Open-Ended Sessions: Workflow Archaeology
A conversation about how considered use of AI can help small and medium-sized businesses thrive.
In the spirit of working with the garage door open, we’ll do periodic livestreams to share what we’re learning at unfinishe_.
In this first “Open-Ended” session, we discussed:
The principles that led us to start the business.
Insights from Reid Hoffman’s and Greg Beato’s new book Superagency — especially as they apply to small and medium sized businesses.
Workflow archaeology, our approach to designing solutions that are aligned from both a strategic and human perspective.
We’d love to know what you think.
Transcript
(AI generated.)
Jorge: All right, Greg. Good morning, sir.
Greg: Yeah, good morning. Well, it’s good to see you live streamed.
Jorge: I’m excited, yeah, same here, and just before we jumped on, we were having a bit of a fingernail-biting moment trying to get everything set up right. We’re very much figuring it out as we go. But we are doing what I think are interesting things, and we were hoping to share with folks. And this seems like an easy way to do it. Do you want to explain a bit about what this is all about?
Greg: Yeah, thank you for setting it up nicely and actually talking about how this is an unfinished moment in and of itself. Jorge and I have known each other for a long time, and we’ve worked together at moments. And we’re both really fascinated by where we are right now—the culture and the implementation of technology and AI. I think we both feel like a lot of the things that we’ve learned in the past aren’t really applicable in this new environment, and that we have to learn new things. At some level, learning those new things means disrupting ourselves and examining practices that we’ve held dear over the last 20 years in our careers and seeing if they’re still valid, and then also exploring the territory that’s available in this new space. Right? And I think we started that conversation and decided, hey, let’s put something together. And so we started this thing we’re calling Unfinishe. The D is missing on purpose. It tells a story about, I think, the market, the space, and the place that we find ourselves in. I don’t know, maybe you could talk a little bit more about your… I’m taking some airtime here, so you jump in and talk a little bit about what you think Unfinishe is.
Jorge: Well, I just wanted to touch on something you said. I think you said that the things we learned in the past aren’t applicable. Is that what you said?
Greg: I said that we need to re-examine. I did, but I think what I really meant was we need to examine whether they are still applicable.
Jorge: Right, right. Well, the reason I started there is because there’s a flip side to that, which is that as disruptive as the current moment feels—and we’re talking specifically about AI, right? Like, there is a new major technology that is upending a lot of things. And as disruptive as this moment feels, both you and I have been through another disruptive moment like this, which was the dot-com era, you know, the appearance of the World Wide Web in particular. Right? That was a major, major thing. And we now kind of take it for granted because it’s become so pervasive in our world. But I remember going through that time when design was up in the air, and publishing was up in the air, and there were all these things where it’s like, well, this needs to be reinvented clearly because we have this different thing happening. In retrospect, it feels like, well, of course that’s how it would turn out, but it wasn’t obvious at the time. And it entailed a lot of experimentation. And part of the reason why, circling back to Unfinishe and the concept of making things that are unfinished, is I think that we have this drive for closure. We want things to be neatly wrapped up. But in times of transformational change like we’re going through now, we don’t really know how things are going to turn out. We don’t really understand the technology’s implications yet. We’re in the process of discovering that. And one of the things that I learned—and maybe you can chime in on your experience—but one of the things that I learned from the previous wave of disruption that I was part of was that you can have these big ideas about how technology is going to transform things. You can have ideals about how it should transform things. But the changes actually happen more incrementally through a bottom-up approach with people trying things, seeing what sticks, and then that is what affects the transformation.
