salimismail: Okay.
Kevin Allen: Bill, if you do see Kent, in the waiting room, let's make sure we let him in.
Kevin Allen: But anyway, we'll let everyone in in a minute's time.
Gill: I'll look for him first, he's not here yet.
salimismail: Yeah, I don't think he's here yet. I see 4 participants. Maybe I'm in the wrong…
Kevin Allen: No, no, no, no, no, yeah, yeah, you know, you are just a participant, so you don't see all the, all the…
Gill: Please Ken, let me add them quickly?
Kevin Allen: all the… all the people in the waiting room and everything, because that just adds complexity to your thing. Hey there, Keynes.
Kevin Allen: Okay, so we… Can't you look confused?
Kent Langley: I'm just still waking up, to be quite honest.
Gill: I was gonna say, and you just had a full-on change, like…
Kent Langley: Yeah, and I did a quick change.
Kevin Allen: Okay, perfect, perfect. I do see, Jill, that there's one or two note-takers still, yeah.
Kevin Allen: So let's just quickly try and remove those, and then we'll… then we'll open up the…
Kent Langley: Do not disturb. Recommended for everyone.
Kent Langley: So we can focus…
Kevin Allen: Okay.
Kent Langley: Does everybody have WhatsApp up, and the show flow?
Kevin Allen: Yes.
salimismail: Yes.
Kevin Allen: So, okay, so I think we can… yeah, we can admit everyone, and… and get…
Gill: Hmm.
Kevin Allen: The show started.
Kevin Allen: Good afternoon, good morning, good evening to everybody who is joining us. Great to, see so many folks on the call today. Good to see some faces that we know, faces that have been around, before. A lot of our folks in our pro tier, good to see you as
Kevin Allen: as well.
Kevin Allen: So, I'm Kevin Allen. If you don't know who I am, I am a Chief Community Officer here at OpenEXO. We do have Salim here with us, and Kent, our two co-founders at OpenEXO. Salim, is, I think, in a small hospit… a small office in a hospital in Miami. Kent's in his office.
Kevin Allen: And, we also have Jill here with us from the team, in the background, who will be, sharing all the documents you need, and, and to make sure that everyone's questions are seen, hopefully we get to see you all. There are quite a few people in the room, so if we can start, if you can just, in the chat.
Kevin Allen: just share where it is you're calling in from today. Always great to see the different places that people are calling in from, and I…
Kevin Allen: I already know by some of the names that we have here that we have people who are on at midnight, or past midnight.
Kevin Allen: So, to those of you who are in, in Singapore and South Korea and Australia.
Kevin Allen: and New Zealand, you know, a big thanks for joining us, but, so, so awesome. I, yeah, we, we have, a ton of folks here coming from, from all over the, all over the world, and that's super, super awesome, so great to have you all. I am going to quickly, throw up a…
Kevin Allen: a poll, and this really is just for us to understand who's in the room. And so, whilst you are, filling that in, and we're letting people, join us today, I know, Salim, you did, want to just share a little bit, maybe, maybe have a bit of a, a bit of a rant, as… as people are filling in the
Kevin Allen: poll before we, jump into, our 10X shift proper today.
salimismail: Sure. Welcome, everybody, to the craziest time to be alive in the history of humanity. As Bruce Willis said in Die Hard, welcome to the party, pal. We… we… I'm watching what's happening in Davos with some… with some incredulity.
salimismail: I'm really glad I'm not there. The… apparently there are 3,000 men with machine guns lining the streets, over there. We recorded a podcast episode yesterday with, the normal crew, Peter, myself, Dave Blunden, and Alex Wisner-Gross, and we were… went through some of what's happening, and it's kind of mind-boggling, and I think Kent will…
salimismail: touch on some of that and give us a real-time view on it. We are predicting, instead of, like, classic Moore's Law, 18-month doubling every…
salimismail: price performance doubling over 18 months for computation. We think we're going to see a 40X
salimismail: multiplier and AI this year, which is unbelievable and quite insane. So we'll talk a little bit about that. I'm actually in Florida at a convention of about 11 hospitals called the Golosano
salimismail: Children's Hospital. Tom Golisano is the founder of Paychex, and he's giving a huge amount of his wealth to children's hospitals.
salimismail: And so we're kind of working with them and giving them guidance. The thesis we're showing… saying to them is, look, you're helping 1,000 kids. In a year or two, with all the technology capability, you should be able to deal with 10,000 kids and support that number.
salimismail: a 10x number, and how would you think about doing that? So, it's a pretty interesting conversation. Their eyebrows are like, what? How would we do that? Because, you know, talk about immune systems. In organizations, healthcare has the
salimismail: I think the third worst immune system we've come across, academia being the second worst, and religion being the absolute worst. So, just some updates and thoughts from my side. Happy to discuss more, go into questions when the time is right, but back to you, Kevin.
Kevin Allen: Awesome, thanks, thanks so much, Salem, and thank you to everybody who's filling out this opening poll. I see about half of the people on the call have gone through most of the questions, so I'm gonna keep that open for a while, and let you complete that so that I don't stop you halfway, but I also wanted to just share that
Kevin Allen: You know, ultimately, here at OpenEXO, our main goal is building exponential organizations.
Kevin Allen: And by doing that, really create… helping, you know,
Kevin Allen: Pretty much all organizations out there to,
Kevin Allen: you know, run in a more exponential way, you know, really drive a purposeful agenda, but one that allows you to essentially 10X what you are doing. And so, for today, the aim is really to give you as much value as possible. At OpenExO, we like to really drive a ton of value. We have
Kevin Allen: quite a lot out there, whether it's, on our LinkedIn or Salim's LinkedIn. We will be putting out quite a lot more video content this year, is our, is our plan. And most of that content will be out there for you to watch.
Kevin Allen: And Kent is gonna take you through, very practically, looking at the AI and, algorithms attributes.
Kevin Allen: Which is gonna be really fascinating. It's gonna be pretty fast, and so,
Kevin Allen: if you do have questions, put those in the chat. We may not stop for the questions, but we'll really look to try and answer those, even if it is after the session. And,
Kevin Allen: as we go through the session, one thing which… which we do offer to new folks is to connect with us in a 20-minute call, after, after the session. And so, during the session today, we will be sharing that link where you can, set up a time, that works for you, so that,
Kevin Allen: Yeah, so that we can…
Kevin Allen: We can help you, on… on this journey, really, to… to, become more exponential, and it really is a journey. And so… so with that,
Kevin Allen: I want to just, just see in the chat if, if people are, are really good to go, maybe you can, just type there in the chat, GTG, that we're good to go,
Kevin Allen: I can see that quite a lot of people have… have completed the poll. It's good to see we have a mix of, you know, business leaders and business owners and solopreneurs here, as well as folks who are working in innovation.
Kevin Allen: And really good to also see many people saying, hey, I have an exponential mindset. Although, yeah, there's some… some people are saying, no, I think my mindset's still linear, so, the aim here today is to… is to really help you to… to understand, what it means to, to have that… that exponential mindset. So, awesome, awesome, great to see people saying, hey, we're good to go, we're good to go, and so…
Kevin Allen: With that, I'll, hand over to Kent, who, will,
Kevin Allen: share a little bit, and then, hand over to Selim. So, Kent, over to you.
Kent Langley: First, we unmute. Got it. I actually did it. So there we go.
Kent Langley: Hi everyone, it's so great to have you all here. We have a good number of people on the call today, and this is just a little preview of what we're going to get into.
Kent Langley: Content creation is something that sort of dogs all of us. We all need to be… if we're building an EXO, we need to be making content. And, quite frankly, it can be incredibly time-consuming, it can be difficult, you can get writer's block, there's all kinds of things.
Kent Langley: And over the years, I've developed a whole suite of processes and tools, and I've taken those all and…
Kent Langley: brought them down into something I'm calling a content engine, and so you can think of it today as an EXO content engine, or an EXO builders content engine.
Kent Langley: And we use it at OpenXO, Kevin, you know, and Jillian, they're both on the call. They use these tools in their own adaptations of the flow you'll learn today.
Kent Langley: And… Really importantly, you don't want to be creating what
Kent Langley: A term I really dislike, people call AI slop, right? That is completely avoidable. You can use AI and produce beautiful content, beautiful writing, beautiful…
Kent Langley: pictures and images and video and cases, and you can do it so fast. And so, what Kevin was referring to earlier is, I'm going to be going through my process.
Kent Langley: with an overview. There's a flow chart in your book that will give you kind of a high-level look. We'll go through it step by step by step, and I'll share a case study with you. That's the AI and algorithms part that we're here for today, because
Kent Langley: showing how we do this in content is the gateway to how you can do it for your whole business. And it's… it's really exciting. I…
Kent Langley: I just, in the last 4 weeks, with the release of Opus 4.5, GPT 5.2, what's going on with Grok 4.1,
Kent Langley: Clawed skills, clawed co-work. It is…
Kent Langley: just off the charts. So you're gonna see a lot of that today. And I hope you, enjoy that. I absolutely encourage you to put questions in the chat.
Kent Langley: But before we get into all that, before we dive deep into AI algorithms in the context of content, using and showing a bunch of different ways, methods, and techniques, and some outcomes, Saleem's gonna tell us a little bit about why.
Kent Langley: you need to be in EXO, and why AI and algorithms and content today within it is just one of nine, one of 10 attributes, plus your MTV. So, Celine, back to you, and when you're done, send it back over to me, and we'll make some content today.
Kent Langley: Selling…
salimismail: Very cool. Can you guys hear me? Because my internet is a bit flaky.
Kent Langley: Yeah, we're… you're back, we hear you. You're a little jumpy on the bid, so we'll see how it goes.
salimismail: Alright.
Kevin Allen: Nope.
salimismail: Let me see, I'll just do a quick test. 1, 2, 3, yes, no?
Kevin Allen: Yep.
Kevin Allen: We got you, Celine.
salimismail: So, if I blip out, just let me know, and I'll try and connect in another way via my cell phone or something. So, you know, the… we wrote this book back in 2014, as a forward-looking guide for
salimismail: the… how do you organize for today's world? And we saw that for the first time in history, we were seeing a capability, a new breed of organization, where people were scaling the organization structure as fast as one could scale technology. And we'd never seen that before. And as technology scales faster and faster, the metabolism of our organizations also needs to keep pace.
salimismail: Jack Welch, in his year 2000 GE annual report, said, the minute the metabolism of your company is slower than the outside world, you're dead. The only question is when. You could argue today that the metabolism of almost every company in the world is slower than the outside world.
salimismail: That's a kind of a jaw-dropping insight.
salimismail: And what we do when you run the EXO model is actually radically increase the metabolism of your organization and turns it from an outside-in organization.
salimismail: to an inside-out organization. So you have a big purpose that's trying to achieve huge things. You have a community that you work with to scale your capability. You have very little ownership of your own assets. You try as little as possible to have a huge chunk of full-time staff, etc, etc. Many of you are familiar with the model. We have advised probably
salimismail: 200 of the Fortune 500, right up at CEO level, and we work with people to solve what we call the immune system problem. If you try anything disruptive in a big company, the immune system attacks you.
salimismail: Right? And this is why big companies have difficulty innovating, and how do you navigate that is a huge challenge, because today, disruptive innovation is the high-order bit.
salimismail: And so that's not a non-trivial thing to be able to do. Ken's showing you the model there with five externalities on the right that allow you to keep a small feature footprint, scale very quickly. And on the left, you see 5 internal mechanisms that allow you to manage the control framework and drive culture.
salimismail: Lean startup thinking, decentralized organizations, etc.
salimismail: Over the decade, almost decade and a half now that we've been using this model, it has held up unbelievably well, with a little bit increased emphasis on various attributes over the years.
salimismail: Obviously, the dominant one today is AI and algorithms on the right-hand side, and we'll be spending a good chunk of time today getting you up to speed. I want to, if I could share my screen for one second, let me see if I can do this. I want to show you something that we talked about on the podcast over the last couple of days.
salimismail: This is, The… a…
salimismail: I think you can see that, hold on, there you go. Can you guys see my screen? Yeah.
