Episode 166: Building Products and Riding the Wave of Cutting Edge AI with Darren Wilson, CPO of Soul Machines
In this episode of the Product Thinking podcast, host Melissa Perri is joined by Darren Wilson, Chief Product Officer of Soul Machines. Join them as they explore Darren’s journey to CPO of Soul Machines, a company that produces digital humanoids. They discuss the challenges of building digital avatars, keeping up with AI technology, and leveraging user feedback to shape product strategies.
You’ll hear them talk about:
07:53 - Darren shares insights into the journey of Soul Machines. Started by Mark Sagar, a special effects expert who developed motion capture technologies for blockbuster movies, the company focuses on creating digital avatars that can connect with users in more empathic ways. Initially, Soul Machines pitched avatars as digital assistants for sales and customer service. However, avatars work best when empathic and personal connections are needed, such as helping people make difficult choices or practicing challenging conversations.
12:29 - AI is rapidly advancing. Darren shares that Soul Machines is fortunately riding the wave of development and are able to pivot away from relying on external platforms such as Google, IBM, and Microsoft. They've also introduced ChatGPT into their platform, reducing time to market for customers. The challenge is continually adapting to LLMs coming on board and increasing the multimodality in the Soul Machines platform. Darren says that the challenge is consistent for the product team, with focus and prioritization being crucial inidentifying what the biggest opportunity is for the platform's growth. Understanding what truly adds value to customers are critical.
33:55 - Darren's unusual journey to CPO has shaped his approach. Coming from a design background, he emphasizes the importance of user research and involving real people in the product development process. He also encourages making engineers into advocates and bringing cross-functional teams together. Darren shares that being more open to discussion and less focused on delivery is an advantage he’s gained from his non-traditional background. Plus, always listening to good ideas from technical people and those more knowledgeable than yourself helps in the transition from design to CPO.
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Intro - 00:00:01: Creating great products isn't just about product managers and their day-to-day interactions with developers. It's about how an organization supports products as a whole. The systems, the processes, and cultures in place that help companies deliver value to their customers. With the help of some boundary-pushing guests and inspiration from your most pressing product questions, we'll dive into this system from every angle and help you think like a great product leader. This is the Product Thinking Podcast. Here's your host, Melissa Perri.
Melissa - 00:00:36: Hello, and welcome to another episode of the Product Thinking Podcast. Today, we're joined by Darren Wilson, who's the Chief Product Officer at Soul Machines. This is the company who produces digital people through the use of cutting-edge AI technology and animation artistry. He's helped secure customer user growth quarter-on-quarter, and he's been evolving the platform to meet the ever-evolving generative AI landscape. His career has seen him go from London to New York to New Zealand at both companies big and small. But before we start talking to Darren about this really exciting landscape, it's time for Dear Melissa. This is our segment where you can ask me all of your burning product management questions. Just go to dearmelissa.com and drop me a line and let me know what you want me to answer on a future podcast. All right, this week's question.
Dear Melissa, can you explain the difference between product ops roles and strategy and operations roles? I'm seeing both on my job hunt, and there seems to be some overlap in the job descriptions.
Great question. Okay, so strategy and operations roles are interesting to me because they vary greatly depending on the organization. Many organizations, I've seen them sit outside of product management and not inside product management. And in those roles, they have been kind of looking at the market, looking at where should we play, who are the personas we should target, what kind of industries are out there. And they're doing things like TAM and SAM segmentation, stuff like that. And usually that's being fed into the product management team. But it's very much calculating those things out and trying to figure out where the strategy is. Now, in some organizations, I've seen them define the product strategy or define what should be built and then hand it down to the product organization. I want to say that I think that's bad. I don't think you should be separating out strategy and product management into two different organizations. I think they need to live together in a software. If you're doing a lot more than software, I could totally see where that operates. And maybe you will find that in organizations that are more than software, not SaaS companies, right? Like it could be stripped out. Then I could see it as a broader, overarching corporate strategy type thing. I get that. In a software company, though, I believe that product and strategy go hand in hand and we should not separate those out.