Greg: So, yeah, it’s a maker-builder mindset, right? You know, I oftentimes talk about how some people think to make, and others make to think. I think we’re both makers. One of the things that’s interesting about this space is it’s emergent, right? There’s a conversation going on. It’s really fast. So I think that’s one of the things that’s a little bit different. I don’t know if the dot-com era moved fast, but this era is moving super fast because every week there’s some new model, capability, discovery, or insight. So it’s challenging. I actually think that’s one of the things that we’re thinking about with Unfinishe; it’s also helping organizations make sense of the moment by making practical things. Our insight is that we’re not suggesting that we’re super experts in this space, but what we are saying is that maybe we’re eight weeks ahead of you. We can help be a little bit of a Rosetta Stone or a wayfinder for organizations around how to understand how to use these tools and think about it in a really practical way. I think that’s the basis behind why we think Unfinishe as a consulting practice is actually valuable and necessary right now. In the space that we’re looking at—which is small and medium businesses—and this is something we should also talk a little bit about: why are we looking at the SMB space? There are a whole bunch of opportunities to help organizations punch above their weight, to help them manage some of their complexity more effectively so that they can focus their attention and energy on the things they really love or growing their business in a way that makes sense to them. Some of these tools do give you some superpowers. So how can we help organizations make sense of which ones to use and which outcomes are more applicable now and are most useful? I think that is a journey that we want to help people on. Just back to why we’re calling ourselves Unfinishe. I think one of the things that business leaders have to recognize in this moment is that you are either evolving or you’re not, and that transformation is something that you need to continuously invest in and have a mindset around. Your point earlier that you talked about closure or completion or having it all figured out— I think the ethos now is to dive in, experiment, make, find your way, and keep on that path while recognizing that you need to keep moving forward.
Jorge: I love that you use the word evolve. I will draw a distinction between evolving and reinventing. Because so much of what one reads out there—when people write about AI—and I’ve seen this with a lot of other consultancies, it’s like the pitch is, you need to reinvent your business for the AI age. I think our approach is more, “You know what? That sounds like premature optimization for a world we don’t really understand yet.” It’s much better to try these very carefully defined, pragmatic experiments that help you make steps towards an alternative future, as opposed to this whole huge initiative where it’s like, let’s reinvent everything and rethink everything from the ground up. All right. Let’s not belabor Unfinishe itself. We’ll have more opportunities in the future to talk about what we’re doing in the business. We’re talking about Superagency. This is a book that I had not read. You suggested this book, and I was hoping that you could talk a bit about why Superagency? Why this book? And what is this idea about?
Greg: Yeah, I mean, I think it’s one of the pieces of content this year that tries to unpack where we are in this moment. Hoffman’s book has a couple of tenets in it that I like. One, he talks about technological transformations historically and sort of recognizes the societal disruption and the ramifications of that in those moments to give us a compass for what’s happening right now. What do I mean by that? He talks about the invention of the steam engine, the reaction to industrialization in the Luddite movement. He has a kind of model for a two-by-two of different characteristics of people who have a point of view about where AI is from, you know, when he calls it doomers who believe it’s the end of everything and, you know, the zoomers who are like, “No regulation, no AI at all costs,” etc. And that framework, I think, starts to establish, you know, and then there’s bloomers and gloomers, right? So there’s the four quadrants. I tend to see myself as a bloomer, but that’s because I’m an optimist, and I believe that we get to choose the future we want to live if we’re intentional about how we operate. I think this is one of the things that’s very important, actually, about right now—that we need to be looking at these tools in a really smart way and make sure that humans are in the center of the conversation. The last tenet in his book is around agency, and that these systems should enable us to have agency—that we get to make decisions, that we get to make choices, that we get to use them for things we think are valuable. Obviously, there’ll be some disruption in employment, for sure, but there’ll be new opportunities that emerge out of this technological change as well. That’s why I thought the book was interesting—because it was trying to put this into a context of, “We’re in a messy moment. The way out of that is to actually be intentional about doing things that have a positive impact.”
Jorge: You talked about the four profiles. And I think the way they—it’s two authors, Hoffman and Beato—but I think of this as Hoffman’s book in some ways, right? They talk about these four profiles as people who are part of the conversation. They say these are voices that need to be in the room—you have to accommodate that discussion. You said that you associate or think of yourself more as a bloomer. When I read the book, I too thought, “Totally, I’m a bloomer.” People watching this might not have read the book. Could you give a brief outline of the bloomer profile? And while you’re thinking about that, I’ll say we do have people tuning in. I’ll just put it out there. This series is called Open-Ended Sessions. The idea is to make this a conversation because it’s unfinished, right? So if you, who are tuning in, have any questions for us or any comments, please drop them in the session chat. All right, Greg.
