What Does the AI Backlash Mean for AI Comms?

Today, tech brands are running headfirst into a massive wave of AI backlash marked by growing public skepticism, data center infrastructure pushback, and intense resentment toward automated technologies. If your company is trying to announce an AI-native interface, launch autonomous agents, or roll out a new usage-based pricing model, traditional marketing playbooks are falling flat. On this episode of FiredUp!, we tackle the critical challenge of navigating AI company communications in an increasingly hostile market. We address the problems founders face when trying to break through widespread AI skepticism and deliver a clear, tactical roadmap to achieve a perfect media message fit. Learn how to distance your brand from industry hype, ground your value proposition in concrete customer outcomes, and shift your public narrative from artificial intelligence novelties to undeniable, real-world utility. This week, episode 137 of the FiredUp! podcast is about what the AI backlash means for AI comms! 

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In this episode of the FiredUp! podcast, the Firebrand team shares about the growing skepticism about AI delivering the promised value and actionable steps you can take right now to navigate the AI negativity as a marketer in tech. 

Morgan and Chris discuss:

• Read the Room on Hype: The window for celebrating AI for AI’s sake is completely closed. To cut through the noise of the AI backlash, strip away empty promises of "autonomous magic" and ground every single piece of outbound messaging in concrete, measurable business value.
• The Media Message Fit Test: Journalists are actively screening for overblown tech claims. When pitching your AI native platform, focus entirely on the explicit customer outcomes and the human problem your technology solves, rather than the mechanical sophistication of your underlying models.
• Pricing Model Transparency: Shifting from standard subscriptions to consumption or usage-based pricing models requires flawless internal and external alignment. Structure your pricing communications to clearly tie increased customer usage to clear business success, neutralizing any financial anxiety or skepticism from your buyers.
• Leverage Independent Validation: In a skeptical market, self-promotion isn't enough. Lean heavily on your industry analyst relationships and existing customers to carry some water for you, utilizing their third-party endorsements to inject external weight and philosophy into your major transitions.

Building an AI startup into the eye of a market storm is undeniably difficult, but it forces an invaluable discipline: your messaging has to be built on reality, not just potential. Are your communications still coasting on yesterday's hype, or are you ready to prove your brand's undeniable utility?  

Thank you for listening! Tune in to all the episodes for practical tips on crushing your startup marketing goals. Don’t forget to follow, rate, and review the podcast, and tell us your key takeaways!

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5.5.2026

Transcript

Morgan McLintic: 0:00

AI is facing a major backlash at the moment, but what does that mean if you're running comms for an AI company? Join us as we explore the implications of the AI backlash on PR today. Hello, everyone. Welcome to Fired Up, the podcast for marketers working in early and late stage startups. Hello, everyone. Welcome to Fired Up. My name is Morgan McClintic, and today I am joined by our head of media, Chris Albrecht. Hey, Chris, how you doing?

Chris Ulbrich: 0:33

Hey, good to be here.

Morgan McLintic: 0:34

We are going to talk about the AI backlash, Chris, and specifically what that means if you're an AI company, because the rules of engagement have changed a little bit, and you've got to read the room, and when I say AI backlash, I don't mean people are getting a bit bored of AI slop, and you should need to change the way that you write. We've covered that deeply before. What I mean is real sort of groundswell of antipathy and even hatred towards AI in general and AI companies specifically. So, let's just unpack what we mean by that. I guess an easy one is Eric Schmidt did the commencement speech at the University of Arizona recently for a whole crowd full of students, and started talking about the potential of AI, and got booed, and there's been many other instances of that, and that generation of people are deeply worried about AI, and actually roll their eyes when you talk to any of them, they just, they shut down, so that cohort is definitely against AI, but there are other examples, right?

