Product Rebels
Product Rebels
From 1,000 Interns to One Day Sprints
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What does it actually look like to run a one-day sprint cycle? To have agents building product overnight? To compress months of work into days — and still ship things that matter?
Kris Kaneta, Chief Product & Innovation Officer at Norstella — one of fast company's most innovative companies of 2025 — is doing it. And in this episode, he shares how with hosts Heather Samarin and Vidya Dinamani.
From the premium on clarity in an AI-led pdlc, to the difference between building to learn and building to earn, to why ai is exposing — not hiding — weak product thinking, Kris gives one of the most operationally grounded views of AI-first product leadership we've heard.
If I've suddenly gone from a traditional two-week sprint down to sprinting a day, what we're actually learning is that the teams who are investing in clarity, the teams who are investing in understanding well-defined problem statements, that are investing in well-defined product experiences and can articulate that are actually getting so much better results coming out of a development that is largely AI-driven. Because as incredible as the AI tooling that all of us are adopting is, at the end of the day, it's still like a thousand interns. And you've got to be really explicit about what it is you're trying to accomplish with an intern, right? If I can't be explicit about what good looks like, I'm going to get something that looks entirely nothing at all like what I maybe had in my mind. And so the premium now is on clarity. And I actually think the adoption of AI is going to expose product managers that haven't taken the time to actually understand what good looks like.
SPEAKER_02Chris has an unusual path to the CPOC. He came up through marketing and strategy, spending nearly six years as CMO and global strategy leader at GE Healthcare, then serving as CMO at Teletracking, a healthcare operations company. At Northella, Chris has spent the last several years unifying what was a collection of legacy pharma intelligence brands into a shared AI-first product platform. We're excited to dig into how Chris thinks about product leadership at the intersection of data, AI, in one of the most complex industries in the world. Welcome, Chris.
SPEAKER_00Chris, thank you so much for being on the podcast today.
SPEAKER_03Thank you so much for having me. A longtime listener, happy to be part of the conversation today.
SPEAKER_00Oh, we're so delighted to hear that. So we're going to start with our favorite question, the one we always start with, which is what does a product rebel mean to you?
SPEAKER_03First, let me start by saying I think this is such a timely question given the evolution and transformation of what a product manager is. And I think first and foremost, to me, it starts with a maniacal focus on how we create customer value. I think over the last several years, product management has gotten complicated with ceremonies and moving information and running meetings. But at the end of the day, you got to clear all that noise out. And it's about how am I creating value for the customer? And then everything else can wait. And if anything, what we're seeing in the world of AI is just bringing that into so much focus and so much clarity. And it's just raising the stakes for how important it is for product managers to be thinking about value creation.
SPEAKER_02Oh my gosh, Chris, you're so right. Music to our ears. I would love to hear a story how your hidden rebel is showing up now in this age of AI. How are you sort of maintaining this maniacal focus on value now?
SPEAKER_03Yeah, think of a normal distribution curve, if you will, and just the x-axis being time, the sequential order of things in a traditional product management world. And I think historically, although we're supposed to always be market focused and thinking about what's the problem we're trying to solve, the job to be done, when you rack and stack the amount of time that product managers spend in this distribution curve, very little happens there. And so much happens in the act of building a product, the act of writing product requirements, specifications, spending their time in tickets, and thinking about how am I gonna QA that and all those other steps that happen. And what I think has changed most substantially is that distribution curve is now inverted. The amount of time it takes us to build is so small compared to what it used to be, which means now I've got a whole lot more time to be thinking about where's the market going? How are my customers' roles and their jobs to be done evolving? A lot more time thinking about how do I bring this product to market? How do I evolve it to find the right product market fit? So what used to be long, skinny tails are now really fat tails on the left and right of that distribution curve, which I think is going to be tremendously liberating for the very best product managers out there for those product rebels.
SPEAKER_00Oh gosh, this is amazing. We could probably spend the next hour just talking about this. So I want to explore this a little bit further. I read recently a characterization of this, which is, you know, product has always been hard. And now we just get to that 20% that's really hard much faster, right? And the thing that we got to focus and we've got to work on the temptation to ignore the pieces that you've said and highlighted are so important. Is it real? And we're seeing a lot of teams fall into the trap of ignoring that hard work. So the fact that you we're talking about this, you're recognizing it. How are you communicating this to teams? Because I think there's so much pressure to go quickly, to bypass that early sort of work and then really understanding what matters. How are you communicating this? I'm sort of jumping ahead in many ways, but I love this kind of conversation around how are we communicating that the core of the work that we do is the most important. And how are you talking about that?
