Dr. Christina Agapakis on Turning Science into Products (and Back Again)

Introduction to Synthetic Biology and Product Management

Rina Alexin | 00:02.204–00:55.06

Hi everyone, and welcome to Productside Stories, the podcast where we reveal the very real and raw lessons learned from product leaders and thinkers all over the world. I’m your host, Rina Alexin Alexin, CEO of Productside. And today I’ll be speaking with Dr. Christina Agapakis, a synthetic biologist, writer, and creative leader whose career lives at the intersection of biology, design, and storytelling.

Christina is the founder of Oscillator and the former SVP of Creative and Marketing at Ginkgo Bioworks. She’s known for translating complex scientific concepts into cultural stories and experiences that resonate. I’m thrilled to have her here to talk about what scientists can learn from product management and vice versa. Welcome to the pod, Christina.

Christina Agapakis | 00:55.06–00:57.318

Thank you so much. It’s great to be here.

Rina Alexin | 00:57.318–01:14.31

Well, Christina, you are a very unique person for me to interview. We don’t normally get scientists on this show. And with that, I’d love to hear a little bit more about your story and just how you got in, essentially, how did you end up becoming the founder of Oscillator?

Christina Agapakis | 01:14.31–03:22.786

Thanks. Yeah, I think it is a little bit weird, my path, I’d say. I did start out as a biologist, obsessed with biochemistry, honestly, like how cells made energy and made things and made organisms, and in particular microbiology, like what microbes can do in the world and with our bodies and in the environment.

And I wanted to do that forever. And so I started a PhD in biology and I ended up meeting a professor who was doing synthetic biology. And I had never heard of synthetic biology. I was like, well, what are you doing? What does it mean to be synthetic and biology at the same time? She’s like, well, I’m a biologist, but synthetic biology is all about designing living things, designing biology to solve big problems.

to solve climate change, to make new kinds of medicines, to do things in the world. And that was really exciting to me, this idea that the stuff I loved about biochemistry, how enzymes work and how microbes do things, could actually start to be applied to solve these big problems. And so…

I became a synthetic biologist. I joined the lab and I started doing projects in biofuels. So yeah, applying biochemistry, the metabolism of microbes to creating fuels that could be used for everything. And so what happened though, what ended up happening to me in that process is sort of like…

learning about like what what sort of determines all of these things that happen in the world? How do people make choices? What are the kind of like policy implications? What happens when new kinds of fuels or technologies kind of enter these these very very complicated geopolitical things that happen when we’re talking about climate change and energy? And I kept being like, I don’t know guys, this seems like a bigger thing than enzymes and like what I can do at the bench.

The Journey from Biology to Synthetic Biology

Christina Agapakis | 03:22.786–04:56.85

And there was a sense, think, from the sort of scientists and the engineers, again, like the point was to solve these problems, but we knew that they were just too big and like beyond what we could really do. So there was a sense of like, don’t worry about that. Like just think about your enzymes. And it just didn’t feel right to me. And so like, I spent a lot of time like, you know, reading and learning and trying to figure out like, what do I do as a scientist?

who wants to really understand and solve problems in the real world. When we are pointing our research into the real world, what does it take to do that translation? And I found this whole world of design, of product, of social studies, science, of the political and economic and real cultural dimensions of how science translates. And that is a really, really interesting and big and messy world.

And so I didn’t really, anyway, I spent a lot of time just trying to learn and read and write and think. And that reading and writing and thinking turned into collaborations with designers, a blog about synthetic biology in the world, interesting kinds of new sorts of projects, and led me eventually to work at Ginkgo in marketing, which is again, where does the science interface with the world?

What are the things that we need to do to like be be in the world? What are the stories we’re telling about the future? And about those like the actual things that happen to be able to translate that science into impact

Rina Alexin | 04:56.85–05:03.699

Yeah. So I love your story. And honestly, I have also the same kind of reaction. What is synthetic biology? Like an oxymoron, right? But essentially, what you are saying really resonates with me and I think with our audience because in product, we often, I think we use a lot of very similar, I will say like scientific exploration methods, where at the end, you have to be curious, you have to know how to experiment.

Christina Agapakis | 05:03.699–05:21.486

Yeah.