Kent Langley: Yeah.
salimismail: So, these are the code generation startups that have been all the rage, lovable.
salimismail: Replit, etc, that look like they may get completely steamrolled by Claude code.
salimismail: Okay? And the, these companies are less than a year old in some cases, raised hundreds of millions of dollars, and they're out of date already.
salimismail: This is, like, unreal to see how fast this is going. So this is in the… just in this very edge of the bleeding edge of AI, but then look over here.
salimismail: And you see, these are some of the companies that are being decimated by what we think will happen with AI. And there are some fairly notable, radically interesting new companies there. Webflow, HubSpot, Slack, and many of us use these tools.
salimismail: And it looks like a lot of these will be under severe threat, okay? So today, the only hope you have is to have a big purpose, build a community around that purpose, and then very radically accelerate the use of tools to keep yourself on the cutting edge.
salimismail: And Mikal Monit, one of our community members, made a point a few months ago and surfaced an article
salimismail: that the… once you achieve product-market fit, it used to be that you were kind of safe as a company. Now, the new tools are actually decimating the product-market fit of legacy companies, and really taking them out. So, we think what's going to happen now is that you'll have your standard company, and you'll be building an AI-native
salimismail: A digital twin.
salimismail: on the side, and over time, that AI-native digital twin will be the real mothership, and you'll slowly deprecate the old, and that is being built, that needs to be built as an EXO. So those are some of the high-level kind of observations we're seeing. We work, as you may have heard of, we work with a lot of governments. We're advising the government of the Ukraine on how to rebuild their country using the EXO methodology.
salimismail: One of the biggest.
salimismail: consulting firms in the world and accounting firms in the world is using EXO to transform itself from the bottom up.
salimismail: And so I'm doing workshops with their senior leadership, etc. So it's an interesting time. Kevin coined this phrase, the decade of the EXO, and we think we're kind of
salimismail: right now in the middle of it. So, those are quick, kind of, broad observations. Let me pass it back to you folks, and we can get into Q&A or discussion as we move ahead in this agenda.
Kent Langley: Okay.
Kent Langley: I'll take that. The…
Kent Langley: thing… now… now that you've gotten a little bit of an introduction from Salim about what it sort of means to be an IXO, why we want to be an IXO,
Kent Langley: what are you thinking? Just put something in the chat, like, what's your reason, for wanting to be in EXO? That's what I'd like to hear, if anybody could just sort of drop that into the chat. Obviously, you can do questions.
Kent Langley: One quick question, we should take, Celine, from Perti. Would you elaborate a little bit on what AI Native Digital Twin means, and what form it could take?
salimismail: Yeah, I think what we're seeing there, is we're seeing the rise of, almost like an enterprise operating system that's AI native.
salimismail: where you take your data and your organization, and you put a layer on top of it, and enterprise AI, very lightweight, and then you build use cases, almost like apps on that, and you essentially automate all of your workflows and business use cases using this new model with an AI-centric
salimismail: foundation.
salimismail: And when you do that, it gives you extreme opportunity and flexibility to rebuild your entire functional stack. Now, today, what's happening is people are automating certain roles, content management, customer service, accounting, legal.
salimismail: And you're basically replacing what the human being was doing. I don't think this takes advantage of what's possible with AI. Kent will cover more of this, because I call this radio over TV. When we first created television, we took radio announcers who used to read scripts in front of mics, and we put them in front of a screen. And they read the same scripts, but instead of in front of a screen. And so you're like, well, that doesn't take advantage of the medium at all.
salimismail: Until we develop plots and sitcoms and drama series and etc.
salimismail: We then started taking more advantage of it. So now we're… this initial wave of AI was basically automating spin…
salimismail: -Oh. Then we'll… let's say you automate some workflow. Well, over time, what'll happen is the AI will automate that workflow for you as it gets more sophisticated and understands that. So, you will see organizations being rebuilt
salimismail: with an AI-centric foundation, and then everything else will layer on top of that. So that's the quick answer there. Aqua asked a pretty typically detailed question. Aqua, I remember you from the Meeting of the Life session. Very interesting, list that you have there. But let's talk about consciousness and some of the other stuff separately.
Kent Langley: Yeah, and Saleem, a number of people have dropped their reasons for wanting to be an EXO in the chat. You might want to look through some of those.
salimismail: Yes. I mean.
Kent Langley: Picks them out, yeah.
salimismail: so, Gary, sustained relevance as a human, right? That's pretty huge. flexi-skilling in the age of AI, from, from, Ram, right? Very powerful. James is saying you're using AI to help
salimismail: people leaving military service and have workforce skills, okay? Hugely important in today's world.
salimismail: build relevancy and adaptability into organization culture and attributes from Charles. This goes back to the comment I made about metabolism. If the metabolism of your organization is not moving very quickly, and the umbrella framing is all of our organizations have been optimized
salimismail: In classic organizational design for two things.
salimismail: Efficiency and predictability.
salimismail: Every single workflow
salimismail: KPI was around delivering predictability and delivering efficiency. But today, you need to be architected for agility, flexibility, adaptability, and speed, under the aegis of the MTP that gives you that guidance as to how one should be doing.
salimismail: what purpose you're trying to achieve. So, very powerful, but good comments, here.
Kent Langley: Yeah, these are fantastic. Thank you all for sharing that. And one of my favorites that I see in there right now, which feeds in really well to what we're going to do today, is Joel Strange. I am very interested in utilizing technology investments
Kent Langley: to unleash my uniquely blended skill sets to assist organizations in migrating from linear to exponential as first movers in their industry to ideally reach GOAT status, right? So you should reach out to Kevin, definitely book, because we need to talk to you. If you're not doing some stuff already, there's a load of stuff that we can help you do that. I love that one. That's Saleem. I mean, that's, in a nutshell, what we've been doing for a decade in building EXOs with people, so…
Kent Langley: So that one's great.
salimismail: since…
Kent Langley: Well, that's a good…
salimismail: Accident, not an accident, we're both bald, by the way.
Kent Langley: Yeah, I mean, I had more… girls had more hair when we started, yeah. Yeah, totally. So, yeah, that's a… yeah, that's exponential hair loss due to exponential organizations. Awesome! So, the,
Kent Langley: We're gonna start to jump in. Now, the…
Kent Langley: next bit is to take a look… just… I just want to get some orientation here on where we are, and you all have a workbook, and these workbooks are provided to help you follow along. They're provided to give you your next steps when you leave, as well, because you… you… we want you to continue this work. We estimate that the typical 10X shift attendee can have two to four
Kent Langley: weeks of work to do when they leave. And this workbook will be your guide. If you have access, recordings will be your guide, afterwards. And it's
Kent Langley: critical that today is just not sort of a flash in the pan, you get inspired, then don't do something. So every single thing from this point on in this is about helping you do something, and
Kent Langley: The part that we're going to be focusing on the most today, there are actually two primary parts we'll focus on today. One is here, algorithms. We'll be actually working inside the AI and algorithms attribute.
Kent Langley: again, as I mentioned earlier, on content management, and then as a special bonus for everyone, because it's just so popular when we do it, we're going to be doing a guided MTP
Kent Langley: and kind of a teardown or analysis. So, if you have an MTP, an MTP in process, and you think, maybe that's not quite it, or I just don't have one at all.
Kent Langley: be thinking, I'd like to volunteer and get picked on a little bit by Kent and Saleem, because we would love to help you advance your MT, because showing everyone how to do that is really powerful. Those are our two primary goals today, that we want to achieve. And again, please just follow along in the workbook.
Kent Langley: Don't stress too much if you don't get all the notes or get everything. Kevin and the team and Jillian will have everything tidied up for us so that you can grab stuff, get the swiped files, everything that's necessary, okay?
Kent Langley: So that's great. The, the next bit is just to talk briefly about the algorithms attribute itself.
Kent Langley: And we have the… Little… Let's see, I want to go over here, and… We're going to talk
Kent Langley: Do I want to do this part first? Yeah, I suppose I do. I want to talk.
salimismail: Let me say…
Kent Langley: Go ahead, please.
salimismail: let me say one thing. Every week, we put out a newsletter.
salimismail: And if you want to make sure you get that, just type newsletter into the chat, we'll make sure we kind of put you up to date. We kind of put this… I talked to Peter Diamandis a couple of days ago, and he goes, I read your newsletter every… every time it comes out. It's his way of keeping up to date with our world. Because in his world, we're talking mostly about the technology side, but how you organize and react and adapt
salimismail: Aptitude is really, really powerful.
salimismail: We now have over 40,000 people in the global community, so very powerful. So, please put a newsletter in if you want to kind of be part of that, okay? Sorry, back to you, Ken.
Kent Langley: No, no worries, thank you for that. You know, it's funny, it's like, Peter's like, I read your newsletters, and he's like, I watch your podcast, Peter. Can I be in your newsletter? Can I be… yeah, it's like, kind of this whole giant bromance thing you guys have going on. But I love it. It's really… I totally agree.
salimismail: I'll tell you what… I'll tell you what blew my mind. We had, as the first three guests on the podcast this last few weeks, Ray Kurzweil, Elon Musk, Tony Robbins, okay? And the feedback we got was.
salimismail: Yeah, those guys are great, but four of you are better on your own. We learn more from just the four of you than having some high-level guest, and we're like, holy crap! So…
Kent Langley: That's nice, yeah. Awesome, man, that's really good.
salimismail: But… but no pressure.
Kent Langley: Alright. Alright, so we're gonna get right into it,
Kent Langley: I got a question. How many of you
Kent Langley: posted to X, or LinkedIn, or Instagram, or your own newsletter, or a blog post this week. Just give me a 1 if yes, a 2 if no, in the chat. You did that this week. That means Monday through… it's been 3 days. So 1s, I see a lot of ones, I see a lot of… I see a few twos.
Kent Langley: So 1s are yes, twos are no.
Kent Langley: Okay, I don't know exactly what the spread is on that, Kev. Did you… did you get that by chance?
Kevin Allen: Yeah, it's… it's 65% saying yes, so…
Kent Langley: Okay, awesome.
Kevin Allen: Two-thirds. Two-thirds. Right now? Yes.
Kent Langley: Okay, now let's do it again. How many of you did all of those?
Kent Langley: One if yes, two if no.
Kent Langley: Yeah, that's… so what we're seeing here is a flip, right?
Kevin Allen: This is horrible. Right now, 6% said yes, they did all of them.
Kent Langley: Right, right. Now, no, look, the reality… Yeah, the reality is most people don't need to do all of them, but we live in a multimedia, multi-channel world, and it is crucial that people be able to
Kent Langley: create and repurpose and republish content again and again, and then drive that all back to a place where they can capture leads. Because how are you going to grow your EXO if you can't get new business, right? And then you've got to be able to convert those leads. That's not going to be the topic of the day, sales, although we will do some
Kent Langley: 10X shifts that focus more on sales, which is, could be classified in engagement and other areas. And the…
Kent Langley: I think this is gonna look a little blurry, but you have it in your workbook. I don't know why it's blurry, and I can't fix that necessarily right this second. Hang on a second, why is this blurry?
Kent Langley: Apologies.
Kent Langley: Let me just maybe delete.
Kent Langley: Add back?
Kent Langley: No, it's blurry.
Kent Langley: Okay, everybody follow along in your,
Kent Langley: Here, I'm gonna get another copy of that. Excuse me one moment, Kevin, please, pull the curtains. Give me one moment.
Kent Langley: That's just not gonna work if it's blurry.
Kevin Allen: Well, actually, this is… this is probably a good time, and I'll add myself to the spotlight here, just to, let everybody know that, some of you who've been around for a while, may have, joined in one of our meet.openexo.com sessions, our Speed Meet sessions.
Kevin Allen: And we've been… we, at the end of last year, tested these a few times. They're essentially 4-minute long, networking, that… that happens where you are paired with someone, and it is using, essentially, serendipity to, find people. And from next week, we are actually going to be launching that to be running every single week.
Kevin Allen: for our Premium and Pro members, but next week, we are going to be launching that for anybody to join. And so, Jill has put a link in the chat, and we will share this with everybody who joined afterwards, and we'll also share it nearer to the end. But there we go, Kent's actually showing it.
Kevin Allen: And, and if you were signed in, Kent, you would actually see, see, see all the sessions, that, that will be happening, next week. If you click there on view all, yeah. And so, ultimately, we've got sessions set up for, all the different time zones.
Kevin Allen: And so this is just another way that we really want to try and get people to connect, because that's where, you know, you meet that person, and really start driving, your EXO more. So, Kent, hopefully in that time, you fixed the thing.
Kent Langley: I fixed it.
Kevin Allen: Yes.
Elkin Echeverri: Thank you.
