Sarah Bernstein on AI workflow redesign

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Welcome, everyone, to the Work Blueprint. This is a show where we bring on the most incredible leaders who are not only pioneering, but have their sleeves rolled up right in this new era of AI and building what will be the workforces of our future. Today, I am joined by Sarah. Sarah, welcome to the show!

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Thanks, Siobhan. I'm so excited to be here, and our partners have been so critical in this work, so happy to be here with you. Oh, I love it. So, folks, my guest today, Sarah, is helping shape how organizations prepare their people and their operating models for the AI era.

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Sarah is the Vice President and Organizational Transformation and Capability Development Leader at Lumen, where she leads the enterprise-wide efforts to help the company evolve into a technology-driven.

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AI-enabled organization. Her work spans AI workforce transformation, leadership development, and the operating rhythms that turn strategy into measurable results, and we are so grateful to have her here today. For folks that don't know Lumen, Lumen Technologies is a global networking and technology infrastructure company. It helps businesses connect people, data, applications, and cloud services

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Through high-speed fiber networks, Cybersecurity, edge cloud, and AI-ready connectivity solutions.

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Everybody, welcome Sarah! Lovely to have you! Sarah, tell us about you! We want to know everything a little bit about you and your background. Absolutely. So, Siobhan, I've, helped, in many organizations at the intersection of really, technology shift, scale for organizations.

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And therefore thinking through digital transformation, operating model transformation, workforce strategy design.

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And then really how we land that with our leaders, so that they're aligned against where we're going strategically, and they have the best people on the right work at the right time. And now with AI coming full force by, that's thinking through, you know, an identified workforce, where AI and people can partner to actually make those strategies real. Currently, as you said, I'm at Lumen Digital. Lumen is actually transforming from being a traditional telco

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to a digital network service provider that's truly the backbone for our AI-enabled economy. That means taking our physical strength, tying that through to a digital network, and then really changing and shifting about how we sell through, sell through, and sell with partners.

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to provide, you know, that real scale, no matter what device you're on, no matter where you're located. So, you know, really enabling this AI era through the shift in our work at Lumen.

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It's kind of crazy. Not only are you going through a workforce transformation, but your whole business model is shifting. Yeah. What does it feel like to work at Lumen right now? Well, it's multiple layers of transformation all at once. Like, we truly are, you know, changing everything about the company. We, are in the midst of that transformation, and it means really driving together, using our Luminate behavior. We dig into teamwork.

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We dig into a learning mindset, and we dig into winning together with both AI and our digital network for our customers and for our luminaries. That's what we call our employees Luminaries. Well, I did get the luminary experience last week in Seattle.

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So I'm still coming off that, like, vibe and that buzz of the team. That was, like, for those who don't know, we had, and Sarah, you have to spill the beans a little bit about what we were up to, but…

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We flew into Seattle, we got to hang out with the Lumen…

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big business team to get really focused on this transformation in this new world, and, it was incredibly exciting to see your team in action, I have to say.

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Thank you. Yeah, it was exciting to be there with you, Siobhan, and I will say again that the partnership with Reejig has been really instrumental in thinking through, you know, what is the true work that our employees are doing today?

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Unearthing that work really takes us into a journey of saying, like, what are the tasks that every function in a company does, what are the subtasks, and then how do you reimagine that? How do you choose?

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What actually should an agent do in partnership with humans? What should always be human at the helm?

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What should be automated instead of actually identified, right? And then thinking all the way down to some of the costs for that. So, in that workshop, it was so exciting to design together, Siobhan. We were shoulder to shoulder with those that truly create the agents, thinking through actually identifying those workflows, determining what you should hand over to an agent, what should stay human, and then what's very unique about Lumen is thinking through

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how do you start upskilling immediately when you see the future of that workforce, right? So we can talk about that further, but we did all that in a day together, and that learning mindset, that curiosity, that teamwork was really felt and seen throughout that whole experience. Yeah, it was, it was incredible, and also, like, the leadership level buy-in across your business is, like, one thing that I took away. The second thing that I took away was

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your commitment to be, like, super bold as an organization, but also wanting to make sure that your people are on that journey, that was, like, weaved into the whole day. You know, like, from the… from the swag that we were wearing, and the fun that we were having, right down to we were doing, like, really important work. So I think… I think also, like, your decision of, like, bringing Reejig and Microsoft and you all together in one place.

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So, like, one of the things that kind of frustrates me a little bit right now is there's so much talk in industry, there's so much talk about AI and what AI will do, and what will don't, and what it won't do, and I think where you have been, like, you know, I've watched your work, your sleeves rolled up, you're in it, you're learning, and never everything's gonna be perfect.

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But you are live building, and one of the things I talk about a lot is, like, you need to have, like, a couple of different, like, mindsets. You need to have an architect mindset, where you're, like, sketching up your new house.

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But you also need to have the builder mindset, which brings it to life.

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And you had both. And, I mean, your brain is like both, to be clear, but then your whole team brought that together, which was, which was amazing. And then we had Microsoft if anything went wrong. That's right, yeah. We had the adults in the room with Microsoft that we're running with and building everything we're doing, on our Agentic journey at Lumen as well.

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I think it would be really good if you could share a little bit of, like, you did a really good keynote on the day of, like, setting the scene. Why don't you talk a little bit about that sort of mindset that you brought to that team, and the way that you're thinking about your journey around AI? Because I think it's really important the way you're bringing both sort of the bold and the responsible together. I would love for you to share a little bit about that.

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Yeah, so I'll try to dock that in where I think, kind of everyone is, you know, always on, on LinkedIn and in other forums, talking about where we're at with AI and what you need to be doing, and what you don't need to be doing. I think for my team and myself, we have the advantage of we've been

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really working on, our transformation as a company, and we also have been thinking about how do you move through this Agentic journey for, I'd say, about a year now. And for us, in the beginning, myself, and I'll call out Annie Roberts, who's, you know, my… one of my key partners.

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You know, we've looked at with our business leaders, how do you get down to those use cases in the Agentic world that are going to really move value, value for customers and value for luminaries.

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And we sort of began our journey with almost, like, a thousand flowers blooming, Siobhan, on what we needed to create as our biggest bets at the company level, and then what we needed to do at each BU level. We further refined that as we've gone along, and we've seen compounding value against these use cases. Now, that starts to lean you into how you reimagine your workforce.

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Right? And there's same sort of thinking that goes into play, Siobhan, around where you see compounding value, and how you can look across functions, and also within work, task, and subtask, to actually reimagine a function at its fullest level. And then the last piece is, my team also owns learning and development.