Christina Agapakis | 05:21.486–05:26.652

Mm.

Rina Alexin | 05:26.652–05:30.921

but you also need to have this also commercial view. and so I’m curious because it sounds like, you know, given your background in biology, but also your understanding of marketing, your work has really helped you just understand the two sides of research, but also application in the real world and the commercial implications of that. So maybe you can share a little bit about.

Christina Agapakis | 05:30.921–05:51.57

Hmm.

Christina Agapakis | 05:51.57–05:54.138

Yeah.

Rina Alexin | 05:54.138–06:04.11

some of the parallels you see having been on both sides of, I guess, is it sides of science and product?

Christina Agapakis | 06:04.11–08:24.148

Yeah, actually like, maybe that’s a funny thing for us to sort of keep unpacking and exploring, right? Like, what is that edge? Like, are they sides? Are they a continuum? Like, are they like a messy, tangled, like, you know, hairball of things of sort of going back and forth? I think as a scientist, like when you’re sort of like, I’m a scientist, I do basic research, I care about science.

Like we do like really put up a wall between kind of science and its application and like the world, right? It really is separate things and it’s separate kinds of work to think about how it might be applied and how it might become technology. And so, and we often think of like the technology kind of part and innovation and applied science is like, that’s a little bit downstream from science. And then downstream from that, like maybe then you start thinking about,

the commercialization like okay, wait, who is going to buy it? And then maybe after that you’ll think about marketing like what’s the story? How do we talk to people? And I think actually like my experience over time has been like it’s actually the big tangled mess, right? Like we are thinking about and worrying about like that kind of story how people make sense of new technologies, how people think about in the context of bioengineering, genetic engineering, synthetic biology.

How do they think about GMOs and GMO technology and how that gets into their daily life? Those are stories that are very salient to us and they influence the way that we might think about the scientific questions we’re asking, even at a very basic level. And then in the technology side too, again, we have to be thinking about where is the money coming from to be able to invest into research and development of new kinds of technologies.

How will people use these kinds of things? Where are they going? There’s always this kind of tangle up of everything, right? There’s even a back and forth with the science, right? New kinds of technologies give us access to new kinds of things. We can see into cells in a different way than we could have before, right? We can ask new kinds of questions as scientists, and we can make new kinds of products as engineers and in the sort of industry context.

Bridging Science and Product Management

Christina Agapakis | 08:24.148–08:35.824

right? And so I think we’re always thinking about all of these all the time and then always kind of like putting up the barriers in between them. I’m not sure I’m answering your question which is like what is the similarity? Yeah.

Rina Alexin | 08:35.824–08:47.212

Well, that’s going to do a little bit. Because I think there’s really a lot in what you’re saying. And when I see it in a non-science world, right, in the enterprise space, for example, I see very similar types of walls being kind of potentially built around like the engineering and the technology department, as well as product and marketing from the perspective of actually then almost exactly as how you outlined it. It’s like, here’s this cool thing. Here are the implications of what we can now do.

Christina Agapakis | 08:47.212–09:04.07

Yeah.

Rina Alexin | 09:04.07–09:16.558

But then only downstream do we start thinking about the people who might use it or buy it. And I think a company gets into a lot of trouble sometimes when the technology is that forcing function versus a clear understanding of how are people going to then use and pay for it because they find it valuable. Whereas maybe in some more science-based research,

The Interplay of Science, Technology, and Society

Christina Agapakis | 09:16.558–09:28.69

Mm-hmm.

Rina Alexin | 09:28.69–09:47.889

the money comes from grants and curiosity around specific questions that might be bigger than an immediate commercial application. it’s like the, it’s different constraints when it’s a private company versus funded research. But the process is what I’m interested in is does the process completely change because of those constraints? Or do see that there are still

Christina Agapakis | 09:47.889–09:58.214

Yeah. Yeah. I think often, yeah, like the

Rina Alexin | 09:58.214–10:12.686

because there should be some benefit ultimately to an end user or end consumer from even the grant research type of funding model. So there should be something there.

Christina Agapakis | 10:12.686–12:33.742

in the grants, right? Like there is often a downstream impact kind of considered. Like, you know, the more we can understand about the processes of what’s happening inside of a cell, like that actually helps us understand things about disease progression. often again, it’s linked in that way. Or like the more I can understand about the metabolism of certain kinds of weird microbes, actually like that could point us towards different kinds of processes that could be used in an industrial.