SPEAKER_03I think the best part is that as we have gone nearly fully agenc across a product development lifecycle, it's actually exposed when we lack that clarity. Right. So the way I think about it is if I suddenly gone from let's just call it a traditional two-week sprint down to sprinting a day. And by the way, I'd even argue that terminology is wrong for the new world that we live in. But let's just, for consistency's sake, say it's a sprint a day. What we're actually learning is that the teams who are investing in clarity, the teams who are investing in understanding well-defined problem statements, that are investing in well-defined product experiences and can articulate that, are actually getting so much better results coming out of a development that is largely AI-driven. Because as incredible as the AI tooling that all of us are adopting is, at the end of the day, it's still like a thousand interns. And you've got to be really explicit about what it is you're trying to accomplish with an intern, right? Take a very simple metaphor. If I were to ask for a cup of coffee, that's one thing if it's at a basic coffee pot. But if I'm sending somebody to Starbucks, they're gonna want to know how many shots, foam, no foam, how many pumps, or whatever it is the complicated order is. And if I can't be explicit about what good looks like, I'm going to get something that looks entirely nothing at all like what I maybe had in my mind. And so the premium now is on clarity, it's on being able to convey how value is created in the product experience. And I actually think the adoption of AI is going to expose product managers that haven't taken the time to actually understand what good looks like.
SPEAKER_02We are in 100% agreement. I'd love to hear how you're doing it. I know you just recently launched a couple AI-powered products. I'd love to hear how you are infusing not just the mindset, but practices in your new product management or product development lifecycle that really does get at this clarity. What's changed for you? What have you done? What are some of the practices that you've implemented?
SPEAKER_03Yeah, maybe I'll start by for your listeners, maybe backing up, because I think Northello, who's the company for which I have the privilege of being chief product officer, is uniquely positioned because we are first and foremost, from a history standpoint, a data company. And so over the last few years, we've been really investing in a connected data fabric that is AI ready. Right. So think about all the pieces of information required to make key decisions in a drug development lifecycle from preclinical, early pipeline, all the way to bringing a life-changing therapy to market, where we've for years brought data and insights to support those critical decisions. And for the last few years, we've really focused on how do we link all these assets together, structure them in a way that they are AI ready. So we have the advantage of really having an incredible context layer when we think about AI and we think about product development. So that has created, I think, for us, an incredible head start as we think about this journey, but that also raises the stakes because we do have this incredible context layer for how we move and we develop product and bring new products to market. And so one of the things that actually just really recently in the last kind of 48 hours that we had a big aha around was as we look at the quality of production in an AI-led product development lifecycle, was distinguishing between when it was a tooling issue versus when it was a product requirements issue and identifying the differences. Because to answer your question, I think the biggest risk that we faced was really thinking about how do we make sure that teams are leaning in and fully adopting this new way of working. And the last thing I want to do is say, you know what, your product requirements, your specs, they weren't good. When actually it was a tooling thing, because I've got a design system, I've got standard components, I've got architectural things to take into consideration. And again, a thousand interns, it's still a thousand, it's a lot, but it's still a thousand interns, right? So being able to distinguish between when it was about clarity and precision and how we think about requirements and when it was about tooling, because compressing something from a two-week sprint to a one-day sprint, there's gonna be a lot of unknowns and a lot of assumptions, and we've got to continue to drive deeper and deeper insights into how the system is working for our product managers and their technology counterparts.
SPEAKER_00So interesting. And I really like the separation of like, where is this happening? One of the things that I think we've talked about before outside of this conversation is failure. And this idea of like, now sprints are no two weeks, they're a day. There's so many people, again, going back to the start of this conversation and clarity, there's still this idea of experimentation inside of it. So, how are you kind of reconciling those two things? Diagnosing like how to move people quickly, letting them experiment, but also focusing on clarity. What does that combination look like?