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And so we very quickly, within this journey, started saying, how do we actually create

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The toolset, mindset, and skill set for leaders, developers, and for all luminaries that is required to actually thrive in an Agentic era.

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And so, when we think about that day, I think it comes down to, you need to approach this work, and actually surfing the model. We use the surfing analogy, that day in the session. What's it mean to surf the model?

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while we're redesigning, we don't know the end of this game within AI, and I would be wary of anybody who tells you that they do, because we don't exactly know what shape our functions are going to take in the future. What we do know is that you need to stay very keen on how the models are shifting, the models and the tools.

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Right? And then you also need to have this always-on learn.

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unlearn, relearn mindset. So, you want to be responsible and human first, but you need to be bold, right? And think about where you think the puck is moving to.

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Yeah, and I think that was, like, super loud and clear for the team, because not only were you, like, setting the, here's where we're going, but there's, like, a little bit of, like, safety net in… we're not all gonna figure this out perfectly, and that was why, sort of, those types of days are so valuable.

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for bringing everyone on the journey, and I think that's where I could see your team were getting an incredible amount of value from that. One of the things that I'd love to kind of dip into a little bit, so you talked about the task, you talked about the subtask.

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So, there's a lot of customers that, you know, they talk about the task, but they don't actually realize that the subtask is actually mostly where the agent is performing at today. So, when we're looking at, like, creating the map of, like, work within Lumen, we understand, you know, we've obviously created the architecture for it to grind against, because it has to make sense to your business.

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But then we're looking at what's the task, what's the subtask.

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One of the things that you and I have figured out really clearly is, you know, if you're using task data for AI potential, that's a good signal of, like, what's happening. But if you really want to get into actually redesigning work, having a high-level task is not enough.

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So, like, why… like, it would be great to talk a little bit about, like, that journey that we've been on together around, like, the depth of data becomes really important for that true transformation. Yes. I think this is,

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Very important point, and

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like, there's a part of me, Siobhan, that wishes you could go faster, and wishes that you didn't have to go down to subtasks, but when you think about reimagining how we've worked for different

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decades. You need to understand what are you truly trying to design or get out of any particular function at a company, and that means understanding both the task and subtask.

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So that front-end work of understanding what does that function really do, what's the gritty, kind of.

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stuck work that you think you're doing on repeat that might, should be best served by an agent or by automation, because it can actually free up time for more creative, more joy work, for your more, kind of forward-leaning strategic thinking within a new function. You have to surface that.

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You also have to provide, as you're creating the agent that might take over that sticky, you know, that very kind of repeat work, you have to give it context, because what may work on Lumen's ground or soil would be different than what might work on Palo Alto Network's ground or soil, a place I've been before, or call it Johnson & Johnson.

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Right? And then all the way back up to, listen, banks or healthcare have different regulations and different, you know, elements of where you have

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PPI or sensitive data that you may not want to ever get, you know, anything but human hands on. So, it's really important that you go down to task and subtasks. It does take some time. We're unlocking that by really putting those with great AI expertise against it.

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Paired with people that can really get down to what is a truly thoughtful way to process math, in partnership with wise partners like Reejig, and then go hard in the paint on how you actually think about reimagining the future with those that are best enabled to create change, change readiness.

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upskilling and actually move a function with human-centered, you know? Yeah. Human-centeredness at its heart.

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Yeah, I think, like, the task data's becoming so democratized now that you could just, like, plug into Copilot and ask for what are the top 10 tasks and the AI potential for a job, right? But if you truly are looking at, like, AI reinvention.

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what you really need to focus on is understanding how work runs. Yeah. And that's the difference, right? And this is what we have been, like, you know, we started a task, subtasks, because, like, I'll give an example. So, let's say you're paying an invoice in Lumen.

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like, the agent doesn't take the full payment invoice. There's, you know, the steps that you have to go through to pay the invoice, they would be classified as the subtasks.

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Most of the customers that are in large, I mean, fortune-top companies, they're not gonna, like, vibe code their companies. There are always gonna be elements of having humans in the loop, so what you have to actually look at is from a risk perspective and, like, what's possible, like, what is the task, what is the subtask, and then what is that last mile of work context?

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So think of, like, the handoff point, what system it goes to, and that is extremely important context if you want to build an agent.

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And this is where I think you and I have, like, I've loved working alongside of you, because we're, like, building while inventing, while jumping off the cliff, and, like, learning, and one of the things that we've ended up building into the product is the ability to capture not only tasks, subtasks, but now the context graph.

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And that becomes how you are able to create the output, which is the recipes to go and build the agent.

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without having that context, the agent build Blueprint isn't super valuable. It's, like, 80% right, but, like, 80% is not, in my opinion, good enough if we want to be able to build the capability across all of our teams to do this at scale. So, that was incredible, things to learn. The other thing I observed from your team was, you know, when teams actually talk about, so that was an ability for your teams to actually talk how that work ran.

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and have, like, a… there was a word you used, it was like they were digesting, you know, and, like, thinking through that hole, and, like, some of the things, they were like, actually, we wouldn't even bother automating that. That's not actually… there's no point. So that was another thing that I thought was really impressive about the team, kind of, like, thinking through, like, is this valuable to even go after?

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Yeah, Siobhan, I want to, pick up on something that you talked about, which is, you know, our live lab had two components to it. Building shoulder to shoulder with those that are best enabled to create AI agents to actually look at our workflows.

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Right? Against the workflows we unpacked. And then we also had a second component was, about something that we're doing very uniquely at Lumen, which is trying to go through the upscale journey as we surface where the function is going in just-in-time learning.

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And I will say for those talking that that second element of really going through, now, what is

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The remaining and the kind of reimagined function.

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And what do I need to upskill this team on now, and how do I most, kind of.

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kindly, quickly, you know, in an agile form and fashion, get them ready to be contributing in this new function. That loop of going through that and talking through that, talking through the baton handoffs, as you're alluding to, was just as formative and just as important.

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to really understand and think through what do we need, what don't we need, how do we get them ready and enabled, and I think that's a very important part. We talked about in New York, in your Pioneer session that you guys so, gracefully hosted, that many companies are running fast, but not actually creating the readiness or enablement.

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And you're seeing that, of course, in the LinkedIn echo chamber. Why? Because you're not creating the enablement within these functions to actually move for the future. So, it's a really important part to both unpack the work, move through through what the future is, and then enable people to actually be successful in that future.