So you're going to have to ask yourself in the strategies and ops roles, are those for product or are they for the company in a broader part of the organization? That would be a key difference between that and product operations. Product operations, you may be doing stuff like TAM segmentation or SAM segmentation, which could definitely help the product team. That's that market research aspect of it. Or you could be working on many other things. Product operations, really the goal here is to remove obstacles from doing great product management and doing great product strategy. So when we break it down into the three pillars, there's many different places that you could actually play. If you're leading a team, you're kind of bringing all these things together. But I would really ask the organization what they mean by product operations. You could be doing things like helping to bring in the right products, let's say, to view strategy so that you're helping to bubble up to leadership and to the rest of the product managers, like the stats and the health metrics on their products, the dashboards that they're going to be looking at, the metrics that they want to refine. You could be bubbling up insights even on what customers are doing. Sometimes there's more of a data component to it. So you're going to want to find out, is it data related?
Other times it could be more streamlining user research focused, right? Like it could be trying to standardize how we go out and collect the research and where do we put it? What repository should it live in? How can we help make it easier for people to talk to customers? That's our customer market research area. Or it could be on the governance side. It could be helping with things like templates, rolling them out, making sure they're consistent, finding the right tools. There's a lot that kind of goes into product operations. So you're going to want to ask how that company defines it and really what they're looking for. In product operations, too, you might be playing a role cross-referencing. So maybe you're working with a sales team to make sure that all the sales information actually ends up in product. So if they're talking to a customer and they request a feature list or something like that, it makes its way to product. That feedback is actually pulled out of their systems. We can look at that great information that they're capturing, talking to potential customers or active customers, and we can use that to refine our product. So a lot definitely goes into product operations. Depending on what size company you're looking at, the larger it is, I would say the more specific the product operations role might be.
From a perspective of you might be doing one of those things that I just mentioned, and it might be something where you granularize who's doing what. In a smaller company, you might be looking at all the product operations and trying to figure out how do I make product management better here? So it really depends on what size company you're looking for and where you want to act. I'd say product operations is always going to sit much closer to the product management team. The strategy and operations role usually is a little bit broader over the whole company. It may be working closely with product or it may be working with sales. It may be working with CEO. You're going to want to say, see how they actually define what strategy and operations means to them at those companies. Because it is very different company to company. Product operations is still new and definitely coming out there. So I could totally see where somebody might be calling it a strategy and operations role, but there's a lot of product operations that plays into it. They might be using that language right now, but I'd say product operations is emerging. It's just getting started. It's getting a lot of momentum though. So you're going to see it more standardized as we go out there. I would just look at the strategy and operations role and try to figure out what level of the company is it playing on.
Is it corporate or is it more granular working with the product team? If it's working with the product team, there might not be a huge difference between a strategy and operations role. Role and a Product Operations role. It might be the same thing if it reports into the product team. So I hope that clears it up. I know there's not a really cut and dry way to explain those two things and the differences now. And I think that's because of the way that companies explain them in the job description. In our book that Denise and I wrote, Product Operations, we do define the job roles of Product Operations pretty explicitly in there and who you should be hiring and looking at. So that might give you a good idea on what Product Operations could entail and if it's close to strategy and operations. And you can also get those job descriptions on our website at productoperations.com. And you can look at those roles there. I compare that to what you're seeing with strategy and ops and try to figure out is it the same or is it different. All right, so that's it for Dear Melissa this week. Again, if you have a question for me, please go to dearmelissa.com and drop it off so that I can answer it in a future episode. Now it's time to talk to Darren.
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Darren - 00:07:53: Thank you very much. It's a real pleasure to be here.
Melissa - 00:07:56: So you are chief product officer of a really interesting company called Soul Machines, which makes digital humanoids, which is a long way away from, I think, what we think about as caricatures online like Wallace and Gromit, which was years ago. How does Soul Machines get started? And how are you harnessing AI to bring in these very lifelike images of people?
