Why Workplace Learning Needs an Existential Reset with Lori Niles-Hofmann

Hey, Foresight listeners. Thanks for tuning into our show. If you like what you hear and want a monthly roundup, a sneak peek into the insights from our Foresight Plus members-only events and more, sign up for our monthly newsletter. It's free and subscribing also gets you access to our quarterly Foresight whitepaper. This quarter's whitepaper is about rethinking entry-level work in the age of AI, produced in collaboration with Dr. Miranda Rodak from Indiana University's Kelley School of Business., an important topic for HR leadership and parents, students, and society as a whole. Link to subscribe in our show notes. Now on to today's episode. You're listening to Foresight, the weekly podcast about HR leadership and the future of work. We explore the ideas, trends, and the real stories reshaping how work gets done. I'm your co-host, Mark Edgar, a former consultant and coach, turned Chief People Officer on a mission to make work more human. And I'm Naomi Teitelman, former big firm consultant and HR executive, now striving to make work better one leader and one organization at a time. Every week, we chat with top experts and dive deep into the issues facing HR and business leaders today, from retention and engagement to AI, flexible work, culture, and leadership effectiveness, with ideas you can use right now to lead with confidence into the future of work. Welcome to Foresight, a podcast about HR leadership and the future of work. I'm one of your co-hosts, Naomi Teitelman, and I'm joined today by our next special guest, Laurie Niles Hoffman. I met Laurie a couple of years ago through a mutual friend in the edtech space who introduced us because, of course, because we both live in Toronto. And since then, I've been following and appreciating Laurie's perspectives on the world of L&D and her occasional cat memes. But in all seriousness, Lori is a guru on all things edtech. We welcomed Lori to our Foresight+ community for a deep dive on the concepts from her book, The Eight Levers of Edtech Transformation. And I thought our listeners need to know this information too. So welcome to the podcast, Lori. It's great to have you here. How are you today and where are you joining us from? Well, it is wonderful to be here. I'm really excited because I feel like this will actually be a documentation of our conversations because normally we have those over, we've had that over coffee or over Zoom. I am well. A little jet lagged, but I am coming in from Toronto, rainy and cold Toronto as we discussed previously. And I'm on the back end. I just returned from a trip to London and then I'm going back to Frankfurt. So there's a lot of laundry behind me. Yes, a lot of laundry and a lot of frustration with, we were just discussing the prices of flights and travel is not for the faint of heart these days. No, but no, I, I, anybody who could invent teleporting, I would be so, so on for that. Oh, me too. You have two investors right here. So anybody inventing teleporting, I think that, I think it's possible. I think AI, with AI, it's possible. Exactly. Just rearrange my cells, you know, it's fine. It's fine. It's all good. Awesome. Well, let's check in before we get started. So my check-in question today is, if you had to describe the vibe of L&D right now in one word, I, I'll give you two if you want two, what would it be? The word that I would go with right now is perplexed. And I think there's— that's because for me perplexed has an element of curiosity, and that's definitely there. They're kind of, you know, poking at the thing going, hmm, you know, that's interesting. But I think there's also a lot of uncertainty, and there's a lot of fear of what this will mean to our industry. And it's also preventing movement. I think that's the other thing with perplexity. There's a bit of analysis paralysis. I gave a lot of words there. Yeah, no, I love all those words and we will dive more into what we mean by those things in just a moment. Let's start with you, Lori. If you could just share with our listeners a bit about your journey to where you are today and what compelled you to write your book, The Eight Levers of EdTech Transformation. Certainly. So I won't go all the way, all the way back, but education is something I've always been, been interested in. It was something that followed me through, through school. And eventually I started at BMO and I was an instructional designer. And from there implemented— that was when learning management systems were coming up. And so I started implementing these at a global scale at different companies. And what would happen is I would do one and then I'd move to the next one and I would do it all again, move on to the next one, do it all again. And they would get complex and the technology got more integrated. And so it was lesson after lesson. But I really started looking at some of these and saying, wait a second, I technically make these run and my, you know, project timelines and integrations and APIs are spot