Signaling Trust to AI Agents, with Max George, Advisor to Brands on AI Shopping and Agentic Commerce

Transcript

Our transcripts are generated by AI. Please excuse any typos and if you have any specific questions please email info@digitalshelfinstitute.org.

Lauren Livak Gilbert (00:00):

Welcome to Unpacking the Digital Shelf, where industry leaders share insights, strategies, and stories to help brands win in the ever-changing world of commerce.

 

Peter Crosby (00:22):

Hey everyone, Peter Crosby here from the Digital Shelf Institute. As Agentic Commerce continues to rapidly evolve, one thing is completely clear. Gaining trust from AI agents is a critical component for securing the Agentic recommendation across your product portfolio. And as personal agents like Muse and ChatGPT Dots ask for the keys to act on behalf of the shopper, that need for trust, both machine to machine and machine to human, will only increase. Joining us to detail how brands can build this vital trust is Max George, an advisor to brands on AI shopping and agentic commerce who previously served as Google's global product lead overseeing agentic commerce. She shares actionable strategies and tactics for leveraging digital signals so AI agents reliably identify and recommend your product to shoppers. Max, welcome to the podcast. We are so looking forward to chatting with you. Thank you so much for coming on.

 

Max George (01:22):

Awesome. Thank you so much, Peter, for having me. Excited to be here today.

 

Peter Crosby (01:24):

Well, you have been right in the midst of it when it comes to agentic commerce, having previously worked on the agentic commerce product portfolio at Google, and now you're directly advising brands. So you really know firsthand on both sides, retailer and brand side, about what's happening right now to drive this new era forward. So based on that, tell us how do you define agentic commerce and where do you think we are today? Where are we headed?

 

Max George (01:53):

Great place to start. And also just wanted to say I've been following the podcast for a while, so I'm really excited to be here today.

 

Peter Crosby (01:57):

Oh my gosh, thank you.

 

Max George (01:59):

I know there are a lot of definitions floating around for agentic commerce, but I really view Agentic as experiences where an AI agent takes action on behalf of a user. So the classic example is of course Agentic Checkout where an agent completes a transaction on a user's behalf. So they handle filling in their credit card information, their delivery address, et cetera. But there are also many instances before and after checkout where an agent can act. So that can be hunting for deals, replenishing an item that you use frequently, creating a basket of goods to meet a set budget that the user inputs, or even starting a return. We're still in the very, very early innings of Agentic commerce. So most of what you're seeing in the market today are these conversational assistance experiences where AI help shoppers research products, but they don't yet autonomously take that action.

 

(02:49):

So for example, that's where you see a lot of experience in ChatGPT today or retailer experiences like Ask Target for example. And these are really laying the foundation for Agentic commerce on these different platforms, but they're not quite Agentic yet. And then you're starting to see some big players testing Agentic features. So for example, Google's new Universal Cart with Agentic Checkout or Alexa for Shopping's price alerts and Buy For Me. But I expect that we're going to see Agentic capabilities really accelerate across the platforms in the coming months here, Peter, as a reaction to the arrival of more of these personal agents like Meta's Muse, like Instinct, which are bringing Agentic experiences to users at a greater scale and making it really accessible for users. What we've seen so far is Agentic is a very reactive space because all the players are, they're really competing to become that user's agent of choice.

 

(03:37):

And so advancements with one platform tend to spur action across the ecosystem.

 

Lauren Livak Gilbert (03:42):

And when you think about content for Agentic commerce, or really mostly for Agentic Discovery right now, you hear a lot of people talking about machine readability and making sure that your content is optimized. And one of the things I loved about our prep call is you were talking about the balance of machine readability, but also prompt relevance and how those two things interconnect together. So talk a little bit about that and how our listeners, our brands should be thinking about it.

 

Max George (04:14):

Yeah, that's a great question, Lauren. And honestly, it's something I don't think brands are spending enough time thinking about. So obviously machine readability is very important. We all know this. You need to make sure that your product information is in a format that AI can parse and it can understand, otherwise you won't be visible to them. But being understood alone, it just isn't enough. What I've seen is that in order to be selected, you have to be relevant to that user's prompt. So AI is only driving users' expectations up. More and more they're asking highly specific questions of these AI assistants. And with query fan out, AI can run multiple searches to find a product that fits exactly what the user's asking for. In order to be selected by AI and presented to the user, brands need to A, make the context and depth of information that users are seeking accessible to AI, and B, speak the language of the shopper.