So again, often there is that sort of link to a kind of very far downstream application. But maybe like, yeah, beyond that sort of like the negative of like, yeah, we draw, we create all these boundaries and that’s similar across. Maybe the other thing that’s kind of been interesting to me when I, in thinking about kind of both, like really the nitty gritty of the process of scientific discovery, like and the nitty gritty process of like product discovery.

and kind of like the design process. I think that we often have this kind of like a very kind of like simplified model, like where you kind of, you’ll draw, you can draw a little diagram of what the process looks like, right? So the scientific method, you are going to like observe something, you’re going to come up with a hypothesis, you’re going to experiment that hypothesis, you’re going to like get results and analyze them, and that’s going to like bring you new observation and the cycle repeats.

I think you have a similar kind of thing that people draw different lines. You can call it design thinking, you can call it product discovery, you can call it anything, but there’s a similar kinds of structural, like there’s little arrows and there’s very sort of simplified schematic. You could put it on a PowerPoint slide. But then, I’ve had this experience now to also teaching, and I’m curious if you’ve had this experience where the students are like, you’re not actually teaching me how to do these things. You’re just like.

telling me to do them. And then I’m realizing, that’s actually right. It’s really hard to actually explain what happens in your brain when you are coming up with a hypothesis. What happens when you’re like, of like, I don’t want, that doesn’t feel right. I’m gonna try this other thing. like, what happens when you’re kind of testing, not that hypothesis yet, but even kind of checking it against what people have done before. You Google the question, right?

The Messy Reality of Scientific Discovery

Christina Agapakis | 12:33.742–12:49.446

You see how other people, like the methods that they’ve used to sort of talk about that question. It is like, it’s not a straightforward, simple loop, right? Like there’s all of these things. So I think there’s more, what I’m saying is there’s more parallels than there are differences. Yeah.

Rina Alexin | 12:49.446–12:55.778

I think you’re right. And by the way, when we do talk about design thinking, the PowerPoint slide that we do bring up is not neat whatsoever. In fact, it represents essentially what you might be alluding to the tangled mess, which is the reality is there is this sterile way of viewing design thinking where you like it go from each stage to one to the other, and then you come up with the answer, but that’s not how it happens.

Christina Agapakis | 12:55.778–13:04.023

Yeah. really? OK.

Christina Agapakis | 13:04.023–13:16.24

Nice.

Rina Alexin | 13:16.24–13:21.772

You always go back, you always find something new and you set yourself up on various paths depending on that information that comes up. And I think that really is, that’s what you’re talking about. That truly is what scientific discovery feels like as well, where you might start somewhere with a hypothesis of where you’re going and where you end up is completely different because of that new information that arises. Yeah.

Christina Agapakis | 13:21.772–13:41.07

Mm-hmm.

Christina Agapakis | 13:41.07–13:42.812

Absolutely.

Rina Alexin | 13:42.812–13:43.918

So, but I still think that there is something here for us to kind of talk about, which is maybe it’s like the culture aspect. And I don’t know, so you know, I don’t know how the scientific world operates, but I’m curious because you brought up this idea around silos and silos can, in some ways they try to organize how people think and work and work together. That’s why they come up. know, they try to, I think most people have silos,

Christina Agapakis | 13:43.918–13:51.234

Yeah.

Christina Agapakis | 13:51.234–14:12.306

Yeah.

Rina Alexin | 14:12.306–14:21.164

in an effort to be helpful to the organization. And then there’s actually impedance on the outcomes generated because people are stopped talking to each other or some other process or something comes in the way. what do you think in terms of having experienced scientific exploration and then marketing? I would imagine you work differently.

Christina Agapakis | 14:21.164–14:41.646

Mm hmm.

Silos in Science and Product Teams

Rina Alexin | 14:41.646–14:50.51

in a marketing team than you do on a research team. so maybe we can talk a little bit about how those two types of teams operate and what they can maybe learn from each other.