Kevin Allen: That was just an ad break.
Elkin Echeverri: Let's say you need.
Kent Langley: Me too.
Elkin Echeverri: In Thailand.
Kent Langley: We can mute if we are not presenting, please.
Elkin Echeverri: Big government doesn't.
Kent Langley: All right, Elkin, we know you misbehave. I haven't seen you in ages. It's great to see you. Always being disrupted. Elkin Echeveri, from Colombia, he runs one of the
Kent Langley: most interesting and innovative of innovation arms in South America, as far as I'm concerned. So, Elkin, it's great to see you. We need to catch up. All right, so here we go. Content Marketing Engine, and really quick.
Kent Langley: Overview. We're gonna go from an idea and a project over to a number of different types of content that generate leads and sales. I've got a little case study I'm going to share with you that I ran last week that has been incredibly successful for that particular business builder.
Kent Langley: And I think it's gonna be a lot of fun. So, we're going to start right here, with the idea, and as I go along, I will turn these green so we can kind of keep up, see, and know where we are.
Kent Langley: when we want to get started creating content, we've got to have something to start with, and so in my case today, I want to start with what we're doing here, right? We're actually…
Kent Langley: talking to, we're talking about using artificial intelligence to build exponential organizations and using content to do it. So, why don't we try this out? You're just going to see me demonstrating using a variety of tools. This isn't about the tools themselves, although there are many.
Kent Langley: There are many ways you can approach, the activities that fill in any one of these boxes, so here we go.
Kent Langley: I'm gonna use a little AI here I've made.
Kent Langley: I want to write about, using artificial intelligence and content to grow my exponential organization
Kent Langley: I'm on the call with Celine Ismael, a group of about 70 other people, Kevin Allen and Jillian, and we are all… we all want to sort of group publish
Kent Langley: a blog post.
Kent Langley: So we'll just go with that. And that's pretty loose, right? The… who knows? I mean, that's not really good, you know, but at least it's an idea. And you can see here that I've put myself into agent mode.
Kent Langley: I'm gonna click send, and under the hood, what's gonna happen is an AI is going to wake up, and that AI is… is programmed to… this is a tool, by the way, that OpenXL uses. I guess, Jill and Kevin, you probably use it almost every day. And they use a version of this. And so now, what we've got here is an AI that's woken up.
Kent Langley: And it is asking to say, hey, thanks for sharing some context, what is it you want to do? Well, I think…
Kent Langley: I'm just gonna take the easy button for a lot of this and take its suggestions. So I'm just gonna say I want to showcase practical ways AI can accelerate growth in exponential organizations. And we're going to let the AI do its thing. Now, as we go along, something I want to emphasize. We're going to be using
Kent Langley: Probably.
Kent Langley: 3 or 4 different frontier models, several agents, a number of skills, templates, resources. There's so much that's going to be going on under the hood here. It's just not even…
Kent Langley: it's not easy, necessarily, to explain the level of what's going on underneath, but you'll see. So, alright, so excellent. The AI's still talking to me, and it knows we don't have enough to write a blog post yet, so it's going to start asking me more questions. So, focusing on practical ways AI can accelerate growth in EXOs.
Kent Langley: Right, with many people. Would you like to emphasize? Yeah, yeah, let's do that. I have a use case I'm going to share with you today. Let's emphasize real-life use cases. I have a case…
Kent Langley: For a landscape architecture, design firm.
Kent Langley: Okay, so, and, you know, it's asking me a bunch more questions. I'm not going to be extremely diligent about how I would normally answer all of these questions, but I don't want to keep us here all day going through the agentic part of this. So…
Kent Langley: Having a real-world case is great. Here's a quick follow-up. Can you share ways… yeah, I can, because we're going to be talking about content today.
Kent Langley: The primary way we're going to do this today is to discuss content generation, repurposing, reuse, republishing to increase the velocity of leads into an organization, to raise sales, and we might get a little bit into how that same AI can influence operations.
Kent Langley: And increase margins.
Kent Langley: Although the margin expansion is a secondary topic of less importance for this post.
Kent Langley: Great. So you can see what's happening here. I had just a really, you know, kind of broad idea of what I want, but the AI is now forcing me to come in, come in, come in. This is something we call context engineering now, and this context engineering, by analogy, is best described as sculpting, not building LEGO.
Kent Langley: creations. So, you walked into the studio of the sculptor, you saw a giant
Kent Langley: Rectangular block of marble sitting there. You're Michelangelo.
Kent Langley: And you see David. But to get David out, you've got to take some stuff away, right? David's in there, but you've got to remove some stuff. And that's the best analogy I know for what we're doing. We're taking the entire marble block of the universe of what LLMs know.
Kent Langley: We're getting to bring it down and down and down through this sort of semi-Socratic process.
Kent Langley: All right, the added clarity is perfect. Do you want the main case study highlighted in… yeah, sure, let's do that.
Kent Langley: Okay?
Kent Langley: Now, what's gonna happen next is once it gets what it wants from me, it's going to actually create another AI. So what is going on? I'm talking to an AI with an AI that's going to create a new AI that's gonna help us write a blog post.
Kent Langley: Okay? So,
Kent Langley: when I proposed doing this with Kevin, I was like, I don't know if people are gonna follow, and he's like, well, it's okay, this is a little bit, like kind of what I say sometimes, which is reading the book backwards. You're gonna see possibilities, okay? So here we go. Featuring a case study is a dedicated section, great, which option best aligns with voice of the readers? Would you like to have a clear narrative moment?
Kent Langley: a thread through.
Kent Langley: Okay, what I'm looking for here is an inspirational piece that helps people see the power of artificial intelligence to scale their exponential organization.
Kent Langley: Okay.
Kent Langley: If anybody's curious, I use an AI called Whisper, Mac Whisper, to talk to the thing, because it lets me talk to anything. It's not… I don't have to depend on some third-party voice to text. It's really powerful. All right, great. Finally, we have a…
Kent Langley: outline. So, given our goals and inputs.
Kent Langley: here's the recommended approach, it's gonna do this, it's gonna start with a brief, it's gonna highlight the firm, it's going to add a section of actionable big picture strategies, weave in shorter industry examples, and end with a motivating call to action. Great. If you confirm, which I'm about to, it'll initialize co-author. Co-Arthur is the other AI. So this AI is going to go wake up another AI, and all I have to do to do that is click this little button over here, which
Kent Langley: It just sends a command in called Proceed, which is a trigger that tells it what to do.
Kent Langley: Alright, so this is what happens when you want to program agents.
Kent Langley: for your own workflows. And I will also say, while we are focusing on content creation, I chose that because everybody needs to do it. This works for lead generation, this works for sales, this works for
Kent Langley: finance. This works for everything that you might need to do. So, co-author has just been created by my AI based on the context we engineered as an expert in exponential organization. Sorry, Sleep.
Kent Langley: You're… you're out. I've got co-author. And it's an AI-powered content strategy and growth acceleration partner that I now have, and it only lives right now.
Kent Langley: It's dynamic. This was created for me right now in context. That's pretty cool.
Kent Langley: No dev team had to be paid more money to do this, and it says it's gonna do it this way, so let's lock it in. Could you provide just a few sentences describing the before and after?
Kent Langley: Firm went from relatively unknown, generating about one lead a quarter, to a well, expanding, awareness and brand awareness on.
Kent Langley: LinkedIn, and through their website, which has…
Kent Langley: Taken their average views from around 40 a post.
Kent Langley: to 2,000.
Kent Langley: Or around 100 to 2,000. So, long story short, it's really increased their brand and their presence in the market, and that's going to be a flywheel effect that helps them drive leads. And it's already…
Kent Langley: They're getting more leads in a day now than they were getting in an entire quarter before.
Kent Langley: We all want that, I think, if we're building businesses.
Kent Langley: Sorry for the wait times, there's really nothing to be done about that.
Kent Langley: All right, so here we go. That's a powerful transformation, and that's what we're all here about. So before AI, you see what it's doing here is reflecting. We all know that in good communications, reflection is a powerful technique, so you might imagine that I programmed that into the AI to reflect.
Kent Langley: Very cool. So, let's confirm two quick things. Now, I'm kind of done answering questions, so write the Draft.
Kent Langley: I'm just gonna tell it, I've had enough, just… just go ahead, you know, write the draft.
Kent Langley: Now, it will do one of two things at this point. It will create an outline and then follow the outline, or it will attempt to just bang out the draft in one big go. I actually kind of hope it does the latter in this case, although if it does the former, that's okay too. We'll end up with a much longer piece.
Kent Langley: And this is the difference in how you make things like…
Kent Langley: reports and books versus how you make blog posts and ex-posts and such. So, here we go. It did good. It did what I wanted. It's done a first-pass draft of the Inspirational Action Focus Group article for Unleashing Exponential Growth, How AI-Powered Content Ignites Your Organization's Future.
Kent Langley: Pretty cool, alright?
Kent Langley: So… Let's see, because Atlanta's a farm story. I don't know what the farm means.
Kent Langley: Firm Farm. So I got a little confused there. That's okay, we're not going to worry about that, because I'm actually going to take this now, and I'm going to shift over to another tool, because we all know that good content needs a hook.
Kent Langley: And so…
Kent Langley: I'm actually… I've created this app called the Hook Scorecard, and I'm going to put into it this entire post, and it's going to start to attempt to help me craft a hook.
Kent Langley: And this is really pretty cool. So there you go. If I knew more information about my ICP, actually, I can put it here, my ideal client persona, again, this is for marketing and sales, let's just say I'm…
Kent Langley: Wanting to convince… Business Builders.
Kent Langley: Could be EXOs, so something like that. Really simple in this case. And we'll wake up this AI. This is the third AI we've interacted with so far, and it's going to use a whole framework that I learned, in another program.
Kent Langley: a marketing program about writing hooks that I took that's four hooks on these 5 things, and this hook should be quite terrible. Permission denied. Okay, that's gonna mess up my entire thing if that doesn't work. Let's try one more time.
Kent Langley: Okay, interesting.
Kent Langley: It's a day of… of fun.
Kent Langley: What the ?
Kent Langley: Same.
Kent Langley: If they have fun technical glitches. Let's try one more time.
Kent Langley: Maybe it just went to sleep on me.
Kent Langley: I'm finding more and more that the…
Kent Langley: places that host these things are setting your resources up so that when you start, it provisions resources for you, but then if you walk away, see, I set this up, like, 2 hours ago, it turned off my instance, and so I just had to re-insantiate the whole thing.
Kent Langley: So, it gave me a 7 out of 15. I expected that, because I just pasted a whole AI-generated draft article in, and it's beating me up pretty good. The hook's generic, it relies on corporate buzzwords, and without specific language. Great. And it's given me a refined version. Your content gets 40 views, maybe 1 lead a quarter, a small firm… so you see what it did there.
Kent Langley: it picked up on everything I fed in as the context, so I like that. I'm gonna add that variation, then I'm gonna take a peek, and I'm gonna…
Kent Langley: how might I change this, me the human, in the loop?
Kent Langley: Your content gets 40 views, maybe generates…
Kent Langley: Maybe generates 1 lead a quarter.
Kent Langley: small… Architecture… Burn.
Kent Langley: used AI to jump to thousands of views and more.
Kent Langley: And more.
Kent Langley: And it's not in one day. In this case, we spent about a week, maybe
Kent Langley: Maybe an hour in the morning, 3 times in a week, so call it 3 hours.
Kent Langley: Okay, I think that's pretty good. So, let's put that there, and let's score this one, and see if we have improved. As we improve, you'll see the scores going up, hopefully, hopefully going up and turning green, and this turning green at the bottom.
Kent Langley: Okay, now I've got a 14 out of 15. For the purposes of this, I am perfectly happy with that. So I'm gonna go ahead and say, got it. I'm gonna send this one down, and this is my final version that I want to use. I'm gonna copy that out.
Kent Langley: And I'm gonna start creating my post, and I'm just gonna use a Google Doc to do this. You've got a hook now. Yay. All right, back over to…
Kent Langley: Clogged, and collected. Alright, so here, I'm going to, again, grab the post.
Kent Langley: And I'm gonna show you…
Kent Langley: I've got another series of tools that I've created. They're a little bit more advanced than the ones I've programmed into Collective, and so we're going to use those. So use the writer skill.
Kent Langley: To complete my blog post.