Chris Ulbrich: 1:47

Right, and you're seeing this pushback across the country against the construction of data centers in their neighborhoods, so the AI industry is as a whole generating this kind of ambient unease, resentment, anger, even as in by other metrics it continues to boom. Right, we have the anthropic IPO, apparently in the near to medium term. SpaceX is a big part of that offering as well, because it's all folded in, so you have these gigantic financial events raising all this money, and Anthropic, in particular, is just seems to be just blowing away its targets, making money hand over fist, and yet that success, and it may be no coincidence that it's closely related. That kind of success is also generating a resentment, and we started to see articles like the one there was an op-ed, I believe it was Jasmine Sun in the New York Times. It was titled Silicon Valley is bracing for a permanent underclass, right, and we're starting to get more and more open acknowledgements from people in the AI industry, many of whom she interviewed, that yeah, this is not going to be a bloodless transition. For a long time, the rhetoric about AI was that this was a tool that would augment human capability, but not replace it, but increasingly we're seeing that rhetoric go by the wayside, and there is more frank acknowledgment that no, that this is going to be a threat to employment, is especially going to affect people, it is thought often at the lower end, the earlier of their career, so people who are just starting out, so yeah, no surprise that students are booing this technology, because I think it's become conventional wisdom that AI is one of the biggest obstacles to them getting started in their careers, and we're already dealing with an economy where younger people feel like they don't have as much opportunity as their parents or grandparents did, and all the talk about AI and what we're actually seeing it play out does seem to reinforce those fears. So, it's a real phenomenon, and there's a sort of anger creeping into the public discourse around AI now that marketers and PR people who work with AI companies obviously need to be cognizant of,

Morgan McLintic: 4:25

yeah, the data center pushback, data centers being a sort of an embodiment of the AI industry, if you like, putting aside objections around water or electricity, I think a lot of that is mobilized around the fear of AI, and there's a data point here that there were 48 data center projects representing $156 billion of investment were blocked or stalled in 2025 with cancelations jumping from six in 2024 to 2025 projects, and then. In the first quarter of 2026 there have been another 20 already killed. This is a data center watch statistic that was cited in Fortune just in May. The pushback there is very real, and people in the AI industry are talking about it stalling development and adoption, but I think it's a symptom of the resentment towards AI, and with these IPOs, Tropic being a five year old company, people who joined three years ago are becoming senti millionaires, and at the same time students are not going to do as well. So, you've really got this sort of bifurcation here that some people, a small group of people, are doing really well out of this, and a lot of people maybe feel that they haven't had a chance to benefit from it, and, in fact, are dealing with some of the downsides, and we're talking about in the US here, we're not even talking about Europe or other countries.

Chris Ulbrich: 5:54

Yeah, I mean, I think it's worth reading the first sentence, which I think is going to be a famous first sentence. People will be reading it for years to come. Of that New York Times op-ed I mentioned about the permanent Silicon Valley underclass, and it begins, most people I know in the AI industry think the median person is screwed, and they have no idea what to do about it. It's very stark, right? Yeah, and if you pay attention to sub stacks in the industry and rumblings in people industry, like that is not a sentiment that will be unfamiliar to you, but to hear it put so bluntly in a mainstream publication like the New York Times, which tends to, I think, probably soft pedal the effects of like they're even handed, right? They're not polemic by and large. This is an op-ed, but even so, this is a really bold statement to see in the paper of record, and I think that reflects this emerging sense that the effects of AI are unknown and that the technology is getting off the leash, and we don't really know what the long-term impact is going to be, but it doesn't look good for these categories of people that we've been talking about, young people in jobs that are easily automated, and yeah, so what I think the big takeaway then at the top is just that if you are coming in representing the AI industry, it means you're not going to get the benefit of the doubt from the public, and specifically from reporters who are, as a group with definite exceptions, but as a group skeptical of AI and concerned about its impact, because they are part of a profession which has been relentlessly hammered by successive waves of technology and journalism has shrunk dramatically in the last 2025 years as the internet has taken center stage and now AI, so there was already this built-in skepticism and you pair that with the kinds of sort of social, and you might even say at this point almost unrest around AI, and it means that you cannot show up and expect a positive reception, you have to work for it, and you're going to have to prove yourself.

Morgan McLintic: 8:19

I think when we first saw AI come out, and we knew it was going to make a big transition, and there was parallels with the agrarian revolution, and people say people are not working in fields anymore, and actually that's quite good, and the sort of the theory was good, and there was a sort of hand waving around, but of course there'll be some retraining, and some jobs are going to go away, and some jobs are going to appear, there's no one standing in the elevator pressing the up and down button anymore, but we all got used to it. But here we are, we're right now, and we're talking to the person who's the bellhop, and they're losing their jobs, and this is becoming very real now. But it's happening on a massive scale, and your point about reporters is well made, because even just recently Google has changed AI mode to be the default on its homepage, and the result of that is it's not driving traffic to publications. Organic traffic to publications is way down, even since that happened at Google IO a couple of weeks ago. So this is a live and acute problem, so if you're doing comms for an AI company, that's the room you're walking into today, and you just have to be alive to that.

