Build Your Career by Collapsing the Talent Stack | Scott Belsky (CPO Adobe)

well it's one of my biggest frustrations with a lot of Founders I meet with and to be an entrepreneur to start something from nothing whether in a big company or whether you're doing it on your own there's a bit of a craziness to it what drives us to do it is having this Vision in our Mind's Eye this passion for some future State some future solution something that we feel needs to exist and what I've seen all too often is that passion gets people to take that risk to declare some amazing vision and then build a team and convince them to join you and then set off on years of work and then when you actually put something in a market it doesn't resonate and you're like wow we built an amazing product like what's going on here and it's just 30° off product Market fit like there's just something wrong and usually in my experience now that tracks back to a lack of empathy for the customer that they were ultimately serving my guest today is Scott bski adobe's Chief strategy officer and Executive Vice President of design and emerging products Scott has advised hundreds of startups and writes a popular newsletter called implications I spoke to him about why the talent stack is collapsing and what you can do about it how to improve the first mile experience for your product and the 4p framework for building generative AI products Scott is a leader who obsesses about customer empathy and keeping High performing teams as small as possible if you enjoy our conversation please like And subscribe to support this podcast all right Scott well thanks for joining me yeah definitely have been reading implications and have a lot of questions we could talk about yeah well thanks for having me Peter and thanks for following along this implications newsletter project has been a real you know fun exercise and getting ideas out there and getting feedback and connecting do yeah it's amazing so one of the recent

issues you wrote is about collapsing the talent stack maybe you can just kind of briefly share what you mean by that well I think the traditional organization has always been a lot of functions and a lot of these folks across different functions working together and yeah that's just been the way companies have been conceived and scaled for probably you know centuries to some degree and the question you know when you're a founder and you're building something very small you learn that one of the superpowers is when the founder is also the product leader or also the engineer and also has a design background or your co-founder also is a salesperson I mean the things you can only do in the beginning in a non-scalable fashion are actually great advantages for any new company and they actually allow you for some period of time to compete with big companies and I've thought a lot about that and I think the reason is of course is that you're just you have tighter conduits in decision making and in making realizations and making decisions and so one of the things I've been thinking a lot about is how does new technology multiplayer web apps in you know for across functions in the Enterprise the role that AI plays in connecting dots the reduction of a lot of the below of these functions as a result of this technology what you're starting to have is an opportunity where people can sort of do things across different functions even in a larger team and maybe can capture some of the benefits of collapsing the stack that are ordinarily only available to super small teams yeah like you know when you're at a startup like you wear multiple hats and you know the theory is as a company gets larger you have to specialize but like I think we should question that fundamental assumption right like what why yeah why do you have to special this whole like producer manager thing where people you know you're a great product person and then you are a founder and you start a company and then eventually you're like oh well I have so much management now that I have to hire a chief product officer to do all the product stuff for me even though that's my superpower and that's how I started this whole thing well maybe in this new world where AI can actually assist you in the management of your teams and can kind of give you the data you would ordinarily have to get in one-on ones every week and it can start to actually guide you in the communications you would other have to spend time doing maybe you can actually not hire that product person and continue to lead product as well as be the CEO of the company so that's just one example but I think we're going to start seeing it happen uh and I think it's going to make products and companies better how do you I mean you like probably a pretty large product work at Adobe how do you advise your employees

to get ready for this new state where teams are smaller like should they try to learn other function skills or well I think first of all in the incubation Zone of the company where we have smaller groups of people tackling problems you know in groups of three to five people in some instances they're able to have the benefits of collapsing the stack that we're discussing when it comes to how larger teams can operate more efficiently I've been you know my latest you know slogan I keep using is that concept of never waste a crisis you know as we've gone through a bit of a shaky kind of last few years postco world it's been an opportunity to refactor how we work you know as a company we never did Mass layoffs most companies did we didn't instead what we did is we said to teams you have to refactor how you do this you have to re rep prioritize and shift resources around you have to have new Frameworks for how you're executing and I think that those made us a stronger company H do you find that I've talked to some other prod leaders and they've I think people are starting speak their mind now with this economy but like do you find that like actually like the smaller teams can get like a lot of done or like execute very well smaller kind of empowered teams yeah sure I mean yeah the in the earlier days of building it's always an advantage to again have those Tighter conduits and collap the stack in any way possible and just have fewer people that you have to have agree on anything but the reality is that when you start to go to market and bring things to scale there's a lot of folks that need to be involved if you're going across geographies if you're selling into the Enterprise and need contracts and need certain security measures I mean you know it's very quick it's very easy to get to the point where you need lots of people to do something it's about though just segmenting you know making sure you don't do that until you absolutely need to got it makes sense maybe since you know you the founder of beans and you work for the design com really cares about the design

