It— I mean, it really depends. If you're using AI like ChatGPT for free, then that is all going to ChatGPT and, you know, for better targeting you and things like that. If you're using an enterprise one where your company owns it and, you know, you have a login, then that's kind of firewalled off just for your company. But anything that you're using for free and sometimes things that you have just a, you know, very inexpensive membership to, you know, that what the information that you're putting in there is actually fed into, you know, the collective of the intelligence. A great way to start is literally to ask the AI, what happens to my data when I put it in here? I mean, yeah.

I mean, just because—

It's most commonly gone. Yeah, not gone, but I mean, it's take— it's used by the bigger forces.

Yeah. And I do differentiate between them because I've got my kind of work account as well, which is locked down endlessly. But on the, you know, it's amazing how much information leaks out. Everybody, everybody who's sharing contact detail, customer process, workflow, anything, you know, most of that in practice, like the contractor market, is ending up in a learning engine for somebody else to steal your lunch at some point.

And, you know, if I can add, most tools actually should allow you to delete the data or dispose of the data once the work is done. What the risk with that is, you get a reset, everything gets reset.

And so, you know, it's not really doing that. So it's still going to be somewhere in there.

It is. But, you know, it's the idea about privacy because I've dealt with privacy. I come from deep martech and adtech. background with privacy, at least in the US. I mean, let's be clear, in the US, privacy laws prohibit companies from, you know, they have to anonymize the data. But at least to your, you know, to your point earlier, if you use an enterprise tool, then it uses your own data, then there is a contract and there is protection that you use. When it's free, when it's open, then yeah, you're kind of, it's a— It's a wild, wild, wild west there.

I can add that because when we, when I built our product, I made a choice to have our AI agent be independent across different platforms because I didn't want to be beholden to one. So I can actually point the agent to Google Gemini or Mistral if I wanted, or Anthropic. It runs and I had to design it in a way, but also make sure that my client's information and mine was private.

'Cause of the IP.

So checking the rules, and my agent actually not only checks to see if each of the agents that I can deploy it on are alive, every so often it sends a canary out, but it also will check the privacy rules 'cause those change over time. And to Emily's point, right? I mean, if you have a paid account, an enterprise account, that's supposedly safe, but there's always that risk. You know, there's always that risk.

Here's, here's a question that I'll throw, and this is more of an ethereal question though. As you think about AI, as you think about the aggregation of information in this data, how many unique propositions are there going to be in the world versus what there are today in the future? And my guess is, is that AI is going to outpace that IP and unique and ownable. Now, would I tell Coca-Cola to put their secret recipe out on this? No. But a lot, I'd say 70% of businesses, is not unique and ownable. And truthfully, that's where the, I think the efficiencies and the synergies that are going to drive the operational efficiencies that are going to derive from that 70— 50 to 70%. I think that's where, you know, yes, there is a concern about safety, but I think it's, it's, it's a fool's errand to think that you have to protect everything you're doing because it's so unique in tomorrow's world.

I just wanted to thank everybody for coming out here. Sorry we have to cut it a couple minutes short, but it's 3 minutes before the hour and I gotta again, another meeting. But I want to thank Laura for doing this roundtable with me. If you guys are interested in co-producing other events using everybody's LinkedIn and connections and doing this, you know, blending everybody's connections, putting your arm around your friend or your soon-to-be friend is a great way to kind of get business and also share collective thoughts. So, um, feel free to reach out to me if you need help. I need to go to market strategy. Feel free to talk to Laura about her endeavors on her new agency. It's really interesting what she's doing in AI. And, uh, would love to, uh, keep in touch. God bless. Thank you, everybody.

Thanks, everyone.