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Ep 6. Inflection AI’s CEO on Why Trust Is the Future of AI
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Inflection AI’s CEO, Sean White, takes us behind the scenes to explore why trust is the cornerstone of the AI revolution. With boardrooms and tech leaders demanding an “AI-first” strategy, he reveals how building human-centered, conversational systems isn’t just about technology - it’s about forging genuine trust and empowering people. Drawing parallels to the transformative shifts of the 90s and the rapid innovations seen today, he explains how agentic systems and AI-driven insights are reshaping everything from customer service to enterprise data analysis.
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Transcript
Introduction to the Horse's Mouth podcast
00:00:12
Speaker
You're listening to From the Horse's Mouth, intrepid conversations with Phil First. Ready to meet the disruptors who are guiding us to the new great utopia by reshaping our world and pushing past corporate spin for honest conversations about the future impact of current and emerging technologies?
00:00:30
Speaker
Tune in now.
Meet Sean White, CEO of Inflection AI
00:00:37
Speaker
Greetings everyone, and welcome to the latest edition of the Horse's Mouth podcast. I'm Phil First. Joining me today is Sean White, who is a re-founder and CEO at Inflection AI. The reason he's a re-founder is the company who was actually founded by Mustafa Suleiman and Reid Hoffman, and they invited Storn to come in and head up the firm.
00:00:59
Speaker
So Sean is going to talk a lot about one, his views on Agentech AI and the future of technology, and a little bit about why we want to keep doing great core things until we end our lives.
00:01:13
Speaker
So let's let's get started. So tell me about Inflection and what you guys are doing. Obviously, you've had a very impressive start to life with some big names like Mustafa and Reid tied to it. And I'd love to get a bit of a history on what you guys are doing.
Inflection AI and its evolution
00:01:31
Speaker
So starting off, this was this was founded by... Liedhoffman Mustafa, and the the goal was really to push the limits of what we could do with personal AI.
00:01:43
Speaker
So at the time, for instance, just to give you a sense for what was happening, there are about seven companies that were asked to make these White House commitments because things were moving so fast.
00:01:55
Speaker
in terms of the growth. And so you have OpenAI i and Google and Meta and Inflection. So we were in that race.
00:02:06
Speaker
And ah around a year and a couple of weeks ago, last year, Mustafa decided together with Microsoft and Satya that he was going to move over to Microsoft.
00:02:18
Speaker
But you know that was now 20,000 people in a fairly large corporation with lot of resources. I was asked to take over and the board had already decided this was going to start moving in a commercial direction.
00:02:31
Speaker
I've had experience in startups, large and small, large companies, academic work. you know Most recently, starting this group that was around neuroscience and AI, as well as spending about a half a decade as the chief R&D officer at Mozilla. But also, you were talking about the internet going all the way back.
00:02:52
Speaker
you know I'd had an early internet startup as the CTO. We were in that same feel, that same wave where everybody had to get some internet, and we were doing this brand new thing called web-based email.
00:03:02
Speaker
And I mentioned it also, not just to reference what you were talking about in terms of the feel of everything that's going on, but because i liked that business model, which was that we had Mail City, which was free for people. It really gave people access who had never had access before.
00:03:20
Speaker
And it white-labeled the web-based mail to all these companies like Excite and Lycos, The Wall Street Journal, hundreds And that was a really successful company. And so my mental model when I joined Inflection was to do the same thing.
AI in Enterprise: Opportunities and Challenges
00:03:34
Speaker
That is, can we continue and improve Pi, which we can talk about, this amazing chatbot and personal intelligence, And do that through building out to the enterprise and taking all of the things that we had learned, these large models, and you know we continue to build these, all the fine tuning pipelines, the expertise at inference at scale, and bring that to the enterprise in interesting ways.
00:04:01
Speaker
And so that's really what we've done over the last year. So we opened up the API for people to use. One of my colleagues, Ted Shelton, was at the Vision Conference sharing with people inflection insights, which takes a lot of the work that we had done. you know We've continued to build these ever-larger models, but as well as distilling down models, takes our orchestration that lets you do this really interesting thing, which is have conversation a conversation, dialogue with your data warehouse for all the data that you have, make it much more meaningful.
00:04:34
Speaker
And so now we have this range of enterprise products that we're working on, as well as all of the value that we created in conversational intelligence and empathy and things like that from Pyne.