Greg: Yeah, so bloomers, right? I think bloomers are optimists. They believe in progress, and they believe there are opportunities that can be created by the emergence of new technology, identifying opportunities to use that for positive outcomes. I feel like that is my mindset. I’m not unaware of some of the challenges and issues and problems that are materializing because of this change or this moment we’re in—the environmental consequences of building data centers, the background of how the content has been created. But I feel for me—and one of the reasons why I think I want this partnership you and I are putting together—is to be intentional about helping organizations make the choices that make sense for them and allow them to be successful and do it in a way that’s human and places humans in the center of the conversation. That’s the kind of work that I want to do. I think the bloomer category is someone who believes that the long-term impact of this is actually going to be good for society. It may be rough in the beginning, but there are positive outcomes to be had. But it means that we have to put in the effort and the energy to make sure that that happens.
Jorge: The phrase that kept coming to my mind when I was reading the book is this is a glass-half-full mindset. But that doesn’t mean—it’s an optimistic approach, right?—that doesn’t mean a Pollyanna approach. To your point, there’s a recognition that this is a very powerful technology, and like all powerful technologies, they need to be deployed mindfully. Now, the devil is in the details, right? The question is, what does that mean? They get into a bunch of things about regulation in the book, which I don’t think we’re going to touch on here. But you mentioned when you were introducing the work that we’re doing that we have decided to focus our offerings toward small and medium businesses.
Greg: Yeah.
Jorge: I’m curious about this idea of superagency and what it might mean for small and medium businesses. I have ideas about that, but I’d love to hear your take on what those are.
Greg: Yeah, I mean, I think one of the things that’s interesting is that small teams can do more things in a way, right? That’s evidenced by some of our work. If you think about, you know, one of our more recent engagements, we discovered that an organization we were helping was spending a significant amount of time doing administrative tasks to fulfill legal requirements and compliance requirements for their work. We’re talking vaguely because they just don’t want to say who it is or what they’re up to. That number was increasing over time, hitting their margins, and they didn’t really understand what was going on. At a certain level, it was sort of like they were like a frog in water—turning up the heat, they’re getting boiled by more and more content they had to manage. This was preventing them from doing the things they wanted to do, the things they valued, and the things they felt differentiated them in their marketplace. One of the things we did was work with them to try to understand how they operated. From that, we discerned what might be simple, small, practical things that they could automate or use AI to assist so that they could focus their attention on things of high value to them. That’s an allegory for what we can help small and medium businesses with. You said it right: no one loves to do the laundry. Some people do, but most people don’t like to do the laundry. So let’s help you do your laundry so you can focus on what’s truly important to you. We can talk a little bit about how we’re doing that. The second thing is small and medium businesses are much more willing to try things and experiment. You don’t have the layers of bureaucracy that might hinder a larger organization around what you can and can’t do. The opportunity for innovation could be higher.
Jorge: I want to be fair; the laundry analogy comes from—I’m not sure how to pronounce her surname—but Joanna Maciejewska. I must be butchering that. She put out a tweet saying that the problem with AI was directionality—we’re trying to automate the wrong things. We’ve been automating writing and creating art. What we want is for AI to automate doing the dishes and the laundry so that we can focus on writing and creating art. I think that’s fundamentally right. I think it’s also more… It feels to me correct regarding the state of the technology itself.
Greg: Yeah, I agree with you there, too. Is it ready for all of this agent-to-agent conversation stuff that’s going on? I don’t think so. Maybe at some point in the future, but what we found in the engagement I was just talking about is that, in the abstract, technology alone isn’t something that will land in an organization. You need to understand the culture of the organization, how people work, their mental models, and the flow of information. We came up with this term; we call it workflow archaeology. It’s a bit different than service design practice or the UX space we’ve come from because it requires some additional investigation, but it leverages that skill set. It’s understanding the journey from start to finish of an outcome or a job—something valuable for an organization. Then you have to dig in and see how that happens. You need to understand the information flow, the shape of the data, where it’s stored, and how it’s managed. You also need to understand how people expect it to show up on their desktop or in any way they work, and then you can affect change. You can add a small intervention or a small evolution— I like the word evolution versus reinvention. Evolution enables a performance gain or improvement or unlocks some extra capability they’ve always wanted to do but haven’t been able to do before. You do that incrementally. This moment isn’t calling for us to blow up the firm and say to start over; it’s much more about getting you up to speed on one thing so that not only do you have something valuable, but you also start to understand how these things work so you, as an organization, can recognize how you want to use them and what they mean to you and what’s meaningful. In the case of the organization we supported, we delivered an outcome that led to productivity gains, but their intention wasn’t to let go of people; their intention was to spend more time on things they viewed as high value. Every organization is going to have a different calculus about what matters to them, but right now, these things have to be small; they benefit from prototyping your way of making. We talked about this maker mindset earlier. That’s part of the journey we want to help people take on—practical, straightforward things you can do that add value as quickly as possible.