on. But a lot of times they would just deliver lackluster results. And so I sat down and really looked at what were the core reasons. And some of them were within our control, some of them were without, some of them also were ever evolving. And that's really why I sat down and wrote the book because I wanted to put these things all together to say, I know what needs to be done if you really want a transformation to work, and these are the mistakes that you're going to run into, and these are the ways to avoid the pitfalls that, that I have. I even opened the book with, this is a culmination of all of my mistakes. My editor was like, that's the opening line? I'm like, yes it is. I love that. It's what it is. It's what it is. So yeah, you know, learn, learn from those so you don't get the bruises that I did. Well, thank you for that. I'm sure lots of our listeners will appreciate that for sure, because there are so many pitfalls that we can fall into in these big L&D transformations. And so, L&D has promised that technology would revolutionize workplace learning for at least 2 decades. E-learning, MOOCs, microlearning, and now AI. So, from where you sit, what has actually changed and what has stayed frustratingly the same? I think the big thing that's changed with this evolution is with the others that you mentioned, like e-learning, MOOCs, microlearning, those were happening in a bubble within learning. They weren't things that people were necessarily experiencing in their day-to-day lives or in their work lives. E-learning— and people go to YouTube, people go to TikTok to learn how to repair a toilet or how to change, you know, some, some wiring in the house or something like that. Actually, call an electrician for that, don't rely on YouTube. But they were not doing a click next to continue module on these things. These were things that we invented. Microlearning, again, you could argue that some of those formats were that, but we still, we, we, we our microlearning still would have learning objectives and it was very constructed and it, it often was just, like I said, in our bubble. I think what's changed right now is AI, not just AI, but the way that people interact with technology is forever changed. And that is, L&D has two responsibilities. One, we have to help people keep pace. Two, we ourselves have to deliver a like experience. We can't deliver things the way that we did before. Because they're not as effective. It's not just because it's a feeling change or it's a preference. No, it's because we know it's not as effective. Where I think we are stuck, it's an existential crisis, is we keep wanting to build courses and that's just not— one-size-fits-all courses are not going to be the future. We know it. I don't know what the reluctance is for it, but this isn't the direction we're going to go in. Mm-hmm. I feel that viscerally. In fact, I was talking about a component of our community platform and how AI is really changing how I think about content consumption, right? It used to be you either go to a live session online or in person. If you don't make the live session, usually you're sent a recording, but then you have to find the time to watch the recording, take notes, maybe watch it on 1.5 speed so you could fit it into the half an hour, right? But now with AI, you actually just have to go in, ask AI either, what did I miss at the last session that's going to be relevant for XYZ that I'm working on? Or has there ever been any information that's been shared in this platform about this problem I'm working on? Right? So it really flips the learning on its head. And I think that's so hard for L&D and HR departments to get our heads around because how do you How do you structure that? How do you build that? How do you deploy that? Really good questions. And there are, and there are definitely ways to do that. I think though, sometimes, and I say this with love being an L&D person, there's a bit of an ego problem. We have to set aside some of those things. We're not main character anymore in this journey. The learner always should be, and now they are the main character. And I think when we look at these ecosystems and how they operate and how we can deliver hyper-personalized and contextualized learning to people at scale, how we can do experimentation, simulations, feedback at scale. It's a whole new world and it's far more effective. And to your point, saves time. It's, it's more impactful and applicable. And that we just, we just need to step aside on some of this. Yeah. I mean, listen, the minute our, our learning courses go live, a lot of the content is irrelevant, right? And then you have to go back and figure out where, you know, that line has been in all of the different modules, right? And now, you know, even for that problem, you know, I'm using, we're using a platform in Foresight+ that literally, like, you make a change to one module and it'll find where it is in every single module and cascade it. It's amazing. Well, and, and which is, I mean, just the time saving alone is, is phenomenal. And