Darren - 00:08:20: That's a very good question. And it's been a while since someone's mentioned Wallace and Gromit to me, so maybe we'll get back to that later so I can try to remember. So Soul Machines was started by Mark Sagar. He was a special effects guru working on blockbuster movies. And his area of speciality was motion capture, particularly around the face on major movies. At the time of working on those films, he developed some technologies to support that work that spanned out into a research project that ultimately became Soul Machines. And his big thing or his big story was really about the face being access to an emotional connection for users and for using technology beyond the way that we're used to. So he built these digital avatars that could connect to customers, potentially, in more empathic ways. I joined the company five years ago to introduce a level of design thinking as well as product thinking or attempt to bring some product thinking into what was at that stage a very research-focused engineering-led team. So, the challenges that we had at that stage were building a design and product team to try to help not just a very engineering-led company evolve into more product-led, which is where we are today, but also transition from kind of a very vision-based company that trying to an aspirational selling a major vision to big enterprises to actually democratize the process of building digital people so that smaller companies can work on and build and create digital avatar for their own unique use cases.
Melissa - 00:09:51: And what are those use cases? Like who needs digital avatars?
Darren - 00:09:56: So that's a very good question. And I'll be honest, we're still in the process at the moment of trying to identify those unique use cases that actually bring real value. A lot of the work that we've done up to this stage, and you asked about the connection with AI, and I'll come back to that shortly. A lot of the work that we've done at this stage has been around democratizing the ability to create avatars and also reducing the time to build these very realistic, customized faces and unique faces from three to six months to build to 30 minutes really for an individual to try and create them. The original pitch, the original opportunity that was being explored at Soul Machines as I came on board was digital assistants to help with a sales drive or to replace a call centers or to connect your customers to your brand in a very personalized way. What we're starting to find really the value that we're starting to explore as we've opened up the platform to get more users on board for our free tier, as opposed to the previous model where we charged a lot of money for a long-term project. The use cases we're starting to see are really getting to be super interesting where it's actually where empathic, really personal connection is useful.
So, rather than being an area of transactional kind of interface, which is what effectively the internet is about today and digital media is today, we're very transactional, very get in, get out. What we're finding, the digital avatar doesn't work very well in that space. There's limitations with the technology, the response delays too great. So inserting something like a fake face or a fake human between an experience that people are used to is actually not very successful. Where we are finding, that there are successes is helping people make difficult choices or helping people have difficult conversations or practice difficult conversations. For example, this interview today, I've done a couple of times with an avatar where I had the avatar playing your role and helping me stumble through words. And that practice ,the loop kind of without judgment and talking to an emotional face that actually connects to you is super effective and super useful. So. One of the big use cases is really language practice. You know, we had a Korean influencer who used one of our avatars a couple of months back to practice kind of speaking English. And just for practice responses. It's that engagement without judgment is, is an area that we're exploring.
Melissa - 00:12:29: That's a really cool use case. I can see I like the idea of the practicing without judgment. Like I speak really awful Italian, but it's because I can't practice. So I can understand extremely well, but I'm so afraid to go practice it because everybody just kind of looks at me weird. And I don't get a chance to speak with native speakers, you know, living in South Carolina, where actually I did find two people who speak Italian here, which is very random, but wouldn't expect it. But I don't get to talk to them as often. So I've always I've been like, man, I wish I could could practice more. And I've looked into like other courses, but I love the AI component of that too. Like not having a real human there judging your feedback and knowing that it's okay to say like whatever you want. That like really breaks down the barrier.
Darren - 00:13:07: I was going to say, and it's totally correct, because I think what we found is that we sort of went into this business of trying to create a level of utility that existed and that worked in existing channels or in existing markets. Actually, as the technology matured and as ChatGPT arrived and GenAI came on board, we found people were starting to use our digital people as kind of re-prompting them in different directions, like taking the one that we had on Soul Machines's website. They were reworking that to be a sleep coach, giving it a brief to say, I would like you to be this. So that kind of looking for that personal use case that making a digital person that is adaptable. And because the technology is really geared towards being able to connect with the viewer emotionally or respond in terms of expression appropriately, it works really well in those areas where you don't want judgment or you want a response or you want to see if things work. And once you layer in. ChatGPT, you're starting to kind of have this kind of fusion of an experience that is a little bit unique.