SPEAKER_03This is such a great question, and it leads to a larger question that kind of keeps me up at night. Let's just pretend for a moment that suddenly now my teams have 10x their output, right? We're doing a sprint a day, we're delivering products and features and capabilities at 10 times the pace. You know what that's ignoring is the fact that the market cannot absorb 10 times the pace, like at least not yet, right? So just because I can create 10 times the value in the market doesn't necessarily mean I can get paid for 10 times the value that I'm creating. And so one of the principles that we're learning to embrace here, and Marty Kagan, the Silicon Valley product group says it best, it's delineating between building to learn and building to earn. So what I really want, you know, really anybody, it could be product managers, but anybody in a kind of a market or customer-facing role, thinking about building a rapid prototype, putting some ideas down on paper, putting that in front of a customer. Like we can literally do that now. In after an hour of conversation, go vibe code something really crude, but at least get the point down and something that I can take to the market and get feedback on and understand whether or not this is actually going to hit the mark. And is it gonna hit the mark for an N of one? Or is this actually something that has a real opportunity in the market? And by the way, I'm interested in understanding both because an N of one might be a very interesting bespoke services opportunity that I can go bring to the market and learn from. And maybe eventually that scales to something that is an N of 100 or N of a thousand or whatever that opportunity might be. But it's really embracing hey, we want to build, we want to go learn, and then we want to go build to earn on something that's got the highest probability of product market fit. What I can't do is assume everything I build is gonna have that same level of product market fit because I can't enable my sales force fast enough. I can't enable my marketing channels fast enough, right? All of those things, all we've done is we've moved the bottleneck downstream if we take a traditional approach. So instead, it's about hey, go fail early and often upstream as possible. And then let's go find the ones that really have the highest probability of product market fit.
SPEAKER_02Love it. And tough to do, right? I'm trying to decide which path to go down because I'm still really interested in something you said earlier, which was how do we diagnose this lack of clarity or when we have challenges later in the pipeline, and whether or not it's the lack of clarity or the tooling issues. And that's one path that I want to go down. But then the other is just how have you changed the sort of discovery prototyping and testing cycle and process and who's doing it, right? Because I think the role of a product manager and the role of the cross-functional team has changed dramatically and the roles are blurring. And so I'm really interested in hearing about what does this new scaled prototyping and testing and experimenting and learning look like in your organization? And then maybe I'll come back to the other question because I think they're both a tracking and a process perspective to understand whether or not you're actually weeding out and ending up with clarity and making the right decisions.
SPEAKER_03First, let me say I don't have the answer.
SPEAKER_02A lot of folks haven't done it yet, right? So you've got legal, you even failed or not.
SPEAKER_03I literally reminding teams that we are going down a path for which there is no HBR case study, there's no book that has been written about this, right? And as someone I used to work with a long time ago used to say, I reserve the right to get smarter. And first, I'll say we are taking a very open approach, and by that I mean anyone that is interacting with the market that has an opportunity to extract valuable insights from a customer, from their customers, from the market. I want them armed with the ability to put their best ideas on paper. Because you know what? The role of a product manager is not just to be the eyes and ears of a company. In fact, the best companies understand that the eyes and ears are anywhere, right? It could be your salespeople, it could be your client success folks, it could be, I don't know, if you've got a consulting arm or services delivery arm, whatever. Every single one of those roles is an opportunity to find the right signals. And what a product manager needs to recognize is I now have 10 times the number of opportunities to understand where is a problem we're solving and what is the magnitude of that problem we're solving. So we have armed everyone in our organization with standard tooling for them to be able to go do this, right? To go prototype, to go design, to go build a mock-up. And really now what it comes down to is find me the right evidence and the signal in the noise, because there's going to be a lot of noise. We live in a world now where the AI slop is real. That is a real thing that exists. And so the idea now of judgment and clarity, like we talked about, and applying it in the context of does this make sense with where I want to go, with where I see the market going, with the strengths of our portfolio, all of these things don't go away, right? The stakes actually go up because what I don't want to do is create a lot of noise and distraction for an organization because my product portfolio and my roadmap lacks clarity.
SPEAKER_00I want to click down on one piece of this, and then we can go back to Heather's question on clarity. We're hearing a lot about the amount of pressure on product managers, and you talked about the role, and it is changing, and there's such a huge expectation to do so much more and to build. Are you how are your teams feeling? Like how are your product managers doing?