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Yeah, and what I've learned in this journey, and like, I, as you know, still stay super close to customer. We're still in the learning mode where it requires founders, in my opinion.

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And the feedback cycle that goes from, like, being on the grind with the customer straight back to product is pretty instant. Your team would have got the preview of the new products from even just being in the session, of how fast it changes, right? And I think one of the things that I have learned through watching… I mean, I'm watching over 60 major enterprise transformations right now, where I'm trying to stay as much as possible close to what's happening.

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And let's imagine, like, the look of what you need to do to, like, create a new operating model to build and reinvent is, one, you gotta, like, understand your work.

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And no task, subtasks, and what's the context? So, essentially, we're, like, create a work context graph of your work.

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Step 2 is you need the intelligence, like a GPS, to tell you where to go. Step three is you need to, like, redesign for the new world. So some customers, like, can be more adventurous than others, like, you know, insurances, banks, pharmaceuticals, there's regulation in place that won't allow, like, a complete vibe coding moment.

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Right? Like, there's just, you know, there's rules in place for reasons, right? And then the step would be then reinventing and designing an AI workflow with the agents that are approved.

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All of that I've solved, right? The one thing that I'm totally obsessed with right now is exactly what you just described, just-in-time learning.

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So, I have watched so many deployments of agents, where what has happened is that prompt training has been issued to the employees, and then the gap between that initial, like, high level… I would say that's, like, top of the funnel awareness, but let's imagine you go and you reinvent how the invoice is being paid.

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Yeah. You actually need to show people how to work in a new way.

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And that is the part where I think I… my worry is not about the agent, it's not about the work, it is now, oh my goodness, how do I get 100 people to work in a completely new way?

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How do I do it in a way… like, transformation feels like a one-time thing. I actually think it needs to be more like stealth change management, and you and I talk about this, you know, imagine your iPhone upgrade.

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How do we, like, get work updates into the system in a way where our people get comfortable with, by the way, that invoice that we've just automated, in 6 months' time, whatever tech you're using is gonna have, like, new releases that are gonna make that even faster? How do we create that? And I think the way you described the just-in-time learning, for me, that falls into that bracket.

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Because I think that's the cliff that we're all about to face, and I don't think, to be clear, that most people are feeling that, because you're kind of really early on the real live build of pushing hard, and they haven't discovered that yet, so talk a little bit more about that, because people need to know you're right up front.

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kind of, like, pioneering, like, that part, I think I have seen is gonna be a thing.

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Yeah, I think, you know, there's a few things there, Siobhan. I mean, first, I'm benefiting from the great leadership of, you know, both Anna White, our CHO, and then Kate, our CEO.

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That they created early on, the mindset that we need to be curious, we have to have safety, and we also need to be thoughtful about where we're spending, creating value most for our customers and our luminaries. I've said that already in this conversation, but they truly are carving the safe space to do that. Secondarily.

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Anna had me take on both our learning and development and our succession teams, probably about 8 months ago, and working on both transformation AI and L&D and capability. So rare. Yeah, real, a lot of levers, right? To think about how are you creating that always-on learning muscle. Now, when I took on

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Learning and development. Angela Pappas is on my team, and we had the, benefit of working together at Lumen.

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or sorry, at Palo Alto Networks and at Lumen, said, you know, we really need this learning to be bright and tight, we need it to be in the flow of work, and we need it to be always on, because of where we're headed.

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And so, even out of our session together, Siobhan, and you and I would not have had a chance to catch up on this, you know, we did two things, which is create a learning journey for those Agentic paths that we designed in the room. We're in the midst of creating those, and then we'll launch those to our organization to think about what is the new flow of work for our TEA team, and how do they learn immediately the right capabilities and the right motions

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To actually work in a new way. That's part one. But out of that session, we also said, you know, we really want to lean into this always-on change and sort of consultative mindset that you need to apply the higher level of curiosity and judgment that most functions are going to. And so, we are designing a whole learning path out of that session that is about that.

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That capability, both for our people leaders and our business leaders.

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I love that, and you know what? I'm gonna show you, when I see you next. So, in the product, we've just released the SOPs. So, if I design a workflow, and I've now got the agents and the steps.

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when you publish a workflow, it'll automatically populate, you know, the ROI and the changes of the workflow, but it'll also give you the SO… like, the workflow for your employee. You can then package that up as part of your learning journey, so that folks know… it's like an employee should be, like, treated like they haven't done it before, and just show them, like, here's the new way. So, like, that'll be something that you hopefully can get some value from when you're stitching together your learning journeys.

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Because I do think it's gonna be, like, a requirement to do this, like, constantly.

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You know? Like, it's an always-on, like, that upgrade of the iPhone, you know? Like, how do we keep at the pace

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of doing that, and I think that's where the way that your teams were together, I think, was incredible. Another part would be awesome to hear as well. So, we talked about, you know, rebuilding and redesigning and rejigging work, and building agents. Talk a little bit more about, okay, so, like, the other part of the… I think your day two was then about

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the strategy itself around skilling, and how do we think about not leaving our folks behind. Give us a little bit of a flavor of, like, what that conversation was.

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Yeah, I would say, you know, listen, let's go back to what you were just talking about, that it would be great if you can, you know, have this always-on muscle and just show people the new way of working, at sort of net new, as if they're brand new.

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That gets right at the heart of our second day. You know, as folks that are leading transformation at a company and thinking through how do we actually evolve an entire company from being a legacy telco to a digital network service provider that's AI-enabled, you know, in every way.

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You go back to some of, you know, what are, kind of, people or transformation leader, kind of DNA, which is, you know, people don't love to change, Siobhan. It turns out it's hard for them to change.

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And, you know, you drive up the fear, and you drive up not knowing the end of the story, and it gets people even potentially a little more frozen. Yeah. You know, there was research out this week that even those that are most kind of ingrained in this AI journey.

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are not necessarily showing big signs of optimism, and part of that is around, you know, the…

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You know, AI takes different muscle, it takes different always-on muscle, and people don't know the end of the story. So that second day, we really focused on how do you dig into some of the basics of, like.

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What is the true, kind of, new orientation?

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How do you make sure that these people are pilots, not passengers? So this is a little bit of dare-to-lead thinking, but, you know, pilots are curious. Pilots are actually showing that they're applying judgment in a kind of, truly, what is a product thinking around what a particular function should be doing? How do you think about adaptability and that always-on muscle and resilience, right?

