Category: Uncategorized

• MongoDB (MDB, Financial) is pursuing FedRAMP High and Impact Level 5 (IL5) authorizations.
• Currently trusted by 13 U.S. Federal Cabinet-level agencies and all Department of Defense branches.
• State of Utah implemented MongoDB Atlas for a 25% increase in benefits processing speed.

MongoDB, Inc. (MDB), a leading name in database solutions, has announced its commitment to achieve Federal Risk and Authorization Management Program (FedRAMP) High and Impact Level 5 (IL5) authorizations for its product, MongoDB Atlas for Government. This strategic move will enable MongoDB to manage highly sensitive, unclassified data for the U.S. public sector, expanding its market reach within federal agencies that demand stringent security measures.

The MongoDB Atlas for Government platform, operating currently at a FedRAMP Moderate level, is already a trusted solution for 13 U.S. Federal Cabinet-level agencies, including every branch of the Department of Defense. The platform employs MongoDB’s proprietary Queryable Encryption technology to ensure data protection throughout its lifecycle, which is increasingly critical for federal clients.

Mongodb’s Queryable Encryption is a first-of-its-kind in-use encryption technology, designed to maintain the privacy and security of sensitive data during its entire lifecycle—whether in transit, at rest, or in use. Furthermore, decryption happens only client-side, ensuring additional layers of data security.

A notable success story is the State of Utah, which utilized MongoDB Atlas for Government to manage state benefit eligibility data. The state reported a 25% boost in the speed of benefits calculations, drastically reduced management times, and an improved disaster recovery time, from 58 hours to just 5 minutes.

This move to secure FedRAMP High and IL5 authorizations aligns with MongoDB’s ambition to support critical government sectors such as emergency services, law enforcement, financial, and health systems. Achieving these authorizations will allow MongoDB to serve federal agencies managing the most sensitive unclassified data, positioning it as a formidable competitor for high-value, long-term government contracts.

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Transcript

Olimpiu Pop: Hello, everybody. I’m Olimpiu Pop. And I have in front of me Savannah Kunovsky and Jenna Fizel from IDEO. Well, if you don’t know anything about the company, you can join me as well. I just found a couple of weeks ago that they are the ones who brought the mouse to the shape that is currently in. And thank you for that. And without any further ado, I’ll ask Savannah and Jenna to introduce themselves.

Savannah Kunovsky: Thank you so much for having us and for having us at QCon last month. We had a great time. My name is Savannah Kunovsky. And I’m one of the managing directors of IDEO’s Emerging Tech Lab. IDEO is a global design and innovation firm, and so we work all around the world to use the process of human-centred design and design thinking to help businesses figure out what’s next. And a lot of the work that Jenna and I do in the Emerging Tech Lab is exploring the frontiers of technology, and how to make that technology more useful, and more human, and a lot of the time more interesting. And we like to explore the future of technology, both in the process of design, and the process of how we make things, and also in the outputs of what we create.

And my background is kind of general. I was a software engineer. Towards the beginning of my career, I co-founded a chain of tech schools and was based in Nairobi, Kenya. Lived there and ran that for a couple of years. And I’ve been working in the AI space since before it was cool for over a decade and emerging technology at IDEO for quite some time, too. Jenna?

Jenna Fizel: I am co-MD with Savannah of our Emerging Tech Lab. And we have somewhat similar, but a little bit divergent backgrounds. So, my academic background is in computational geometry and architecture. So, always sat right square in that intersection between design and engineering. I’ve spent a lot of time as a technologist and as a software developer for lots of different kinds of applications, often focused on helping explain complex data to a variety of audiences. And all of my work is really focused on what new technology means in the context of everyday experiences. So, thinking about walking into a room or picking up an everyday object and how those experiences can be changed through new technologies.

Olimpiu Pop: That sounds really cool and quite a nice symbiosis. So, Jenna is identifying new technology and then Savannah is looking how can we better interact with that as humans. I shouldn’t ask this, but where do I apply? It’s really, really cool. So, where do I apply? I’m joking, almost.

Savannah Kunovsky: The answer is through the website.

Jenna Fizel: Yes. We have a careers page. It’s real.

Savannah Kunovsky: And that actually is the best way to come through.