SPEAKER_03So I think first and foremost, there is a great deal of excitement. So we've been on a multi-month journey where we're taking product teams by product teams and enabling them on this AI PDLC stack, right? So we've built a harness, we've built a brain and a context layer, and obviously wherever possible using frontier models and everything, but we're tuning them for the way that we work. And as we bring each of these teams on, it's like the every time without fail, it's the Gartner hype cycle, right? A few days before we launch with that team, massive excitement, right? Everybody's getting ready. And then a day or two in, it's wow, this sucks. It's really hard to do, right? But then they're realizing, you know what? The biggest difference is in a two-week sprint, I have these asynchronous opportunities to interact with my design team, with my tech team, with my architects, with a market expert, right? What did we really mean when we said X? When you go for two weeks to a day, you don't have that asynchronous approach. And so you learn how to get in front of that, and then you come out of that downward cycle and you realize, holy moly, I just delivered, you know, again, we have to rethink new names for this, but I delivered 10 times the number of points in two days that would have taken me a full two-week sprint, right? And I say we need to rethink what that means because at this point, I'm not even sure what a sprint means, what story points mean. It's the language we have today, but over time, it's not really about that. It's about I set out with a certain number of goals to meet a certain market reality or a certain customer need or a certain vulnerability, whatever it is. And I was able to solve for that in a couple of days. And the second step that I think we're gonna see and I'm starting to observe is the idea of like a roadmap. I don't even know what that means anymore because things are changing so quickly. Now, I think from broader strategic objectives, that's still really important. But to say, hey, Q1 looks like this and Q2 looks like this and Q3 looks like this, first of all, not only is the AI landscape changing for us on a daily basis, but it's also changing for our customers and for the markets that we serve. And so for me to place a bunch of bets that I think are gonna pay off in the next two, three years, I think that's growing increasingly difficult. And so what we're trying to embrace and harness is okay, if you really think that's true, what are the things that we can do right now? What are the leading indicators that we can extract from the market right now? And how do I go build those things? So let's start building foundations so that if we think a market is going in this yonder direction, I'm at least taking steps that involve legitimate real customer and market validation along the way because the landscape is just changing at such a remarkable pace, as you guys know, and as every guest that you've had on your podcast probably in the last six, 12 months has probably articulated.
SPEAKER_02Yeah, and so tough. We still have big enterprise clients that are on a two-year time horizon roadmap. Like it just doesn't work that way anymore. It's a dramatic change. And so it's a much more pragmatic way of looking at problems, customers, and you're sort of looking at what's very short term, learning as fast as you can.
SPEAKER_03Yeah, no, it really is about how do we learn as fast as we can, right? Hopefully have some meaningful impact along the way.
SPEAKER_02And the big challenge now that we're hearing from a lot of product leaders is how do you build the connective tissue to the outcomes? So, how are you learning in a way and then proving out whether or not you've achieved your outcomes? And then you mentioned, you know, it's very clear lack of clarity is being exposed faster. But how are you diagnosing that and making sure you're learning from that so that what you're doing at warp speed is driven by outcomes and achieving those outcomes, right? The biggest challenge we're hearing from product leaders is that they're not able to connect the dots between ROI and the work they're doing. And that seems to be the recurring question. I'd love to hear how you're thinking about it.
SPEAKER_03Yeah, great question. Tough question to answer. I'll try to answer it in a way that I think about ROI. And really, it's gonna differ based on where the organization is, right? Are they a growth company? Are they a more mature company? And what are the strategic imperatives? But for me, as I think about ROI, so first at like a PDLC level, I am looking at velocity, not in like a traditional agile sense, but I'm looking at velocity of how quickly can I have a concept and get to something real that has market validation that then I go and start to build for scale. Now, to put that into context, three years ago, my big measure of speed and ROI is how can I get to a working beta prototype or early adopter in six sprints or less in a hundred days. Three years ago, that was like my big audacious challenge to a team because I don't have more than 100 days because in four or five, six months, the market will have moved and they will have solved that problem through some other means. So that was the objective I set. And then we go bring that to market. And hopefully within a couple of months, we've learned a whole lot about what we have built and about how the market wants to consume it. Now it's how do I go do that in a day and then spend the next two months really building greater clarity, really building better understanding of willingness to pay, the value that it's gonna create? And I spent a lot more time thinking about the tweaking and the enhancements and the business model and how I'm gonna expose certain features. To me, that's where the real ROI becomes. It's less about can I build a product that somebody's gonna sell, but it's can I create something that is gonna provoke a response in the market that will create new value that I'm going to get paid in a manner commensurate with the value that I've created? And that now can happen in two, three, four weeks as opposed to two, three, four months.