Kent Langley: Okay, for those of you who don't know, Anthropic created skills as a standard. Google, OpenAI, Anthropic, I think Grok will pick it up soon, have all adopted this. It followed on from their work standardizing MCPs, but in this case, skills are how you embed
Kent Langley: the way you want something done, like an SOP,
Kent Langley: So that the AI can load that up on demand. And so I'm gonna say, there's my hook.
Kent Langley: Right? Which we got from my hook tool, and I'm gonna say, content.
Kent Langley: I'll say post here, and I need to go back and grab that.
Kent Langley: Here, text.
Kent Langley: Now, why would I do this? I would do this because I know that Claude, with Opus 4.5, and the skill I made, is going to take this to the next level. It's also going to combine the output from two tools into a single. Now, I could have just taken the hook, gone back to Collective, and done it there.
Kent Langley: I'm doing this almost as a contrived example to show you other ways.
Kent Langley: I want you to be aware that you have many choices inside any individual box.
Kent Langley: on this diagram, okay? So we're… we went from this box, To making a hook.
Kent Langley: And now, we are working on a blog post that we would normally put on our own website these days, which is, by the way, what I recommend, that you put your base content on your own site, and you're going to see why.
Kent Langley: In just a moment. I skipped over this, so we're not gonna… we're not going to do this today. But this particular person that I made this flow for every single week does a 30-second pitch at a networking event to drive leads through a membership group, and so that's why this short pitch is always first for this user, but we don't need to do that today.
Kent Langley: Alright, so we're gonna go back to Claude, and let's see what we've got. And I want to show you, before we look at the actual output, I want to show you what happened here, it's really cool. So, take a look. First, I'll read the writer's skill. The rider skill is a skill that I've developed over
Kent Langley: couple years, alright, to get it in to the format that Clawb can use now. But what's amazing about skills is that it loaded that skill on demand.
Kent Langley: Okay, and then it read it, and it read all the templates that are based within it to learn how to write a blog post the way I wanted to write a blog post.
Kent Langley: And it says, now that I've got the context, let me craft this. I don't know why it keeps going to the farm, but…
Kent Langley: We'll work on that. So it's going to create the blog post, and then it's going to present the file. Then it's going to tell me what it's done, it's written a blog post, it rewrote it from my draft.
Kent Langley: Used another… it's like, think of the version of co-authored that.
Kent Langley: elective made as version 2. This is kind of version 3, and…
Kent Langley: On the right-hand side, we have the post. So we're actually going to slow down for a second and read a little bit, because I want you to see just how dramatic, of a change we've gone from where I started, which, if you remember, was all the way over here, we…
Kent Langley: started with a half-baked thought, right? And then we started, and we… and we're now at this point.
Kent Langley: So let's just take a moment to read what's up on the screen right now before we proceed.
Kent Langley: Okay, great. Now, first of all, I just gotta fix this farm thing.
Kent Langley: Let's not call it farm.
Kent Langley: I don't know where that came from, it's called Regenerate.
Kent Langley: fix it. So…
Kent Langley: Now, everybody debates with me whether I should be polite with AIs or not. That's a bit terse. I don't actually… you don't actually have to be polite to them, I just try to be plain, is the way I think of it. I don't want to be mean.
Kent Langley: But I just try to be plain. And look what it's done. It's treating my post like code. It's added some lines, it's removed some lines. If I were to click into this, I can see exactly
Kent Langley: what it's adding and removing, and it's updating the draft over here to find all the places where it called the thing farm, and change it, I hope, to regenerate. Yeah, there it goes. And now it's going to present me a new version.
Kent Langley: And?
Kent Langley: It should be good.
Kent Langley: Yeah, there it is. Okay, awesome. So this is really good. So I think we're in a really good position here to use this. And again, I'm not being super discerning today. I normally would stop, I would read very carefully, I would probably edit this, because I'm the person, right? This is going to represent me.
Kent Langley: So I want it to be me by the time it gets out. But again, remember, I've baked me into all the underlying AIs that we're using, and I just happen to know that this one does the very best job of producing final draft output that I'll then need to take.
Kent Langley: To make live. And what would I do with that? Well, I would go to my LinkedIn.
Kent Langley: Actually, in this case, she would go to her LinkedIn, but I'm gonna use mine, because, you know, that's easier. And then I would go here to content editing. Let's get this out of the way.
Kent Langley: postdraft, and I'll just paste it in.
Kent Langley: And, now.
Kent Langley: I'm doing LinkedIn. The actual output for this one, ended up over here on a…
Kent Langley: blog post. So this is what I mean by a blog post on your own website. This is not my website, it's the architect in question. And this is the case study, for a Healdsburg project, right here on her website. This became the
Kent Langley: Again, look at the flow. This becomes the foundational data. This becomes data.
Kent Langley: for all the stuff that you're gonna see come later, one of which I am about to complete.
Kent Langley: Okay, so blog post, we need to go to LinkedIn article. So we have a blog post now.
Kent Langley: That's what this is. And we would put this on our own website. I'm not saying this randomly.
Kent Langley: You need to go back to putting your blog posts on your own website. You need to SEO empower them, you need to have an LLMS.txt file, and a sitemap.xml. Nerdy stuff, not going to show examples of that, but you want AI to find you.
Kent Langley: And this is how you're gonna do it. You need your own content back on your own destination site. Really important tip for you today.
Kent Langley: So, we're gonna take this blog post that we've created, and I'm gonna show you two ways that you can take it and turn it into the next thing. So, I'm gonna start a new session here in the tool we started with, and I'm gonna say, take this blog post and make it a…
Kent Langley: ain't… End.
Kent Langley: post.
Kent Langley: And I'm gonna say this, and I'm gonna put the blog post in there.
Kent Langley: And then I'm gonna click this little button here. These are more AIs.
Kent Langley: So there's 4 more AIs that are available under the hood, under the two, sort of, overseer AIs that we have. And I'm just going to click LinkedIn Post. Now, what is this thing? This AI is created from me having gone to, I think, 5 or 6 different workshops on how to write effective LinkedIn posts.
Kent Langley: And I just took all the best stuff that made… that made sense for me, and I baked that into a…
Kent Langley: an AI, that then helps me write these kinds of posts, right? So I should have not posted my entire blog post into LinkedIn. I'm going to take and put the LinkedIn one here. And now I have a post that, if I was a landscape architect, which I am not, so I am not going to post this on LinkedIn, I could do, and it looks like this, and…
Kent Langley: On the right-hand side, this just gives you a little preview of your LinkedIn post, and you can see that this is what it would look like.
Kent Langley: And if you're doing this for real, and you're a landscape architect, then you actually will want T…
Kent Langley: use M and here, actually.
Kent Langley: Can I show you one? You'll want to do images, right? So I can show you an example from a past post, I think.
Kent Langley: Yeah, like, here's one.
Kent Langley: Here's one I did. So, you can see I drew this on a notepad, and I uploaded it, and this is my LinkedIn post.
Kent Langley: It's not the architect's post, so this is an example of what you would do next, right? So in this draft, I don't have an image to attach to this right now, so I can't, but if I did, I would. And you can see that this tool is telling me this post is too long, so I need to make it a little shorter. That's fine. But this is how you go from
Kent Langley: To review… A loose idea
Kent Langley: Develop your hooks first, it's just like on YouTube, you develop your thumbnails and your titles first, you develop your hooks first for writing, you create your blog post, which becomes your data source, and then you create your LinkedIn post.
Kent Langley: Okay, we did that.
Kent Langley: Now… I also,
Kent Langley: need to post, in this particular flow, the architect in question actually would post on Instagram.
Kent Langley: I'm not doing that today, because I don't actually use Instagram very much, so I'm just gonna pretend and do X. So, then I'll go back over here.
Kent Langley: in this case, to Claude, and I'll say, That's great.
Kent Langley: Now, use the… Writing.
Kent Langley: X. Post to skill.
Kent Langley: And rework that for X.
Kent Langley: I don't know if you're following, but on X right now, it's going through a massive algorithm change.
Kent Langley: And this is the kind of stuff that can throw your content
Kent Langley: operations sideways very quickly, but they published a How to Post on XGuide. So I took the how to post on XGuide, I used Grok, and I asked
Kent Langley: Grok, Super Grok, how everybody else is saying that they're getting success on X. I compiled all that down into, a file. I used that file to build a new Clawed skill. I named that skill.
Kent Langley: writing X post, and now I've just fed it my draft blog post, and I've asked it to output an X post.
Kent Langley: And this is that.
Kent Langley: And if we stop for a second again, if we just slow down and we read a little bit, you'll see.
Kent Langley: The bones are all there, but this is formatted for somebody who's on a phone, scrolling, and whose attention is hard to keep.
Kent Langley: Okay.
Kent Langley: Who would like to generate,
Kent Langley: Well, gosh, this went 10X. So, who would like to generate 10 times more views on all of their content and new leads every day?
Kent Langley: I'm actually jealous of this when it's going so well. So, yeah, so it's really, really good.
Kent Langley: So it tells the story of the firm.
Kent Langley: It talks about what changed, why.
Kent Langley: Posts on X that drive and talk about transformation stories win.
Kent Langley: if you watch YouTube, there's this…
Kent Langley: sort of chateau renovation series called Escape to Rural France. Incredibly popular. The dude has figured out how to monetize YouTube to renovate a chateau in France and make that his life's work.
Kent Langley: it's the same thing, right? You know, it's just… it's unbelievable. So…
Kent Langley: Alright, so see, this is, like, meta, because this is what we're talking about today. We don't want to just post more, necessarily. We want contact… content that attracts attention, builds trust, converts to conversations. Conversations become projects. Projects generate new insights. New insights fuel more content. I didn't even feed it this.
Kent Langley: But it figured it out. That's pretty cool.
Kent Langley: Alright, so now we have generated an X post. I'm not going to go show you how to post on X. I think if you want to post on X, you're good. So…
Kent Langley: But it's totally different today than it was a week ago, so pay attention there. And now, we have come full circle for a content workflow. There are other things that I won't be doing in this one, although, well, I will do one.
Kent Langley: So, okay, I'll say, I don't actually have a skill for this, so I'm gonna just make a guess. Actually, what I'll do is use the LinkedIn
Kent Langley: article skill, and create a draft newsletter for Kevin.
Kent Langley: Right? So, Kevin, I'll be sending you a draft for next week's newsletter about this, and, you know, you can decide if you wanted to send this out. So, it's checking the LinkedIn post skill, which is yet another skill I've created.
Kent Langley: Also, again, you'll remember that I have that skill over here as a tool.
Kent Langley: Okay.
Kent Langley: But this one uses a different foundation model.
Kent Langley: Then Claude. So, this way, I can actually go back and forth very easily if I want to.
Kent Langley: So now, it's creating the newsletter draft for Kevin.
Kent Langley: I don't suspect that I would straight up publish this, but Kevin will take it in, and he would then use it, plus all the same tooling that I've showed you, and he would say, okay, we need to make this a little bit more about being in EXO, because it's more about being a landscape architect at the moment, right? And it's also made notes.
Kent Langley: Engagement boosters, Everything else, and here is the newsletter.
Kent Langley: Okay, how long did that take? I think that's the whole cycle, Kevin.
Kent Langley: That's… that's a week's worth of content that I just did in…
Kent Langley: 20, 30 minutes, I don't know how long I went. Sorry, I got into it.
Kent Langley: I'm gonna stop there, and ask you if there are questions.
salimismail: So, Rob is asking a question, how does this connect into the EXO framework? Rob, the idea behind this is a short… to have this be a short demonstration of how quickly you can use AI to radically change the way you do this. Like, this would have taken hours for anybody
salimismail: in a traditional model, right? And Ken did this in a few minutes. And I think this is what's incredibly impactful. Now, when you can do the same thing across a bunch of these… well, you know, just a quick story here. When we wrote the second edition of the EXO book, three years ago.
salimismail: We… we finished the book, and we had an early glimpse of what was coming with ChatGPT via Imar Mustagh, who's on our advisory board. He was the founder of Stability AI.
salimismail: He gave us an early glimpse. I had to call Peter up and say, Peter, we have to rewrite the whole book, because every attribute changes with generative AI. Because, say, lean startup or experimentation, you can use AI to actually think up the experiments you should be running.
salimismail: And so, AI is becoming kind of a foundational layer in each of these examples, and Kent just went through one of them to show you how you could take a traditional workflow
salimismail: and radically automate it in a very aggressive, but yet very elegant way. So, that's the broader framing around all of this, okay?