Christina Agapakis | 14:50.51–15:05.942

So fun. I think…

Christina Agapakis | 15:05.942–17:23.148

Gosh, it’s such a big question. I do like the point where you’re saying about like, I do think that there is a clearly a utility in silos, right? Like and sort of like being able to like name a practice and like articulate it and like talk about like what happens at the transitions between these different kinds of teams or things that need to operate. I think my…

It’s funny because I think my sort of experience has been so gradually kind of moving from research to marketing that I’m almost like a frog in the water. Like, I’m like, it was always the same. again, like I’d be like, and it’s an often with the same people. Like, you know, I’m sitting in the room with like some scientists, like we’re trying to figure out like us interesting problem. We’re trying to apply it. Like we’re kind of like, yeah, we’re.

we sort of see a problem, we have a kind of goal in mind, we see the kind of issues and observe and we’re like, let’s try something out, like, what about this? like, and it would kind of like push on each other and try something out, see how it goes, like do it. Like, I think that the tactics look very different, right? So like 20 years ago when I was in the lab and the guys and I were chatting, we’d be like, oh, like, let’s go see what happens if we like got that gene and put it into the E. coli.

I wonder if what would happen if, and when I’m in marketing, like, I wonder if we could, there’s a story here that we should write an op-ed about this or that, or like, what if I made a sticker that had this funny thing on it, right? like, people would really, at the conference, people would really resonate with something like this, right? So the tactics are different in the kind of mark-coms, or even on the Productside.

And the Productside is actually where they’re exactly meeting, right? So like some of the work I was doing at Ginkgo a couple of years ago was even thinking about like, yeah, what are the ways we work in lab to generate data? And how does generating data, like now it needs to be a product that people can actually buy and access? Like scientists want to make better AI models. They need better data for those models.

The Role of Collaboration in Research and Marketing

Christina Agapakis | 17:23.148–18:27.388

How do we build trustworthy data sets? How do we do data generation as a service? Now that starts to look pretty similar. Like, what if we tried this cell type? Would lots of people be able to use that? Would it get us high quality data? How do you think about this? And again, partnering across specializations happens immediately. So not even silos, but everybody has such unique specialized

skill sets in a lab context and in an industry context. Like, like I know a guy who knows this or that or like, we have to talk to this person. She knows so much about like, yeah, like how to, you know, do CRISPR screens in mammalian cells. we have to talk up to this person. She’s the best at sequencing microbial genomes. And so like you’re always kind of finding like the specific expertise, like and trying to kind of synthesize across like all of those people’s constraints.

towards some kind of output.

Rina Alexin | 18:27.388–18:36.334

So is that what you were doing when you were in a lab? Because what you’re describing does very much sound like a product process to me.

Christina Agapakis | 18:36.334–19:10.192

Yeah, I mean both, right? Like I’m saying like in the lab it would be like, okay, I want to well, especially because we were doing synthetic biology. was like, I want to make a bacteria that can produce hydrogen like, okay, like I need I need to find this piece that could do that. Like, let’s test it out. Like, let’s try this one. that didn’t work for the street. Like, let’s keep kind of assembling the parts. Here’s a prototype. How does it operate in this context? Like, let’s try that again, right? Like, and then that was very much a kind of iterative engineering kind of

product process. The other one was explicitly a product process. Yeah.

Rina Alexin | 19:10.192–19:21.196

Yeah, okay. The reason why I ask that is because I’m just curious, you know, in a lab environment, again, without a specific user in mind, you might be asking very similar types of questions, designing similar types of experiments, right? That’s what we’re talking about. I mean, we talk about it all the time in our class, like the how might we statements, right? To create the hypothesis and then what is the small type of investment you can make in an experiment.

Christina Agapakis | 19:21.196–19:29.602

Mm-hmm. Mm-hmm. Mm-hmm.

Christina Agapakis | 19:29.602–19:38.256

Mm-hmm.

Rina Alexin | 19:38.256–19:58.602

But there’s a difference, I think, with commercially applicable or even not commercially applicable, because there are IT teams that might not have, be selling something to someone, but they have end users versus how, like they get feedback from the market.

If you don’t have that, work it. Yeah.