Melissa - 00:14:09: That's really interesting. I'm excited to see what other use cases you guys come up with too over time. So when you were developing this, you're basically building stuff at the forefront of technology here. AI is exploding now. I know we've had it for a long time, but talk to me a little bit about what it's like leading a product team around something that's so new. You're not sure ChatGPT came out, wowed everybody. People are coming up with different LLMs every single day. AI is advancing super fast. Now we've got Sora out there with the video creation. The pace of this is so rapid. How do you keep up with the technology and how do you anticipate what's going to happen and take bets against that?
Darren - 00:14:49: It's a challenge. We've been fortunate because I think at this stage, we've been fortunate because we've been able to ride the advances. And you know, previously, we've spent a lot of time focusing on how the face of the digital person looks and the production of those assets. But we spent less time on the conversational creation because we could not compete with Google and IBM and Microsoft on their platforms for NLP. And that effort to create the conversational corpus just takes a lot of time and a lot of expense. So really, last year for us, we were in an ideal position that we could pivot away from the dependency on those platforms and unlock more customers or more potential for experimentation for our customers with plug-ins into GPT. It just reduced the time to market for our customers and also for us internally to be able to experiment and to prove things. So we kind of had these two platforms that we made a bet originally that the effort in scale was going to be on the creation of the avatar itself. And then hopefully someone else would speed up the creation of the conversational content, which is what we've seen. So we're kind of at that point now. The challenge we have is be continually adaptable to new LLMs that come on board. The next stage really is multi-modality where we have aspects of that in our platform. So a digital avatar can actually see you and it can see your reaction and it can see your room and see what's going on, how it perceives those items and how that gets fed back to the LLM is the next stage for us in our evolution.
So really being able to capture content in the real world through the avatar and in the digital world on the website and then take it or in the place where it sits and then taking that back to the LLM. So that's the challenge that we've got and we're trying to work on at the moment. From a team perspective, in terms of working in that space, I think the challenge is pretty consistent. The product people here as it is in other areas, it's about focus and it's about prioritization and it's about being able to pick and quantify the best bets for your market at that time. Now, what's the biggest opportunity for growth for us? Where do we need to target to move the company forward? And I think the challenges are pretty consistent. It's just a little bit more dramatic, I think, because the platform's unstable. There's new things coming in. You need a particular target type of product operator to be able to adapt to those changes. But also not get caught up in the gold rush to the new and shiny, right, which is where everyone's going and quantifying that somehow. I think that's pretty much the truth of it is that the more dramatic and changeable the landscape is, the more the basic skills of being a good product person come to the fore. Intuition, focus on what's important, think about the customer. Where does this add value? Is this helping us retain customers? Is this going to change the bottom line? Those same questions are consistent, just maybe a little bit harder to quantify.
Melissa - 00:17:53: Especially coming from an organization where it sounds like, you know, this was research focused. A lot of people were like, I guess it kind of built out of, can we do this? How do we do it? How do we create these things, right? A product kind of searching for a problem. How do you keep the company, you know, as a chief product officer in check with not running after every new shiny thing that you were just talking about? How do you make sure that things are like focused and there's a strategy and you're not just chasing all the new things that could be out there?
Darren - 00:18:21: I wish I had the answer to that because it's the constant struggle. I can tell you how we try. Literally a conversation yesterday, a Slack message, just as I was going to bed yesterday about a brand new feature that we really must need to do because it's a differentiator and it's going to have a major impact and it's exactly what our customers are going to need from a couple of the engineering leads. You just break it down with a simple set. In that instance, you break it down to the customer needs. You kind of introduce where does the value get added? How does this change what we're trying to do? How is this more important than these other 10 priorities that you already know that we need to do? So just kind of context setting I think is critical. Kind of that education piece and constantly educating the teams around why we're doing what we're doing and trying to reinforce that knowledge for them so they have the reference point to come back to. From an organization, really the prioritization process, we introduced that two years ago. We worked with a really good operations officer who came on board and really helped us restructure how we do ops. I know that you've been doing a lot of work in this area and it resonates hugely because I think that piece of the business, that operations layer is so critical. And getting that right was just a game changer for us.
Melissa - 00:19:37: What types of things are you doing on the app layer that really made a difference?