Kent Langley: Yeah, and it's a good question, Rob. The reason I started was here was to show you the whole model, and then what we do in the 10X shift is every month.
Kent Langley: We go typically over one or two attributes, and we give real-world examples of how to implement them in your business. So today, I've showed you how to do content creation and breakdown into other content types, which is part of the AI and algorithms attribute, and this interacts with all the others.
Kent Langley: So, what happens is, if you do this, then you're going to build community and crowd. If you build community and crowd.
Kent Langley: Right? Then, you are going to start to…
Kent Langley: want to deploy autonomy to that. You might feed it into your internal social, and then you end up with an entire EXO
Kent Langley: implementation, it started from an experiment, if you will, with AI and algorithms. So what the task will be, leaving today is to design your own content experiment with artificial intelligence that helps you
Kent Langley: In your… your journey, to becoming an EXO, and it fits in with all the other attributes.
Kent Langley: at some point today, this tool will be dropped for you. This is the Experiments tool.
Kent Langley: And so, I'm just basically showing you how… what the output of an experiment I ran for content generating artificial intelligence that helped me accelerate the content process, not just for me, but for many, many entrepreneurs, is. So that's how it fits in. I hope that helps, and sorry for any confusion.
Kent Langley: Do you have a follow-on question? Does that help you?
Kent Langley: Rob?
Kent Langley: Okay.
salimismail: Oh, that helps, thank you. Awesome.
Kent Langley: Very good. We try not to leave… we try to make sure it's a loop. We want everything to close. So, let's see. Okay, we've got another question in. Would you mind explaining if this flow is designed to be automatic? Manual? Oh, great question. It is not designed to be automatic.
Kent Langley: Most of the systems I design are meant to have a human in the loop to amplify the human's capacity, capability, or augment them with new skills. Like, how do I write an X post? I don't even know.
Kent Langley: And now, if you want to automate it, you certainly can, but that comes with another suite of tools, so that then you, would maybe just feed an idea in one side, and then a tool like N8N, or Make, or…
Kent Langley: Any of the many, many tools like it exist today will trigger each of those, but you will lose control
Kent Langley: of it, and you will find that you have a lot of rework on the far end of that for what you get out, and in no way can you trust that to just automatically post for you. That's what people generally tag as AISwap. So I… I have created this in a way that's meant for you to interact with as the person building in EXO.
Kent Langley: Great. Oh, Gary, good question.
salimismail: I think this question.
Kent Langley: What are the advantages?
Kent Langley: Oh, please.
salimismail: I think you should cover Gary, and then also Perti's question, I think, is really important. I struggle with that question.
Kent Langley: Okay, so Gary says, what are the advantages over Notebook LM other than… well, okay, so…
Kent Langley: Okay. Notebook LM is a phenomenal tool. It is incredibly useful. What I didn't do yet was show you the actual final output case study, so let me do that, Gary, as part of answering your question. Alright, so this is what happens when you run that process.
Kent Langley: As that particular landscape architecture firm. I'm just showing you real outputs that worked this week and generated an outcome. So the project in this case was Healdsburg. We used that project output to generate a case study.
Kent Langley: That case study, Gary, is right here, and this is a case study that we made with Notebook LM.
Kent Langley: Okay, so, all of that image there, these slides here, these are all based on having fed it the plant.
Kent Langley: palette. And the designs and all this, I mean, so much stuff went into creating this. And then in a few cases, we replaced Notebook LM slides with our own slides, and so on and so forth. So this is how I integrated Notebook LM into the case study part of the process.
Kent Langley: For this particular use case, and the outcome here was that the first post this person ever made got 3 impressions. The second post they ever made before we implemented the flow that you saw today got 111 impressions. The third post
Kent Langley: with the full linking back to the blog post, not only now has generated over 2,500 impressions, I think, but it has also generated new leads.
Kent Langley: And we have a whole other suite of AIs that we use to process leads as intake and turn into proposals. We're… we can get the entire lead processing and proposal process done in under a half an hour now.
Kent Langley: This was days of work before, okay? So it's all interrelated. If you want to be an EXO, you need to learn how to do these things. So this is… this is what we're doing there. So,
Kent Langley: Also, with your question, Gary, the… Notebook LM is, like.
Kent Langley: nothing about notebook… one notebook LM notebook is connected to the other notebook LM notebook.
Kent Langley: As you use tools like Claude, in particular, it has memory, and it learns, and it learns, and it learns, and it starts to tell… it starts to tell you what you think you want.
Kent Langley: And notebook element can't do that, because each notebook's discrete. But man, when I need to generate presentations, infographics, here, look, this is another,
Kent Langley: Another the outcomes, again, following through. So we had the case study that was made with Notebook LM, and then human augmentation. This is the actual, blog post on the website. This is how discovery on LinkedIn exploded as a result of the cross work.
Kent Langley: This is the actual LinkedIn post that was made, and then, after the post got a significant amount of engagement, we go back into LinkedIn, and we post a comment to ourself, leading them to the website. That generated new leads.
Kent Langley: And then those leads?
Kent Langley: hey, if, you know, if we get the sale, we'll generate new sales. It has actually already generated new sales, but not for the lead that was generated from this cycle this week. So, really cool. So that shows how it all comes together and includes Notebook LM. So, Notebook LM isn't…
Kent Langley: It's not apples to apples, it's just use the right tool for the right job. Okay, so, next one.
Kevin Allen: was Bertie's…
Kent Langley: Yeah.
Kevin Allen: How do you decide if you use,
Kevin Allen: purpose-specific or use-case-specific AI tools versus LLMs like Claude, and when do you do the same Thing with them.
Kent Langley: Yeah, this is a really great question, and everybody struggles with this.
Kent Langley: So there are no silver bullet…
Kent Langley: tools. Zero. You will end up using a wide variety of tools. I've just demonstrated to you using Claude.
Kent Langley: ChatGPT, various models, not even… what you saw with Collective actually used 3 different ChatGPT models. I used only Opus 4.5 on Claude, I used
Kent Langley: Notebook LN, but to feed Notebook LM, I actually used Gemini and NanoBanana Pro to seed it with the content that was necessary to create a
Kent Langley: output of the quality that you see here, which gave me about 80% of the final presentation in this case. So, the way that I choose is based on which tool is best at the other thing. So, I…
Kent Langley: I did too,
Kent Langley: I wonder if I can show you this really quick. Where did I put this? Hang on.
Kent Langley: Yeah, no, I don't know where that is, so I don't want to randomly poke around. The,
Kent Langley: I did two, because I wasn't sure if Claude… I actually used Claude code.
Kent Langley: To generate a presentation.
Kent Langley: or Notebook LM would do a better job.
Kent Langley: Because I keep hearing that Claude Cody's gotten so much better, so much better, so much better, if you use Opus 4.5. So I did it. I ran the entire presentation generation process through both of them. I don't have handy the one that I generated with Claude, but it was…
Kent Langley: It was kind of like a plain white napkin with some text on it.
Kent Langley: And this was a visually rich, powerful.
Kent Langley: I mean, this is a one-shot slide. We did nothing for that. And to pick that up from the plant pallet.
Kent Langley: And… and made just beautiful slides.
Kent Langley: clock codes looked like what a programmer would write. So… so, you know, again, I think, Pirate, you've got to practice with all the different tools to know what they're best at in your context. What works for a landscape architect, what works for me, they're different.
Kent Langley: And the tool mix is different. But under no circumstances should you confine yourself to any one tool, because they change every single day. And you may… and you need your workflow to be able to adapt, which is why I create flows like this.
Kent Langley: Because I used, like I said, I used, Notebook LM to generate the case study presentation, but I used
Kent Langley: flawed with my writer skills to write the case study blog post. Then I fed that into the Notebook LM. So you see.
Kent Langley: There is just no one tool, and there never will be.
Kent Langley: Didn't quote me on that. It's just not gonna happen.
Kent Langley: They're trained different, they have different data source sets, they're, like, different people.
Kent Langley: So you hire them for different roles. Hope that helps.
Kent Langley: Let's see…
Kent Langley: Joe says, when you say we should be writing for our personal blog, does that mean literally for a business we own, a book we've written? Yes, it does. It means whatever your… I make an assumption here in these that everybody's building an EXO that's coming to this, or might want to, and probably either has their own business, or they're a coach or consultant helping other people build their businesses. So that's what I mean when I… I say that.
Kent Langley: Joe. And the reason for that is because since we've moved from sort of a Google-centric search world
Kent Langley: With paid ads, we've… we've moved now
Kent Langley: Well, it might swing back. We'll see what this experiment OpenAI is doing, is going to do to the market.
Kent Langley: But now, you've got these LLMs that are out there just looking for every bit of information they can grab.
Kent Langley: you want to be indexed, right? Go to ChatGPT and ask it, who is Saleem Ismail? Ask it, who is Kent Langley.
Kent Langley: And it will lead you to our websites, it will lead you to our content, it will… it will tell you about our speaking, it will do all of that stuff. And that's what you… you need. And you won't get that if you don't have any content on your site. If it's nothing but a CTA landing page, the LLM will ignore you.
Kent Langley: That's what I mean.
Kent Langley: Okay?
Kent Langley: Alright, let's see…
Kent Langley: James, I almost made a page of notes. Thank you. All right, and yeah, so take those notes and design an experiment using the experimentation tool.
Kent Langley: Kevin, I'll rely on you to take us into the MTP section, since I'm not watching the clock perfectly. Let me keep going on looking for any questions. Luciano says…
Kent Langley: Oh, that's a great, a great question and comment, Luciano. You know, isn't it possible that eventually our content gets boring, loses engagement? I think it's quite the opposite. This opens up the palette for what you have time and incentive to talk about massively, and you can bring in
Kent Langley: what I like to do is I just… I book a call, like, with somebody I… I want to talk to. So I'll book a call with Kevin, or Saleem, or anybody, and we'll just riff. I'll capture all that in Granola, and then I'll feed that to… I use Collective, and I have a tool that does text analysis. I'll take that text analysis.
Kent Langley: And it'll have what are called propositions in it. Each of those propositions, and it'll also have claims in it, each of those can become a new topic.
Kent Langley: And it's really fresh, because I just had the conversation with somebody, or I have a client that's giving me input, or we have an EXO member that asks a question. I could take this entire series of questions that have come up in the chat today and produce 50 articles
Kent Langley: In the next hour. And it is highly varied, it's not boring, and it's not slob, because it's based on real-world needs.
Kent Langley: Mark Lynn asked about the experimentation tool. Yes, we've posted that for you, Mark. I hope you see that there.
Kent Langley: And then Joel Strange is saying, my preference is to automate up to 95%, leaving the last 5%. Absolutely. If that does it for you, do it.
Kent Langley: That's a good move. It is not my preference. I prefer to be in the loop more, automating probably about 80% of the time I spend, not necessarily the thing that gets created. It's slightly different. I think we probably end up with a similar output in terms of overall speed, but it does require my oversight.
Kent Langley: Let's see… RAM.
Kent Langley: Oh, interesting one. Celine, maybe you jump in on this one, too. Ram says, as we move from a LEGO block approach, which I think of as engineering versus art or sculpting, to a content sculpting approach, do we hit the paradox of abundance? And how do we engineer context
Kent Langley: To ensure our sculpting remains an asset rather than a liability in an oversaturated market.
Kent Langley: I'll answer this, and then, Celine, maybe you want to weigh on. This is a very interesting question. Sure. The…
Kent Langley: somebody asked me if I've got two startups, and they both make a widget.
Kent Langley: and they both do it pretty well, how do I decide which one to invest in?
Kent Langley: was 2 different startups with two different founders, or two different EXOs with two different EXO builders.
Kent Langley: I'm gonna invest in the one that has the best EXO builder, or the best founder. I'm gonna invest in the person.
Kent Langley: You're the spark, you're the secret, you're the difference.
Kent Langley: In all of this, because you're the one bringing the context as your experience, your knowledge, your wisdom. And…
Kent Langley: I guess if that's… Repetitive and boring.
Kent Langley: you want to think, you know, okay, well, how can I improve that? Like, what can I do to grow?
Kent Langley: Sign.
salimismail: Yeah, I'm not quite sure what the difference is between a LEGO block or sculpting. I'm a little lost. Oh, sure. Oh, sure.
Kent Langley: Oh, sure. But when you… when you build a… say you want to build the LEGO Death Star, it's one brick at a time.