maybe can you talk about like what the ideal design to pmip is you know like how should roles become more blurred or yeah well the ideal design PM relationship the controversial answer is they're the same person that's the ideal yeah and in behance we actually never had a PM in the early days for the first five to seven years and today the leader of design for beams is the leader of the product as well so we we've always tried to have a tightly coupled system there and if you can find those are the true unicorns right people who can do that I think that's the Holy Grail short of that I think you have to have product and there's two types of product managers right there's the product manager and the product leader a product leader sets the flag for where we're going is constantly telling this narrative about this journey that we're on and Merchandising progress and keeping our eye on the prize so to speak whereas the product manager is simply dayto day managing the operations and keeping people coordinated and holding us onto our road map step by step but they're kind of walking looking at their feet as opposed to a product leader who's walking looking at the flag I think that it's important to have a product leader I think a lot of companies make the mistake of just hiring product managers and they end up someplace different than where they had hoped or they don't even know where the flag is planted and then you also need product managers you need the people who are just going to you know be in every meeting and are helping manage the project as well as the sort of product requirements so that's my take and design of course plays a role in both but I always like to lead with design I feel like that notion of a prototype being worth 100 meetings you know is really important in the world of building your products yeah I think um there's been a trend towards Less on producing using intermediate collateral like documentation or stuff like that more than just like building prototypes and playing with a product it's kind of hard to know what it feels like un you have in your hands you know so that's great yeah okay and when you say product leader are you refering someone just be clear like who has like who's managing a ton of PMS or can like a PM be a prod leader too as it's not just too focused on the execution set of things yeah well I think that when I say product leader I mean it's someone has the capacity to really innovate and think about the world that this product is going to existed in a few years and what it needs to be successful in that world it's leadership it's bringing people somewhere they don't fully understand it's convincing people of something they don't fully believe you know it's all the leadership aspects can you have a product leader that also does the managing day-to-day 100% like that's an amazing T feat my point though is that often times a great product manager is not a great product leader and we just have to realize that and be on the lookout got it and you tweeted something this morning saying that I think something about like to have a good Vision you have to have empathy first right and maybe talk a little bit more about that because a lot of people think you know I just have to be a Visionary know where we're going May me talk about the order of operations well it's one of my biggest frustrations with the founding you know with a lot of Founders I meet where and you know to be an entrepreneur to start something from nothing whether you're in a big company or whether you're doing it on your own it is there's a bit of a craziness to it right and how we what drives us to do it is having this Vision in our Mind's Eye you know this passion for some future State some future solution something that we feel needs to exist and what I've seen all too often is that passion gets people to take that risk to declare some amazing vision and then build a team and convince them to join you and then set off on years of work and then when you actually put something in the market it doesn't resonate and you're like wow we built an amazing product like what's going on here and it's just 30° off product Market fit like there's just something wrong and usually in my experience now that tracks back to a lack of empathy for the customer that they were ultimately serving they failed to realize for example in an Enterprise product that and customer is actually always insecure you know with what their boss thinks of them and needs to have some sense of like gratification or credit in order to use a product or the consumer you know they were trying to engage with their app you know is lazy Vain and selfish in their first 30 seconds of using a new product and has no care about the value proposition of the product in Practical reality so it the passion piece what I was saying earlier this morning is in some ways a red herring of product it's like what you think is supposed to drive you when in fact what really should be driving you is your empathy with the customer suffering problem and so if you go shoulder toosh shoulder with customers and you just watch their day and you ask them questions like why did you do that oh why did you take that spreadsheet and re format it in a different way and add what you added to it it's like oh because you know people often times pass my work on as their own oh yeah that's interesting so you would probably feel uncomfortable building a dashboard that everyone else has access to unless you got credit for it and they're like well I don't care about credit and you're like well you kind of do because you just admitted that you do like this is what I'm talking about like that's tuning into the empathy with like what they're actually struggling with and I think that those are some of the insights that make all the difference in building products for both you know Enterprise and consumer yeah I think have a certain level of humidity because you can have some sort of arrogance like customers does know what they want I which doesn't lead to a good place yeah but Peter the cheat code of course is if you're solving your own problem like that's why a lot of Founders who are successful solve their own problem because they are the customer you're in that sense you're collapsing the stack of empathy yeah I think that's why I found a good Niche just like working on Creator products because it's like you know I'm a Creator I know they so there Switching gears a little bit like you know I consider myself a pretty customer focused Pro leader but I think one of the pitfalls is like the core users are the ones who are like the most vocal and complain the most and are willing to spend the most time with you right