Christina Agapakis | 19:58.602–20:04.188

In science, get feedback from the bacteria, like the real world. Your targets are different. And the thing that you’re measuring is not like, the customer buy it? Did they click on it? Did they interact? It’s like, did the bacteria die? Did the bacteria produce the thing I wanted them to? Did they produce it more than before?

Feedback Mechanisms in Science and Product Development

Rina Alexin | 20:04.188–20:26.638

From the back.

Christina Agapakis | 20:26.638–21:12.626

Again, that’s still in an engineering context. In a basic science context, again, you wanna design your experiments in a way that is going to be informative to your ultimate goal, right? yeah, often it is something like, yeah, did it glow or not? Did it move here or not? Did it live or die? Is it related to this? Did it bump into this?

Did they connect to each other here? I, you you’re trying to again, like set up an experiment where the outcome gives you something informative about the fundamental nature of what’s going on. When I delete this gene, the cell, you know, does something weird. Like what happens? Yeah. And so like, yeah, the results of the feedback. Exactly. Yeah. Yeah. Yeah.

Rina Alexin | 21:12.626–21:31.308

Sure. Yeah, so the results are your feedback. Okay, so then let me then ask this question. Are there any true differences in the way that a product team might be exploring a question versus the way a science team would be exploring it?

Christina Agapakis | 21:31.308–22:19.708

I think at some fundamental abstract level, I don’t think so. Again, I think that ultimately iterative exploration of the world is fundamental and fundamental to how we understand things and make sense of the world and make things in the world. And so whether you’re doing that, again, in a company trying to sell

some widget or whatever, or you’re a scientist trying to uncover something, or you’re just a normal person trying to do normal things, like make stuff happen in your life. We are constantly trying to sort of, yeah, getting feedback from things that we’re doing in the world, right? And so I think there is something very foundational, fundamental, that is very, very similar.

Rina Alexin | 22:19.708–22:29.016

Do you find that there could be, don’t know, mindsets or practices that the scientific community could learn from the product community, given that at this point I’m ready to kind of like announce to the product community, y’all are scientists.

Christina Agapakis | 22:29.016–22:33.198

Yeah.

Christina Agapakis | 22:33.198–24:32.198

You know what, scientists? I think that,

I think that the difference between, maybe like a difference, like isn’t sort of like the boundaries of our curiosity and the sort of like directionality of like where are the scope and like the scales that we try to bridge, right? So like, I think it’s really hard to kind of bridge across like a molecular scale and like a human commercial scale.

So if I’m asking a question of what is happening when this gene turns on and how does that impact the ultimate behavior of the cell, it’s hard to then say, OK, and what does that mean for the economy of agriculture? That’s sort of a difficult bridge to jump. And I think vice versa, right?

product marketing manager trying to think about introducing a new food product on the market, it’s hard to now say, what’s happening at the molecular level here, beyond what might matter again to consumer. And so I think the ability to of bridge some of those scales, or in particular to care about the human and commercial scale.

I think is a domain that lives more in marketing than it does in science. I think in science, we’re much more comfortable at the molecular or the universe scale. And then it’s hard to bridge into what does it mean? And so I think when you’re asking around the feedback, the user feedback, I think that’s often just too far for most scientific people to think.

The Importance of Understanding Users

Christina Agapakis | 24:32.198–25:08.26

and to kind of get into the theory of mind of a consumer or somebody else is very hard for scientists. we can get in, we do sort of get into the minds of molecules, literally. But thinking about how somebody might understand this in their daily life as a product is often too far. And sometimes, again, like I said, I think we kind of deliberately put that wall up and say, that’s not for me. I can’t do that. I don’t think that’s true.

I think we can be thinking, it’s hard and there are kind of constraints on us, I’d say. So yeah, think about people. That’s the advice.

Rina Alexin | 25:08.26–25:28.856

Yeah. And think about people. Well, I think that makes a really, really good point. And I, you know, we kind of talked a little bit at the start about funding models of like, does re essentially be the question I have here is like, how does research come about? Right? Like who’s funding it? Who’s asking these questions? What is the source? What’s the point? Right. At the end, because the point for a product it’s to solve a useful problem out in the market.

Funding Models in Science vs. Product Development

Christina Agapakis | 25:28.856–25:36.048

Yeah.