Kent Langley: When you want to sculpt Michelangelo as David, you're removing more…
salimismail: Sculpting versus base… base relief.
Kent Langley: Yeah.
Kent Langley: And so, so that…
salimismail: And this is in the context of… this is in the context of content generation?
Kent Langley: Content engineering.
salimismail: Oh, content engineer, okay.
Kent Langley: Yeah, one is reductive in scope. You start with everything, and you reduce down. The other is additive in scope. You add a brick, you add a brick, you add a brick. The reductive method is better for narrowing the total universe of possibilities.
Kent Langley: Remember, when you speak to an LLM and it speaks back to you, it's making a prediction about what it thinks you want.
Kent Langley: This is important. So, you need to narrow the scope of knowledge to narrow the number… the scope of prediction. There's a… there's a technique called verbalized sampling.
Kent Langley: I've made,
Kent Langley: a newsletter post about this. I'll go dig it up and put it in the chat. Verbalized sampling forces the LLM to tell you more of its
Kent Langley: probabilistic outputs.
Kent Langley: In its output to you, so that you're not getting locked into a single prediction.
Kent Langley: And oftentimes, the most…
Kent Langley: The one that you like the best won't be the one that the LLM liked the best, so if you trick it, it's… yeah, verbalized sampling incredibly powerful. I've got a… there's a prompt template that I can share.
Kent Langley: Let me find that.
Kent Langley: So, I don't know if that helps, but yeah. Yeah, so let's keep going, yeah, oh, Gary,
Kent Langley: you know, I use Granola a lot to capture, meetings, and Granola actually connects to Notion, and so I copy some notes I want to, I copy them down into Notion, and I have Notion connected to Claw via MCP,
Kent Langley: So I can ask Claude to go check my notes about a meeting, and then look up in our CRM if I've had any interactions with that person before.
Kent Langley: That's beyond the scope of today's call, but that's an incredibly powerful use case.
Kent Langley: Alright?
Kent Langley: Let's keep going. So where are we, Kev?
Kevin Allen: So, it is time to… to move on to… to chat about MTP, and, and so, Selim, I, over to you to… to get us started on there. But all the questions that you still have.
Kevin Allen: around the, the, you know, AI and algorithms. Please do keep those, share those in the chat, and, so, yeah, Salim, Salim will be sharing a bit about, MTP, and we'll then dive into, into, asking, folks, about your MTPs.
Kevin Allen: And then… and then have some time for more Q&A at the end. So, Selim, over to you.
salimismail: Sure. You know, one of the attributes that we identified very early on when we scanned all the 150 unicorns, and then teased out the EXO model, was the massive transformative purpose.
salimismail: We coined that phrase, I think, in late 2012, and then we saw over the next few years the rise of purpose-driven organizations and people going on about all that stuff. We found that every one of the
salimismail: EXO's had one. Uber is everybody's private driver. In the context of, Kids Hospital, where I'm sitting now, one of our favorite ever MTPs is the Boston Children's Hospital, whose MTP is, until every child is well.
salimismail: And that just, like, how does that not get you, like, super excited, right? Just incredible framing of… and know with an MTP, you may never end… get to the endpoint. It's a canvas on which you paint moonshots. So, Google has organized the world's information.
salimismail: well, it's going to take a long time to organize the world's information, but along the way, they provide tools, etc. So it's a declarative statement and a call to action as to what problem you want to see solved, right? So Waze is solve traffic, Uber is everybody should have a private driver, etc, etc.
salimismail: We've created, an MTP Genie, which is an AI where we've been training it with thousands of MTPs, and so if you… Kent will take us through that in a second. My personal MTP is to transform civilization, a niche project. Why? Because I find myself on the edge of organizational design and kind of…
salimismail: philosophical thinking around that, plus the cutting edge of technology. And it was actually Tony Robbins who called me out on that, so you gotta do something with that. Don't roll back.
salimismail: I'm still cursing him for that one. And so, when you have an MTP, it gives you a very clear heuristic as to what the organization is about. Very important in times of hypergrowth.
salimismail: At the highest level, I remember Paul Pullman, who's the CEO of Unilever, had me come and talk to his top 200 executives. They then ordered every brand in Unilever to take on an MTP.
salimismail: and be more purpose-driven. And 5 years later, the five most profitable brands were the ones that had adopted it the most. So you can see the model kind of start to bite over time. And so the, the importance of the MTP, which we cover at every single one of these ERP workshops, cannot be understated. It should be formed by the, kind of, the founders, whoever's closest to that layer.
salimismail: And kind of really clearly articulate what problem you want to solve as an organization.
salimismail: That way, when you're trying to evaluate where you place your bets, you can say, should I put my chips on this project or this project? Whichever one better satisfies the MTP is where you place your bets. It also turns the organization from conversation in the organization from inside politics to external delivery.
salimismail: And so there's some very powerful things. And the final point I'll make is we're starting to now see a complete alignment of hiring. So, if you're at SpaceX and your mission is to MTP is to get to Mars.
salimismail: you're gonna hire people that have an MTP, a personal MTP, aligned up with getting humanity into space, right? And then you know there's a deep connection between that, and high job satisfaction because of that alignment. I think the statistic I heard
salimismail: is that in the corporate world, 79% of employees are unhappy with their work, so that is not going to sustain well over time. So, I'm going to pause there. Kent, I think you have some exercises and a couple of comments also to make.
Kent Langley: Yeah, so, you know, going back to the… well… I mean, Celine.
Kent Langley: MTP was first elucidated in the first book back in 2014, and I think since then, it's no stretch to say we've helped tens of thousands of people, one way or another, maybe hundreds, I don't even know, right? I'm not sure we have a way to really track it, but it's…
Kent Langley: I mean, even just directly. And this is one of the more fun things, I think, that people get to do. And so, we're going to be going over and using a tool called the MTP Genie. This is a GPT. This is just yet another
Kent Langley: Type of AI, and this one was made quite some time ago now. I'd have to go back and check when we first made it, but I recently updated it to use more models.
Kent Langley: And, the newer models. And,
Kent Langley: the way I'm gonna do this is… is by…
Kent Langley: Asking, who in this room, would like
Kent Langley: to work on their MTP. Maybe you've got one that's half thought through. Maybe you've got a mission statement, you want to turn it into an MTP. This is a live coaching session. Saleem and I, and Kevin, you're free to jump in as well, if you wish, are going to help you do that. So…
Kent Langley: I'm looking for hand raises, in Zoom.
Kent Langley: And speed matters. So, who can get that hand up the fastest, who is not a pro member, and would like to work on their MTP? You want to… you want to build impact.
Kent Langley: Let's hear it.
Kent Langley: I don't see any hands.
Kent Langley: We're gonna work on Celine. Oh, we got one. I was gonna say, we're gonna work on yours, Celine, fixing civilization, if that's what happens. So, alright, we've got a couple up. Kevin, help me out. I think Luciano got his hand up first. Would that be right?
salimismail: But…
Kevin Allen: So Ram had a thumbs up, and then… and then his.
Kent Langley: Oh, whoa.
Kevin Allen: I saw…
Kent Langley: I would say…
Kevin Allen: Graham probably was there first.
Kent Langley: Okay.
Kevin Allen: on her, then, older.
Kent Langley: Okay, we'll count thumbs as hands, and we'll go from there. And if we can get through more, we'll do more, but everybody can follow along with this one. This is really… this is really a workshop-y bit, so the link should be in the chat, and go to the MTP Genie. If you have a chat GPT account, you will be able to follow along as we go, even if we don't get to you today. That's how we scale this a little bit. So…
Kent Langley: Ram, let's get you on stage!
Kent Langley: Hello, hello, nice to meet you!
Ram Venkatraman: Nice to meet you, it's been a very inspiring session.
Kent Langley: Thank you. I think it may be too much information, but I'm guilty of that frequently. When I was a Levi in Florida almost 10 years ago.
Kent Langley: Awesome. Oh, wonderful, wonderful. We've had a long relationship with EY. So, Ram, you're working on an MTP,
Kent Langley: Tell me about it.
Ram Venkatraman: Yeah, I'm, working on, you know, AI, it's in the intersection of AI, talent, and, using the… leveraging the channel of executive coaching and strategic advice. So those are the three circles I'm trying to find that, intersection in between.
Ram Venkatraman: We're, helping organizations
Ram Venkatraman: doing the AI for good, and I'm also leading the societal impacts of AI and responsible AI for a university.
Ram Venkatraman: So, there it is, you know, AI for good, AI for good.
Ram Venkatraman: And, it aligns with something Salim has mentioned. It's, you know, how do I bring better to the community? How do I make quality of life better?
Kent Langley: Love it. Let's pause there, and I did take a liberty to
Kent Langley: listen to you and, grab what you said. And so, I'm gonna just do this the way anybody who's just starting out would do, and I'm basically a proxy for you, Ram. So, we're gonna kind of do this together. So, I just clicked the button, there… oh, I'm not sharing, am I? I just clicked the button in the middle of the screen,
Kent Langley: Hev, you might have to spotlight me, I think, for this to work.
Kent Langley: Yeah.
Kevin Allen: I'm gonna have to just remove Salem and ram quickly.
Kent Langley: Okay, sorry. So, look, I'm gonna go back, because I want to start from the beginning. Alright, here, MTV Genie, there's a button. Click here to find your… refine your MTP. So you click that, and it takes you in here, and it's going to introduce itself and tell you what it's all about.
Kent Langley: If you're curious, this is using ChatGPT 5.2 instant by default. If you have your own ChatGPT,
Kent Langley: premium or pro account, you can even upgrade the model, use whatever model you want. Super interesting to see how the different models respond. This one gives the best overall experience. So, click here to start your journey. Let's do this in three steps. Alright, so, Ram, you gave me some information.
Kent Langley: So, my starter… I'm gonna say my starter is AI for Good.
Kent Langley: And then you told me all this stuff.
Kent Langley: I literally… ripped it from your… your speaking, so… and it's just literally what you said. I didn't,
Kent Langley: I didn't change it. Let me just double check that I got everything.
Kent Langley: I think I missed a little bit, so… Hang on.
Kent Langley: I wanna make sure I get everything you said.
Kent Langley: Okay.
Ram Venkatraman: It is.
Kent Langley: Yeah, okay, just… I'm gonna try…
Kent Langley: Just to make sure. Okay, there we go. So now we've got it all. And I didn't even… I didn't even… you should read what it says. It will guide you. I'm shortcutting a little bit, because I know how the AI works. I made it. So it's,
Kent Langley: it's gonna start to guide us now, it's gonna coach us. So it says that you have a beautiful start, lots of great raw ingredients for a powerful MTP, and now let's alchemize them into something massive and transformative. So it's going to teach us as we go.
Kent Langley: It's gonna say, you're operating at the intersection of AI, human talent leadership, executive coaching, and strategy advice. That's your delivery channel.
Kent Langley: That is a strong foundation, but here's the key insight. An MTP is not the… oh, and by the way, Saleem, if you want to jump in anytime, because you actually wrote the book, and you wrote the thing on MTP, you should jump in and say, hey, the AI's right or wrong, or
Kent Langley: I'm not needed anymore, or whatever, whatever you've got to add there. The MTP is not the intersection, it's the future. This is a really interesting… it's the future the intersection creates, because as you know, as a good coach, you're always creating someone's bigger, better future.
Ram Venkatraman: Right.
Kent Langley: Yeah, so we don't… so we don't say AI talent coaching, we declare what becomes possible because of that intersection, and let's reframe that toward an MTP. So let's translate all of this…
Kent Langley: Let's see… and it's… now what it's done is it's gone and it's given us several options. So, Ram, I'll need your guidance here on whether you think one of these options is better than another. Or if you like 2 or 3 of them, you say, I'd like to combine those, maybe.
Ram Venkatraman: Yeah, I think I like the option 2 and 4. Actually, 5 is… yeah.
Ram Venkatraman: Okay.
Kent Langley: Great.
Kent Langley: Yeah, and let's see what else it's teaching us. There's no we involved, there's no coaching, there's no services. It removed all the stuff that's not going to help us make a good MTP.
Kent Langley: And it's telling us to think about what goes wrong in the world if leaders use AI without wisdom. That's a great question.
Kent Langley: You know, what becomes possible when they augment themselves with AI.