the currency, it keeps your everything relevant. We're all even working on, you know, a genetic layer where it will plug into Jira or wherever you're doing product management. And if any product specs change, we're doing this for a specific client, the agent will flag it in every piece of content. Human in the loop says, oh, okay, yes, yes, yes, yes, that one actually— sorry, because, you know, it can get some things wrong, but yeah, we're going to change that product spec from 16 to 17 centimeters because that's what's changed. Boom, boom, boom, goes out. I don't need to wait for a business partner to tell me. I don't need to have somebody run those modules through QA. It's just the level of automation is, is, is incredible. And that doesn't even need to be done to a course. It can be done what I'm now just calling as content, which is going to be ingested into an intelligent tutor. Yeah. So we're finally there. We're finally in the flow of work-learning, right? And that is, that's mind-blowing. And it's happened really overnight. Like, it really has happened overnight. I find in all the different tools, even this tool that we're recording in, right? Like, like the agentic layer has just been built into Zoom, and I can ask it lots of questions, and that is learning too. And I think part of the challenge is that we don't have, like, an in-the-box definition for learning. Because learning is everywhere, and redefining who really is the expert in all of these different steps that used to define learning versus who are the stakeholders now. Exactly. It gets completely, completely messy. What I would say, though, is right now, the proliferation is happening so fast. But we can look back to Clippy. Clippy, it was essentially what Copilot became. Now, they got rid of Clippy. I've never heard of Clippy, personally. You've never heard of Clippy? No. OK, well, all right. This is where I can show my age. So Clippy was this little paperclip in Microsoft, and it would— you would type just in Word and it would say, hey, sounds like you're trying to write a letter. Oh, I do remember that. I didn't know his name was Clippy. But yes, yeah, I mean, everyone turned Clippy off because it wasn't personalized, it wasn't contextualized, and it didn't do— it was just an annoyance. But gradually, gradually, gradually, gradually, and then look at where we are now. And now there's this explosion. And, and I think your point too about who owns learning— is it a user experience piece? Is a— is it a product piece? Is it an HR piece? So there's gonna be lots of things to decipher, but I also think there's beauty in the messiness. Mm-hmm. Mm-hmm. I agree. And also, like, there is still a need for some, like, offline learning of content, right? And of skills. And, you know, it's not all about, like, instant delivery and clicking the info button and it being in the flow of your work. Completely, completely. And there's also going to be things that just never will be delivered, you know, via technology. But it's the combination of those two. You know, there was a really interesting study. It was actually— I'm gonna do a Canadian shout out to a company called Disco.co. Oh, that's what we— that's our platform in Foresight+. So I'll do it. So I'll do a double shout out. Love Disco. A double shout out. Great. Yes. Love it. So they had an interview with a gentleman from DeepMind at Google. Also Canadian. Well, that— the person, not Google, of course. So clarify that. I'm not going to appropriate that. But it was all about how they were working with LearnLM, and they were doing some studies, and they found that they could isolate AI alone, people learning, AI, or just human learning. And then the best results actually came with human and AI. I think that's where the combination needs to be. The challenge is going to be how we get that mix right. But I don't see things like, you know, learning communities and centers and where people congregate and go ever going away. No. I mean, we learn from each other. That's how we started. We sat around a campfire in a cave and we, you know, to keep warm and to teach survival, we told each other, hey, I saw a bear. Yeah. Yeah. It's really, or don't eat, you know, the red berry over there because it didn't agree with me. That's how we, we learn. 100%. And so it's thinking about, you know, what is better delivered synchronously and asynchronously, then how do we crystallize that learning as a peer community? And we've been talking a lot about this. Obviously, we feel very deeply about that at Future Forward, in Foresight Plus, in Disco. Um, we kind of bring this stuff to life, right? And we, we're constantly experimenting with what should be synchronous, what is okay being asynchronous, and what can we facilitate as in-person gatherings that are mostly around building relationships, but have a learning crystallization component to them as well, right? So if you're just throwing slides at people in a learning session or in a community session, then you're wasting time cuz you're not building on those skills