00:04:46
Speaker
Yeah, but meaningful conversations with data. This resonates with a large number of complicated conversations. One of them actually was a podcast I did recently with chap Jason Averbrook, who's like one of the leading minds in ah HR technology.
00:05:02
Speaker
And a lot of major enterprises today have so much data on their people, but it's just not joined up. It's a mess. Companies are now starting to question, shall we just rip this up and start again?
00:05:16
Speaker
How can ai products really help fix a lot of these terrible data dysfunctions within companies which have built up through decades of history and legacy?
00:05:28
Speaker
So you went, this is the grand unification theory. Yeah, good. I like challenges. Well, I mean, I think there are a couple of things to pull out there. One is that AI itself is both a user interface technology and a computational technology. And so like many of us, I got my PhD in computer science and doing vision, various other things.
00:05:49
Speaker
I really thought of it as a computation technology, right? But what has really changed, and what I mean by user interface technology, is that it is enabling user experiences, user interaction that we've never had before because of the probabilistic nature of it.
00:06:06
Speaker
And so, you know, these old IVR systems are things where you had to have a grammar, and if you went, at the moment you went outside the grammar, it was kind of like playing a video game and you went off the side of the cliff, right?
00:06:16
Speaker
That doesn't happen anymore. And that's really powerful for both the interface and the way in which you gather data. Now, I think it's interesting because and one of the reasons why we spent time around conversational intelligence is that it's foundational to both trust and usability and how you construct that.
00:06:38
Speaker
And so when you are making a new kind of interaction, if you can make something that feels less transactional, more relational, that is a real boon, a benefit for both the the interaction you're doing, the data you're gathering, and you know you improve the system as well as people's engagement with the system, right?
00:06:57
Speaker
as opposed to making something that feels crappy to use. I mean, yeah not going to pick on any particular sales tools or something like that, but you know there are there are people who just decry every day they have to touch some of these tools.
00:07:09
Speaker
It doesn't have to be that way. Yeah. Why doesn't it have to be that way? I mean, how do we get past this huge chasm of change that so many people are terrified of. I mean, we we just completed a major study of over a thousand of the C2K and 45% of enterprises that their staff are terrified.
00:07:30
Speaker
like They literally are, they're looking very negatively at this. Only 15% of AI leaders who feel empowered, but they feel that they're joining up the pieces and have a defined strategy. There's a few in between who are getting there, but nearly half of executives today are privately worried about where this is going for them.
00:07:49
Speaker
Yeah. Say more about what the fear is that you're finding there. Fear for relevance, fear for their jobs, fear for finding some ability to gain competitive advantage, professional advantage from this.
00:08:01
Speaker
I think finding the time to be educated and breaking away from the noise. I think last year was a year of lot of exciting talk and discourse around capabilities, but possibilities.
00:08:14
Speaker
Today, we're hitting a period where people are being, you know, their heads are on the block. They have to deliver. They've been told, start to make this work, start to make this happen. And then you start to get into the real conversations. I mean,
00:08:27
Speaker
One person I spoke to who works in the healthcare sector, their organization deals with half a billion lines of code a year generated. They feel that they can eradicate 90% of the inefficiencies from this and do it in two years.
00:08:43
Speaker
That has a huge ramification on the resources they're deploying, the partners they have, the people they have and the skills they have and everything. It's a, it's a gargantuan change management exercise and something that companies have never done before.
00:08:57
Speaker
A hundred percent. I think this is a huge change management exercise. Let's take the shift to remote, right? Because of COVID. Had to get it done. The companies that got it done were successful, the ones that couldn't get it done had a lot more problems.
00:09:11
Speaker
I think some of that has to do with the way we think about change management. Before I was talking about how the interface itself, the interaction is more relational, less transactional. I think that has to be true for the change management here, which is to say, let's take two accountants.
00:09:27
Speaker
And there's an accountant who runs away from and fears AI because it's being framed as replacing them. And then there is the accountant who learns as much as they can.
00:09:38
Speaker
ah and really tries to use it to give them more agency, superpowers. One of those two people is is going to succeed much better i and succeed much more. And I think part of that is how companies are choosing to talk to their teams, how they're educating, how they think about literacy around this, and the companies they work with to do this, right?
00:10:01
Speaker
This is change management. And so you want to work with companies that you feel like you do have some trust and things things are not going to always work out first or right. And you have to kind of keep at it to get it to work. I think part of that is finding the right partners in the projects that you're doing.