Darren - 00:19:40: It was chaos. It was the Wild West beforehand. So really, it was just a simple putting product as the gating system for prioritization. Anyone can raise a priority against the business, but then just having a format and a forum for executive leadership to make decisions on prioritization and then to have an open discussion about why are we doing these things? And if you want to do this, what are we not doing? Because before that, we had a method of working where it was just every two weeks, there was new priorities and shifting focus and this customer wanted this, so we have to do this. And there was no opportunity for growth. So having that kind of level of simplistic process put in place where it was just a case of roles and responsibilities were very clear, a process for prioritization, an opportunity to discuss and to highlight the importance of new possible priorities or the changes or the impact of those changes. And then also just a roadmap that people can refer back to. I know not everyone does a long-term roadmap and I know we're a little bit out of date and that's us, but having an artifact that people can point to that is live and we can see how things are evolving and changing has been super useful. There's stresses along the line there, of course, but really just having that structure means that there's a space for conversation and things are done in the open rather than engineers change minds and shift off or requests come from different spaces.
Melissa - 00:21:07: You know, I always think it's interesting how when people think about cutting edge technology and high growth products and startups in the early messy days, that process or ops like that don't fit into those companies, right? I think there's this kind of like myth out there, like it's messy. That's just how we do it. How do you balance like keeping people innovative with not putting too much ops or too much process in there? What's your careful balance to allow people to still like explore and still experiment? And where do you draw the line there?
Darren - 00:21:35: I think in regard to some machines, I think we're fortunate because the platform itself is still very experimental at this stage. And that's really part of our product strategy where we're kind of putting a big bet on bringing the GenAI technology and the avatar technology together to build a platform for experimentation is really going to be a space where we can find out more about potential customers, find out more about what works, and then also find out things for ourselves. You know, one of the big challenges that we had previously is we couldn't really experiment with our technology because it's research heavy. The underlying technology needs refactoring because of the dependencies from the past and from the priority tech, which we're trying to shift at the moment. But it was very slow to make any changes and experiment. So we could not make those big changes. Everything was kind of very monolithic. So I'm not sure if this is answering your question, but really that level of experimentation is kind of ingrained into what we've got.
And we've now kind of unlocked speed internally to be able to test quickly, not just dependent on engineering teams, but also within the product team to sort of use our tool to build a different use case, to publish that on the platform, get feedback from customers, move really quickly, get customer insights directly into the engineering teams, remind them of the problems that we're trying to solve, kind of how we can fix that. And I think if you can do that, if you can work on a platform that is, you know, at the cutting edge, but you're bringing in real feedback from customers, from users, that kind of helps shape or retain that sense of what you're doing, rather than it being, let's just go after this new shiny thing. And that will be cool to do some of that. And let's have, you know, minority report style graphics, you know, so it's really just about kind of, I think, just bringing users in to help us experiment and put them at the center of the work that we're doing.
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Melissa - 00:24:01: I love that you bake it into your product. And I think that's key. I think where some people don't understand about startups or like dealing with things in high uncertainty, especially in the AI realm or whatever is new technology, unstable platforms, as you call them, which is a nice way to say it. When you're like in that field of uncertainty, the best thing you can do is act, right? Like throw something out there based on some evidence, right? See how customers react to it. And a lot of times I think instead, people are trying to gravitate towards hard quantitative facts and say, hey, you know, give me all the data that you could possibly say to prove that this is a thing we should build. And that doesn't usually exist. So I love that you designed your platform as a way to kind of say, hey, let's throw this out there and see how people react to it in a lightweight way and still get some data before we decide to commit. That's like such a great way to build a startup and be able to iterate on it. How do you kind of think about getting the customer feedback, targeting the customers on it? I feel like that's a second part that people get nervous about when it comes to startups is like, and especially, you know, ones where you need that feedback desperately targeting people and making them actually say like, yeah, I'll pick up the phone and talk to you or I'm very willing to give you feedback on this. How do you navigate those things?