that have to be built in person. Completely agree. Completely agree. All right, so without giving your whole book away, let's talk about some of the concepts in your book. Can you walk through the logic of why there are 8 levers and whether they're meant to be pulled in sequence or in, or simultaneously? Really good question, especially since when I wrote the first draft of my book, I gave it to the most trusted person in my life, my husband. My husband being very German, the book was originally called The Nine Leavers, and he pointed out, there are only 8, Lori. And I looked at him and went, fein. Because he removed one or because the counting was wrong? My counting was wrong. And I, at this point, I had already bought the domain, The Nine Leavers. So if anybody wants that, it's going cheap. So the 8 levers, and I did debate, should I just, you know, make up another lever? No, I didn't because it just didn't feel right. I really, despite my lack of mathematical capabilities to count to the number 8 or 9, it really, these were the core ones that I felt were important. And in terms of calling them, there is no particular order. And also with some of them, you may never get to, like, there is a maturity model against this. You may never get to level 5 of the maturity because that's where your organization is at. For example, data is one of the levers, and that's hard for a lot of organizations. And there may be systemic issues beyond the capabilities of, of L&D that are going to impact whether they can do the things they want to do in, in, in data. Doesn't mean you failed or your transformation will fail. What is important though is that you do consider every single one in some way, shape, or form and customize it to where your company is at. Because I know that ignoring any one of those layers, any one of the levers, that's where I saw things go off the rails. Hmm. All right. Well, you'll have to take a look at the book to go through all of the 8 levers. So we'll leave that as— Or lovers, levers, lovers. Levers, lovers, lovers. So we will, we'll leave it a bit of a cliffhanger. But you do describe skills management as a supply chain problem, which is interesting framing for an industry that often leans towards the human and relational side of things. So what's the strongest pushback you get on that metaphor? Maybe you can explain the metaphor and then what's the pushback you get and how do you respond? So the idea behind it is I really believe that every time we give learning to an employee or a colleague, I don't even like saying employee because these are, these are the people we, you know, we meet at the water cooler, have lunch with, and they're, they're just the same as us. There's no teacher-student relationship. I've always disliked that. The idea though is we have to operate with precision. So that is every time we give that piece of learning, it is a tax on them. It's a tax on their time. It's a tax on where they cannot expend energy someplace else. We have an obligation to use that very, very wisely. And this is, it's, it's not an infinite resource. And I think we operate under that model way too much that more learning, the better. Yeah. Actually, no. And no, it doesn't serve that person. And when you think of how fast things are moving right now, we have to move with precision. I will sit with organizations and we get to the point to say, and I have some calculations in, in the book, where it's a question of, okay, are we gonna have 16 or 17 people with this skill? Do you need to— not everybody. We need to be that precise. Where are they going to sit? What return on investment will we get? Where— what will that do for that person? What will they expect? So we have get that precise. It's no longer, hey, everybody should learn X, you know, everyone should learn AI, everyone should learn how to prompt. Okay, and that's great, but okay, you're on a factory floor or you are dealing with, you know, completely different issues. Is that a priority? No, it's priority for an evergreen skill, but there are also more competing priorities for what needs to be done where, where that person is. So, when it comes to the supply chain analogy, I think we need to operate that way if we want to serve our colleagues, meaning we don't want them to develop skills that aren't going to be needed and are just going to rot in a warehouse. We also don't want them to be short of skills that are going to impede them from progressing in their careers. So, it's a whole entire system that we need to manage it through. As for the supply chain, and I get that pushback all the time of like, this feels like numbers. I take a different stance and say, when you go to a doctor and you get a blood test done, they operate at a precision level to keep you healthy. Mm-hmm. And I'm applying the same type of thinking to this. It's not that I think people are widgets, and it's not that I think they can be interspersed and, and replaced. I'm saying we have to have more respect for them. We can't afford to be fuzzy in their progression and