Design is more than just drawing websites and mobile apps [03:14]

Olimpiu Pop: Yes, excellent. Excellent. Usually, people think about, when you say design, they are thinking about, well, broadly speaking, how your website looks like or nowadays, how your mobile app looks like or anything else. But in the conversation that I previously had with Savannah, she just said, “No, it’s much more than that”. So, maybe let’s start by clarifying what does actually design mean in the frame that you already provided?

Jenna Fizel: So, I mean, I think at its highest level, design is about figuring out what questions to ask to understand what people want, what can be made, and how value can be created. So, we often talk about these three aspects of what makes for a good design, being desirability, feasibility and viability, which sort of map to those considerations. But I think in my personal practice, I really think of design and engineering as fairly unified and all about that problem definition at core. And that expresses itself differently, whether you’re talking about designing a website or a mobile app, which are important things that we do. Or if you’re thinking about designing, say a clinical workflow that helps patients and providers spend more time with each other, the kind of base set of considerations can be really similar, even across really divergent outputs.

Savannah Kunovsky: The only thing that I would add is that we say that everything is designed and everything can be designed. And there’s just a matter of how much thoughtfulness and intention was put behind how something was designed. So, if we think about things that we have in our home that just work really well and fit really well into the context of our lives, versus other things that we have where we’re just like, okay, it works well enough, but it’s kind of annoying to use and whatever, I’ll put up with it. We really try to be thoughtful about what we’re creating and what the context it’s going to exist inside of is, so that we’re really solving for the true underlying human needs behind the problems that we’re exploring and trying to solve with what we create.

And specifically, when we work in emerging technology, we are exploring far-out futures a lot of the time, and trying to map what we think will be technologically feasible or what is technologically feasible with what people want and need. And that second part of the statement is the big consideration of the design process, is we can start with an exploration of this company wants to use more AI or they want to go in the direction of robotics. But if we start just with the technology, then we don’t tap into the true needs behind the problem that’s being solved and then the products don’t sell or they aren’t as useful. And so, that second part of the equation is incredibly important to us.

Jenna Fizel: To add a little bit onto that. The closed loop of that system is critically important. So, you can ask yourself strategic questions about what people might want or need. But one of my favorite quotes from one of our founders, Bill Moggridge, is the only way to experience an experience is to experience it. And so, when we design, we’re not just wondering what people might like or need. We’re taking tangible expressions of even future technologies through mixed methods, like simulation and design fiction, to give something to actually respond to feel in some way, so that we can with more confidence understand if that desirability is actually there.

Olimpiu Pop: Okay, nice. Still very exciting what you guys are doing, so my enthusiasm remains with me still. So, just put it simple, you’re just designing the whole thought process into the way how people interact or even the flow with interacting with the given technology. And to make it natural, because that’s what I’m thinking now. Most of the things that we use daily and we appreciate the way how we interact with them, they are just plain simple. They are just extensions of humans and that’s pretty much what you’re doing. You’re ideating and then probably creating some kind of prototype in order to define the interaction. That’s nice.

I’m coming from the technology space. I’m very excited about everything that you’re doing. And as I was sharing in our previous conversation with Savannah, one thing remained stuck in my head from my university. It’s actually my master’s years, when we had a topic that was called ubiquitous computer interaction. And most of the things were far-fetched. And it was almost 20 years ago. But now it seems that a lot of the things are not as science fiction anymore as they used to be, because, for instance, in my current day job, we’re using a lot of 3D printing to just create rapid prototypes, either with resin or filament ones.

How to stay on top of emerging technologies in an extremely fast paced world? [08:14]

And it’s very nice just to be able to look at it. But if I’m thinking about technology, I am thinking about Thoughtworks Technology Radar, but you are even further ahead of that. Do you have a radar like that where you’re just thinking about, okay, this is a technology that is worth looking into? That’s something that we will just leave for one more year to get more pride or something like that? Because obviously, everybody is thinking about AI. Some of them are fearful. The others are very excited. And most of the other people are somewhere in between. They don’t have an opinion about it. So, how do you choose your battles? Because there are so many things happening out there.