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Passengers are kind of just going along for the journey. So how do we equip people to know what does this truly mean for their function?

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How do we give them as much clarity as we can, Siobhan, about where their work is going and what the work is shifting to?

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How do you help them understand what is changing, what's not changing, and then how do they lead their teams and others through it? And frankly, how do they get resilience, and how do they give themselves rest, and how do they make sure that they're applying scrutiny to what's coming out of that AI?

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Because we all know that AI can serve up things that are really brilliant, and things that are also very, very off.

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Yes, I have received quite a significant amount of, what do they call it, AI slop at the moment. And that's the tricky part. I think two things that, you know, what you said is really interesting. The fear… I'm kind of cranky at the AI companies for actually making the fear worse.

00:24:53.020 --> 00:24:59.019

They have, like, demonized their own product in market to, like, the everyday consumer.

00:24:59.020 --> 00:25:18.930

by, like, kind of fear-factoring it, of what, I'm gonna take all your jobs, which means that people are also quite resistant to, like, actually adopting a new way, which means it's gonna be so much harder for you and I to actually, like, cut through what was already gonna be a pretty difficult, like, adoption journey, right? Which I just think is just annoying, and I don't… I don't get the…

00:25:18.930 --> 00:25:25.009

I don't get the approach, like, I didn't understand why they were, like, they're selling the product, but they're more negative about their own product.

00:25:25.010 --> 00:25:48.220

It was just weird, right? So I think, like, the… that's kind of, like, one part. And then the other part, I think, is as we start to move into this journey, like, the great thing that you've been able to do is, on one side, you're, like, charting your course with the GPS and Reejig and knowing, like, where we'll go, but you'll also know the impact into workforce based on that. So having the data to tell you both means that you've got an opportunity to

00:25:48.220 --> 00:25:54.309

Do whatever to your luminaries, whether have those conversations, feed that data to your career pathing leaders.

00:25:54.310 --> 00:25:59.549

You know, that's where I think… and by the way, it's quite rare that it both sits under your…

00:25:59.600 --> 00:26:06.950

Title. That's the… that's a new thing as well. I haven't seen that yet play out, where it's, like, that full end-to-end journey as well.

00:26:07.070 --> 00:26:25.829

Yeah, I think, we… listen, I feel very fortunate that, you know, Anna is very forward-leaning in her thinking, as is Kate, and they, you know, have believed in our leadership to guide elements of this journey. I think, you know, something that also comes up from what you said, Siobhan, is, you know.

00:26:25.830 --> 00:26:50.050

I think I saw a stat this week that, you know, likely 65% of jobs and functions will shift. But shift is the key, because, you know, there will be a shift in what work people are doing. We're finding that functions are merging today, so if you look at design, engineering, and PMing, you know, AI brings up, you know, the subject matter expertise and makes it faster, right?

00:26:50.050 --> 00:26:58.149

Right? And so we see the evolution of those functions. But there also is a study out today from JLL that many people believe they're going to add to their headcount.

00:26:58.150 --> 00:27:15.449

what the headcount is, and how it shifts, that's where you really get into, you know, how can we be predictive about where we see functions moving, and how can we help people along that journey? It is. It's a really interesting conversation I had with one of your team members, just in the hallway, and this is the thing with being face-to-face with folks, you just…

00:27:15.560 --> 00:27:31.830

For me, there's, like, little light bulbs of just chatting to people in a hallway, getting a glass of water, and the question was, like, for entry-level talent, there's a lot of negative press right now that all of those entry-level jobs are gone, you know, and graduates trying to get a new job, it's quite tricky.

00:27:31.830 --> 00:27:48.020

And we were chatting about, like, the concept of, like, well, how would you design AI into an entry-level person coming into the workforce for the first time? And it's… I am literally testing this right now. I have taken, in some early career professionals with, kind of, no game tape.

00:27:48.220 --> 00:28:12.890

And what I'm doing is, and one of them has just walked past my office just as I'm having this conversation, but what I'm doing is I'm wrapping around AI, so my bet is, if I can, like, fast track what would have taken 3 to 4 years for this person to get, like, in that kind of, like, level, is it possible? And this is where I think we should look at the entry-level employee, and redesign

00:28:12.890 --> 00:28:33.859

like, how we even think about that, because, like, there is so many incredible folks, and by the way, these folks are coming out of university who will be AI-first thinkers, just because they're starting to, like, tinker now. And, you know, they've grown up like my kids in the era of, like, they chat to ChatGBT versus go to Google, you know? And I think that's where… that's where I think there is this, like.

00:28:33.860 --> 00:28:41.999

Opportunity to not only, like, redesign workflows, but redesign how we actually think about how we design jobs and work.

00:28:42.030 --> 00:28:49.680

And I would challenge folks, and it was just such a good thing that, like, I had this passing conversation, and I was like, huh.

00:28:49.680 --> 00:29:09.519

that's actually something I need to think about, because that is something that would be possible, and I've just been tinkering in my office, but actually, it's the same problem in your company. Like, you're gonna have the same problem across the banks, across the insurance companies, so that was where I got a lot of value, just in, like, being present with your team thinking the way they're thinking, so… yeah.

00:29:09.750 --> 00:29:21.209

What I would offer there is, you know, I was listening to… I'm a pretty avid listener of Lenny's podcast, and there was podcasts with Adam Morrissey, who leads Instagram.

00:29:21.290 --> 00:29:31.329

As product leader at Meta, and, you know, he was cautioning, like, if you're not actually hiring in your early and career folks, you know, what's your pipeline?

00:29:31.330 --> 00:29:55.559

And to your point, though, I believe, you know, it's advantageous for us to use AI and think about how do you onboard and actually upskill these folks faster? Yep. Right? Because can I, with AI, move them through what would have been a, you know, pretty, like, year-over-year journey of, I'm, you know, level 1 product manager, I'm a level 3 product manager, and perhaps that be a 3-4 journey, can we accelerate some of that?

00:29:55.690 --> 00:30:05.430

Both in our onboarding and how we upscale them, point one. Point two is, you know, really thinking about those AI, kind of digital first.

00:30:05.690 --> 00:30:23.049

folks that are fresh thinking and coming in and have that bold, we were talking with Microsoft and saying, how do you really capture the expertise of those that are truly SMEs and have been in a discipline for, call it, 20 years? Yeah. It's capturing those that create… that… that…

00:30:23.050 --> 00:30:36.429

that wisdom, and then using the fresh thinking and that long-term kind of subject matter expert that creates compounding value. So, how do we put the lessons of those together, along with our Agentic partners?