Chris Ulbrich: 9:32

Now, at the same time, you might say, okay, that's the backdrop, but I sell B2B software, and ultimately what my customers care about is whether it delivers value, and yeah, they might be on a personal level concerned with these larger societal issues, or the reporters who cover B2B technology might be concerned with them, but ultimately, surely the question here is. Am I actually delivering on my promises, and that actually brings us to the second really interesting development that marketers and PR need to be aware of, which is that even as there's all this resentment around the momentum and societal impact of AI, there's a growing skepticism that AI is even delivering the value that people claimed it did not that long ago, and I think there are a lot of reasons behind that. One big reason is that I think we've discussed this on the show before, that the preeminent use case for AI is coding, and I think that a lot of AI business plans have been built around the assumption that AI will deliver in other areas what it has delivered for software developers as effectively, and so on. The other side of it, though, is that's becoming increasingly apparent is that even in the realm of coding we're discovering that a lot of the perceived value that came from AI was effectively delivered through subsidy, because now that companies like Anthropic, especially Anthropic, famously are shifting to a usage-based model that is forcing users of Claude code to bear the real costs of their usage, as opposed to having more of an all you can eat subscription now that companies are having to reckon with the actual cost of the AI that they're using, it's not so clear that it's cost effective to develop software this way. So, even in that preeminent use case, CEO's are starting to look askance at those CFOs are starting to look askance at those AI bills and saying, are we really saving by using this rather than people?

Morgan McLintic: 11:51

I'm spending 10 grand a month on tokens here, maybe I should just hire someone, and humans are cheaper than some of the tokens, and I think you've also seen stories famously like Klarna, who came out and said, "We're replacing 700 agents with AI. They got a big bump to their share price. We're going to be out the front here as a pioneer. And then had to hire humans back and climb back from that, because the reality was not as good as people expected. You saw the same, I think, with Salesforce. Mark Bennett, sort of gone out and actually had to say, yeah, that was a mistake, and he's very open about that kind of thing, but mistake nonetheless. So you, you are seeing a little bit more skepticism about the actual outcomes there. And then there was that story, wasn't there, about the company who, you know, well, there's a whole token maxing. Oh, yeah, friend, right? There was this

Chris Ulbrich: 12:46

whole.. there was this all this news about companies that were encouraging, like I think Amazon, that was encouraging their people to just use as many tokens as they possibly could. Some of them kept leaderboards about who was using the most tokens, but it seemed like hard on the heels of all those stories came the news that companies were discovering that their bills were way higher than they expected. You were raising an example right there. Yeah, was that the Axios story?

Morgan McLintic: 13:14

Yeah, the Axios story of a company that spent$500 million million in million, like a half billion dollars in one month with one provider, anthropic, so the sort of default of AI is inherently productive and inherently good, and you should max it and use it in all cases is going, and so I think from what are we going to talk about? For some takeaways here, I think you need to prove the value, like being customer forward, proving the value, and the use, being very specific about the use cases, which has always been true for SaaS software, or what have you. Now, in AI, you got to lead with the customer outcomes and have them endorse it, because it, by default, it's not a benefit,

Chris Ulbrich: 14:05

right? Exactly. So, in the past, you might have gotten away with showing the value on paper, the value in a demo, but now customers are going, whether those are enterprises or individuals, they're going to be much more aware of the potential costs to them, and they're going to be much more value oriented in their analysis, so the question is not just can this work under any conditions, is can this work as a prototype, can this work as the like a Formula One car where STP pours all of its resources into making the perfect Formula One machine, and yeah, okay, that one machine under perfect circumstances can do incredible things, but you can't drive it on the freeway, right? And can you actually afford to use AI in practice? Does it do what it says at the cost. That the customer can afford, and that raises, you know, another sort of important consideration, which I think companies that already sort of race to accommodate and support AI are now all of a sudden, in turn, racing to grapple with what they've just built these structures to offer AI services through some mix of subscription and usage-based pricing, but in a lot of cases those sort of systems and arrangements with the customer were built around the idea that the customer was not likely to encounter radical overages, right, but now that the costs of AI are increasingly getting pushed to the vendor, who is of course going to push them in one way or another to the customer. You have to be on the lookout for reputational damage from customers who might suddenly find themselves faced with unexpected bills, right? Because if you're passing those costs along without much reflection, without thinking, oh, this is coming, this is a wave of new costs for our customers, it's coming up like they're not going to be happy about it. If you haven't thought that through, that's a real reputational risk for you, and it absolutely could show up in forums, in feedback. It is a risk that it has suddenly become more prominent. It was always there, but I would say that it's much more visible now.