Rina Alexin | 25:36.048–25:43.002

whereby that company by solving that problem gets to grow and have value and have revenue. Whereas with the science, Tiffy exploration, it really depends. And I think, you know, given what a lot of the American public has been seeing also about various scientific experiments that they would or would not want to fund. it’s, it’s a good question around like how, what is behind what gets funded and what gets researched.

Christina Agapakis | 25:43.002–26:05.57

Yeah.

Rina Alexin | 26:05.57–26:10.486

And what’s the point of that?

Christina Agapakis | 26:10.486–28:26.67

asking the right questions and I think like huge questions actually. And so I think again, like there’s a similar kind of force at play here where again, as scientists we want, we have this sense of like, there is a sort of purity and objectivity to the practice of science. Like it is about like curiosity.

free of anything else, free of human subjectivity as much as possible, free of politics, and free of the need to have a sort of applied outcome. And that is not true and has never been true about science because somebody is paying.

And again, there’s the kind of science that happened in the olden days where there’s like a rich guy just doing it for the love of the game. And like, again, even then, like there’s a politics to that. Like what are the kinds of questions that like make sense to a person like that? Like what are the questions that matter? How do they have, how have they come to a lifestyle where they can do that? Are all interesting kind of questions that you can start to ask and think about the context of that science.

In the context of the last hundred years in the United States in particular, like a science was very deliberately funded, like as part of a social contract of like funding basic research, like will lead to economic strength and military strengths. That like, if we can, we invest in these kind of basic research questions, like it is deliberately because it makes our nation more economically at

politically and militarily powerful. And like the ways like the direct that we may not be able to predict the direct line between them. But there’s kind of an equation of like, the more money we put in, like the more science there is, the more like, yeah, the more defense power, and the more economic power there is on the other because somebody will figure out how to translate that science into something impactful. And so then in practice, that looks like

Advice for Scientists and Product Managers

Christina Agapakis | 28:26.67–29:45.52

the government agencies that fund that science have ideas about what that looks like. What are the kinds of research that are going to be the kinds of things that in the case of healthcare and basic research in biology, a pharmaceutical company will be able to apply it and translate it into a drug that people can buy in a way that is financially viable for them to exist as a business and helps grow the health and wellbeing of the population.

So they have ideas of what that is. Anyway, so what I’m saying is like, these are big questions about like kind of fundamentally like what is the social contract? Like what is our belief in like what it makes for a good life and like what is a good society and a good country? And we invest in those. And I think that’s like, that is now like changing very dramatically before our very eyes. And I think a lot of that.

we’re coming to a realization of, well, yeah, these conversations are about what matters to us and what future we want to live in. And what are the constraints of our society, our economy, and our institutions that make it hard or easy to translate certain things versus others into impact?

Rina Alexin | 29:45.52–29:50.104

Yeah, you might not like my next question because it’s also going to be a big one, but I love your answers. I love your answers. I think they’re important. mean, I’m glad you and I are having this discussion. I can imagine a lot of people in the US and globally should be having these kinds of discussions because I think that there is a there’s a place and a space for product management type thinking in the scientific community because what you just said, I mean,

Christina Agapakis | 29:50.104–30:08.638

I like big questions.

Christina Agapakis | 30:08.638–30:13.232

Yeah.

Rina Alexin | 30:13.232–30:27.245

Somebody has to make that downstream link eventually, right? And so the way that I think product people think about it is they try to really understand the market, right? Like who are we serving? mean, the personas, do use personas in science? are there… Here’s a question, are there personas in science? Man. Yeah.

Staying with the Trouble: Embracing Complexity

Christina Agapakis | 30:27.245–30:37.102

Mm-hmm.

No.

Christina Agapakis | 30:37.102–31:33.132

Not explicitly. think often again, there may be implicitly, there’s a patient that you might want to understand at the end. But again, often it’s abstracted down to, there’s a patient who has this physiological situation. We’re rarely thinking about the patient holistically. Who are they? How are they living? What are the other kinds of impacts that their condition is having on them?

How might a drug be part of that world? I think it’s again, like that it’s hard. It’s so hard to do science. It’s hard to make drugs. It’s hard to do this kind of research. And so like, I think I’m asking a lot to say like, okay, also think about people. So again, part of it is like, what’s the bridge? What’s the dialogue between the people who are thinking about that at that level? And how can we have better conversations there too? I think that has to be part of it. And keep going.