00:30:36.430 --> 00:30:39.300

And then, you know, really, really skate.

00:30:39.680 --> 00:30:50.999

look at me, like, I'm a live case study, so I don't have a technical background, I have spent my career in HR, in workforce strategy, but here I am leading

00:30:51.150 --> 00:30:58.220

a hyperskill… we're in the classification now on Reejig as hyperskill AI, because of how well we're doing.

00:30:58.340 --> 00:30:59.480

And yet…

00:30:59.560 --> 00:31:23.029

I don't have any technical chops whatsoever. And I think if I look truly at why I'm able to do what I'm doing, is, like, the design of my company is essentially designed in a way where AI wraps around me in every element of what I'm doing. So, like, don't get me wrong, I've got people I can pick up the phone from an advisory capacity on my board and everything else, but I would say most of my time is doing things that I've never done before.

00:31:23.030 --> 00:31:23.840

Like…

00:31:23.840 --> 00:31:46.330

And that doesn't matter if you're, like, you know, old like me, or, you know, coming out of grads, or whatever. Like, the concept is the same. Suddenly, it, like, creates this ability for everybody to kind of 10x on whatever it is. Either go really deep on something that you're really, really good at, and, like, become world best at that, or it gives you the ability to run a company like me. I know how to do everything from

00:31:46.330 --> 00:32:04.449

marketing, sales, partnerships, building a product, I can code, I can ship, I can design, I can make sure I don't run out of money, I can raise money, I can do customer… like, imagine the ability of being able to, like, at scale, be like a Swiss Army knife, and that's what AI has done for me.

00:32:04.450 --> 00:32:23.860

And I think that's where I think, when I talked earlier about getting cranky with the AI companies, I actually think that, like, that's a disservice to the economy, like, we need to be more positive about it, because the opportunity is for everybody to have access to essentially do that kind of work. And, you know, like, how rewarding is it

00:32:23.860 --> 00:32:38.269

to get access to do something like that. And I think that's where I look at my job and kind of go, like, oh my goodness, like, imagine I would have to build… so, for us, building a billion-dollar company with under 100 people is the kind of, like, goal.

00:32:38.270 --> 00:32:55.810

I would… it would be impossible. You've worked in big tech, you know what it is. You're talking, like, for a revenue profile, you'd be 5,000 people in that company for to do what I'm trying to do. And whether I get to 100 people or not, and it's like, I go over, but it's the goal of, like, can I do this in a different way, and

00:32:55.810 --> 00:32:58.430

on the way, share all the things that I get wrong.

00:32:58.440 --> 00:33:12.480

so that everyone else can hopefully learn and not make those same mistakes, because at least I can screw it up on my company, and it's very different than being in a company like yours. Like, the risk, you know, and you're a much bigger company, and, you know, etc. So, that's kind of where I think…

00:33:12.640 --> 00:33:21.400

that there is that excitement within your, within Lumen as well. It's, like, the possibility… even, like, the reinvention of your company is so exciting, you know? Like…

00:33:22.200 --> 00:33:37.270

Yeah, it does require that bold thinking, Siobhan, that you are, really pointing to at Reejig, right? And I think that bold thinking combined with how do you have the right kind of product sense and judgment, how do you have the right tension that comes from

00:33:37.300 --> 00:33:49.990

Our, sort of long-scale wisdom of a product leader, of a design leader, of an engineer, and use those together, right, to create a vision for what the future of work looks like.

00:33:50.060 --> 00:34:02.440

Yeah, and I think we've talked a little bit about, like, the reinvention of work and understanding work, the impacts on the workforce and what to do. There was this other thing that you and I discovered as well, not on purpose, it was like…

00:34:02.650 --> 00:34:21.909

slightly painful. So, there is something about wrapping AI into our way of working. So, on the Reejig side, we build very, very fast, and very, very aggressive, and, like, think of a software engineer who has never used AI, and then suddenly is using AI. They're building, like, 100x the code that they've ever built before.

00:34:21.920 --> 00:34:45.109

Right? Like, that is a real thing that is happening. Now, the one thing where I think it's going to be really important, I haven't cracked the code on this yet, but it's just, I'm flagging it as something for folks to be thinking about. If you imagine that the software engineering job used to be to write code, check the code, send it to QA, and then ship the code, now what's happening is AI is writing the code, and they're checking the code. And if you're

00:34:45.110 --> 00:34:58.640

creating that amount of code. What we didn't do was, like, reset expectations on my team that the actual job of a software engineer had changed at Rig, and we hadn't set up processes, so one of the things that we were doing was shipping so fast.

00:34:58.640 --> 00:35:07.009

That we put a bug in there somewhere along the line, which caused, like, a latency issue, and we were like, how do you… how do you…

00:35:07.010 --> 00:35:18.060

Like, we… and it was really interesting, because I dipped in to see what was going on, and I was like, guys, how is this happening? And they couldn't find the bug. And the reason that they couldn't find the bug was because they didn't write the code.

00:35:18.290 --> 00:35:22.380

And then, so there's this other part of AI, which I think is… is…

00:35:22.410 --> 00:35:40.849

is a little bit like, okay, like, what does that mean about how our job expectation shifts, and how do we think about that? And you and I learned that live, and I was like, called you, and I was like, hey, like, we… this is a learning. Like, I genuinely, like, we couldn't see the bug, and that was where we had, like, whoa, everybody slow down a second.

00:35:41.050 --> 00:35:44.570

Like, we need to put new ways of working in place as our team, so…

00:35:44.640 --> 00:36:03.600

that's an example, and I'm sharing it pretty, like, openly, because I think, like, that was a lesson to me, that, like, I gotta put guardrails in place in my team, and I think all companies now, if they're starting to use AI, what's the kind of governance around how we check what gets out the door? Whether it's to customer, whether it's in our code, whether it's…

00:36:03.810 --> 00:36:23.420

how you're doing financial state, like, there's so much where there's still human… like, it's just so necessary to have that, but, like, what, like, what's your view on, like, when jobs are starting to evolve because the AI's in, like, how do we reset expectations? How do we know how jobs are changing? Because that's going to be really important.

00:36:23.800 --> 00:36:36.910

Well, I'll… I'll take, a crack at this, Siobhan, first, from, you know, having been in that journey of creating, sort of, what is our AI philosophy at Women, thinking through, you know, with

00:36:36.940 --> 00:37:00.769

those that are much more experienced than me, do we need a platform internally? Do we not? To actually scale our AI solutions? You know, what really should be our governance, our security stance? You know, working with leaders across the organization to look at those things, I think your security stance and your governance all up is critical. And it is becoming more critical as the threat landscape, you know.