Morgan McLintic: 16:24

Of the four Ps of marketing, we're mainly focused on promotion as marketers, but price is now a big deal, right? And that change in pricing model to usage-based pricing, it's not an all you can eat anymore, you need to communicate that well, because your basic, your users' costs are going to go up, and, and, and this is a challenge that I think a lot of AI companies are facing now, as they grapple with how many tokens is the average customer going to use, and what are those tiers, and the same time, the frontier models are changing their models, because isn't I think I heard that if you're on the Max plan with Claude, 200 bucks a month, they're actually already paying 5000 bucks in costs, a bit like Uber used to subsidize the trips for us all to get used to running around in black cars, and then other people's cars, they used to subsidize it, so they got us into the habit, and then the prices gradually went up. Still, this is being subsidized, and, but the real price is very high. Of course, token prices are going to come down, the models will become more efficient, etc. etc. So, we'll meet at some point, but yeah, this is a very real comms challenge that a lot of companies I think are facing at the moment, because their suppliers have changed, and so they have to pass that on to their customers.

Chris Ulbrich: 17:48

Yeah, and it's a non-traditional challenge for comms shops that have thought of their role largely as internal communications within the company and media relations outside of it, this is really more about community and customer relations, and I think, as the comms person, it would be really easy not to see this coming, because the people who are closest to it are going to be the product team and the sales team, and you're probably not thinking about the pricing model every day as the comms person at an AI SAS company, but you should think about it. You probably should ask some questions, because just getting usage-based pricing for AI, getting that in place is no small feat. And similarly, my sense is making the kind of complex pricing adjustments that are going to be required to absorb these changes in pricing from companies like Anthropic, that's no small feat either, and it could involve actual changes to the infrastructure that the company, the systems the company

Morgan McLintic: 18:56

uses

Chris Ulbrich: 18:57

to to monitor usage to to build to price, so it should not be surprising if your company's not ready for this. If it is in fact going to be a problem, and your company isn't ready, because it would almost be more surprising if they were ahead of it, because you would have to be very proactive, given how fast things are moving and how much is involved in getting this right, it would be amazing if you did nail it, and so I think it's worth considering the worst case scenario and making a plan.

Morgan McLintic: 19:31

Yeah, that's good advice, because that one's certainly coming down the pike if you haven't already looked at it. So, Chris, I think we've established, look, we're all in on AI, everyone's using it. Our clients are all AI companies, but we're going through this backlash, and the backlash is very real, and it is complex, even for a B2B company, as you just talked about. Should we take AI out of the headline here? It used to be, I want to be a Gen. Tick or AI, that's going to goose my valuation. I want to be AI native and put that front and center in the same way as maybe being cloud based was not being on prem was just inherently more valuable. But is AI powered just table stakes these days? Should I take it out? What do you think?

Chris Ulbrich: 20:20

An interesting question, because I think the answer is yes and no. Let me just observe that the meaning of table stakes is that this is what you have to put on the table just to get in the game, right? So, if AI is table stakes by definition, you need to include it. I don't mean to be pedantic by saying that. I think it's actually a useful way of thinking about this. I don't think AI gets you anything affirmatively at this point, but it is hard to see how you get covered unless your solution is leveraging AI somehow. I've heard reporters say that they are sick and tired of AI pitches, right? They're sick to death of AI, and some of them, who have the freedom to pick their topics, like Christopher Mims at the Wall Street Journal, are more freedom than some. Says, "Oh, I'm more interested in, like, he said, I'm more interested now these days in concrete topics, like this cool story I just did on concrete, hex-gen concrete, that's nice, but at the same time he is writing a lot of stories on AI, and as he pointed out, he's written a whole book on it. So I think that AI exerts a gravity right now that is more or less inescapable, but you should not expect, if you still do, you should not expect that your AI announcement is going to get covered by virtue of being AI, because literally everything is AI, and so it's simply not enough to on top of everything being AI, most companies are following more or less the same product strategy right now, especially companies that predate the launch of generative AI, or the emergence of generative AI. They're all rushing to launch AI native interfaces. They're all rushing to launch AI agents, and so what that means is, yeah, you, you need to communicate that to your customers, right? Because what you're trying to do in launching these features and launching this experience is to communicate that you are every bit as modern as AI native competitors, and you probably will even, as part of your message, say we have all of that, and we have 160 connectors, and we have all of this enterprise class infrastructure that they don't, so that's important for your customers to understand, but at the same time it's important to realize that from a reporter's point of view there is absolutely nothing worth covering in that announcement at that level, because you are doing exactly what every company in your shoes is doing so. What that means is that in the relatively small number of story slots they have in a given week, in a given month, if they cover that news as such, they're not really taking an opportunity to cover news that says something bigger about the industry, instead of covering an announcement that is somehow emblematic of a larger trend, as we love that word trend in this job, but instead of doing that, instead of covering the bigger story, like a story that means something bigger than itself, they're actually covering a story that is unremarkable in and of itself, and that's just not going to be attractive to them. It's commodity news, and it's likely just going to go straight to the news feed. So, that does present that is in some ways the big challenge right now for AI companies seeking coverage.