fuzzy in how we are upskilling, or as I call, right-skilling the workforce. Thank you so much for saying that, because I— my biggest worry in what we do is wasting people's time, right? And giving them, you know, sessions or information that is a waste of their time. And, and there's also that trust component there, right? Because our colleagues trust us to tell them what they need to learn in a lot of cases, right? And if we don't— if that dynamic doesn't exist, It probably should to a certain extent because people are so busy in their day jobs that they're not, they're not going to say, um, excuse me, I think I need to learn XYZ. So we have to be so careful about how we use that relational capital and how we build trust in our organizations. Wouldn't agree more. And, and I would say every time I've opened up a client's LMS and just looked at, you know, what's popular, just, I can guarantee it's going to be some combination of project management, leadership coaching, or Excel. And in all times, when we peel back the, the onion, Excel is just because nobody knows the codes. Now AI can do that for you, so fine. Project management, leadership coaching is because it's the only way they see— people look at and say, how do I get ahead in my career, right? But then you have to look back and say, well, how many PMs do I need? Yeah. And is that, is that viable? Are we teaching them Agile? We're teaching them Waterfall? Like, so many variables in that. So let's capitalize on that so people aren't wasting their, their time, energy, and, and finite resources. Yeah. Yep. That makes a ton of sense. So this kind of goes to my next question, which is we've been kind of order takers in L&D and HR for a long time, but we need to shift this dynamic from order taker to, you know, enabler in, in a real, in a real sense of the word, not just throw away that word and call it enablement. So what's actually different now that makes that achievable and what's the single biggest thing that's holding teams back from making it real? Sure. So I talk about a model called the Autonomous Learning Engine, and that is basically— it really follows supply chain management. I'm not that smart. I just was looking at some of the contents and concepts and plopping it into L&D. But to move us from enablers to order takers, it's data. And if you look at the autonomous learning ecosystem, it's about using an agentic layer to sense skills areas where we have deficiencies, to look at our, you know, wallet of skills that our employee set has, to say who might have something adjacent, and only then do we then target them with learning. Learning actually comes in very late in that entire ecosystem. Learning is essentially procurement, if you think of it that way. But we don't just go out and buy and build and, you know, and do that. We have a whole— there's a whole layer of steps that happen before it comes to us. Those are the conversations we need to be having with the organization, is to to be able to pull that data and say, look, this is, this is where we are at, rather than I'm seeing people, you know, they, you know, I think people need more listening skills. Okay, listening, you have no evidence of that. What is the evidence of that? Let's peel that back. There's no evidence of that, then I get it's a nice to have, but we need to quantify that. Yeah, to me, I've always used data as, as a superpower in conversations. I've not made friends doing that, but I can pull things out to say, okay, You have this opinion, that's fine, but this is what, this is what the data is actually telling us. And doing a learning intervention is actually not going to move the needle. That said, a lot of L&D still operates under a hierarchical structure, and we are in the most difficult position because learning is something everybody has done for a significant portion of their lives, and they think they know just how it should be done. And that's not true, right? It's, it's like, you know, just because you watch numbers of episodes of House, or, you know, ER does not mean you are a doctor, right? You cannot diagnose. So, I also think, too, moving away from things like the clicknicks to continue courses, moving into intelligent tutors, that's also going to garner the respect back to leadership to say, this actually is a professional enabler. We're not just going to do what you say. And let us off that weird construct that we sometimes seem to be in. Yeah, it's interesting because there's also an argument for like learning sessions, right? Like if there's an, a leader who's like adamant about delivering an inclusive leadership course, right? And bringing their team together, there is like a bonding component of it if they're like the person in front of the room. But to your point, it's not gonna achieve the skill development that's required for this moment in time. So it's a little bit of a like, okay, like which sword do I wanna die on? And. You know, how— what— where do I just want to kind of enable you to do your thing versus where do I really want to help you, like, know