00:10:20
Speaker
Right. And making this more natural, making this more human-like, I mean, that was the big element around, i I think, personal intelligence, the pathocracy originally had.
00:10:32
Speaker
Yeah. I mean, you know i would you could say more humane as well, right? And even when we start talking about some of the ah more advanced enterprise systems like Insights, you know, if you have the sort of robotic one and done, that's not actually very useful for learning something more, right? You you want to have the equivalent of a Socratic dialogue with the information to really get those insights, really find the things that are both unpredictable, but to and know how to understand.
00:11:02
Speaker
So tell me a bit about this more empathetic, natural conversation with data. I want to understand about my business. I want to understand about the economy. I want to understand about support making decisions.
00:11:16
Speaker
How do you feel that's developing and working? Can you provide an example or two where you feel you're really getting an edge here?
Conversational AI: Enhancing Customer Interaction
00:11:23
Speaker
I think I mentioned I just gave a talk and we've been so sharing ah bunch of work more on inflection insights.
00:11:30
Speaker
Let me talk a little bit about the why and then a little bit about the what. The why depending on how it gets implemented, right? If this is something external facing, well, that means that you're actually starting to get some voice of the brand or the identity of the company, the things that matter, right?
00:11:45
Speaker
And if someone feels good, you know the old saying, people won't remember what you said, but they'll remember how you made them feel. That is infinitely true, both in talking to people, but also with the systems.
00:11:56
Speaker
i And that matters for the external facing systems, operational efficiency for how you actually get something better out of it. and you know For the individuals, The intention is that there's fewer frustrations, more flow. We were talking about IVR systems before, right? And I'm one of these people who would get on an IVR system and start yelling, human, human, human.
00:12:18
Speaker
And you don't have to do that anymore because these systems are very good and managing the unexpected, at least the ones that we've been building. And so, you know, you have conversations, which conversational intelligence takes a lot of work, right? You have to understand the context that you are representing. Some people do want the sort of just the facts and some people really need to be sort carried along.
00:12:42
Speaker
There's long-term memory and how you handle memory. Like you and I feel, I imagine we will talk again and then we can refer back to some of these discussions and things like that. Then there's a whole bunch of ways in which you implement conversational intelligence.
00:12:57
Speaker
But the interesting thing then is, what does it mean when you actually have that insight from data, right? And so the example that we have, we have a customer right now who is using it to get data insights for supply chain analysis, right?
00:13:13
Speaker
So you're you're making a leap with me from the personal intelligence that is helping somebody talk about, you know, like testing out how they might go through their day to supply chain analysis, right?
00:13:24
Speaker
And, you know, in this case, the interface actually gives you information about what you're seeing, but but in some ways it's the same, right? You can ask a question about the supply chain, like, know, who are my top suppliers and how much did I spend on the top item last year?
00:13:39
Speaker
And, know, It's a set of, and I'll use the word, agentic systems, where first it's trying to understand your context. You already have figured out whether you're connecting to, you know, snowflakes or data breaks or your own data sources.
00:13:54
Speaker
And then it's going through through a combination of current information from the world, the LLM, a SQL query that is created, you now get back things like, oh, well, your top supplier on a total spend for last year was listed in this table below. It gives you graphics and things like that.
00:14:12
Speaker
But you wouldn't want to stop there, right? I mean, you then want to be able to start to ask these questions, these what-if questions, right? Like, all right, well, then what's the impact on the total spending if 25% tariff is placed on all my materials from China?
00:14:28
Speaker
I know that might never happen, but just in case, right? It will do the analysis and get back to you and say, oh, well, you know, the impact is going to be an additional cost of maybe $8 million. dollars And let me show you how.
00:14:40
Speaker
What else can I tell you about it do you want to talk more about the group categories or total spending? And it is like having that conversation with the data itself that to really understand it.
00:14:55
Speaker
This is so wonderful in concept. And we've seen the examples, we've heard about examples, but the reality is, especially when you start to get into the call center world, very little is actually happening.
00:15:07
Speaker
If people are going for cheap chat options, because it's low cost, they're not going for more sophisticated conversational options and hey i was just on the phone to Apple doing something yesterday.
00:15:19
Speaker
You still have to talk to somebody. I'm like, you think someone as sophisticated as Apple would be in a situation now where, hey, I need to get ah box sent to my house to mail back my Mac.
00:15:30
Speaker
Why did I have to actually talk to a human being still? When are we going to get to a point where we're going to start to see this crossover between when you're needed to talk to a human versus I can get this whole thing done in an AI agentic manner?