Rina Alexin | 31:33.132–31:35.958

I mean, I guess that’s the point I’m also trying to make. We’re aligned. We’re very much aligned on this. Given the importance of thinking about it and people, the other part that I was thinking when you were talking is the funding model. At a company, you fund a lot of what we like to encourage people to do is fund a lot of small bets. But in the scientific community, I think some of these bets are quite large.

Christina Agapakis | 31:35.958–31:50.126

Yeah. Yeah. Yeah.

Christina Agapakis | 31:50.126–31:56.738

Yeah.

Christina Agapakis | 31:56.738–32:00.718

Mm-hmm. Mm-hmm. Yeah, yeah.

Rina Alexin | 32:00.718–32:16.706

as well. And so that, you know, a company would not be the right funder of that. Because, I mean, correct me if I’m wrong, but I would imagine that most scientific explorations fail. On purpose, they or they come out with sorry, they come out with a result where, you know, that hypothesis is disproven, and therefore it’s not a viable, you know, observation.

Christina Agapakis | 32:16.706–32:30.63

Yeah.

Rina Alexin | 32:30.63–32:30.947

Can I put it

Christina Agapakis | 32:30.947–34:16.508

Yeah, mean, that’s sorry. Yeah, exactly. I think you’re right, right? Like there’s lots of a lot of these things are not going to become the winner. Like the thing that’s on the market, the thing that everyone uses. I think you’re totally right. And I think that’s actually, again, like an interesting thing that’s happening now. And some of the stuff I’m most excited about is also

Like there are a lot of really interesting organizations that I’ve been working with and collaborating with now in sort of my new world, like no longer at Ginkgo and now at Oscillator, a kind of independent consultancy. And so we’re partnering with a lot of different organizations who are thinking about exactly these questions. Like what, how should we be funding, incentivizing research, thinking about new ways of doing this?

to fill some of the gaps that seem to exist, right? Like exactly what you’re saying, right? Like there are certain kinds of scientific work that are not really ready for like the kinds of pressures that a startup is under to like hit commercial milestones, but need a kind of startup-like focused effort. So like this is now something that people are doing.

called focused research organizations. Again, trying to create a new kind of institution that’s funded in a different way with a different kind of structure that’ll help, again, fund that kind of research that people see that needs to happen that doesn’t quite fit what a company should do or really what an academic lab should do. And so there’s an organization called Convergent Research that’s funding that kind of stuff and trying to find those kinds of gaps.

and the kinds of gaps in the institutions. So like that’s just one example again of like new ways that people are approaching like how we fund and structure the scientific discovery process.

Conclusion and Future Directions

Rina Alexin | 34:16.508–34:19.508

So you’re telling me there’s innovation yet in science. All right. Well, given everything that we’ve talked about, I appreciate this kind of conversation. I want more people to have it. What advice do you have for, let’s say both, product managers and scientists on what they could be doing to make their work more important?

Christina Agapakis | 34:19.508–34:42.72

Yes, yes!

Yeah.

Christina Agapakis | 34:42.72–35:38.32

This is such a fun question because I think like, well, I actually have a question back to you. So like my impression again, like for scientists, like again, we want to make impact. But like once when you’re actually making impacts, like when you’re in the real world, it’s not pure anymore. It’s not necessarily like following your like, your plans exactly as you predicted.

You have to sort of be adjusting to the messiness of the world all the time. And so I’m curious if your experience, like, do you find like that people who are maybe new to product management are getting into it, like that there’s a sense of like, well, I made the roadmap and I made the plan and like, we’re going to do the plan and we’re going to make the product and it’s going to work. But like that they sort of struggle with that moment of like meeting the real world and like, or are they like more ready for it because it’s like built into the way the mindset.

Rina Alexin | 35:38.32–35:44.462

It depends on the, what kinds of principles they follow as product managers. And the reason why I say that is the way that we like to, so at Productside, when we go and we try to teach, new product managers or even product managers who’ve been doing it for a while, but maybe struggle with what you’re saying is that there’s so much unknown out in, in the world that you. Putting a roadmap together really should be about putting a roadmap of what outcomes you’re trying to drive.