SPEAKER_00I love the way that you talk about value. There's so many great things that you've covered here. How are you personally keeping ahead? We've talked about all these changes. There's an avalanche of information. There's so much going on. You're trying to provide clarity to your team. You're guiding them to we're moving now in weeks to providing value. What are you doing? I think we're all wanting to share this information about how are you keeping up?
SPEAKER_03I don't know. Some days I don't feel like I'm keeping up if I'm being really honest.
SPEAKER_00Great. Just like all the rest, that's amazing.
SPEAKER_03So I actually have four agents that fire every morning for me that really gear how I think about every day. And maybe I'll back up and say I think as leaders, as we advance in our careers, at my level, my job is really about how do I make good decisions? How do I help others make good decisions? Because I'm not actually the person that does the real work anymore, right? It's about how am I prioritizing, how I'm supporting and enabling a trade-off to be made, how am I unblocking a blocker, right? So if I think about it in that lens, there's four agents that fire off that really help me think about my day. The first one is like we probably all have, is just here's what my day and week look, right? So going across my calendar, my email, my Monday boards, my juror tickets, everything else that under normal circumstances, I'd be very reactionary to, right? And help me think about the areas that I need to prioritize. The second thing I have is a broader market briefing. What's happening across the market, what's happening from a regulatory perspective, any big news, any financial jitters, things like that that might impact my market. The third one is looking at the competitive landscape. And this one took me a little bit of time to tune up and get the way I wanted because I don't want just the typical name competitors. What I was very interested in is we used to say two guys in a garage. Now it's literally one dude or gal in a garage with some agents, right? That's it. So I want to know who's out there that's making noise like that in my space. Because A, I want to know what they're working on just from a problem-solving perspective. And B, it gives me a sense of the market's appetite to take risks on these hungry early startups. And then the fourth thing is just what's happening for me in pharma, right? We're a highly regulated environment, it's a very diverse landscape, and I just want to understand what the core problems and news is of the day as it relates it to my target buying persona. So every day, those are the four things I start with, and it just brings into focus what actually matters for me. But that's the way I oh, and another one's just about what's happening in AI. That too. So every new release, whether it's Fables launched or Fables Gone, all that other stuff. That's how I think about just keeping up. And then beyond that, it's making time to be with your customers and with the folks that are in front of your customers. I was very lucky. Like yesterday, I spent a day with a handful of our customers just talking about AI and where it's going and where they see their challenges. And I gotta tell you, the more time we can create to do work like that, man, the more clarity we're gonna get in actually understanding what matters.
SPEAKER_02Yeah, I think that captures sort of the product leadership role these days, right? More hands off, but also more hands-on in the technology and experimenting for ourselves so that we can get a better understanding of kind of where we headed. I love that summary. I want to go one level deeper before we start to wrap up here. I'm really interested in how your product teams have changed the most. What are they doing dramatically differently than the old stereotypical product development lifecycle? What are the one or two things that you think have made the biggest difference in being able to make this transition to a one-day build cycle and prototyping cycle, market fit quick, and you're on a 30-day to a 60-day roadmap outlook. What are the one or two things that you've infused or changed about how the organization of the teams work that has enabled this type of change?
SPEAKER_03Yeah. So first and foremost, I think as product leaders, we have always been of a mind that failure is a good thing, right? Failure is a good thing because in that we learn and failing sooner than later is obviously always better from a blast radius perspective. Well, one of the things I'm trying to really encourage is the notion that more than any point in our history, we have an opportunity to fail very quickly, right? If my agents are building product in three, four-hour runs, and even that's a long time, depending on the circumstance. How great is it that I can take some product requirements and within a few hours actually see what is the output? And does it work the way I thought it would work? Or better yet, within an hour or two, put together a rapid prototype and go find out what that means. So the blast radius of being wrong has never been smaller. And we should go out and embrace that because you know what? Being wrong 20 times, but doing that in a course of a week. Imagine how much we've learned in being wrong 20 times in a week.