00:15:44
Speaker
Yeah. I mean, ah my sense is that, you know, we'll be seeing some of that this year and it will grow. i think the addition I would put in there is that I think some of these systems are most powerful when there's a human in the loop.
00:15:57
Speaker
And by that, it might be that most of your conversation is with the AI, and then you know a human may be either working there or may add some piece in there.
00:16:08
Speaker
Or in some cases, the human is getting guidance from an AI about how to best solve your problem. Normally, you call one of these places. I certainly get this frustration with healthcare, for instance, where you know you you call and you get a a different person every time and they know nothing about the history.
00:16:25
Speaker
like They've never talked to you before. Really, each one of us, if we can, in the best of all ah possible situations, it would be like you had your own personal experience.
00:16:36
Speaker
assistant who is helping you each time. They remember everything about it. so When you're calling Apple, they know all of the different pieces that you have used. they They know you're an Apple fanboy and they want to know that you know like they're going to help you and take that as an opportunity to build a relationship, not just make you barely satisfied. 100%, I see that coming.
00:16:56
Speaker
But I 100% believe that makes a better experience both for the individuals on both sides of that game. So what do you think of the impact of, so we saw DeepSeek obviously appear and I must have given you guys a headache, right? And how to combat that, how do you start to see the emergence of like these inference type models coming into play and are they going to decimate the value very quickly and make this very commoditized or do you think something else is at play?
Trust and Privacy in AI Systems
00:17:27
Speaker
Yeah, there's there's a lot in that. And first, we weren't afraid. I mean, just the opposite. We were curious. Now, keep in mind, we have a bunch of smart people here. And so, you know, I would say smart and bold people, you know. And so the first thing, it comes out and all of a sudden the team has, I look on Slack and the team has created a reading group.
00:17:45
Speaker
And you know they're already fine-tuning DeepSeek and really trying to understand some of the stuff about it. And for us, I mean, certainly we have these very large, I think the last model we had explicitly announced was in the 400 billion range. And we certainly have things that are almost twice that size now.
00:18:04
Speaker
And it's important to remember that we do an orchestration across lots of different kinds of models and sizes of models. And so, you know, we can fine-tune LAMA, we can fine-tune DeepSeq and use them purpose-built activities.
00:18:18
Speaker
That seems like a boon for us. You have to know how to do this and and where to use it, where not to use it. I mean, it's kind of... There's a ah piece here, and I've been testing this out with security folks I know to sort of see how to get around this, but there's there is this epistemic security issue with DeepSeq.
00:18:39
Speaker
And by that, I mean the epistemology. And so we already know, for instance, that DeepSeq in its raw form doesn't know anything about Tiananmen squared, never happened. Taiwan is a part of China.
00:18:51
Speaker
And and and you know ah of course, all systems will be biased by their creators. And we have tools for removing those things. Turns out you could get DeepSeek to say it was clawed, right? and So kind of know where some of those things came from.
00:19:06
Speaker
And you can fine tune those out for a certain kind of safety. But the hard part is when you you, those are the known unknowns, but when you have the unknown unknowns, which is to say,
00:19:17
Speaker
If I'm now an enterprise and I'm using DeepSeq for something really important that we haven't explicitly fine-tuned out and removed, that can be problematic. An example I give sometimes is I'm ah looking at sourcing and have some questions about steel and DeepSeek is confident that steel from China is much better quality than steel from Canada because we never actually fine-tuned that out, never did any sort of post-processing.
00:19:47
Speaker
You just don't know what's in there. It's a little bit like going to New York. I love New York and having the hot dog, but you're sure you don't know what's inside that hot dog. And so i think it's worth keeping that in mind.
00:19:59
Speaker
My time at Mozilla, I care a lot about open source. But one of best pieces of work at Mozilla was this project to run open source by design, which is saying, you don't just do it by default.
00:20:11
Speaker
You actually pick what aspects. but you know Do you want it because you are trying to get multiple stakeholders? Are you doing it because you're interested in some kind of security or trust activity?
00:20:21
Speaker
There are reasons for it. And so I keep that in mind with a lot of the deep seek work. And I think it's interesting. Anything that promotes more innovation across the entire ecosystem seems like a good thing to me.
00:20:34
Speaker
There you go. So as we look out at the next couple of years, who's going to win in this game? Because we're already at a point where you'll look at five major LLM tools if you're an average to above average user, right? we We're not at the point we were a year ago where there were hundreds of these things.