where you're actually going to make a difference? Absolutely. I really believe actually that learning should be separated from culture development, from people culture, and the things that fall under people culture— like, that to me would fall under people culture. Yeah, right, exactly. It's supported by L&D because there may be, you know, some components around it, sure, but I don't see that as, as an L&D Yeah, now that makes sense. Now, bringing people to do a hackathon and facilitating that, I would see that as, as learning, and it does sort of touch on people cultures. That line would blur. But I also think that needs to be separated out. L&D has got way too much that's plopped onto them and bolted onto them because this is, oh, well, we think they can do that. Well, not necessarily. You know, the number of times that I've been asked, you know, would you take on a, you know, learning leadership role, and it has DEIB. I'm a firm supporter of DEIB, but I am no expert in that. I have, you know, other than a passion for it, but passion is not enough. Yeah. As you know. And so, but that got bolted on. Well, how did that happen? Don't you want somebody who actually knows the law and the essence and lived experience to be able to, you know, work in that? Because I don't have that. I, I don't know. L&D is one of the delivery mechanisms for DEI, but that's a little bit of a red flag when that's bolted on because it's saying that DEIB is only a learning thing, right? Which can be a whole other episode of our podcast. That's a whole other episode. But, but yeah, it's not us. Yeah, we support it, we support it, but we don't— we cannot lead that. Yeah, makes total sense. So like if you're starting a new company or you have your very first foray into, okay, I finally got some budget to develop my people, right? You know, in the olden days we'd go and we'd evaluate different LMSs maybe, but like where would you start in this day and age given where we are with AI and technology? I would, I would be looking at basically the roadmap for what are, what are companies planning to do and achieve and what are the KPIs that we, that we've looked at. Then I would be as I'm in L&D, I would not be making any decisions there. I would be then, I'm talking to HR, I'm talking to talent acquisition, I'm talking to succession planning. I'm looking at all that because they probably have, you have some sort of idea of where people sit. And then I'm going to sit down with the CTO typically or a CPO and sit down and say, okay, if we're planning to go in this direction, this is what, this is, these are the things that we have in our skills wallet right now. You're planning to go here, I'm seeing possible gaps here, let's sit down and figure out where, where those, those gaps are ideally. But if I'm coming in at the early point, I would already be a skills-based organization, I would have a lot of that, that already done. But that's how I would do it in the rough when I— if I, if I had to think of it, think of it that way. But it really has to go into what direction is the company going, going into. And then we start making decisions. I'm talking talent acquisition and say, well, is it cheaper to or more cost-effective or more culturally effective to get somebody from externally to come in or a consultant to come in, et cetera. You know, all of those, those, those, those models. I would also probably not invest in courses. What I would definitely be moving towards, and I've mentioned and alluded to it before, is an intelligent tutor that I'm going to be— and there's not really good ones yet out there, but we're in an imaginary world. But to me, that will be the mechanism that we're going to deliver that by, and it's probably going to be something that embeds into Copilot or embeds into Gemini, depending on what type of environment you are. Yeah. And you say we're in an imaginary world. We've been having a lot of conversations around do you build this intelligent tutor internally or do you engage an external vendor? And there's just so many players out there right now. And, you know, some unfortunately go out of business. Some are acquired by other companies, right? Like there's so much going on. So there's a real trade-off between like, how do I develop I have a stable learning, you know, tutor in my organization that's going to grow with us versus taking a risk on an external vendor who has, you know, experience with other companies, et cetera. So how do you balance those things? It's, it's a really is a fine line. There was an excellent, when I was in London, excellent presentation done by Dani Johnson of Red Thread Research. And if you, if you're not familiar with her work, the Red Thread is, is, I'm a big, big fan of theirs. And her presentation was on the state of edtech. And she, she counted for corporate, there are about 461 players. I might have gotten it backwards, might be 416, but I think it's 461 because I would have remembered 416 as a— right, shout out to Toronto. Yes, exactly, shout out for the 6. And she broke it down