Jorge: And I think that’s part of the actionable outcome of an engagement like this—the thing you can fire up Monday morning and start doing that changes your workflows and hopefully relieves people in your team from drudgery. But I think there’s another level of value that comes from these engagements, which is that they help the organization get a sense of direction.
Greg: Yeah. I think this is an important piece of the puzzle. Maybe you can talk a bit about how we do that, but this is a really important perspective because many organizations—probably most—don’t know where to start. If they are doing things, they’re often in an unintentional way. There’s a fair amount of evidence that says people are using AI, but it’s not giving them any positive outcomes; it’s just burning time as people sort of goof off or experiment with it. What’s your perspective on that? Why is that so important, and how are we doing it?
Jorge: Well, the sense I get is that there must be a sense of the emperor’s new clothes in people’s minds right now—in that you read the news and see these huge investments happening in data centers and organizations cutting human positions to invest more in AI. There must be a lot of people wondering, what is the AI doing? The experience most people have had with these tools is through chatbots like ChatGPT. What I’ve observed, and I think you’ve seen this as well in talking with folks—especially in small and medium businesses—is that there is curiosity about AI. You can’t help but be curious if you hear about it in the media and everyone is talking about it. Oftentimes, what happens is the organization’s leadership will take someone in the firm—usually from IT—and say, “Okay, you’re our AI person, figure this out for us.” What that person does is get a ChatGPT business account for the firm, give a few people in the company accounts, and then people start dabbling with trying to automate their workflows without any clear step in the process where they are provided a mental model about these tools, how they work, and how they can help. They’re also not given a holistic understanding of where these tools fit into their information workflows because it’s being done ad hoc.
Greg: Yeah.
Jorge: I think one of the tenets that is somewhat unacknowledged, but is central to the work we’re doing, is the fact that all businesses nowadays—all modern businesses, anyway—are, in some sense, information businesses. They have to move information; they have these information workflows where data moves through the organization. If you understand what the technologies can do (and you talked about us being like eight weeks ahead— I think that’s a fair assessment), the idea is to try to grip the capabilities and constraints of the tools. So that’s one aspect of this: understanding what the tools can do. Then you can gain an understanding of the organization’s information flows—how is this organization operating so you can identify areas where people are expending inordinate amounts of time and resources doing things that are necessary for operations but aren’t necessarily adding value to their customers? All companies have to deal with some degree of bureaucracy, and my emergent sense is that particularly large language models can be valuable in helping alleviate some of that tedium so people can focus their time on things that, A, add more value to their customers, and to their companies, but also that they enjoy more. No one likes having to deal with red tape. The point is that part of the value we’re trying to bring to organizations through this process of workflow archaeology is that by understanding the information flows and where the tools might help, the organization gains a new understanding of what the tools can do and a sense of direction. It’s not that we’re going to reinvent the company from day one, but at least we start developing an emergent roadmap of where the low-hanging fruit is and let’s start with a few pragmatically chosen areas to focus on, so we can begin gaining the competency internally to evolve toward that different state of being.
Greg: Yeah, and I think you bring up a couple of important points there. One, it’s a journey that we are bringing our clients on so they gain competency, right? One of the things we’ve built into our engagements is that part of what we’re doing is teaching. We’re showing you a methodology; we call it workflow archaeology, but we’re showing you a methodology for understanding how to make the tacit explicit in an organization, how to identify the IP of an organization—the things it cares about, the culture, the business processes that matter, the things that make them valuable. I think people may think in the back of their minds that many organizations—including small ones—might have a role in which someone’s only job is red tape. That’s also something to help people recognize: as these tools enable us to do more routine, repeat tasks more effectively and efficiently, you need to help your people gain and acquire new skills or focus their attention and energy on things that will benefit the business in new ways. I think we’re trying to promote is a perspective of the evolution of your organization, not revolution. The people who work with you and for you are there with you. That’s another reason why I like small and medium-sized businesses: small and medium-sized business owners are much more in relationship with their employees; many of these kinds of organizations are almost like families. If they care about what they’re trying to accomplish as a business and they care about their people, we can help them transition their organizations to take advantage of these tools while also growing their business or managing it in a way that’s meaningful for them. It’s an interesting moment to be in.