00:20:52
Speaker
And you want these things simplified and you want to be able to trust who you work with. You want to be able trust that what is going on behind the API is going to pull me to the best data, the right the best models, that sort of thing. So how do you see this playing out and who's going to win?
00:21:06
Speaker
then as a second point, the role of services is very important in the work we do at HFS in terms of how the hell do we plug this into your business versus the the concept of software.
00:21:19
Speaker
What do you see happening with the role of the services firms as this whole value proposition plays out? Well, let me roll those back in reverse order. For services firms, and and of course, I don't have a crystal ball. I think we make our futures happen, right? But you know for the services firms, I think, certainly for the first couple of years, we've been talking about the transition and change management.
00:21:42
Speaker
Because nobody really knows how all of these things get integrated, i think it's probably great for services firms. If I was going to make a prediction about what company is making decisions the most revenue on this next year, probably services firms.
00:21:59
Speaker
But then you will see the firms that are adopting AI as part of their workflow and as a tool that they provide. I expect those are the ones that are going to be able to move the best and the fastest.
00:22:13
Speaker
And those are the ones that succeed. And they'll probably be sort of leveling off and tapering off for that. And you know the ones that are convinced that they don't need it or that they're afraid of it, again, i think those are the ones that will have to find something else to do.
00:22:28
Speaker
The last part about who's going to win, well, of course, I think we're going to win. But I think part of that is about, you used the word trust. I think one of the lessons we learned in the browser business is it's amazing what trust relationships get built up, right?
00:22:44
Speaker
you trust your browser, whichever one you use, to keep away all of the malware and the thousands of, tens of thousands of systems and people that are trying to to do something or take from you or or you know put malware in there.
00:23:01
Speaker
And then that trust relationship becomes really important along with the usability. And everybody sort of races to IQ and these tests. And in some ways that will be asymptotic and we all get there. And then I think a large part of this is going to be around the trust relationships that get built.
00:23:19
Speaker
That's one of the reasons why we've leaned pretty heavily into the conversation intelligence. It's a good way to build, and it's an honest way to build trust. So it's been awesome just having more and more conversations around this. You know, how much of an issue do you think privacy is is going to continue to play, particularly with the volatile macro situation as we look at the...
00:23:44
Speaker
all's rollout and how are you looking to capitalize on that? Yeah, that's an interesting question because now we get into geopolitics a little bit. We've always cared about privacy. Enterprises have always cared about privacy. right There are some that care enough to focus on a virtual private cloud where their data is.
00:24:04
Speaker
There are some that need things to be on-prem, to have it air gaps. and And those are either regulated or they care very deeply about their business intelligence and what is happening with them.
00:24:17
Speaker
And that's been true for most enterprises. We, by the way, we do have a system that we deploy on-prem where people can say there is an air gap. But I think you were asking more complicated question.
00:24:29
Speaker
which is what is happening in the world as we get more systems from China, as we get more systems from other players around the globe, and those players, like the Europeans, get more concerned about the predictability and reliability of all those models and think that they need to have sovereign AI, which is the term a lot of folks use.
00:24:56
Speaker
And that's not necessarily new. In in Europe, for instance, there was ah there was already a movement, particularly around GDPR, to have the sovereign data hosted at least in sovereign locations, if not owned by a European company.
00:25:11
Speaker
And, you know, we all figured out ways to address and deal with that. I think it gets more complicated if they start to feel that they need to have a sovereign AI, you know, going back to the hot dog, that they know they know the ingredients in the hot dog, whether that's a ah French hot dog or a German hot dog or...
00:25:29
Speaker
a Thai or Japanese hot dog, doesn't really matter. We and others are certainly being asked to help with these kinds of AI systems. I think one of the with the challenges with that is that you don't want to get cut off from innovation, and I would hold that currently,
00:25:47
Speaker
we and others like us are still the most rapidly innovating. And so I think we'll have to find a balance around that. And I think we'll also have to see how the geopolitics evolves around this as well. but but But my hope is that we continue to have customers and partners and folks all around the world. And I know the other companies do too.
00:26:06
Speaker
I'm curious what you think about this, Phil. I mean you've been you have clearly been thinking about that challenge. What do you think about, well, particularly, you know for instance, American companies working in Europe or the impact of models from Europe or China, other places?