00:37:00.770 --> 00:37:01.960

Yeah, what's the boss.

00:37:01.980 --> 00:37:21.520

And there are leaders, you know, both internally that are creating those flows, and that is a part of our overall governance of AI at Lumen, right? Making sure that things are secure for our customers and for our luminaries is paramount. And I think that has to go in your overall governance as an organization, as you stand up how you approach AI.

00:37:21.610 --> 00:37:37.560

Secondarily, when we go down to discovering a bug in the workflow that was created by AI so it was hard to inspect and find, you can use AI in the way it's scaling to find some of those bugs today, but it goes back to your overall point, which is when you design the future work.

00:37:37.560 --> 00:37:42.560

there are things that probably should never be handed off to an agent. So before you ever publish.

00:37:42.560 --> 00:37:48.669

You know, you really want the right test harnesses, both Agentic and human, as the last and final stamp.

00:37:48.670 --> 00:38:07.919

Before you send out in the marketplace. Now, there's, you know, a whole other dialogue, and I'm not a product leader, on how much you actually put into market and test, and, you know, in an Agentic world, you do that faster. If you want to hear Claire Vogue talk about it, I think it's a good place to go and listen. But I think

00:38:07.920 --> 00:38:26.699

For us at Lumen, you know, baking that into our overall governance of what becomes productized as an Agentic workflow is a very important step to make sure that it's secure, and to make sure that every intent continues to be inspected so that the intent of the agent stays kind of sacrosanct as it goes out there and is live, and

00:38:26.700 --> 00:38:29.139

You know, it's being worked across the environments.

00:38:29.140 --> 00:38:34.830

Yeah, and it was such a, like, lightbulb, again, on, like, for me.

00:38:35.450 --> 00:38:49.940

I'm like, hold on a second, there's consequences of all of these decisions, and then how do I… the other thing then became, like, okay, we gotta reset the expectations with our employees. Because an engineer used to do this, now 90% of what they do is different.

00:38:49.940 --> 00:39:03.349

And overnight, we just suddenly expected them to, like, get it, and like… and when I look back at that, I'm like, oh my god, Siobhan, like, come on, like, that… you would have thought that that was obvious, right? But I can guarantee you that there is a whole pile of people…

00:39:03.350 --> 00:39:15.280

that don't know that this is happening in their companies right now, because, like, that's just gonna be a thing, and I think that's where your governance conversation was really important, right? And I think for me now, we've got, like, a really good system.

00:39:15.280 --> 00:39:23.230

Where we, like, are able to, like, catch things. But also, like, our employees… our engineers have moved from being traditional engineers to builders.

00:39:23.370 --> 00:39:48.339

And the profile of that job is actually… we've shifted them away from traditional into, like, okay, this is… it's kind of like a new identity that they're moving into, because, like, we can't kind of just, like, change that. We've had to, like, upgrade, like, okay, well, this is actually the new role. So I think these are, like, real things that I think folks, you know, should be thinking about if you're in the role of Sarah. It's not just about, like, like, looking at tasks and thinking about where we design, it's, like, the consequences of doing that

00:39:48.340 --> 00:39:53.120

real. You know? And if you are sitting at the helm of one of the biggest companies in the world.

00:39:53.120 --> 00:40:05.380

and your technology, Sarah, is critical for, like, businesses to run and for things to happen, then there is, like, things that have to be put in place to make sure that the workflows are actually gonna be behaving themselves.

00:40:05.390 --> 00:40:17.289

And that the people that are kind of, like, the humans in the loop, essentially, like, are equipped. So, I think, like, we've had, like, the best, I feel like I've been in, like, a McKinsey simulator.

00:40:17.290 --> 00:40:38.749

Where they put me in there, and they're like, we're gonna, like, test you at every angle just to see, and every time, like, I go through these things with you, it's like, oh, okay, that makes sense, and that's a really important thing now, so as part of the SOP, we now had to reset expectations, like, what is the shift for the employees, so that they have an acknowledgement and an understanding about how the workflow not only works.

00:40:38.750 --> 00:40:53.280

But what does that mean in terms of, like, the change? So these are… these have been incredible, and this is why it's… I built the Pioneers Club, right? The Pioneers Club is all of the best customers in the world, in a room, sharing openly what's working, what's not working, like.

00:40:53.280 --> 00:41:02.620

feeding into product, making sure that we're building in the right direction, and everyone in those rooms are connected to being bold and also responsible as well, right? That's where it is.

00:41:02.810 --> 00:41:17.480

I mean, I think the Pioneers Club is, brilliant, Siobhan, and as you've said, like, people are really at the campfire, sharing what they're learning as we're going through this journey. When you don't know the end of the story, which we don't, because the models are consistently changing.

00:41:17.480 --> 00:41:24.580

You know, it's important that we share as we go. I'm a huge, learner, and I love

00:41:24.580 --> 00:41:32.580

Sharing what we've learned. We've been a huge, it's been a huge part of our journey of shaping, kind of, the AI path at

00:41:32.580 --> 00:41:39.760

at Lumen to be able to share knowledge and wisdom with, you know, Microsoft, with Reejig, and with other organizations that are on this path.

00:41:39.760 --> 00:41:56.360

Yeah, and your fingerprints are all over my business. Well, same, and we've really benefited from it. It's helped us move our work forward in a faster way, in a smarter way. And then I only anticipate that that's going to continue as we think about how our workforce shifts.

00:41:56.360 --> 00:42:04.100

I agree. One of the things that I have seen, if you look at my customer base, I'd say 80% of those have now got a U in place.

00:42:04.100 --> 00:42:22.149

that is now responsible for driving this, and it's, like, really exciting to see that most organizations are at the point where they realize that borrowing external talent, like consultants, to do this is like a bridge. It's not the destination, and they're now investing into creating departments like yours.

00:42:22.150 --> 00:42:27.149

And I think, like, you were one of the first to be stood up to do this, which was really, like, exciting.

00:42:27.150 --> 00:42:46.250

But I also think it's now a trend. And across my base, a lot of my time, honestly, is being spent, like, trying to help with the team design. And I think we'd love to get some feedback from you, like, to share with… you know, a lot of people that come to these meetings want to do what you're doing. They just haven't figured out the path to do it. They don't know how to present that up to their company.