Kent Langley: So you can see, this gets pretty deep. So now, you said 2, 4, and 5, so what I will do is…
Kent Langley: go back, I say, I like 2, 4… And then 5.
Kent Langley: Let's use those, to create a final draft Version.
Kent Langley: And I said, well, I'm gonna keep this pretty simple. Obviously, you could take this further in the future if you wish. At the end of this session, I'll get the link.
Kent Langley: And I'll make sure that you get the link to this session so you can pick up where we leave off, Graham.
Kent Langley: in your future. So, alright, so those three together form a very coherent MTP spine. The three you chose, 2, 4, and 5, let's synthesize and come up with a draft.
Kent Langley: Now, this is very interesting, what happens here. There's more tools at our disposal, and this allows us to get into it. MTPs aren't generally really long.
Kent Langley: They're not mission statements.
Kent Langley: when you use the MPP Genie, you actually don't care about that at first. Let it be as long as it wants to be, but when you get there.
Kent Langley: it says… it's even telling us what to do now, because I… I've said this so many times. Next step is, let's compress this, so use the command. So, I'll just say
Kent Langley: And I'll put in…
Kent Langley: what it gave us. So the make memorable command is actually a grammatical trick, to trick the AI into giving us examples that are much, much shorter and more memorable.
Kent Langley: And so what we've ended up with here is align artificial intelligence with human values at the highest levels of leadership.
Ram Venkatraman: Super.
Kent Langley: What do you think, Celine? How did we do?
salimismail: Yeah, this is great. What I found generally is the tool is so good at this point that I need 3 coffees and, some microdoses of psilocybin.
salimismail: even get to about 50% of what the tool can do, right? It does start with your raw
salimismail: Passion.
salimismail: Like, what… what…
salimismail: fundamental problem were you put on Earth to solve, and then you can start from there. Or what… why was your company created, or organization created? What is it trying to achieve? Then this is all kind of framing and articulating and word art around it, which is incredibly powerful.
salimismail: And so you combine the two, and you come up with something that's very elegant in a very, very short space of time. It used to take us running full half-day to one-day workshops to help articulate out an MTP properly. And so now this is down to, like, minutes, right? Which is typical of all these attributes and how we're doing things.
Kent Langley: Right, and remember, we… it took your input, and it's also given us 3 different examples.
Kent Langley: Actually, several. It gave us five different ones. AI Aligned with Human Values is the ultra-short version.
Kent Langley: This is a moonshot version, because we talked about that, earlier. Ensuring artificial intelligence, augmenting the… okay, beautiful. You were going to say?
Kevin Allen: No, I was… I was just gonna say, I mean, one thing using this tool as well is, if you really don't like what it's done, then also tell it that, right?
Kevin Allen: So, you know, perhaps sometimes it may, you know, move in a direction that's not exactly where you want to go, so make sure you're telling the AI that, right? Yeah.
Kent Langley: Here, I don't like any of these, you're crazy, try again, right? So, you know, you can do that, it's fine, and it's gonna be… look, it even gave me a cute little laughing emoji, right? Keeping things light. So, really funny. So, that, I think, Raj.
Kent Langley: That should give you a pretty good… pretty good foundation to work from.
Ram Venkatraman: Yeah, very good. Thank you so much for the opportunity.
Kent Langley: You're absolutely welcome. I'm gonna provide this, link, to Kevin, and he will make sure that you get it. Okay?
Kent Langley: All right, awesome. Thanks, Rand. Are we going to do more, Kevin, or what do you.
Kevin Allen: I think we can do one more. Well, we only have one hand left, which is Holger.
Kevin Allen: I can't remember whose, whose hand was up, it went down. it was up before Holger's, but, oh, there, it's back, it's back, it was Luciano.
Kevin Allen: So, we'll, we'll jump over to Luciana. And maybe we can try, and if we keep this one a little bit short, we can try again.
Kent Langley: I'll try. Well, you've also…
Kent Langley: We've all seen the whole thing now, so I don't have to be as expository about it, right?
Kevin Allen: I will add Luciano here to share quickly.
Kent Langley: Let's do it, Luciano.
Luciano Baccello: Hello? Well, I did some testing while watching the example with RAM.
Luciano Baccello: But I have a facility management company who works in Argentina. I'm Argentinian. I'm currently living in Spain. I saw Salim in Barcelona in the Festival of Abundance.
salimismail: Excellent smile.
Luciano Baccello: Yes, of consciousness. Consciousness, yes, it was not about this. And, and…
Luciano Baccello: Yes, so the MTP, I thought in the beginning, it was…
Luciano Baccello: bring transparency to the facility management industry through KPS. We already have an MVP that is an app that lets the clients and the shareholders in the business, have,
Luciano Baccello: information and KPIs from the work that is done. With facility management, I mean, cleaning, security, private security, all what, has humans,
Luciano Baccello: With the work being done.
Kent Langley: Okay.
Kent Langley: Let me ask you a couple questions.
Kent Langley: Why?
Kent Langley: Why do you want to do that? What about that really gets you excited?
Luciano Baccello: What gets me excited is, what, has to be on, building teams of…
Luciano Baccello: especially people that works in different places and management facilities, it is something I, did, for…
Luciano Baccello: the last couple of years, so yeah, it basically gets me excited, and with transparency, it's not that it actually makes me excited, it's that it's something I think many companies, don't do, so I saw it as a…
Luciano Baccello: Eventually, competitive Albanist.
Kent Langley: Well, you're the first person… I mean, I've run into a lot of these, and I've not actually dug into one in facilities management as a massive transformative purpose. I think that's fascinating.
Kent Langley: And I'm just… I want to dig in one more… one more level. So, what change do you think you'll see in the people
Kent Langley: that come to you, adopt your MTP, and make their facilities management transparent.
Luciano Baccello: I think that it's going to be much more honest for the clients and the data that the suppliers, as an example.
Luciano Baccello: show to the clients. Many facility management companies, or cleaning companies sometimes, I don't know, they are not very transparent on how they actually build their clients.
Luciano Baccello: So, showing real-time data on how things are being done, and that's why I try to put it on traceability, transparency, all this.
Kent Langley: Oh, now we're getting some good stuff. Okay, traceability, transparency, real time. Yeah, this is great. Okay, so I'm gonna use that up to that point, and let me make sure that I have everything again.
Kent Langley: Okay, just one moment.
Kent Langley: Perfect. Alright, so I'm literally just going to take what you said. We're not even starting with an MTP. I'm not even…
Kent Langley: engaging, necessarily. If you're really starting for real and you're doing this on your own, please pay attention to the steps and do what it says, but you'll see that, effectively, I walked you through a small subset of these questions.
Kent Langley: Okay, I capture the responses, and I'm putting it in here.
Kent Langley: I don't think I got it all. Hang on. Stop.
Kent Langley: I wanna make sure I get it all.
Kent Langley: So it's a little cumbersome the way I have to copy this over.
Kent Langley: Oh, come on.
Kent Langley: Okay, let's see if I got it this time.
Kent Langley: I did. Okay, great. So now, this is everything that you said, right? I just… it's not… it will have my questions in it as well.
Kent Langley: So, it's important for you to note that this became a dialogue between the two of us, you know, in a one-to-one dialogue that we're now feeding into AI in order to do its thing. And so, that's excellent raw… it's raw… good raw material, and this is what it thinks
Kent Langley: It's hearing clearly. You're not just managing… we've got to make this massive and transformative, right? That's why I'm asking these questions. So, we want to change how trust is created between clients, suppliers, and operators. That's bigger.
Kent Langley: Right? You're correcting an industry norm where there's opacity.
Kent Langley: data's delayed or massaged or faked, right? So you're going to build in IoT, you're going to build in all kinds of great stuff, right? This is a deep systemic shift. So you're starting to see… this is why I asked you why you care and what is going to change. Those are the two best questions that will move you the quickest through this. So here's the change you create.
Kent Langley: And people and organizations.
Kent Langley: You can see it's done a good job of picking up from you.
Kent Langley: Now let's translate that into MTPs. Option 1. Make facilities management radically transparent. It's okay. It's okay. Trust and honesty. Restore trust in facilities management through radical transparency.
Kent Langley: Maybe. Turn facilities management into real-time, honest systems. I like that one, actually. I think that's best of the bunch so far.
Kent Langley: I really like data is truth.
Kent Langley: in real time, so 3 and 4 personally. But what do you think? Of these 5 options that you see here.
Kent Langley: Does one or two of them really ring true?
Luciano Baccello: I see it a bit pixel, I think it's because of my internet, but the… oh, yes, yes, yes.
Luciano Baccello: What's in there?
Luciano Baccello: I think option 3…
Kent Langley: Okay, great.
Luciano Baccello: Let's work on that. Preferred.
Kent Langley: So I'm just gonna say, let's… I prefer option 3, let's work on that, because I'm not 100% convinced we're there, so let's see what we get.
Kent Langley: So, the things that make this a decent MTP is it's more motionable, more memorable, more magnetic, and then it's going to want us to
Kent Langley: it's going to tell us why, right? And this is really important, because you have to be able to explain your MTP to people, too.
Kent Langley: If you look in the MTP helper tool that we provide, there's something called the MTP Cocktail Test. If you like one of these MTPs that comes out today.
Kent Langley: do that. It's fun. Just do that with people you know who won't think you're crazy, yet, but, you know, it's pretty fun. So…
Kent Langley: Step 2, refine the option. So now it's gone through, and it's done a level of refinement, and it's given us different versions.
Kent Langley: Clean and strong. Turn facilities management into real-time, honest systems. I think that's pretty solid.
Kent Langley: Worthy. Turn facilities management into a real… oh, that's good. Turn facilities management into a real-time system of truth.
Kent Langley: I like truth over honesty, personally.
Kent Langley: Because you know how sometimes when you tell someone you're being honest, they're like, oh, that person's not being honest. Yeah. So, facilities management should operate in real-time truth. That one doesn't land for me.
Kent Langley: Great real-time truth in facilities management. That's… that one's good, too. I like B and D. What do you think?
Luciano Baccello: I'm between the fifth and the other one you also mentioned about truth, I think it was…
Luciano Baccello: The fifth and the 3rd?
Luciano Baccello: Right?
Kent Langley: Well, it went from numbers up here, all the different numbers, to these four options, A, B, C, and D, so… Yes.
Luciano Baccello: Auchos di…
Kent Langley: Okay, got it. All right, so that's awesome. So, create real-time truth and facilities management. That's already very short. We'll try the command anyway to see if it gives us any yield, but more than likely, you can go with that as your baseline MTP, and then test it, because that's what you have to do next, is test it.
Kent Langley: So, the make memorable command has taken our current MTP and given us an ultra-short Real-time truth for facilities.
Kent Langley: Real-time truth in facilities.
Kent Langley: Facilities, managed by real-time truth, or honesty in real-time, or facilities.
Kent Langley: and a poetic version, or a rally cry, where facilities operate in real-time truth. So, you have a lot of stuff here, and it went ahead just like I just did, and it recommended you to do the MTP Cocktail Party, which is where you would walk up to me.
Kent Langley: And we're at a cocktail party, and I say, hey, Luciano, nice to meet you, what do you do? Because that's what always happens, right? And you say.
Kent Langley: You say?
Kent Langley: I help facilities.
Kent Langley: Live in real-time truth, or whichever version of this you want to go with. And I'll either lean in.
Kent Langley: And I'll be like, man, tell me more, or I'll be like, dude's crazy, and I'll walk away.
Kent Langley: Both results are fine, because the dude's crazy walks away actually filters for the people you have no business working with, and the ones that lean in are the ones that are going to help you build your vision. And so, it's not that your vision's crazy or you're crazy, it's just that they're crazy for not wanting to work with you. And so that's pretty cool.
Kent Langley: Alright?
Luciano Baccello: Totally.
Luciano Baccello: Hey, thank you. It was very helpful.
Kent Langley: Awesome. I'll send it to Kevin, and he'll make sure you get it.
Kent Langley: Alright.
Kevin Allen: And we'll… we'll move to… to Holja quickly. And that'll be a really short one. Okay, alright, alright, alright, I'll do it. I'll add you there, Holja, and you can share, and then, and then we'll jump into that.
Kent Langley: By the way, please, before I start with Hold Jeff, in the chat, if you liked any of those MTPs, if you have suggestions for the person whose MTPs we worked on, if you think it's amazing what they're doing and you want to connect with them, DM them, send them, post in the comments. That's what we do here. We help each other. So, oh, how can I help you?