Jorge: There’s another dimension to this, which is that the information itself—if you buy into the idea that all businesses have these information flows as part of the lifeblood of the organization—the truth is that most organizations, even though that is true, probably don’t understand themselves in that light. A lot of that information is managed in a very ersatz way. It’s certainly unstructured. One of the things we are learning—and maybe we can pivot to talk about some of the lessons we’ve learned as part of this initial engagement—is that when you start working with AI, you’re going to have an easier time if the information you’re working with is structured. And hey, guess what? AI can help you do a first pass at structuring the information. I’m mentioning that because I talked earlier about our being eight weeks ahead as one of our differentiators. I think another one of our differentiators, frankly, is that we come at this problem space from the perspective of information architecture and this designerly approach of understanding how information is structured. The idea is like you were saying: to augment your people so they can create more value and enjoy their work more, as well. One way that happens is not just understanding the flow of information but also the state of the information and doing something about it. That might be that the doing something might have nothing to do with AI; it might be that you discover that your information systems are not up to speed to work with AI. You might need to upgrade those. What ends up happening, maybe, is that the AI thing ends up being a MacGuffin for this broader transformation that probably needed to happen anyway. This is just kind of the reason to get it done.
Greg: Yeah, and I think you’re bringing up an important point: that’s why we don’t call it workflow anthropology. I think we both have a design and research background, and we certainly want to research and understand how people work and see them at work. But the reason we’re calling it archaeology is that there’s this new element: the structure of the data in the environment we’re working with. Small businesses tend to not even understand that; they just build it incrementally over time, connecting different technologies, using different stuff. It becomes how they work. You need to be able to unpack it and see how the humans in the system use it; that might be the more anthropological or research lens. But you also need to see the structure of that information and its compatibility for large language models to make sense of it. You hinted that there might be some work to do organizing it more successfully so you can get better accuracy or make it machine-readable. It’s almost like there are layers to the organization that you have to appeal to in this new moment—some of service design, some user research, a bit about spelunking into the technological platforms that organizations use. It’s looking at the files— the artifacts they have— and seeing how they’re formed and shaped and the degree of variety or variation that exists in them. One of the interesting things about us is that we’re not really focused on a hypothesis when we come in; we want to start with artifacts. We want to look at the substrate of the organization and explore it. Like archaeologists, you dig a little of the dirt, find the first layer of civilization, and come up with some thinking about what’s going on. You dig the next layer of dirt and find the next piece. It’s important to understand how people actually get things done, and then you can make suggestions about what to do. One of the lessons we learned recently with this engagement was we saw a process and were like, wow, if you did this differently and this differently, you could achieve this huge productivity gain and here’s how you could do it. It was almost like the management consulting version of showing up with a hypothesis, and the ROI would be an enormous number. Our client just looked at us and went, that doesn’t feel right to us. We don’t believe you and don’t understand this. We had to reset and ask, what’s important to you and the way you work? We found this key insight that drove an outcome they didn’t want to change. It was cultural, and it mattered to them. So from that, we said, Oh, okay, now we know this: We have to get really small, micro. We have to look at one small improvement we could make. We did it—it was valuable to them. Now they’re on this path of, hey, this makes sense; what’s the next small thing we could do? This part of our perspective is to take people on a journey one nugget at a time or one, you know… I’ll probably overuse the archaeological metaphor, but we’ll dig down another layer.
Jorge: I think you started touching on something there that I wanted to expand on because we actually have a question from Katherine in the chat. She asks, “Can you talk more about the deliverables to the organizations and businesses supported? I like the term emergent roadmap. What would that include? Detailed documentation? How-to guides?” So, what do we deliver, Greg?