Jenna Fizel: Yes. So, there are a few ways this happens. A straightforward one is that we’re a client services company, so we have clients and they have desires. And it’s our job to figure out what those desires are, just the way that it’s our job to figure out what sort of end user desires are as well. But we also have a really vibrant and robust creative community within IDEO. And we definitely use the power of not just being individual designers to spot trends, to see where the excitement is amongst our colleagues in the projects and interests that they pursue outside of our direct client work. We have a variety of structures in place to support this. One of which is a learning group that meets once a week and has now been going on for… gosh, coming up on four years, focused on emerging technology.

So, sometimes we have external expert speakers from our professional and personal networks. Sometimes we have folks within IDEO who are pursuing some interesting technical angle personally. And sometimes we have client project teams come in and share where they are in their process, so that we can all learn and get smarter. And hopefully, see around that corner, which is getting more and more crowded all the time and very full of particular AI startups. So, you can’t keep track of them all. And only I think that through the power of using our collective imagination, can we get any kind of a handle on it at all.

Savannah Kunovsky: Yes. We view technology as building blocks that are stacked on top of each other. So, rather than just focusing on one technology at a time, we think about in the future what is going to be technologically feasible because of the fact that other technologies exist. So, we didn’t go straight from the Stone Age to AI. And we think that mixing together various forms of emerging technology is really interesting, because then you get multiple forms of advanced functionality at the same time. We also work on really varied timelines. So, I have projects that I’m working on right now that are looking at two to three years out and projects that I’m working on right now that are looking at 10 years out. And so, the type of mental equations that you’re doing to think about what might be possible at different timelines is also different.

And sometimes when you are thinking about those more extended timelines, it’s actually about inventing the future, and thinking about where this organization want to put its energy, and its funding, and its momentum to build the future that is going to be exciting for them. And so, sometimes, I guess, always, that’s contextualised in what’s happening in industry, and what trends are we seeing, and where do we think that things are headed. And also, sometimes that future, just because it’s so far out, it just doesn’t exist yet. And we can’t say, ‘ Oh, this company is doing something interesting. ‘ Or we saw this interesting thing in an R & D lab in a university, and so that’s going to be the future.

Sometimes it’s really like, if we squint at what we think might be possible with technology 10 years from now, this company actually is going to go out and invent that thing. And that’s a really fun and interesting place for us to be. And so, we actually have a whole practice at IDEO that is called futuring. And we use the processes of speculative design, so creating concepts that are speculative in nature and futuristic feeling to explore both what the technology might look like in the future, and then also just what life might look in the future.

And so, we’re paying attention to all sorts of social, technological, economic, political vectors of where things are headed and what the world might look like in order to try to almost invent those future worlds. And we obviously take a lot of inspiration from sci-fi, because there have been a lot of amazing authors over the years that have started to create those worlds and set those visions for the tech ecosystem, for better or for worse.

Is our future a “Mad Max” or a “Star Trek” episode? [13:04]

Olimpiu Pop: So, that begs the question: Mad Max, or Star Trek, for dystopia or utopia.

Savannah Kunovsky: This one is straight for Jenna.

Jenna Fizel: Well, I mean, personally, I very much hope for Star Trek. You won’t be surprised to learn that I’ve been a Trekkie since childhood. And I think one of the things that I really love about Star Trek isn’t so much its utopianism, but its focus on competence. Obviously, not uniquely, but kind of unusually amongst very popular narratives. It focuses on a group of professional people doing their jobs mostly well. And I mean, I think my highest aspiration for what my work does is to help in that pursuit. So, do I think we’ll get to a post-scarcity socialist utopia soon? Very, very doubtful for many reasons. However, I do think that design should strive to encourage flourishing in some way.

And I really like how utopian science fiction like Star Trek explores that. While at the same time using the tools of dystopian fiction is really interesting, because it pushes you to consider extremes. And I think that is really critical in the design process, to not just be imagining that sort of happy middle path, but also to be imagining what could go spectacularly wrong or spectacularly well, and making sure that you have room within the systems that you’re designing to accommodate that range of outcomes.

Olimpiu Pop: Okay. Live long and prosper, I suppose. From my point of view, it’ll be a good balance in understanding the need to use our resources carefully. And usually, I would put it in a dystopian frame, but also dream big about what the shiny future could be. There are the utopian ones. And that’s the nice balance, if that can be thought of. So, then I am very jealous of your time budget for your projects, three to 10 years. I think everybody in the software industry only dreams about something like that when people are just negotiating for weeks and months. So, that’s nice. That’s securing the future quite nicely.