Morgan McLintic: 23:57

This is big, because if you are a SaaS company, and you're now, you've gone through the transition to be AI first and have a chat interface. You're maybe launching your agents. This is a big strategic move for you. It's very important for customer comms. It's been a huge engineering lift to get it out there, and it's got to be successful. This is the future of the company, right? If it wants to remain competitive, and yet, as you said, that very transition is the same one that every other SaaS company is doing all about the same time. In our inbox this week I've had companies saying, hey, we're launching our AI agent, and I wonder if you can help me with that. I'm like, okay, but not as a standalone just announcement, because who's going to cover that? Because this is my inbox, and I'm not the reporter, and I'm seeing there's plenty, so I think you need to find. Ways to show the value of your AI native interface in different ways with the customers, with the analysts, with the influencers over time. Don't not announce it, you have to announce it. But I think this is a classic example where message media fit. You've heard us talk about what the media want to cover and what your messages are, and you've got to find the overlap. There's not a lot of overlap with this particular announcement, because the media is not going to be that interested in it, but, and, but it is a message for your company, and so I think just setting expectations, and then thinking, okay, how do we find other ways to tell this story about the transformation of our business, right, and the benefits to our customers is really important.

Chris Ulbrich: 25:45

Yeah, that's right. I know it's incredibly frustrating for companies in this position, right, because it is a big lift to create all this new functionality in the product. It does mean re-engineering the product in many cases, top to bottom, and it feels like a big achievement, and it is a big achievement, and yet you know it's sort of like parenthood in that way. It is a massive achievement, and totally unremarkable.

Morgan McLintic: 26:13

Right?

Chris Ulbrich: 26:13

Right, it's the most common thing in the world, right? It's an experience that people share, and yet, when you're in it, it feels like the most distinctive and important thing you've ever undertaken, and it is both things are true that raises the question, then what can you do, and even acknowledging that you're starting from behind the eight ball here, that this big lift is not in and of itself going to be perceived as very newsworthy. I think this is the time when you go back, you need to go back to the unique value that you deliver, the end, and the sort of the deep philosophy that animates the company, because what you're really doing is you're trying to get down to your deepest differentiators here, right, because the product itself is going to seem more or less indistinguishable, probably from your competitors, but to a reporter, definitely from a bunch of other announcements that look more or less the same, so what a reporter is going to be looking for is what are you doing out of all the different approaches to a problem out here? Where are you putting your chips, and what are the reasons you have for thinking that your approach to this solution is more compelling than these others? And so, for instance, famous, like I just saw Frederick Lardinois posting about how he's at a conference, I think he's in Amsterdam, and he was saying, not surprisingly, all the talk here was relentlessly about this idea of context. Now, if you're in anywhere intersecting the AI industry right now, you've heard this term context, and it's everywhere. Everyone wants to claim that they provide the content and the guardrails, and the mixing terms here, because some people say guardrails are the hardest, and context is the content, but point being, everyone is trying to say that, sure, our competitors have agents, but our agents work, because our agents have the quote unquote contacts to steer them to the right information, the right data, where the agents of our competitors are just blundering around, making mistakes, not ours. Ours have the information they need to make the right decisions. That's context, but what you notice, you see enough of these companies making that claim, they all have a different opinion about what context matters, right? And some find context in SQL logs, and some companies find it in semantics. Some companies would say that semantics are actually just an element of context, and the context is just about touching all the data and getting access to the data, but semantics is what makes it meaningful and what actually gives the agents the guidance they need to make smart decisions. Everyone has an opinion on this. Probably the place for you to focus is what's your angle on the big question that you and your competitors are tackling. So, the news is less, we've launched an agent, that's the second, third, or fourth point from the reporter's point of view in the story. The story is more going like that's an excuse to write the story, but probably the reason they write the story is because they've never really taken an in-depth look at your approach, your philosophical approach. So I would say treat the launch as the news hook, but pitch the approach, pitch the philosophy, and find someone who hasn't written a story like that in your field about one of your competitors or something that's tangential to what. Find someone who hasn't done this already, because what you're going to be asking them to do is go deep on the topic and get to grips with what's probably a pretty technical. Subject, and really engage with it for a few days, and they're probably going to be less inclined to do that if they've covered either a competitor or a technology that is similar in some ways, if they feel like they're just going to be running over the same ground. So that's really the challenge is broadening your scope, the scope of the pitch, or elevating the pitch, you might say away from the AI native interface, above the AI interface, and finding a reporter who is going to engage with it and hasn't engaged with that topic recently.