Greg: Yeah, so I think one of the things we’ve done is we prototype from the beginning. We’re constantly making. I can give you an outline of the things we did and want to continue doing. We ran a workshop with our client around how they work, helping them identify jobs to be done or workflows or outcomes that were particularly important to the firm but where they were spending a lot of time. Then we started making stuff with them. We explored the art of the possible together. As we went through this process, two things happened: one, they started learning to use these tools and were surprised by the efficacy of the results. We were surprised sometimes—like, wow, that didn’t work, or that could work if our data structure were more organized. Oh shoot, we need to do that before we can make this happen. In the end, we built, you know, we built an agent. It’s not an autonomous one—it’s one that you work with. There was a huge aha moment in there. I don’t know, maybe Jorge, you were more involved with this and want to talk about the importance of understanding the discernment of an organization and the collective knowledge in being able to build something that sorts through, triages, and does the right work. How did you do that? Talk a little about the last mile of the effort we did.
Jorge: Yeah, and you talked about starting with prototypes and the last mile, which is right: it’s about prototyping throughout the process. You mentioned skepticism, which I expect we’ll encounter a lot, because many suspect there’s a lot of hype around this stuff. The quicker you can get to testing hypotheses and validating hypotheses… When we did the first pass at the workflow archaeology thing in this engagement, we came out with a couple of hypotheses about what might be good uses for AI in this context. The immediate next step should be, “What’s the minimal test we can do to validate this hypothesis?” It might be that the data isn’t there; it might be that the culture isn’t there. It might be, and this is now going to your question, that the knowledge that needs to be articulated as part of this AI assistant or agent or whatever you want to call it is so dispersed culturally in the organization and not described explicitly. A lot of the knowledge—if you want to use tools that help augment people’s work—you have to get people to express what it is that they do.
Greg: And that’s important, right?
Jorge: Exactly. The thing is, people don’t tell you what they do—you have to find other ways of getting that out. Prototyping is one way to do it, right? It’s a way to get that done. That is one of the, I think, deliverables to Katherine’s question. But also to honor the notion of the emergent roadmap, the other thing we worked on in parallel is basically a business case. It’s not just about building a proof of concept here—something that is like a minimal test, a minimal validation of whether there’s any “there” there. If that test proves successful, then what would it mean to scale this? What would it mean to get it into production? You want to come out of this process—not just with a tool that someone can use to automate a particular workflow, but also a sense of direction of where we could go next and how to take this initial experiment and start moving it so it has a larger impact. One way to do that, I think the grown-up way to do that, is to start putting numbers to it and having the numbers be realistic so leadership can make decisions about whether this is something they want to invest in or not.
Greg: Yeah, I think we had another aha moment. We invested in building a pretty comprehensive model; we did time on task, understood the billable rates, the team costs, and how much time it took to accomplish things. We could give a very accurate picture of if the evolution we were promoting—the prototype we had—was utilized at a certain level by the organization; they could achieve this outcome. What was really interesting was and unexpected—they asked a really good question: “Okay, now that we have more time because this effort we solved is going to give us time back, what do we use it for?” That was a really interesting and valuable question and one of the things that’s interesting about small and medium businesses: their perspective was not that they needed fewer people but that they reduced some aspect they didn’t want to manage. They asked how they could use this gift of time toward something meaningful for them and what the value of that would be for the firm. That’s harder for us to solve for, but we can facilitate conversations around goals and outcomes. One of the interesting things about our work is our last client walked away with a recognition of part of their business they didn’t even understand and its implications. They didn’t understand that part of their business they’d been doing forever was consuming more time. It was like a frog boiled in water; if they hadn’t paid attention to it, it would cut their margins to the point where the business would be less successful, and they wouldn’t understand why. This process of workflow archaeology isn’t just about the technology; it’s about helping identify and see yourself as an organization and then ideally craft a path toward a better outcome. To come back to the question that was asked, part of what we did early on—and this is really important—we helped them prioritize the outcomes and workflows against the current state of AI. That gave them confidence: we had this two-by-two framework where the upper right quadrant was high value and easy to do. So we said, “You should just work on those right now.” The other things all sound cool and could be transformational and amazing, but let’s work on practical things of high value that conceptually have high value. Let’s help discover what those are because they may not be the things that people talk about—the things they think are high value are the things they love to do. But in terms of pushing an organization forward or allowing it to achieve its goals, the necessary things often are the important things. If you can make those more straightforward, the benefits accrue over time. Part of what we left them with was a roadmap of what’s the next workflow they should tackle. They don’t need us anymore to do it, which is interesting, too. We taught them how to do it.