so like how do you like going into this first mile experience of the product like how do you even build empathy for like the new users which is like you know if they don't like your product just leave how do you even get do empathy for it just yeah well I think the you know the the tragedy of most products is that they start beautifully simple you know users flock to a simple product and then that product takes those users for granted starts to build new features to monetize and they also start to only listen to the customers that talk to them the most which are the power users the minority the vocal minority and as a result stop feeling empathetic for the new customers in the funnel that have no idea what this product is or how it works and how they whether they want to use it or not and then they end up building a very complicated product over time and the whole process repeats itself and then users eventually flock to a new simple product and that's probably the Silicon Valley product life cycle that no one really talks about and so I think you're asking like how do you defy that like how do you keep your product accessible to new customers how do you hold on to Simplicity I think part of it is an obsession that is not momentary but ongoing around the first mile experience ensuring that it gets better and also remembering that every new cohort of new customers is different the when you first launch a product is filled with these willing and forgiving Lean Forward early adopters right and they have a higher tolerance for friction and so your first might work perfectly for them and then a year and a half later the customers that are coming to your funnel are a bit more of the pragmatists and that first mile might be horrible for them so you actually have to continually change the first mile for that reason and also just because the world changes like people's expectations change people's tolerance for friction is just going down consistently in humanity in my view and so you have to constantly iterate it I think that's one of the hacks towards keeping a product simple enough and using tools like Progressive disclosure and you know other ways to make sure it only adds complexity when a customer is ready for it got it and a lot of the teams that are focused on first M like the onboarding team I've observed that tend to be very growth oriented so they like you know run a bunch of experiments and like AB test everything and uh lately just being a trend more towards craft or just like believing what you should ship like yeah do you have any thoughts on that or yeah well I think is the question really around you know as you're crafting that first M experience like how do you tune in to what should and shouldn't be in there or what I'm going to make sure I think you know as I've been a PM for more years I start to have like a negative impression of like just experimenting everything and shipping MVPs and like I tend to want to like take my time and like do something that I feel proud of and I'm wondering if that applies to like this first mile experience thing we're talking about well you know I think the this question in my mind relates to always the question around the MVP you know and what is sufficient versus what do you have to really get right and you know I always believe that we should try to get the minimum of everything that the customer kind of needs but the couple things that make this product differentiated in market like this the competitive advantage of your product should be perfectly Polished before you ship and test it because that's what you're testing like you know the data is flawed if you don't get what accentuates your product most right so don't you know always polish that to Perfection the second rule of them that I use with a lot of teams is to optimize for the problems they want to have so what is a problem you want to have well if customers flow through my funnel and they successfully sign up in droves and they immediately get some satisfaction from the product but then they start to complain because they want to be able to do this new Nuance thing or they want to be able to bring in a colleague roll it out to their whole organization because they love it so much or you know all those things those are problems you want to have so don't address them before you launch but problems you don't want to have are things like I couldn't sign up or I couldn't get value out of it I had too much friction and I didn't find my path my way like those are things you should never launch with because they will again destroy and skew your data yeah and those problems are usually not set out loud right you kind of have look at the data to understand if that's even a problemo or not or try to prodct yourself 10 times you know yeah it's a debate you know we're always looking at a road map and feature list we're always debating what's above and below the line before we ship something I think these are like helpful Frameworks towards making the right tradeoffs got it do you have any you know I think

you also WR about how AI will hyper personalize the first mile experience and adobi has made a big bet on this do you have any principles when it comes to building you know gender of AI products at Adobe like is there any kind of like rules of thumb that you guys follow wow well you know a million thoughts come to mind um but at the end of the day I also am really focused on empathy with like the problems we're trying to solve I think that's a part of it you know we've certainly pioneered a playground first approach or we kind of test things on the Firefly Standalone experience first and then we bring them into our products we do so in ways that are progressively disclosed so you see it when you need it we again anchor ourselves with customer workflows and pain points we do a lot of user research our design team is our customer zero at Adobe on all of this stuff so you know I have a design organization that battle Pro you know pressure tests all of our stuff and is very honest with a couple things not only is the product is the outcome good enough is the integration good enough but also the ethics of it like what are the pro provocations you know is this what sorts of safety measures should we put in place before we release these features and our design team has been really helpful in helping must execute this strategy in the right way do you have like a specific example of that like from a feature that you shipped sure I mean we just recently launched a feature called generative match and what this allows you to do is it allows you to when you're generating an asset using AI you can use a reference image of your own so if you want to mimic the style that you did for that client previously or that same color palette or brush Strokes or whatever you can leverage that asset and it really helps people scale their production to meet client demands and people are pretty excited about it but it can also be abused people could leverage someone else's work without permission and sort of you know RI rip their style and that's something we wanted to discourage so we not only made customers attest to the fact that they're using their content we not only decided that we will not indemnify customers if they use someone else's asset without their permission or someone something they don't have a license to MH but we also actually developed some technology that we made integrated by default into these flows you know one is we add content credentials to the asset and the Conta credentials actually say that a reference image was used so Conta credentials are added to these new generated assets with the provenance and the history of the asset and that's on you know because we believe that people should be transparent uh if they use a reference asset and then we also store the reference asset that was used so that if there's any future legal issue or you know some sort of takeown request or something like that you know Adobe is in the position to help you know some form of law enforcement in some country or something like that and so these are the types of things that we decided and the design team had a big you know role in guiding us around and you know there were great active debates you know in the organization about what's right what's wrong how much is too much how do we make sure we ship this in a way we're proud out of and that's ultimately the bar we hold ourselves to that's awesome yeah whenever a new AI feature launches there's usually like a sigma of customers who are like I guess very anti- AI so like just like taking extra time to think about these edge cases and like the safety side of things probably helps a lot I think yeah