 

(05:06):

So for example, if you are a hair care brand and your shopper is asking for products to prevent breakage and your product content never mentions breakage, it only talks about the reverse strengthening it. Your competitor who frames their product's benefits in the language of the shopper might be more likely to be chosen. That's why I always tell brands they need to include prompt research in their GEO strategy right alongside readability and prompt research in this updating product content. Tha needs to be something that they do regularly because as users continue to learn the power of AI, their queries continue to change.

 

Lauren Livak Gilbert (05:37):

Two questions to that, Max. So the first one is for the audience who might not be familiar with a fan out query, can you just talk a little bit about that? Because I think it's important to understand that so that brands can understand how these LLMs reason and compute. And then just to double click on that, you talked about the timing of content updates and maybe helpful to say what is the best practice for that? So two-pronged question.

 

Max George (06:05):

Yeah. Great question. So query fan out is this process in which it's an AI search technique where basically takes a single user prompt, breaks it into different parts like sub-queries, and then runs multiple searches on all those different queries. So it's what makes AI so powerful because whereas I as a user, I can only go in and ask one single question. AI can take my question and it can ask multiple questions off of that to gather more information and bring that back. So that's what query fan out is and that's why you have to make sure that you've got the breadth of information that AI might look for when it's running multiple queries on behalf of a user. And then your second question was, oh yes, the timing for updating that product content. I think that's a great question, Lauren. I've gotten that a lot.

 

(06:53):

So honestly, I tell brands it's different for every single vertical, every kind of product category because it depends on how your user searches are changing. So if you are in a very seasonal product category and so what your users are asking for in the spring is different from what your users, your shoppers is different from what they're asking for in the fall, then you need to make sure that you're updating your product content between those two different periods to be in line with the language that users are going to be using to request your products. So it really depends on how often your users are changing those queries. What I recommend doing in order to find out what kind of cadence you should be updating at is pay attention to what your users are searching. Do some prompt research, some prompt intelligence and track when there's been a meaningful difference in how they're querying for your products and then update your product content then to meet it.

 

(07:48):

And after doing this for a while, you get a history of doing this, you'll have an understanding of how frequently you need to do it. But really it's less about saying update it once a month, for example, and more about update it when it makes sense for your user. But my guess is going to be that's more than twice a year, which is what I've seen a lot of brands have done so far.

 

Peter Crosby (08:06):

And probably, and tell me if this is not true, probably across a wider breadth of your catalog than you're sort of accustomed paying attention to just because the opportunities, as you said, are coming from, I don't know, I think about it as more and more niches of the use cases of your product line depending upon the consumer's needs. And are you finding that they need to pay attention to more of their product catalog in addition to just their top 20% or something?

 

Max George (08:39):

Yes, absolutely. Because that's the exciting part for users, but the challenge for brands when it comes to AI shopping is that AI has the ability to do a lot more research than a user typically would. And so they're able to find more of those products that perhaps user might not have found on their own. And so you want to make sure that you are, any product that's in a category that users are searching for, you want to make sure that you have all your product content updated and relevant to what users care about at the time. I'm not sure if that answered your question, Peter.

 

Peter Crosby (09:14):

No, that totally did. And it made me just wonder, and I know always the answer is it depends, but when you think about your work with the brands that you're advising, what are their mindsets right now almost as human beings and leaders of this in terms of is it interest? Is it panic? Is it I really don't want to do this or I don't think this is all that important, but my boss told me. I don't know. I just love your sense of where people are at and beginning to form their strategies to this.

 

Max George (09:51):

Yeah. I would say brands fall into one of two categories with how they approach it, and I'll come back to that in a second. But in general, I think everyone understands that this is happening. Everyone understands that this is important. Folks are seeing the dips in traffic to their website. They're seeing the dips in traffic from some historically really strong channels, and they're able to see that, okay, that traffic, it's probably moving to AI search. And also AI search, AI shopping, what's so exciting about it again from the user perspective is that a lot of it is intuitive. These tools are designed to work with us the way that we naturally ask questions. Humans are naturally curious and these tools are able to give us more and more information. So you're seeing strong user adoption for a lot of AI assistance. So I think if you'd asked me 10 months ago versus now, I think brands for the most part understand that this is happening.