Holger: Yes, I have written something in the chat, so maybe you can just copy things so that you don't have to write everything from scratch.
Holger: I'm running a non-profit organization that is called CloudStos, the people in the Cloud, and I'm running this since 20 years. And it's a kind of a commons incubator. In my main profession, I'm an enterprise architect for many years for SAP and Porsche.
Holger: And I see the similarities, between an architecture for a non-profit world as also for a for-profit world. And we came to the…
Holger: conclusion that the AI in future, is definitely demanding from all of us to have more shared ownership, and we seek for the profile of a commons engineer that helps to create businesses
Holger: Projects, cities, regenerative areas,
Holger: And I'd like to see, or I would like to see a million type of commons engineers in the world over the next couple of decades to build these type of new organizations.
Holger: That is why I have written that I somehow feel it's about a systematic approach, so engineering, sustainable futures.
Holger: You know, the main topic is about, commons, commons engineering, and Commons is a kind of a…
Holger: Yeah, shared responsibility for resources, whatever the resource might be.
Kent Langley: Okay, let's stop there. I'm gonna…
Kent Langley: do a little interesting thing here. I'm going to teach you guys a little trick that I do sometimes when I run into situations like this, because you kind of came in knowing what you want. So, I've taken and I've said starter is the first part you gave us, which has an OTP in it, and I've given this a dollar sign in front of it. This is called variabilizing your context, and I know that's a little bit…
Kent Langley: Technical, but it allows us to
Kent Langley: craft or engineer the context along the way, and then I've taken everything you just said, and I've put it in as info, okay? So we have two variables and some information.
Kent Langley: So here's a starter MTP and some additional info for us.
Holger: Would you mind sharing your screen?
Kent Langley: I wouldn't… I would totally love to share my screen, thank you. So, here is the… what I did was I said, here's a starter NTP and some additional info for us to get started. I took what you typed in the chat, and I called it starter.
Kent Langley: And I took what you said to me, and I made it info, and so you see what I'm doing here is then I'm… I'm giving… I just want to be more precise.
Kent Langley: Okay? So this variableizes, and it's like sticking signposts in your context for the AI to be more precise. And then I've just sent that in, to the AI, and it's running.
Kent Langley: All right, fantastic. It even knows who you are now, so there you go.
Kent Langley: You are being watched, and they just need distillation. Okay, so here's what I'm hearing reflected back. At the core.
Kent Langley: Cloudsters is about… Engineers, I believe, here.
Kent Langley: And Kevin told me I have to go fast, so, apologies.
Kent Langley: But we will, and creating a repeatable engineering-grade way, long-term aspirations. This is not about cloud, SAP, or consulting, it's about how humanity organizes value, ownership, and responsibility in an AI-powered world. That's awesome.
Kent Langley: And a key MTP insight, your text is right, but, well, of course, we know this, this is obvious. And this is just telling you how to get to a better MTP from the body of information that we've provided, and now, as usual, we have a draft.
Kent Langley: Engineering Shared Futures for a Sustainable World.
Kent Langley: Option 1.
Kent Langley: Engineering the commons for a sustainable civilization. That's big. You and Celine can work together.
Kevin Allen: that, because…
Kent Langley: It's totally messed up. All right, creating a world built by commons engineers, I wouldn't, just so you know, I wouldn't go with this, because nobody knows what a commons engineer is, right? You have work to do to make that
Kent Langley: Understandable.
Kent Langley: Redesigning ownership, value, and responsibility for the AI age. That's pretty cool.
Kent Langley: I like that. Engineering regenerative systems for shared prosperity. That took a whole different path. So, do any of those, sort of ring true with you?
Holger: Yeah, I think 2 and 5 resonates with me.
Kent Langley: Okay, awesome. So you guys know the drill by now?
Holger: Yeah, thank you for the link, so I, of course, will play with that.
Kent Langley: Yeah, of course, I'll send you that, same as the others. I like 2N5, let's work with that.
Kent Langley: And what we're gonna do again is we're gonna have it come back, it's gonna probably combine the two, make some new suggestions, perhaps we pick one and make it memorable. So then, I think we're off to the races. And again, just like I said to the prior, the prior person.
Kent Langley: You have to test these. You know, test all… test all of them, you know, but ultimately.
Holger: Nope.
Kent Langley: is saying the most EXL pure is engineering the commons for regenerative civilization. That is certainly massive, and it would be transformative. I don't know if everybody knows what the commons is. I mean, we probably all do here, but, you know, understanding the commons is not all that common.
Kent Langley: So more action-oriented engineering or regenerative comments for the world. This could work because regenerative has really taken off.
Kent Langley: more poetic.
Kent Langley: Building a regenerative world through the commons. This goes more in the direction of Boston Children's Hospital until every child is well.
Kent Langley: You see, so remember that the genie knows what successful MTPs look like.
Kent Langley: So, you're seeing echoes of successful NTPs in there.
Kent Langley: These are great. Do any of these,
Kent Langley: Sort of kind of go, that one's interesting.
Holger: I don't know exactly which ones, but I liked at least 2 to 3 of them.
Kent Langley: Okay, so let's do this. It's the question, of course.
Kent Langley: So, I'm just gonna go meta, and I'll say all the final ones.
Kent Langley: And so, why not? You know, let's do it. It'll try to make memorable all the final candidates to give you crisp iconic versions for each one. This is the kind of stuff I do when I'm using this tool myself. You know, it's got rails, and it will keep you on the rails if you want it to, but you can also push it. And it does a pretty good job. So, civilization scale.
Kent Langley: Engineering the commons, here's your version, a regenerative civilization through the commons.
Kent Langley: I mean, that speaks to me, personally, but… Pretty neat.
Kent Langley: Pretty good. Alright, I'm gonna send you these. I think these are great. Thank you so much, for sharing. Is that helpful for you?
salimismail: Things are really important.
Holger: Thank you so much.
salimismail: I think the super important point here is if we don't engineer and manage the commons, we're not going to have much of a world left.
salimismail: So we're doing a pretty bad job of it right now, so I love this, approach, Holger.
Kent Langley: Couldn't agree.
Holger: Thank you so much.
Kent Langley: These are great.
Kent Langley: you're gonna find a lot of people in the EXO world, Holger, that…
Kent Langley: will be attracted to these MTPs. A lot.
Kent Langley: If you look.
Kent Langley: Alright, Kevin. We did 3 today, that was awesome.
Holger: Thank you.
Kent Langley: So, I hope everybody has a good handle on, kind of, a way that they can get their process going.
Kent Langley: What we promised when we started was that you would walk away with a lot of actionable tools, homework that might take two to four weeks to get done, and I hope that you've received a lot of value from what we've done here in this coaching and approach.
Kent Langley: the… the trick is that you go do it, right? And one of the ways that you can do that is to come and join us here at these events, like the 10X Shift. We do these every month.
Kent Langley: They're discrete events that talk about only a fraction of the model. Today, we focused on AI and algorithms, and we focused on MTP. As Saleem said, we do MTP in every single session, because it's just so valuable to people.
Kent Langley: And next time, we'll probably be doing a different attribute, so feel free to come see us again. If you want to build your own EXO,
Kent Langley: As Kevin said, at the beginning, we meet every single Wednesday. Saleem's there, I'm there, Kevin's there, and we help you build your EXOs. If you want to do that, raise your hand by just saying so in the chat that you want to know more. Kevin will reach out. If you don't have any idea if that's good for you, book that 20-minute call.
Kent Langley: It's free. It's just part of what you bought today, and we'll help you start your EXO, no matter whether we ever see you again or not. We just want to help. Yeah. So…
salimismail: The first thing people should do is just, if you have any questions or want to use this model a lot, or more, just book the 20-minute call, and we'll guide you through that next step.
Kent Langley: I think I'd love to hear in the comments what were people's biggest takeaways today.
salimismail: and… or any live comments, if anybody has it, or questions. I think this is such an interesting time to be navigating the world. It's, like, pretty surreal. So, if you guys have any comments, what was your biggest takeaway today?
salimismail: I'd love to hear.
cunds: It's Clint Unseth in Canada. I think we're all astutely or acutely sensitive to the radical change, the pace.
cunds: And the demonstration of the leveraging AI capabilities, like, in marketing context, that's great. But I am still reminded of the connection of the people, and sharing different perspectives, and the type of synergy in this EXO community.
cunds: As an example, that just jumps at me again, like.
cunds: I want to get more engaged again more often, because it's sharing ideas, and that experience, and the thought leadership, the mindset, that's what it is. I'll leave it at that.
Kent Langley: Beautiful.
Kent Langley: Raise your hand, folks. Post in the chat, just type pro, if you're a pro, right, because there are a ton of people here that already got trained on this at some point, and they're here to support new people coming in, and so that's.
cunds: Right?
Kent Langley: show up to keep learning, reinforce learning, and then if they can help you, they'll help you. We have a wonderful community, so I really am grateful that you pointed that out. Thank you.
Kevin Allen: Yeah, and Jill did, again, post the Meets, link, so meet.openingxo.com, and ultimately, next week.
Kevin Allen: We will have 8 sessions where you can pick whichever one works for you. If you want to join it at 1 in the morning, great. But you can pick whichever one works for you, and ultimately.
Kevin Allen: meet with people randomly, which… that serendipity is… is a big part of, you know, being an EXO, right? In the book, Salim speaks about that as well. So please do, you know, when you get the link in the follow-up emails that come.
Kevin Allen: do click that and join one of those, right? They are really fantastic. Salim will be at a few of them, Kent will be at a few of them, so will I.
Kevin Allen: So you're gonna, you know, potentially meet with some, some awesome people, and then I already see a bunch of people have, have, signed up for a 20-minute, session, so, thanks for that. You know, we, we really want to help you, and, yeah, so, so with that…
Kevin Allen: Just a quick comment.
salimismail: Yeah. Marco, you have a quick question?
salimismail: Or comment?
salimismail: You're muted.
Marco Abilhoa: Hi, Salim, and everybody. I'm a Brazilian businessman and board member in several, high-tech companies, not only AI, but software, renewable energy, and nanotech, and biotech.
Marco Abilhoa: And, I'm just… it's just astounding how the Brazilian business community… I know you have been there, Salim, a couple times in the last few months, because I follow all the moonshots, and but it's amazing how this businessman there.
Marco Abilhoa: are so, uninformed about the evolution of AI, and so wrong about it. You know, they think it's much far away, that it's not going to affect their business, and that worries me a lot, you know? Like, when I go to a lunch.
Marco Abilhoa: Go ahead.
salimismail: No, no, it's a great point you're making, Marco. You know, there's pretty clear there's going to be two types of businesses in the future, those that are using AI for everything they do, and those that won't be around.
salimismail: It's kind of… it's kind of… that leaves one type of business, basically. It's an incredibly powerful time, and the… what's going to happen is teams of 3 or 4 vibe coders are going to start displacing billion-dollar companies over the next 6 months.
salimismail: And you'd rather be the team of 3 or 4 ride builders doing powerful things. Unfortunately, I think we're running out of time, Holger. We'll have to leave your comment or question until next time. But Marco will be doing a lot more in Brazil.
salimismail: Over the next month or two, because clearly there's lots to do there, so I look forward to seeing you down there sometime soon.
cunds: Alright, cheers.
Marco Abilhoa: Okay, great.
salimismail: So…
Marco Abilhoa: Everyone, thanks very much for attending today. This was amazing. Kevin, I'll let you take us out.
cunds: Thank you.
Kevin Allen: Awesome. So, thanks, everybody, for joining. We will be getting a recording out probably Thursday or Friday.
Kevin Allen: so be on the lookout for that. We will also share a bunch of links. Apologies about the fact that some of the slides, were a bit blurry. Our PDF was about 40 meg, and we… we used the minimizer, which never blurs the slides, but…
Kevin Allen: I don't know what the AI did, so apologies for that. And so we will be sending through something that is also better.
Kevin Allen: But yeah, look forward to connecting with as many of you as possible, and as Kent said, this is about implementation, and so, what we shared today, you can spend a couple weeks on, you know, really perfecting. And so, with that, it was wonderful to see you all. We'll see you all again soon, hopefully, and, thanks, everybody. Have a great day or evening, wherever you are.
salimismail: For the pro members, we'll see you again soon. Cheers, guys.
Marco Abilhoa: Cheers, everybody. Bye. Bye.