Jorge: I wanted to circle back to something you said because it was intentional on our part: helping the client understand their current state better. When we originally discussed the offering, we riffed on an old Velvet Underground song and called it “We’ll Be Your Mirror.” You remember that?
Greg: Right, right.
Jorge: That’s because this technological disruption—this opportunity—presents one of those rare moments where you can step back and examine the state of what you’re doing. Organizations are systems, and long-running organizations are complex systems that have evolved over time to perform their functions. These engagements present the rare opportunity to take a step back and take stock of how the whole system is operating. Obviously, you want to improve how it’s working; that’s the whole point of the engagement. But, at a minimum, if you get nothing else out of it, having that high-level picture—even if we’re just a part of the business—is really valuable. I want to pivot here because we have about six minutes left.
Greg: Yeah.
Jorge: By the way, Katherine is following up and saying they work in government, and this process is very applicable there in addition to small and medium-sized businesses. Yes, I believe that’s right, Katherine. When we say small and medium-sized businesses, departments within large organizations sometimes function like small and medium-sized businesses. Enterprises have different constraints, making them slightly different. I suspect that government does as well. That’s a good point. What I wanted to suggest, Greg, given we only have about five minutes left here—and we didn’t plan this beforehand, so again, very emergent, unfinished conversation. What would be one takeaway for folks tuning in? Something that maybe they can do differently or think differently about this new technology that, I don’t know if I want to complicate by saying, might be counterintuitive or might be surprising. Something we’ve learned that might help them.
Greg: Yeah, I mean, I think culture is really important. People talk about how culture eats strategy for lunch, right? You need to understand what’s important to people. You can anchor this kind of work into that so it feels like it’s part of a journey people are on together. That may sound altruistic and optimistic of me, but personally, I think one of the reasons you and I are doing this is that we want to see real impact and see that impact is meaningful, where humans have agency in the conversation. If you just talk about the technology, you won’t understand that aspects of the way people currently work will stop you from making progress unless you understand it. If you understand it, then you can use that as an anchor to drive something forward. So don’t ignore…
Jorge: Culture. I love that you said culture is important, and I will add that culture is also fragile.
Greg: Very much so.
Jorge: Organizations with a dysfunctional culture probably want to change it, but I would expect those folks might not be looking to institute or add AI to the mix necessarily. So assuming that the culture in your organization is healthy—which was certainly the case with our client—then I think a question becomes how do you introduce such a disruptive technology without ruining it? That’s yet another reason to delve into this new space, but do it mindfully, not with the goal of transforming the whole thing from the ground up day one, but rather, let’s take this one step at a time. Let’s ensure it’s true to who you are as an organization and helps you become more of who you are, as opposed to trying to change you into something completely unrecognizable.
Greg: Also allow you to recognize what change you will have to go through. This isn’t going to happen overnight, right? Even for small and medium-sized organizations, there will be some disruption and impact and roles that will change. But do it in a way that’s intentional and mindful, so you understand the implications. Don’t just do it. I know that’s more than one thing, but I think that’s important. I think you should also make stuff. That’s something to help impress people with—don’t just make anything, but be focused on what you make first. That may not have a benefit immediately, but at least you’re focused on it. Then you learn and make the next thing. Don’t try to do everything at once. Be focused and intentional about the evolution of your organization. If we can help organizations do that, then I think you can give them comfort about their trajectory. Leadership will have agency and ideally communicate that to their employees so they can evolve together in this new environment rather than have it imposed on them.
Jorge: Yeah, that’s a superagency thing, right? It’s not being imposed on me; I’m a participant in this. We are at time. I think this was a great first conversation. We will have more of these. For those who want to follow up with us, our website is unfinishe (without the D)—unfinishe.com—and we do have a Substack where we’ll be posting hopefully fairly regularly what we learn; that’s at thoughts.unfinishe.com—so Unfinishe Thoughts, basically. All right, Greg, thank you. We will let folks know when we have another one of these scheduled.
Greg: Thanks. All right.
Jorge: And thank you to everyone who tuned in, by the way.
We’d love to know your thoughts—especially since we plan to do more of these. Are there questions or topics you’d like to bring to the table? Please let us know in the comments below.