SPEAKER_02Sorry, are you learning from customers that fast as well? And is there any secret to getting that customer access and turnaround?
SPEAKER_03So I will say that's perhaps not second nature to us just yet, but that was actually one of the reasons why yesterday I was with a round table of customers was to walk them through some of the innovations. Now, one is something that we've launched or just launched a couple of days ago and given them a sense of where we're going and the capabilities that it's going to enable over the next several months to a couple of years. And the other was a totally white piece of paper prototype that my solution consulting team had been ruminating on and toying with and collecting VOC on. And so we thought, you know what, why not put that in front of our customers? And first of all, the market is hungry to understand where a company like Nostella is going from an innovation footing and how we are investing to better support them. They actually want us to succeed and they want to tell us everything that's wrong with it and everything that's good with it. And I want them both. But yeah, the idea that whole thing came together in really a couple of weeks of this is a great idea that we want to get some feedback on. And that can happen in as short as a few days. I can walk out of a customer meeting saying, you know what, he really had a problem that he articulated to me that I don't have a product for, but I'm pretty sure I could solve that. And call back the next day. This is the culture that we're trying to infuse. I wouldn't say we're there yet. Again, it's all very early, and there's a lot of, to your point, roles are converging in the broader scheme of things, but we're gonna figure it out. I absolutely believe we'll figure it out.
SPEAKER_00So many gems in what you've said. And I'm gonna be quoting you on things a thousand interns. I love that. So many other pieces. As we finish, you are ahead of many of the people we talk to. And we like you, spending time with customers, ours are product leaders, and we've had the opportunity over the last few months to talk to gosh 50, 60 product leaders, and we're all in different boats trying to move to do some of the things that you're doing. If you were to give one piece of advice to a product leader who's looking at this and saying, gosh, it feels so far away. How do I get there? Like, how do I start? What would you say?
SPEAKER_03Yeah, so there's an old Asian proverb that says, the best time to plant a tree is 20 years ago, and the second best time is today. So my advice is you gotta just start. And if you're not sure where to start, again, at no point in our history has information been so available, instructional information. You can go ask a Chat GPT or a Claude, how do I build this? How do I build a skill? How do I build an agent? How do I think about X? And you will get very compelling information. Now, it may not be 100% right, but that's part of the journey. Go learn and decide for yourself which parts of it were right and worth keeping and what part of it was just noise because these LLMs are trained to sound very convincing. But that's part of the journey. That's part of the journey is for you to go and expose what you don't know in an effort to learn it and be a little bit vulnerable. And if you can't be vulnerable to a machine, then how will you ever be vulnerable to a customer to a market? So, this is what I absolutely encourage new product managers to do. And the tools are out there. And the second thing I would say is find somebody or some people that are willing to go on this journey with you. Because the other thing that I have found really important is me and my CTO, we talk practically daily about the things that we're learning and we're observing. And his perspective is very different than mine. But at the end of the day, we are both committed to how do I create speed, productivity, and ultimately value for the market. And we talk every day about these constraints and what we're learning. Find a peer group to go through this journey with, same company, different company, doesn't even matter. But find that group that you can learn with and share with because that's how you create accountability, right? You create accountability by feeling accountable to share what you've learned and hopefully learn from that person or people.
SPEAKER_02That's great. Great advice. This has been so wonderful. Such it's chock full of advice and really great perspective. You are definitely ahead of the game in quite a few areas, and this is going to be certainly helpful for our audience and just really appreciate your time and energy here. And we wish you the best of luck in your endeavors in AI and transforming your teams to work faster as well as smarter. Again, appreciate your.
SPEAKER_03Thank you so much for having me, guys.
SPEAKER_00Thank you, Chris. Thanks, Chris. Thanks for listening to this episode of the Product Rebels Podcast.
SPEAKER_01If you enjoyed this conversation and want to learn more from Product Rebels from companies like Netflix, Amplitude, and beyond, please follow us wherever you listen to podcasts and join us for another impactful interview in about two weeks.