 

(10:43):

When it comes to fear versus excitement, I think there's obviously some concern because this is new, it's novel, and it has the potential to have a really big impact on the digital ecosystem. So I think everyone's a little nervous about what might come next, but also obviously change brings opportunity. But I'd say in general, I'm seeing brands fall into one or two categories. They're either they want to be first. They want to immediately adopt all these solutions. They want to adopt these different technologies, try these different protocols and really get out ahead of this. Or I'd say see a lot of brands are falling into that fast follower category where they're like, okay, we don't know what's happening. We want to be there, but we want to wait until we see the first wave of brands invest and figure out this space. Then we want to be a fast follower once the playbook is written.

 

(11:33):

And each strategy obviously has its pros and cons, but the one thing that I will say to brands is I think we're going to see the continued rollout of AI shopping, AI search, agenta commerce accelerate more than any technology that we've seen in the past because it's so intuitive to users and also because it's so competitive for the platforms and the players, whether that's the retailers, the horizontal agents, the personal agents, everyone wants to end up being that agent of choice for the user. I personally don't predict that, I know there are different perspectives out there. I personally don't predict that users are going to have five different agents running for them. I think they're going to gravitate to just a couple. And so it's very competitive for the different players in that ecosystem and they're really pushing these experiences as quickly as possible to end up being the one of choice and not getting left behind.

 

(12:24):

So all that to say, I think the learning period for brands will be shorter than perhaps we've seen with other technologies.

 

Peter Crosby (12:29):

And do you think about it like it was as SEO was developing, the first adopters really saw a lot of people had to pay later through a lot of ads to gain their place rather than be that first adopter that kind of got in early. Is there a similarity here do you think with agentech commerce?

 

Max George (12:56):

There's a similarity and there's also a new aspect to it. So I'll say there's a similarity because again, these are very new experiences. All the players, again, the retailers, the horizontal agents, et cetera, all the players are testing new experiences. And so a lot of these experiences aren't yet monetized, but they will be eventually. They will

 

Peter Crosby (13:15):

Be.

 

Max George (13:16):

We can all expect that they'll be monetized. These are companies that have got to make money, but they learn first with these sort of free experiences and then they monetize them later on. And so brands have the opportunity to start to build their playbook now or they'll build their playbook later, but they may have to pay more money then because experiences might be monetized by that time. But then the second thing that I'll say as well is that the other advantage of being more of an early mover at this time is data. These experiences run on AI shopping experiences run massive amounts of data. The more that you can understand about your consumer and how they're shopping, the better you can tailor your strategy. And so if you are getting ahead of the curve and you're starting to learn early, you'll have more of those learnings, you'll have better data about how your shopper leverage these tools than if you were to do this later on.

 

(14:11):

And again, the data is really a differentiator for AI shopping.

 

Peter Crosby (14:17):

Well, and part of that data is what other people are saying about your product and that AI loves to go validate what their initial search is telling them. And that's often from third parties that you don't really control, but the team that usually at brands, and I'd love your thoughts on this, it's PR and corp comms, folks that our e-commerce teams may have known where they sit, but may not exactly know how they spend their day. And how are you seeing that, I would imagine, necessary collaboration start to evolve to make sure that the whole universe of perspective on the product that you're selling is being managed and monitored?

 

Max George (15:05):

Yes, yes. So I mean, I've seen a few brands do this. I think more brands need to do this, really bring in all those cross-functional teams. Your digital team or e-commerce team has to be talking to your comms team because how you're represented across the internet really impacts how you show up. Across the internet, across the digital ecosystem really impacts how you show up in these experiences. And mapping your digital footprint is especially important for these enterprise legacy brands that have a lot of content about them out there. Before answering that though, I want to note why this is so important. It touches on what you mentioned a moment ago, Peter, validation, but what I say is trust, right? Trust is repeatedly cited as a consumer's number one hesitation with adopting AI agents and the platforms that we use or trust will become that user's agent of choice.

 

(15:58):

And so platforms have a really high bar for ensuring the information that they provide to users is accurate. And to do this, they do a lot of research on products like that query fan app that I talked about previously. They're looking at multiple sources across the internet, so brands need to get their arms around their digital presence. I tell all the brands I work with to do three things. One, understand how your products show up across the digital ecosystem. So what are the sources that are talking about your products, whether they're your own sources like your website, like your product feeds, but of course those non-owned sources, how are they talking about your product? What's the specific language that they're using? So not just sentiment, but also the language that they're using. Is that consistent with how you talk about your products? Is that consistent with how you want your products to be talked about?