Christina Agapakis | 35:44.462–35:55.587

Mm-hmm.

Christina Agapakis | 35:55.587–36:07.246

Mm-hmm.

Christina Agapakis | 36:07.246–36:07.6

Cool.

Rina Alexin | 36:07.6–36:37.574

And the experimentation that you do on a day to day, all that discovery work, as well as the experimentation, validation of your assumptions should be as small as possible. And you need to get used to most of them not working out. so, that’s something that if you are going to be in the product management career, you need to be very comfortable with. And it sounds like for science scientists as well. mean, and I even think about it, and maybe this thought came into my head.

I get really, I empathize a lot with product teams where they were not put in a situation where they could validate early and realize whatever they’re working on isn’t going to be viable. And those teams end up sometimes putting in years of their career into a product that has no adoption out in market. That, you know, outside of the business financial loss, that is a people loss. that, those are.

Christina Agapakis | 36:37.574–37:07.1

No.

Yeah. Yeah. Yeah.

Rina Alexin | 37:07.1–37:45.172

two years, three years of people’s valuable time spent on something that’s not valuable. And so that’s why I say, at ProductSite, we really try to break it down into these smaller bets so that you don’t end up in that kind of situation. But I don’t know if that’s true in science, right? Sometimes, especially with pharmaceuticals, right? It takes a long time to know whether not something’s gonna work out. And so you have to just, that’s part of, I think that’s like a feature.

in some ways in those kinds of cycles versus where we’re talking about software where you can get this immediate user feedback. I get your answer to your question?

Christina Agapakis | 37:45.172–39:04.178

No, I think you did. So I think it’s great. So I think you’re saying, yeah, you’re even trying to make sure in the training that people are kind of staying in it and iterating quickly and going to where they can get that kind of feedback that matters most. I think that, to me,

I think, there’s a sense, or fear that I hear from scientists and that sort of anxiety about sort of like what it looks like to do the real impact work. Like we want the impact, but it’s like, it’s too hard. It’s too far away. It’s too messy. It’s not pure anymore. It’s not research. It’s something else. so like my advice to people is always like, yeah, like be in it, like be with it. There’s a writer I love, her name is Donna Haraway.

She was a scientist and sort of became this philosopher of science and she talks a lot about staying with the trouble of exactly this, like science and the world and technology is messy. It is full of trouble. And like the way that we live through that and work through that is not to retreat into our labs, but to stay with the trouble. And I think that’s like, that’s maybe what you’re saying too, that like being in it and like doing those fast iterations and like trying to like always test.

it into the real world is what matters.

Rina Alexin | 39:04.178–39:23.086

I would agree with you. I also, that so resonates. want to, can you send me the book that you just mentioned? Because I think that’s true, by the way, applied not just in science or in career, you got to lean into it in your life. The world really is messy. it’s almost reflective of like a growth mindset of like you want to

Christina Agapakis | 39:23.086–39:28.454

Yeah.

Rina Alexin | 39:28.454–39:35.179

to accept the world as it is and overcome each challenge because it’s blessing, not a curse, right? So, I absolutely love this conversation. Thanks for joining me. Where can our listeners, how can they stay in touch or follow you after they hear this recording?

Christina Agapakis | 39:35.179–39:47.938

Yeah.

Christina Agapakis | 39:47.938–40:05.03

So I am writing periodically on my sub stack, which is at oscillator.blog, like getting into some of these things again, like what is the way we make science and how does science make impact? So maybe that’s the best way for people to keep in touch.

Rina Alexin | 40:05.03–40:27.33

Wonderful, Christina. We’re going to share a link to that in the webpage where you find this, where you find your podcasts. And if you have found our conversation fun, valuable, interesting today, please don’t keep it to yourself. Please share it with a friend and make sure to subscribe to Productside Stories so you don’t miss a future episode. Thank you for tuning in and I hope today’s insights inspire you and propel your product journey forward.

Rina Alexin | 40:32.655–40:32.655

Visit us at Productside.com for more free resources, including webinars, templates, playbooks, and other product wisdom repackaged for you. I’m Rina Alexin Alexin and until next time, keep innovating, keep leading, and keep creating stories worth sharing.