Darren - 00:25:09: I think once again, we've been lucky because of a few choices that were made on the approach that Soul Machine took to business over the last few years. So we've had long-term partners who have worked in very much being attracted to us because a few years ago, AI was the big thing and then something else was the big thing and now AI is back. But we kind of rose that wave initially of businesses wanting to be part of the AI movement and seeing what's out there. See what's coming next and the Metaverse, et cetera. So long-term relationships with research labs in other businesses has been very useful for us because they've been an audience using our tools. It's been a challenge as well because the one thing that we find is our tooling is very internally based. Originally, it was built for us to help us make stuff and then we put it into customers' hands. Some of the customers I just talked about. And then we try to fix the tool for those customers. So the balance there that we're finding at the moment is supporting those existing customers with real needs for them and their business or the experiments or the use cases they're looking at.
Balancing that against trying to find new opportunities and making our product better, looking for that product market fit, fixing the end user experience, moving it away from just supporting what we have to tackling new markets. And I think that's the big challenge of balancing those two things. We're fortunate to get the feedback from customers there, but then you layer in new feedback from new customers and new audiences. And that's kind of where we are at the moment. As I think I mentioned previously. We just opened up the platform so that there's a freemium tier where you can come on board and you can experience without deploying. We're getting a lot of information from customers who are coming on board there about what they want. Lots of learnings, lots of surprises, but they have very different needs from maybe the legacy enterprise customers that we've got who already exist. So kind of balancing that feedback between the two audiences is where we sit at the moment.
Melissa - 00:27:14: That's really interesting because I feel like a lot of companies get to that crux too, where you will have the people who started with you and then you're trying to figure out how to expand or maybe how to reposition or anything like that. And then you've got these new users who are coming out there and you have to try to weigh your product strategy. Like, are we going after enterprise customers, even though they're legacy? Are we trying to expand there? Are we trying new markets? And I feel like everybody has kind of a system to start to think through what way they should go. How do you think about balancing those two things and what types of questions are you asking when you're trying to shape your product strategy and really narrow down your ICP?
Darren - 00:27:50: So that's exactly where we are at the moment. We've taken on board the freemium customers. We have kind of our pioneer who are the middle of the road. And then we have our enterprise that are still kind of more legacy and spend more money for a very white glove service. We're kind of analyzing those different data points that we have at the moment and looking at where are the opportunities to experiment and to measure the impact. I'll give a good example, really. And this is lessons learned from trying to test things. As I mentioned, we just opened up our freemium tier and we've had a huge amount of free customers come on board, lots of month-on-month growth. The challenge there is the turnaround for people turning to paying customers actually reduced from our previous tiers where it was a free trial that you would come on board and then convert. So we've kind of lost that conversion because we went too far into the free tier mode. Now, it's not necessarily a bad thing because we kind of race to build the free tier and it's something that we need.
And kind of going to refactor things so that we can bring people in into the right packages and into a different approach for our pricing package. But the challenge has been kind of, and the challenge will be is, how do we optimize for that? How do we optimize for the right people coming into the platform? How do we define our ICP? Who are the people that are going to benefit the most from our technology? Where are we going to find the growth markets? And I think we're still in that place of building that platform where we can experiment and shift the dial and see which sticks. So you see what sticks to try to bring that back into the product. It's super early days because, like I say, it's really just been sort of the last six months where we've had this platform available to start gathering that level of information to measure that against our existing insights. But that's really the next stage for us.
Melissa - 00:29:45: And this is not your first experience building on an unstable platform at the pace of AI either. You've worked for other companies as well. What did you take from them into Soul Machines?
Darren - 00:29:56: I think really my biggest learnings came from working in two companies, really. I originally started my career working for what we would have called back then as a small startup, but it was before startups were invented. So it was just a couple of guys who came out of art college and were working for the BBC, making branded content for the BBC. And that was awesome because that was, I mean, I'm going to age myself because that was CD-ROMs. So that was just as the internet was starting. But I loved it. I loved it at that stage because there was no rules. Nothing was defined. We were just trying to get this content onto this small medium and reach a market. Now, that cutting edge, doing a bit of everything, wearing multiple hats, you were an animator, an audio recorder, trying to find the best way to compress graphics, you know, straight out of college and doing everything. That was kind of the biggest learning for me. And that's what went with me as I moved into Intel, really. At Intel, it was the same sort of thing. It was a company that was acquired by Intel to build a full stack operating system. So this was pre-iPad for Intel's cheap netbooks. They were like small laptops that they were trying to sell into developing markets.