 

(16:44):

Understand how your product category shows up across the digital ecosystem to AI so that when someone goes out there and asks an AI assistant, what's the best pair of running shoes for a 34-year-old woman with fallen arches training on gravel roads? Not only what sources does AI consult, but what information is it pulling from those sources? And then identify the gaps between how your products are represented in this digital ecosystem and what AI is looking for, and then work to fill those gaps. The digital ecosystem is of course constantly changing, so this needs to be an ongoing exercise just like updating your product data. It can't be a one-off, whether it's a massive, massive spreadsheet or a software tool that's scraping the internet for you, brands should really track the delta between how their products are represented online in aggregate and how they want those products portrayed.

 

(17:37):

And with limited resources, I know that's constantly a challenge with commerce. They need to pay the most attention to the sources that signal trustworthiness to AI. And that's going to vary by product category, of course, and by platform, but third party experts and real user reviews are a good place to start. The more authoritative, the more weight that it can carry for an AI platform.

 

Lauren Livak Gilbert (17:58):

And speaking of figuring out where the impact is, I think a big piece of that is measuring what's happening and how it's happening. And that's a very big question for brands, how you actually measure the success of the agentic shelf, of agentic commerce. And it's a space that's currently evolving and we don't have a ton of straight answers necessarily. So what's your recommendation for measuring this space or how brands should start to think about it? Because it's not as cut and dry as say digital shelf content that we've measured previously.

 

Max George (18:35):

Yes. Right now, I'd say it's more about building the muscle of measurement than anything else, Lauren. There's actually a great article out there on Forbes. It's by publicist Jason Goldberg, so I recommend that everyone go check that out. I love sharing that article with folks. But the reason that I say it's about building the muscle and not about the actual numbers themselves is because these experiences are very new. So they haven't quite found product market fit. Traffic is growing, but it's still low compared to established product features. So features are changing across platforms. And as these experiences change and the composition of the users change from your early adopters to more mass users, the numbers that you're measuring, they're going to change as well. So that said, I recommend that all brands, I'm sure they're probably starting to do now, is pay attention to the shifts in traffic that you're getting from channels like direct site visits or organic search to get a sense of what might be moving to more AI search.

 

(19:31):

What kinds of pages are no longer getting as much traffic? Are there keywords you used to get a lot of traffic for that you no longer get traffic for? These to be good signs that some of those kinds of searches are moving to AI tools or the kinds of things that your users just feel more comfortable asking AI about these days. And then the kinds of things that I recommend brands pay a lot of attention to right now, the kinds of things I think are worth tracking. One is going to be your accuracy of your product data, really making sure that information, especially inventory information or logistics information like your shipping and delivery information, it's really important to make sure that all that information is accurate. So that's something that I recommend that brands track because again, you want to make sure that you're maintaining the trust of these agents because these agents want to make sure that they're maintaining the trust of users.

 

(20:18):

So I recommend investing effort there. Percentage of products that are machine readable to make sure that the processes and systems that you have in place to make sure that your product data is parsible by AI, that's something that I think is worth investing time in measuring. And then again, keeping an eye out on those traffic fluctuations and those kinds of keywords, those kinds of pages that perhaps aren't getting as much traffic, or perhaps there's some that are getting more traffic than before. Because what we've seen is that users will perhaps start their journey more and more. We are seeing that they're starting their journeys more and more in these AI search tools. I've seen that from working with the brands I work with. And then they're going and they're doing more research on their own. Again, that trust isn't there. They're going back to do more research on the information that they found.

 

(21:04):

And so keep an eye on, okay, what are we actually seeing perhaps an increase in? And it's important to understand again, what kinds of content user are using AI for versus perhaps what kinds of content they're going direct or information, sorry, they're going direct to your site for or they're perhaps going to traditional channels for, because then you can figure out, okay, how do I then get the right information to the right sources for where the user is interacting with my brand?

 

Peter Crosby (21:31):

Just a note, I did some quick searching and the Forbes Jason Goldberg article, I think it's the one from August you're talking about. AI visibility numbers are unreliable, measure them anyway.

 

Max George (21:42):

Yes.

 

Peter Crosby (21:43):

Is that the one you're thinking of? Great. So if you ask your agent to go search for that article, you'll find it. I just wanted to make sure, because Jason writes a lot of great stuff and publishes on Forbes, as does Lauren. So they're both competing Forbes columnists, not competing, collaborating.

 

Max George (22:01):

Complimentary work.