Morgan McLintic: 30:32

I like that, because you're trying to inject an element of news of conflict, right, an element of news which is conflict, and we think this, and they think that, and you're bringing in some risk. We could be wrong, and our company is at stake here. The stakes are high, but we think we're right for these reasons, and that's that's fundamentally what makes it more engaging, even if you're new to your company as an emerging sort of brand? We're back, we're betting this is right, we're in this camp, and it's borne out in this agent, but the philosophy behind it is this, and, and we could be wrong. So watch this space, and then you're sort of bringing the reader along with you, and that just, I think, just makes it a much more interesting story, rather than just functionally, hey, you used to have to pull this drop down menu, now you can just chat into it in natural language, or we've got an agent that goes out and does this for you and comes back when it's done, and we've trained it, bring the conflict, I think is what I would say, that's

Chris Ulbrich: 31:40

right, and that difference, conflict, difference of opinion, it creates stakes, but I think, in addition to that, it also helps a reporter place the story in the larger context of their coverage of the space, because I think more than ever, reporters are outside of the ones who are assigned to cover the giants like Open AI, Anthropic, Google, etc. If you're covering developments in AI-powered data engineering, you're probably less focused on covering the ups and downs of individual companies and more about informing your readers about the possibilities, the different possibilities, right? And chances are, my impression is reporters are less interested in covering you as a company and more about making sure that their readers are aware of an interesting, of different interesting options, and they can fold at that point effectively other companies that are doing the same thing under that, they will feel like, okay, yeah, there are other companies out there that are doing that. My job is not so much to make my readers aware of all the different options. There are stories that articles that do that. There's like listicle stories, but typically it's more like you are trying to make your readers aware there are these competing ways of doing it out there, and these are the pros and cons, and so again, it makes it easier for them to write a story that is more trend-based, more industry-based, rather than anointing one company versus another as worthy of attention. Of course, that's how it feels when you're the company getting coverage, or when you're the company not getting right, and that's look, that's what we do, is we try to make sure that our clients are the ones who are the standard bearers for a particular approach, but that's not, I think, how most reporters think of the job, and so this gets back to the idea of media message fit, you are trying to structure your pitch in a way that's most congruent with what a reporter is looking at,

Morgan McLintic: 33:44

and just final point on this. Obviously, it's great to have a customer who's going to endorse the operational value of this new agent, but they probably have only given the speed that companies are working at, they probably haven't had a chance to beta test it much at all, and often they're big companies, and it's hard to get them to do that, so I think this is the time to also lean on all of your analyst relationships that you've got, you've got to bring them in and carry some water for you and endorse your philosophy on this, whereas maybe you wouldn't on other announcements, but this is a big transition, so get some people on your side to give it some weight, I think, in place, or maybe, as well as having the customers, if you totally, if you're able to. All right, Chris, I think this is a good place to wrap. We've talked about the backlash, like it's very real. We've talked about some actual tactical challenges that companies are facing now when they have to update their pricing model, or they're about to launch their AI native experience, or their new fleet of agents that need some careful navigation, because you're doing it into the eye of this storm at the moment, and others are facing the same challenge as well. It's just a bit of a tricky messaging. Situation at the moment, and so we wanted to dive deeply into this topic. So, thanks, Chris, for sharing your views on that, and we hope you found that deep dive useful. If you did, we'd love it if you could subscribe to the podcast, or drop us a comment with some great comments on our YouTube recently. So, thank you for those, and we will see you all again next time.

Unknown: 35:25

Bye.