I didn't want to spend a hundred bucks licensing that Microsoft were charging for Windows. So they wanted a new operating system. So we were a team to put in place to build this operating system that could replace Windows. And the thing that I learned, I guess, from all of those and that those experiences were just really about putting in practice common sense, really. It's strange, that you know, you kind of talk about common sense as being not very common, but really like trusting your intuition about what users want, about how things are going to work. It's kind of studying the data, kind of getting engineers to see users using your platform as quickly as possible. That was a big game changer at Intel because we had a big group of engineers who knew the answers. And there was an instantaneous change the moment that we put them in a room with users doing diary studies on the things that they were building, actually just seeing the reaction of these engineers working, looking at real users, trying to make stuff with what they were working. And that's something I go back to constantly, you know, always go back to bring real people into your day to day, into the work that you do, because it does the work for you.
Melissa - 00:32:11: I think a lot of people have a question about how to balance that, right? You want your engineers and the rest of the team to come out and listen to customers, see the work, do those different things. How do you balance that with their day job? I get this question all the time for product managers. Like, what's enough to bring people into the field? What's enough to show them what's going on?
Darren - 00:32:31: That's a good point. I think I'm fortunate in the role because there's like so many things that could be improved and there's some fundamental challenges that we have. So it's very easy to insert strategic points, user research into the process and kind of educate people into that. We tend to do stuff at quarterly planning. You know, we'll bring use cases in or we'll bring feedback from customers and we'll do it on a three month cycle. So then you can plant the seeds into the engineering team mind at that cycle. We're doing this because of this. And there's a playback and you can play it back. And a lot of the time the engineering teams will take that on board and become advocates for it themselves. And I think that comes back to your previous question really about things that I've learned and things that are beneficial. I think the key thing about working in this space is really make advocates with the engineering teams for what you're trying to do. You know, don't be that CEO product person where you're telling them what to do. They're interested in product. They want to do better work. You're there to help their life be easier. Help them understand that. And I think really that helps so much if you can kind of engage on them at that level. They can also do the job for you that they become advocates for your work. And they also kind of repeat the things that you say or that you think are the reasoning. It answers the questions for them. And then they will hopefully answer questions to their colleagues. And you build consensus that way. And I think that's super powerful.
Melissa - 00:33:55: I agree. I think getting developers on your team to understand what you're doing and be your advocate is probably one of the best things that you do as a product person. So I love to hear you say that. You actually come from a design background too, right?
Darren - 00:34:08: Yes, sort of, I guess it was a long time ago. Probably if you ask some of the designers on my team, they will doubt that ever happened. But yeah, my original background was in design and that's where I was trained. And that's kind of the roots. That's really quite non-traditional for a CPO, I think, to come from that background.
Melissa - 00:34:25: Yeah, exactly. I wanted to ask you a little bit about what you think that gives you as a chief product officer. How has that helped shape who you are as a chief product officer? How does it shape how you lead? For me, I was always a hybrid UX product person. So I never had the design separated out from product for the longest time. And I didn't realize they were two separate things. So I always approach all problems from a UX problem. That's how I get up to speed on products. That's how I see things is the way it's designed and the way that people interact with it. I'm curious how that's shaped. You know, how you lead product teams and think about product strategy and get up to speed on products.
Darren - 00:35:00: I think the key part is the user research is one that we spoke about. I think that's my leaning towards that is super critical there. I think looking for motivations, I always think about motivations, not just in the design of a product, but also in the day-to-day working with other people, you know, managing people or having challenging conversations with stakeholders. You know, what are their motivations, understanding where they're coming from, what they're trying to do. So that kind of has a dual benefit, I think, that came from user experience of trying to understand what a user wants to do and what they're trying to do. Looking at insights, I had a real privilege of working with some really, really smart researchers who don't just do user research, but do user insights. And sitting in on those interviews with people when they, you know, navigate conversations with real people to kind of understand what their values are and kind of looking at the opportunities there. That was early on in my career. And that kind of seeded how I operate as a designer and bringing that straight into the work I do today.