 

Peter Crosby (22:02):

Exactly. Thank you. Thank you. You got me out of that one. So when you think about measuring agentic commerce more broadly, one of the big questions is whether or not brands can think about this as an incremental gain of dollars. And the jury of course is massively out on that, I would imagine. I'm wondering how you think about with what we were talking about early, the idea that the sale can often be to a niche set of particular shopper requirements. Is there an opportunity for incrementality because you're capturing commerce you may not have captured without that extent of specificity of answers? Do you have just a sense about incrementality in this world?

 

Max George (22:55):

So I think that's a really good question, Peter. I expect as users continue to use these tools, I think we can expect to see an increase in the amount of incremental sales that AI assistants drive. Because again, platforms have to train users on how to use AI assistance. They got to get them comfortable with these assistants. They got to help them understand what they can do and what they're capable of first. And so I think in the early innings, we'll see perhaps more deal hunting, more price tracking, for example, price tracking for Alexa for shopping, different deal hunting tools. But I think that as users understand what AI assistants are capable of, and as platforms continue to get more context on what users are searching for, what kind of products they perhaps currently have, what kind of products they have in their basket, they'll have the context and the information to recommend additional products to help grow that basket size.

 

(23:49):

And so I do think that AI assistants will be a great tool for driving incremental product sales for driving greater basket sizes because they understand so much about users and users will continue to trust that their AI assistants will know more and more about what could be useful for them, what kinds of products could be helpful for them. And so I do think that we'll see an increase in the value that AI assistants can drive to brands as time goes on.

 

Peter Crosby (24:16):

That's great to hear. And it makes me wonder when you engage with brands, and again, I know it depends, but are you finding you're being brought in by the owners of e-commerce and helping them educate and manage and strategize up into the organization? I was just wondering about the entry point of a lot of your work, but so often our listeners have the role of also convincing their organization of why this is important, what should be done, where the investments need to go, and sometimes fight through that resistance. And I'm just wondering where you're finding your role is as advisor in a lot of the accounts that you work with.

 

Max George (25:01):

Yes. I've talked to folks up and down the organization because I think everybody really cares about this moment. Everyone knows something's happening. Everyone wants to get smart on AI search, AI shopping, agenta commerce. I typically work most with those digital P&L owners, so the digital teams, the e-commerce teams. But I think your point, Peter, that you're making about the need to educate the broader org about what's happening, I'm definitely seeing that that's important to the folks that I'm working with because obviously in these early days where we perhaps don't have the most reliable measurement tools, it's obviously harder for the digital teams to make the case to their cross-functional stakeholders that we need to pay attention to this and we need to really invest significant dollars now because we don't have the measurement tools necessary to prove what that ROI is going to be quite yet.

 

(25:53):

So they're having to make a case of this is coming, this is growing, this is happening. And we have tangential metrics that we can show to say, okay, we're perhaps seeing a traffic dip here or according to this software tool or that software tool that is tracking measurement, our visibility is this, but they don't have those hard sales numbers yet. They can't yet say AI is driving this percentage of our digital sales case to make. You're having to get everyone to be very forward looking and take a little bit of a chance.

 

Peter Crosby (26:29):

Always easy.

 

Lauren Livak Gilbert (26:32):

So easy for brands to take risks. What are you talking about?

 

Peter Crosby (26:38):

All those huge margins, they can just throw money where it's -

 

Max George (26:41):

Exactly, right.

 

Peter Crosby (26:41):

It's why I think so well of our audience because they are fighting those battles every day. So you've talked so much about earning trust, signaling trust, which I think is at the core of all of this working. And when I see things like real personal assistance like Muse and ChatGPT Dots, the idea is that consumers will give them more of the keys to their life in order to be able to perform those tasks, to be able to do the list of things that you talked about in the beginning. That requires massive trust. When I've taken a look at it, I just kind of go, oh, I don't know if I can do that. And I'm wondering if you have a sense of the current consumer pulse on what is sort of the line of trust they're at now? What do you think will convince somebody be enough trust to be able to actually hand some of those keys over?

 

(27:41):

Where are we at today and what do you think the milestones might be?