by like all the capabilities and who the— what are the— who are the players and what are the trends and, and, and everything else. And surprisingly, intelligent tutor was, was not that high. And I've yet to see ones that I'm actually really interested in that I would put my name against. We're seeing more of a proliferation, for example, in AI coaches, and there's very good movement there. Another shout out to a Canadian-started company, Valence. They've got Nadia, their AI coach. So, I, I would not be building my own, and here's why. It takes an incredible amount of care and maintenance and feeding, and a lot of things can go horribly wrong. You don't want to take on that responsibility. Also, too, if you're operating in Europe, for example, your AI has to be defensible. If it is, if it's making suggestions on people development and of course, internal mobility, any of that, you don't want to play with that unless you really know what you're doing. And by that, I mean you are a company that develops this type of product for your own clients. I wouldn't dabble in that. I wouldn't trust, you know, somebody just moving into that. If I had to say, well, where would I take my bets? I would actually be looking at— and this is not endorsing any solution, but I would be looking at some of the AI coaches because I think they're the ones that are best positioned Yeah, but at a bare minimum, what am I looking for in an intelligent tutor? I'm looking for one that is bidirectional. It doesn't just— it's not just a prompt bar. There's— it interacts with you. It has to have multiple plugins to your ecosystem to be able to understand what the person's doing, where they are, what they already brought into the organization, what projects they're working on. That needs to be enabled. You need to have the ability to turn the dial up on certain skills, turn the dial down on other skills. So there's, there's, and it has to be paced learning over time. It's not just one-off interactions. It remembers you. It has memory. It is talking to you over time to know, because that's how skills get developed. It's not a once and done. It's not a, yeah, there's, there's certain things that they'll teach you, but if you want somebody to learn some deep skills, that could take place over the course of a year, if not longer. So it has to have those components. Yeah, it sounds like you have your next job cut out for you, Laurie. I would love to do it. Love to do it. We are getting to the end end of our time together. And it's so fascinating how much the landscape has changed since we last spoke, right? I mean, it's going so fast. So first of all, everyone follow Laurie on LinkedIn, but where else can people learn about the great work that you're doing? Oh, you're, you're very kind. You're very kind. LinkedIn, as I said, I actually put a lot of articles and things up on LinkedIn. That's probably my most socially active location, but you can also look at our website. It's 8 Levers, 8 as in the, the number 8, and then Levers. Which for all other Canadians, it does not spell Belieber. I am not a Justin Belieber, but it does look like that. I've had a few people say that to me. They're like, wait a minute, but no, it's not a B, it's an H. So maybe I have some marketing things that I need to work on, but you can always find me there and you always drop me a note on LinkedIn. I'm a little bit bad at checking my inmail, but I'm on there. Amazing. So Laurie, we like to end on a high note. This whole episode has been a high note for me, but what are you feeling good about today? I had the best news this morning. So it's, it's gonna start off with a little sad news. So, um, fortunately in December we lost two family members. It's been a, you know, it's been a tough time. It's been a really tough time. Sorry. And thank you. It's, it's, you know, these are life things that happen. And another family member was admitted to hospital for a week and we just got an all clear this morning. Oh, that's so nice. And I cannot be more thrilled. All of us are just so happy. And yeah, I think, you know, sometimes, Sometimes you just get a little break in the universe, and I think there's a lot of things to just be happy about. Great. Well, that is a wonderful note to end on. I'm really sorry about your loss, but very happy for your good news that you got this week. It's been a delight to chat with you, and hope to do it again soon. We said we're gonna go find a patio when this weather— we love talking about the weather in Toronto, but when this weather clears up, we're gonna find a patio. Oh God, absolutely. And you know what? I think even too, we should might even branch out, like Little Italy, Little Portugal. Oh, I love it. Oh yeah, there's so many places in Toronto that need to be explored. Yeah, that sounds great. So until next time, everyone, you can come find us on a patio or tune in next week and take care. Yeah. Thanks for listening to Foresight. If you enjoyed the episode, we would love to hear from you. 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