But moving back, as you said, your company worked a lot. And as you mentioned, it started in the 1970s, when the mouse was initially built. Just now featuring the past somehow. Are there any situations, any technologies that you said this could have done better in this way or some kind of retrospective, and learning from the past, and the way just to change the design process that you use?

Savannah Kunovsky: Yes. We have many iconic products that are things that people have heard of and used. We worked on the Swiffer, and the View-Master, and the Apple Mouse, and the Palm V, and all of these early iconic products. And the original thinking was taking the process of design and then extending that into a methodology for how to do innovation and how to come up with what’s next. And so, all the time we’re coming up with terrible ideas. And the terrible ideas are actually important for us, because we call them sacrificial concepts. And we take them into testing with potential users and get their reactions to understand how they feel about them. And those terrible ideas take us into what the good ideas actually will be.

And we have definitely predicted things 10 years in the future. And it’s not our job to say here are all of the things and how the world is definitely going to look 10 years in the future. That’s just an impossible thing for us to do. But what we do in our futuring practice is come up with a set of plausible futures, all of which could be possible given the circumstances of future technological breakthroughs, potential resources, and cultural shifts. If those things come true or come somewhat true, then these plausible futures could exist.

And so, we use multiple plausible futures as those anchor points for what might be possible and a lot of time for our recommendations. And not all of them are correct. They’re really well-informed and they’re kind of meant to be guardrails and good anchor points. And as our clients and we go through the process of actually trying to build and discover things, it’s okay if those shift a bit based on what new technological breakthroughs are happening or what the resource needs are all around the world.

Jenna Fizel: I’ll add one more example, because we just got some really exciting news last week, which is that one of our client partners, Teal Health, got FDA approval for the first at-home cervical cancer screening kit. So, this is basically a Pap smear that you can self-administer. The first time this has ever been approved. And we helped with the design of a few aspects, including the unboxing experience and how a person actually comes to learn how to use this new device that they’ve never seen before, because it’s never existed. But also, actually, physically prototyping the mechanism and the physical design of the product itself, which we did during the pandemic when it was quite challenging to get access to prototyping resources.

We used a lot of home 3D printing. So, you mentioned that earlier as something that you’re engaged with as well. And I think this is just a really great example of being able to push just a little bit into the future, go a little bit further to bring something to market, and actually, through a clearance process in a really kind of stunningly short amount of time compared to the usual. I’m just thrilled to see this on the market and out there helping people.

How can you measure the design’s impact? [19:03]

Olimpiu Pop: I can imagine, especially that this has an impact given the aggressiveness with which the cancer is spreading, and it’s only presence. Even me personally, we had a bunch of examples in our family and I know what that means, so kudos for that. And how do you actually measure impact as a company, because you are the managing directors, so this has to be on your agenda as well. It’s obvious the part with the projects where it’s about commercial feasibility, but then we are looking also in impact, because you cannot think about the future without the impact.

Savannah Kunovsky: One of my favorite things is when one of our clients gets promoted because of our work or when new parts of an organization are built because of our work. A lot of the time it depends on how the work is received by the organization. And we try to be really collaborative in the process of design, so we’re not the types of consultants where you give us a challenge, and we go off, and we come back three months later and we’re like, “Here’s the thing”. We’re the type of organization that really want to collaborate with our clients to make sure that whatever it is that we are creating and whatever we’re recommending is contextualized in the needs of the business. And a lot of the time business leaders bring us in because they’re kind of stuck and they don’t necessarily have the capabilities to think outside of their current operating model.

And a lot of the time, businesses are geared up to create one thing or a set of things. And that’s what they’ve been doing and they do really well, but it’s hard for them to get outside of that. And so, we try to work with our clients to have the ability to extend outside of what is currently possible for them, but in a way that still makes sense for their business and makes sense for the types of bets that they want to make.

Will the keyboard become obsolete any time soon? [20:59]

Olimpiu Pop: So, one potential key result for you is promotions per year. So, I’m joking. So, since you started the conversation, one thing was going around in my head over and over again. As we’re talking about the future, we’re talking about the way how things will evolve, but we are still stuck with the keyboard. So, what are you doing here? The next step will be just using our brainwaves to do that? So, basically, what I’m saying is that for me it seems that the evolution of technology is getting at a fast rhythm. If we look in 20 years, 10 years ago, things were slower-paced. Now things are happening so fast. How can you embrace the challenge that you mentioned, where we are doing something appropriately, so that we have a proper interaction? Isn’t it a challenge for you as a company, as a group?