00:42:46.250 --> 00:42:52.769

Would love for you to give a little bit of context into, like, one, how should someone position this to get

00:42:52.770 --> 00:43:07.950

sort of into that world that you're driving, it would be really helpful to understand so that the business sees value on that. And then secondly, like, what is the team capability? You've got an amazing team, by the way. Your team are lovely. Like, talk me through the type of skill sets.

00:43:07.980 --> 00:43:13.860

That you're gonna need to be able to deliver on this, because as people are starting to sketch up their team.

00:43:14.130 --> 00:43:31.539

I think your Blueprint is great. Thank you. Thank you for that, Siobhan. I think, listen, I'll talk first about, what I think is important to think about in kind of an AI world as you, move through, this

00:43:31.820 --> 00:43:41.969

kind of new way of working, and I think, that ability to think kind of systemically and think from a transformation lens is important, because as you were just saying.

00:43:41.970 --> 00:43:59.890

This work is like a transformation times a transformation times a transformation. It's very compounded, so being able to think big picture, and from, like, truly an operating model, what governance would be required, how do you work cross-functionally as a company to stand up

00:43:59.890 --> 00:44:03.739

you know, new ways of working in this AI and fast-moving,

00:44:03.800 --> 00:44:16.049

shift in technology is important, and it goes to, really the heart of the matter is that AI is really a transformation, it's not a new technology, right? So you have to approach this

00:44:16.050 --> 00:44:27.329

I think, you know, that's why you see Anna as our CHRO and our, you know, AI leader at the company, is that it truly is about transforming work. It's not just about a

00:44:27.330 --> 00:44:32.300

technology that you sprinkle along how work is currently being done. So that's part one.

00:44:32.300 --> 00:44:51.529

Part two is, in the midst of this, as a people leader, you know, this is about making sure that you're still connecting to your overall strategy at the company, understanding your AI why at your company, right? What's the why for you to actually create AI enablement at your company? Where is your company at in its current market stance?

00:44:51.530 --> 00:45:11.199

And what are you moving towards? And then, what does AI mean in that? And what's your narrative for your, leaders in terms of why we're adopting AI and where we're moving to with it? So that's part two, and I think that came through at Pioneers, that, like, you have to ground that in your overall strategy, and it has to be right for your approach and your organization and your culture.

00:45:11.210 --> 00:45:29.519

The next part is, as a people leader, I think that this work really docks into transformation, workforce strategy, organizational effectiveness, how are you really thinking through how the orgs will operate in the future? And then back to, kind of, that enablement.

00:45:29.520 --> 00:45:49.290

how are you creating both the change narrative, but also, like, the skill and the new work, evolution for every employee at different levels? And then I'd probably be remiss in saying, like, that learning journey of the toolset, mindset, skill set for actually helping people be oriented to how you use AI is foundational as well.

00:45:49.430 --> 00:46:01.870

Yeah. From a… from a team capability, like, if I'm putting… so, say I come and I pitch you, and I say, Sarah, like, I'm gonna… I'm gonna build the capability for our company.

00:46:01.870 --> 00:46:17.019

to be able to do this ourselves, because it's a forever change to work, and we need to have the capability. Like, you've got DevOps, and RevOps, and all of the different kind of, like, departments that were formed because of new technologies. I think this is another one. Tell me about, like.

00:46:17.280 --> 00:46:36.599

the type of skills that you're gonna need on the team to be able to execute? Like, is there sort of, like, skills folks that can be repurposed? Like, tell me a little bit about, like, the kind of, like, profiles of folks that you'll need to be able to deliver everything from, like, building up your work architecture and knowing your work, to redesigning to build? Like, what's the team look like?

00:46:36.800 --> 00:46:48.480

Well, let's, start at the highest level first. Let's talk about what kind of, like, behaviors or competence you want. We've talked about it throughout this discussion, Shiwan, but I think you want

00:46:48.480 --> 00:47:00.249

you know, sort of bold thinking and systems thinking. You want real judgment and product sense in terms of what you're shipping. You want curiosity and always-on learning, so the ability to relearn

00:47:00.250 --> 00:47:15.299

Consistently, and really dive in and be curious about what is the tool, where is it going, how do I combine this to actually have the future of work, right? Those are fundamental, kind of, competencies or features that you want to be hiring for across any function today.

00:47:15.370 --> 00:47:31.779

And then I would say also the resilience. Like, listen, this is changing fast, we don't know the end of the story, you don't… you want to make sure that you're, you know, really, looking at optimism and resilience, and you're either… you are fueling that, and you're hiring for it. So that's part one. Part two is.

00:47:32.380 --> 00:47:41.749

We're finding in the work, when you really are starting to think about what are the biggest value movers for the company, what are the really big movers for customers.

00:47:41.750 --> 00:48:03.590

you want, probably, a cross-functional pod that's going to move those intents forward. And that takes, you know, folks that are experts in AI, folks that can really dig in deep and help you process map down to your task, your subtasks, and really thinking through to your SOP. And then you want to combine that with individuals who are, in Microsoft's best thinking, a manager within the

00:48:03.590 --> 00:48:04.950

particular function.

00:48:04.950 --> 00:48:19.420

So they're truly a subject matter expert, a manager because you get faster change if a manager is involved in designing the future work, and then you want a change enabler and somebody who's also adept at upskilling.

00:48:19.420 --> 00:48:26.350

And that cross-functional pod, an extra credit is, take someone from outside the function you're trying to redesign.

00:48:26.350 --> 00:48:33.689

Why? Because if I'm trying to redesign the people team, and I've been very close to only, let's call it, you know,

00:48:33.690 --> 00:48:40.330

talent acquisition my entire career, it's a little harder for me to reimagine my function, because I'm so close to the glass.

00:48:40.330 --> 00:48:54.079

I also may have fear triggers, which is very natural around what's happening. So, in terms of moving your actual identified work forward, we think that's the future, but I always say within this work, listen.

00:48:54.220 --> 00:49:13.790

I may sound like I have answers, I am here to learn, just like you are. So where I am testing and learning, I do not know it all. You're in your lab! You're cooking! Learning as we go, yeah. I love it, I love it. You know what, like, gets me so excited? I was, like, smiling from the inside when just listening to you chat.

00:49:13.790 --> 00:49:22.340

This is the most exciting time in our careers! Isn't it just so exciting? I think this is so exciting. I think this is, like…

00:49:22.410 --> 00:49:36.019

What is the chances of being right at the forefront of this once-in-a-generation change, and you're kind of like this once-in-a-generation leader who gets to shape, essentially, the wiring of how your company will run?