AI's Global Impact and Collaboration
00:26:24
Speaker
I think that what's happened in the last few months has actually forced the European countries together to realize we can't just be depending on the United States for innovation, weapons support, whatever you want. Keeping politics completely aside, actually think this is a good thing for Europe.
00:26:42
Speaker
It's making people look like the more unified we are, the more power we have as a collective versus as individual nations. And I've always believed that with the US. The US as the leader of the free world has been the benevolent country which has inspired innovation and inspired commerce, inspired growth. And I don't think a few tactical annoyances around tariffs and things is going to prevent longer term progress. I really don't.
00:27:06
Speaker
And I think we'll continue to evolve in a way where we'll continue to innovate. China will continue to threaten us by doing things cheaper and more efficiently. I'm hoping we get past the next few months of, I would just say, volatility into a world where the global economy is growing and we prosper together. So I think ultimately one wants a recession.
00:27:30
Speaker
No one wants to reverse years of progress. And I think a lot of the noise right now is more about short term deals and some better equity of trade laws and things like that more than anything else.
00:27:44
Speaker
i But I do feel when you mentioned supply chains, it's so important in a global world to have great access to data and inventory and goods and movement and flows. it's so important to have access to talent across the world.
00:27:56
Speaker
And for example, all of Global 2000 now have global capability centers in India growing at 20% a year. You can't stop that. Those are employees of those global companies.
00:28:08
Speaker
You can maybe slow down outsourcing and you can slow down trade and you can tax this and you tax that. But ultimately, and don't think you can stop progress. And now I've been worried like everybody else, but I'm quietly confident that we'll get through and difficult times and come out in a more prosperous world.
00:28:26
Speaker
I'm quietly confident and I'm i'm a fairly cynical person as an analyst, but i I'm actually quietly confident that we're going to come out of this okay. And the development of agentic and AI is just It's just awesome, man.
Embracing AI Innovation in Life and Work
00:28:41
Speaker
Like we couldn't ask for a more exciting time in technology where you can literally start talking to your computer and getting stuff done. mean, I'm an analyst. We can pump in flat files in Excel and it pumps out really nicely written analysis, which just saved me like a week's worth of work. I mean, this is incredible stuff and you've got to embrace it.
00:29:01
Speaker
Oh, agree. and and And I am... I think like you, and i'll I'll go all the way back to one of the things we were talking about when we're when we were talking about you know conversational intelligence, which was in the long term, the things that succeed, I think will be relational, not transactional.
00:29:18
Speaker
Because that's how we build together, right? I'm a firm believer in that. And I really do think that is the the right direction, both for, certainly for us, but also for the the AI ecosystem, because I think that makes a much more better, brighter future for the kinds of things we want to build.
00:29:36
Speaker
Yeah. And I also, so i mean, I'll finish by saying hiring people's great. Employment is a good thing. And people's value can never be underestimated just because we have technology that can take more of human activities and replicate them into pieces of the software.
00:29:54
Speaker
I think it's challenging us as individuals to be a little smarter about how we do our jobs. You know, what where do you get the right to not innovate and go with technology and go with some of the things on offer today. But I mean, what is what is on offer phone in terms of some of these large language models and tools and things getting thrown at us is I'm spending more and more time just enjoying trying them all out. You know, I just, know, CHETGPT is requesting to become my primary search engine. I thought, you know, why not?
00:30:23
Speaker
Yep. Well, look, and and gives you more agency, gives you more superpowers. That's exactly the kind of way we want to be designing these things, right? I hope I keep on working till the day i die doing interesting things.
00:30:36
Speaker
And I would love to have more superpowers to do that. And on that note, I think that's a quote that can use to advertise this
Conclusion and Engagement Invitation
00:30:44
Speaker
show. But Sean White, founder, CEO Intellection, been wonderful having you on today. And I really look forward to sharing this conversation with with our global audience.
00:30:53
Speaker
Thank you, Phil. I've appreciated the invite and i really enjoyed the conversation. Thank you.
00:31:02
Speaker
Thanks for tuning in to From the Horse's Mouth, intrepid conversations with Phil First. Remember to follow Phil on LinkedIn and subscribe and like on YouTube, Apple Podcasts, Spotify, or your favorite platform for no-nonsense takes on the intricate dance between technology, business, and ideological systems.
00:31:21
Speaker
Got something to add to the discussion? Let's have it. Drop us a line at fromthehorsesmouth at hfsresearch.com or connect with Phil on LinkedIn.