I'm sure listen a lot of people struggle with the speed of technology these days and you know if you go back in the history when the first digital tools came around you know painters were very angry when cameras were invented painters were angry right when digital cameras were invented analog photographers were angry and a lot of Photography associations around the world did not allow you to submit images or be a part of them if you were a digital photographer so it's just this repeated tendency for us to sort of be threatened and skeptical of new technology but for good reason like this is you know this is the healthy tension that makes us do it in a better way and you know I've as I've matured in my own approach to all this stuff I kind of welcome the provocation and the outrage so to speak because it makes us better you know it's part of the conversation we can't hide ourselves from it we have to engage in it yeah I think one of the things that I'm really worried about with AI is just like and I think you mentioned this a little bit this like you know images or videos become not real like you know for example a couple days ago with the conflict in the Middle East like you know it was unclear who hit the hospital so yeah do you think I mean I'm like really worried about this I mean what do you think about this problem well you know so I've been worried about this problem also you know for maybe 5 years now I mean ever since there was this feature called content whereare fill in After Effects that allowed you to move remove a moving image or person you know from a video in seconds and as soon as I saw that you know I remember thinking with the team like we need to launch this with the right narrative and the right safeguards and we need to start being creative of what goes right not just what goes wrong I'm sorry not what goes wrong not just what goes right and so you know in our case we came out with something called content credentials that is an open-source effort for cameras and tools and certainly Adobe tools to add information metadata about how the asset was changed or made what AI was used and the intention of this is not to you know point out the Bad actors it's actually to help surface the good actors you know and help people show that they can be trusted and I think that we're going to enter a world now where most things we're going to have to assume might not be true unless we can see the transparency of how it was made and who made it that's awesome and I think there's some other P out there like the community nose product on X that kind of help with that too yeah totally I think we're you know we're in the early days you know yeah how about why don't we

close with this then I think a lot of people you know create PMS or whoever want to explore the space there's a lot of noise in the space too you know like there's like 99 8i tools you must try so like you have this like a framework you have this 4p framework right for teams or people to explore AI maybe you can share a little bit more about that yeah sure you know a common question I get from teams these days is we are excited about AI we know it is going to impact the way we work the volume of content we can create the you know the scope you know of our business but we just don't know how to get started and so I always advise them to think about you know four things you know the first being the first P you know is play like allow your team to play with this it's important and it's sometimes not so intuitive to some companies to like let their teams just play with new tools that don't have any clear commercial value yet but novelty proceeds utility we have to be able to play with something to start to discover its use cases so that's the first thing I think the second one is pilot like find a project that you're going to Pilot this technology with and do the new way but you have to protect the third p is protect the people that are doing that pilot by giving them a new set of kpis or measures that are not the traditional ones like the objective of this pilot should not be to make more money than we usually make doing this or to do it more cheaply the kpi should be whether we learn from it you know and whether there's something interesting here and just completing the pilot you know should be the goal and so you have to kind of protect the team otherwise they'll take the risk and they'll be punished for it and I think the fourth P that we talked about earlier is provocation you know you have to invite the provocative questions you have to allow people to disagree or Surface their concerns because that's part of making sure you do it right and can ship something you're proud of awesome what's being your favorite AI use case for your personal life like what was supposed to be what do you use it for being use case for my personal life I mean I would say you know for my implications newsletters I actually sometimes want a graphic for one of the points and I just like have no idea you know how to secure that graphic cuz it's such like a nuanced thing like old machines versus new machines or something like that and I love using Firefly to generate assets you know for some of those use cases personally and then you know and then I love making poems for my kids using chat GPT you know there's that kind of stuff that I do had a big kick out of yeah it's really good at explaining simple to my kids like how some something works so you know yeah that's great all right man I want to respect your time so mean you know lots of new use cases to come and I'm sure life will get you know more interesting you know as they hit the main stream yeah it's very exciting it saves a lot of time and like it's very fun to use too so yeah