00:49:36.170 --> 00:49:47.199

And I just think this is, like… like, how grateful of a moment to be part of what will be… you're essentially, like, laying the road that everyone else is gonna be on at this moment.

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So I think, like, I was, like, super giddy when you were doing that, because I was like, I feel… I felt like I was having, like, a little moment myself, where I was like, I'm actually here doing this, and this is real, and I'm talking to some women, and this is what we're talking about. And I just think, like, for folks that are listening, honestly, like, if you listen to what Sarah is saying.

00:50:04.290 --> 00:50:10.080

this is it. Like, it is… don't get me wrong, this is complicated and it's hard, sure, but, like.

00:50:10.200 --> 00:50:21.909

you can do it. Like, it's totally possible. You know, there's… she's giving you the Blueprint that's, like, laying it all out in terms of, like, what's important, how to think about it, what are the steps that you need to take. She's right up front.

00:50:21.930 --> 00:50:46.930

having all the pain and breaking things so that she's, like, feeding it back. I get the learning from that, because I get to build a better product, and I think this Pardabyte team, like, this will be the hottest team that sits in enterprise. Because, let me just tell you right now, the bridge thing around bringing in externals is a temporary gap filler, because every leader right now wants this to be forever changing, and they know they're going to invest into capabilities.

00:50:46.930 --> 00:50:52.090

So if anyone is on this, like, show listening, like, this is it. Like, if you need to…

00:50:52.260 --> 00:51:14.710

you know, come up with a plan. We will share Sarah's, like, thinking after this on how she shapes this and the team, because bring that to your leaders and talk about the team that you're gonna build, because I think, Sarah, this has been such an exciting, real conversation about, like, what's actually happening versus, what did you call it, the echo chamber on LinkedIn, where everyone's, like, peacocking about, like, the stuff that they're doing.

00:51:14.710 --> 00:51:27.430

And a lot of it is, like, not super real, true, whatever you want to call, like, you know, like, and that's okay, but I think the stuff which is really important is actually sharing the heart stuff as well.

00:51:27.430 --> 00:51:40.590

Yeah, and listen, we've been, you know, really, really served well by having partnership with folks like Reejig and Microsoft, so we've been really, you know, aided in our learning journey and in the lab.

00:51:40.590 --> 00:52:05.100

By those partnerships, you know, we are lucky. I have brilliant people on my team who have great skill and competence and org effectiveness, and thinking through radical transformation, and, you know, are really exemplifying our dare-to-lead behaviors, you know, of a learning mindset, and truly leaning into teamwork, and leaning into a customer-first mindset. And that really aids us in this AI journey, and then

00:52:05.100 --> 00:52:29.789

also, you know, just great leadership, you know, from Anna as our AI leader, to our chief AI officer, Rosella, you know, and Kathy, who's working on some of our biggest initiatives within AI at the company, and then our leaders, you know, who have been really thinking boldly through this journey with us. Anna is so impressive, by the way. So impressive. So impressive, and I think, like, I'm so grateful that

00:52:29.790 --> 00:52:43.490

we get to be part of your story, because I think, like, not only be part of the story, but also, like, you're with us on the journey, and feedbacking, and we build, and you feedback, and we build, and we learn a new thing, and then we build, and I think, like.

00:52:43.490 --> 00:52:57.280

maybe this is a once-in-a-like-a-moment opportunity where everyone's a little bit more open, because it is new, so there's a little bit of grace that's wrapped into, like, okay, everyone knows that everyone… like, you see how fast we're building, it's pretty nice.

00:52:57.280 --> 00:53:04.309

You know, like, and I think, like, sometimes things don't go well, and sometimes we make mistakes, but I think the partnership element with the pioneers is, like.

00:53:04.320 --> 00:53:19.459

If it doesn't work, shut it down. Like, shut… like, there's this, like, don't get caught up on, like, on the small things, like, keep going and keep trying and testing and iterating, and I think your point about the models at the very opening of this call was, like, you gotta ride the wave of the models.

00:53:19.460 --> 00:53:30.820

That's so true at the pace that the change is coming in. Something that you build today might be our date by Friday, you know? Like, and it's like that whole, like, shift that's happening as well in the space.

00:53:31.020 --> 00:53:48.489

I have thoroughly enjoyed this session. Before you go, like, if you were to leave us with kind of, like, a context bomb to take everything home, I think a lot of people will be on the Peloton listening to this as well after this, so get us going, like, tell me, like, what's that kind of leave us with thing?

00:53:48.500 --> 00:54:00.149

Yeah, my two context bonds, I think, would be three points. You know, the first, Siobhan, is, be human first in this agent… in this agent creation journey, right? Yeah.

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We want to design the future of work with a human-first mindset, so that's my first ask of all of those that are in this work, is be human-centric, help humans move along in this work, and, you know, think about what's the best

00:54:14.910 --> 00:54:20.329

for humanity, as we bring on ancient partners. That's part one. Part two.

00:54:20.330 --> 00:54:37.679

Second… second bomb, you know, a little more, spirited, is, you know, those that are moving fast and reimagining the future of work and really thinking through, like, their operating model and how work will truly be, you know, future ready with agent partnerships, those are the ones that will win.

00:54:37.720 --> 00:54:45.419

Right? Those… they're reimagining how work will be in the future. We are going to be the ones that are the pioneers, that are saying…

00:54:45.600 --> 00:54:52.080

here's what the future truly looks like, you know? And the last is, like, just more holistic, which is, like.

00:54:52.080 --> 00:54:55.899

Do what you love, share what you love, and share what you're learning.

00:54:55.900 --> 00:55:18.729

Yeah. Sharing the learning, I agree. Yeah, share your learning. It's always great to bring, whether it's somebody that's brand new in the field, or somebody that's, you know, you know, right along in there, learning along with you, bring others along. I mean, be safe about your firewalls, be safe about what you're sharing, you know, be wise about your company, but share your lessons, right? We can all… we can all benefit from that.

00:55:19.500 --> 00:55:30.489

Sarah, incredible. I think I need a nap. I need a nap, I'm so excited. Overstimulated. This was incredible, and thank you to everyone dialing in.

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For the next show, we will see you next week. Until then, you can download the Work Architect course, and it'll bring to life everything that Sarah's saying, but we'll also share after the fact the Blueprint for how Sarah is going to bring this whole to life for you. Thank you, folks! Thank you, Sarah!