 

Max George (27:46):

Yeah, great question. We are definitely in the early innings, but there's certainly consumer interest here. So Muse, I mean, it's November. Muse just rolled out in September and they got over 10 million downloads in a little over a month. So we're seeing interest. We're certainly seeing interest from users. Obviously, a lot of these tools are going to get adoption with the super users, the AI super users, those who are really interested in technology. But what I think a lot of these platforms are doing a good job about, and every time I see an ad for Muse, I think they're doing a good job of showcasing the value that these tools can bring to consumers. And so I think that's what's really going to drive that trust. I think consumers, I mean, we saw this with the dawn of online shopping in the beginning. Everyone was like, "We're not going to put our credit card online.

 

(28:37):

That's crazy." And then as consumers saw the value of online shopping, the ease and then the breadth of products that they could shop for, they were more willing to take a bit of that risk. And then once you get that tap dripping, it's easier to go from there. And so I think where we're at right now, we're at super users, we're at early interest. A lot of consumers just use AI assistance, but when it comes to truly autonomous, agentic AI agents, we're obviously still very much in the early innings. We just saw Muse, Dots, Instinct as well just come onto the scene recently. But I think if these platforms do a really good job of showcasing to users, "Hey, here's the value that you get. Don't think about it as this alien technology, like an agent, but think about it as something that's helping you book a trip faster or something that's helping you track the prices of a product, something that's helping you meet a budget.

 

(29:35):

If these platforms do a really good job of just showing the basic value that it can bring to users, I think we're going to get more and more adoption from users.

 

Peter Crosby (29:44):

And I forget the citation, so forgive me for this, but I did see recently, I think it was the head of a major bank saying that if you choose to give your credit card information or your bank information to an agent, that's going to be a different thing. You will have to bear the cost of any misuse of that. Which is different, I think. And especially in these days where AI is also making it possible for cyber criminals to be a lot more effective. I'm just wondering, that seems like Wild West to me, and I wonder how you think, and I know you're not a seer into the world of banking and finance, but I'm just wondering if you have a sense of how that will play out to really make it a safe space. It seems like more than credit cards with e-commerce, but I could be - Yes.

 

(30:48):

Yeah, I just wonder what you think about that.

 

Max George (30:50):

Yeah, I think that's a good point. I will be completely honest and say payments are slightly outside of my wheelhouse, but from what I've seen, I mean, I've seen different players take different stances on it, and not just the payment providers, but even the retailers. Some are more willing to take on some of that risk than others. Like you said, it's the wild, wild rest out here. We haven't seen any alignment between the different ecosystem players on who's going to bear the brunt if something goes awry. Retailers may, they may not, payment providers may or may not, the brands may or may not. We haven't seen a trend in everyone saying, "This is the ecosystem player who's going to be on the line if an agent goes out and does something that it's not authorized to." But there are a lot of companies that are working in this space to minimize that risk.

 

(31:43):

There are protocols for agent to agent payments. There's tokenization and setting around tokens, et cetera. So where all that's going to land, I won't pretend to know right now, but I think it'll land somewhere.

 

Peter Crosby (32:03):

It will

 

Max George (32:04):

Mature.

 

Peter Crosby (32:05):

There's money to be made. People won't want to put too many barriers in front of that. And so we'll figure it out.

 

Max George (32:13):

Exactly. And I don't remember exactly what the very early days of... I don't remember exactly the posture of the banks and payment providers in the very early days of online shopping, but I bet if we were to go back and do a little bit of research, we probably would've found a few players that came out and said the same thing of like, "Oh, we're not sure about that yet." But then more systems of security, et cetera, came out to make it less daunting. And so more folks were willing to accept online payments as a new part of our reality.

 

Peter Crosby (32:44):

Fascinating times, for sure. And Max, first of all, I wondered if there's any of our listeners who want to reach out to you or get in touch with you, what's a good way to do that?

 

Max George (32:56):

Yeah, they absolutely can. I'm easy to find on LinkedIn. Max George, there aren't a lot of us, so I'd say they could reach out to me that way or shoot me an email. My email is also my LinkedIn as well, so they can find me there. Happy to always have a conversation, answer questions, and see if I can be of help.

 

Peter Crosby (33:14):

Thanks, Max. We are so grateful that you would take some time and guide us through this ever-changing world and the fundamentals that you spoke about, about establishing and signaling trust and the breadth of collaboration internally and externally that takes to pull off, I think is a really good watch word for our listeners to think about as we move into Good Lord 2027. So thank you so much for joining us next.

 

Max George (33:41):

Thank you for having me both. It's been good to be here.

 

Lauren Livak Gilbert (33:43):

Thanks so much, Max.

 

Peter Crosby (33:46):

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