And then I think probably strategically, I think you design everything, right? You know, you try to design, whether or not it's about lining everything up on Miro in a perfect form or kind of trying to build structures or bring an organization or order to organizations, I should say. I think there's a level of focusing on detail that came from that mindset of drilling into going from a very high level to a very pixel perfect approach. And I think those combination of those behaviors mean that you kind of approach things a little bit differently, kind of lean a little bit more intuition on things that feel right. You look for things that feel good. You look for emotional response. You look for engagement. You look for a connection. And I think that works in, for me anyway, that works with communicating with people as well as working with teams or trying to build things.
Melissa - 00:36:50: Coming from a design background, what did you have to learn or what did you have to get exposed to, I guess, to move into the CPO role to be successful?
Darren - 00:36:59: So much and still so much still to learn. I think just having a better understanding of kind of technology, I think, you know, because I think coming from a creative background, technology is always quite challenging for me. Being interested in that level of detail, understanding the way that product managers think and some of the techniques. And you learn that from some really good books. But I think that there's an element of just being more open to discussion and less driven by delivery. I think that's the big one for me. I'm quite an opinionated person. I was as a designer and you sort of thrive on that level of trying to drive your idea forward and the challenge of doing that. But really, that's only kind of one mode of operation. The other mode is to listen to the good ideas from other people. It's kind of to absorb things from people who are technically more knowledgeable than you in different fields and trust them and their decision making. That's probably the biggest piece for me.
Melissa - 00:37:57: I think that's really good advice for aspiring designers who want to be CPOs out there to listen to that. I also wanted to ask you about your advice for companies that want to be more, let's say, forward-facing, right? They want to be at the front of technology, especially when it comes to AI these days. I think every company thinks they need an AI strategy. So they're trying to figure out how to integrate it, what to do with it. You've worked in a massive organization like Intel, still future-facing technologies. You've worked for startups. You work for agencies. And I know that you created this framework as well for thinking through how your future-facing business should operate and what that should look like. Can you tell us a little bit about the principles in that framework and how you use them to guide your teams or guide your business?
Darren - 00:38:43: So the advice I would give is, it's just really about introducing privatization. So it's not really a groundbreaking piece of advice. So it's not really like massively unique, but like establishing that structure for successful operations across the business where you can grow healthy and happy teams, right? It's not just about the structure for delivery. It's the structure of growth of the individual is massively critical. If you don't have happy people operating in your organization, then you're not going to be successful. The next piece is like adopting a process that's familiar to the team that already exists. You don't have to kind of take something off the shelf. You don't have to do prescribed agile. You kind of just need to do something that works and the people can move towards and you can build an agreement, measure the success of that team, however that works for you guys. And that can evolve as you move forward. The third piece is, I think we mentioned this, is just put customers into the conversation as quickly as you can put users in there.
So, people can see that and you can leverage the insights that they gathered from there. And then really use the above just to define a clear set of outcomes. Target and Northstar kind of have somewhere that you can use immediate priorities that you can start moving towards and it kind of brings the organization together and you can then frame your strategy and your vision and your roadmap against those. Even if it's wrong, just moving fast and kind of moving towards something and then you can evolve as an organization. It's super critical. You're going to get it wrong. You know, failure is a big part of everything that we do. That's the only consistency that we have, right? We know something's going to fail more often than not. But if you're moving and you're making progress, then you're gathering data and you're learning and you're evolving. And I think, I think that's the most important thing.
Melissa - 00:40:29: Thank you so much, Darren, for that advice. And thank you for being on the Product Thinking Podcast. If people want to learn more about you and Soul Machines, where can they go?
Darren - 00:40:37: So you can go to soulmachines.com and please sign up to Digital DNA Studio and have a play. Or you can find me on LinkedIn as like dpjwilson. It's the best place to contact me.
Melissa - 00:40:48: Great. And we will put all of those links in our show notes at the productthinkingpodcast.com. So go to productthinkingpodcast.com, find Darren's episode, and we will have all those links in there. Thank you for listening to the Product Thinking Podcast. We'll be back next Wednesday with another episode and another great guest. In the meantime, get all your questions into me at dearmelissa.com. I'm happy to answer any of your questions about product management, and we will see you next time. Thanks for coming, Darren.
Darren - 00:41:13: Thank you very much.