Jenna Fizel: Definitely is, especially because some of that stuff is really highly concentrated in the pre-commercial space basically. And so, we have long-standing collaborations with some academic institutions, for example, the MIT Media Lab, where we’ll often create some speculative work together. And we visit each other and learn about some of those brain computer interfaces, different kinds of haptics, different kinds of XR interfaces. And then we engage in some of that work directly with client organizations as well. And actually, in the realm of new kinds of interactions, we recently wrapped up support of a design sprint, a non-commercial one, for the Apple Vision Pro and medical applications.

So, trying to find clinically meaningful interventions that you could use that hardware and the different kinds of interactions that you can create with that hardware, including… I’m going to use a prop for a second. I know this is a podcast. But including taking everyday objects, tracking them, and using them as stand-ins for pieces of medical equipment that you would need to train with. So, this was, for example, for inserting a catheter into a large vein. Glass was used as a stand-in for an ultrasound.

It was really exciting to lend our space and expertise to that group, allowing us to see how younger designers from the community, non-IDRs, and real clinicians, as well as institutions like Mass General, could come together to understand and imagine new ways of using these technologies for meaningful results. But not necessarily ones that need to be commercially viable yet, allowing us to take that little leap into the future again.

Olimpiu Pop: Well, that’s quite nice. I was just thinking that, I think last year, I was working with a partner of mine. And we are considering doing some kind of consultancy work with people from the US. And then we are just envisioning how nice it would be that rather than going back and forth between Europe and the US, we can just use the new VRs, the Apple Pro in this case. And we’ll just kickstart the interaction in person, and then probably we’ll have a couple of new sessions, and then back and forth.

Provide prototypes to users to understand how they will actually use the technology [24:05]

And then I was just thinking that it’s quite nice to be on the edge, as you are, and then just envision different stuff. But then when they appear on the market, people use them for other stuff as well. So, it feels a lot like an inception. Does it ever happen to you to just look at something that you design and say, “No, that’s not the way how it was intended? Or, it’s more loose than that? It’s like, okay, you just dream big, you come with an interaction and then you learn from what you see people doing differently.

Savannah Kunovsky: I think that’s kind of the point for us actually, is that we create something and then we watch how people interact with it. And we’re like, oh, that’s what you actually need. So, part of our research that we do oftentimes, and especially when we’re designing physical things, IDEO has its roots in industrial design, although we design everything now from supersonic jets to avocado packaging, to digital government services and beyond. But our roots and especially the practice of design research will actually take us sometimes into people’s homes. And we’ll bring sacrificial concepts like I talked about earlier, so early, kind of messy concepts that just sort of illustrate an idea. And those can be things that we 3D printed and actual physical objects. Or I’ve brought in paper plates as a prop when I was working on a project. There are all sorts of ways that you can just simulate what that end experience would be.

And you take those things into people’s homes and you’re like, “Oh, actually, this is way too big to fit in your house”. Or, “Your kid immediately broke it. Okay, great, good to know that this is just not going to work”. Or you go in and you say, “Oh, they’re actually currently doing this thing in this totally other way that we had never seen before”. So, for example, we worked on PillPack, which was, I think, later sold to Amazon. But one of the big insights there was… I guess the end product that we ended up with was these packaged daily packs of pills that you take. If you have a couple of different prescriptions that you’re taking, it has them just clustered in there for you. But one of the big insights that led to that nice, easy to open plastic packaging, was that the team went into an elderly woman’s home and they were like, “Okay, show us your daily routine and how you take your pills”.

And she walked over to this table-top blade, like a grinder blade, electronic blade. And she was like, “Well, my hands are too frail to open up a regular pill bottle, so whenever I need to open up a new pill bottle, I’m using this massive blade to grind off the pill cap”. And we’re like, “Oh, okay, that makes sense”. Those pill bottles don’t actually work for a lot of people who are taking a lot of pills, which is the older adult population. And so, that took us to the form factor of this plastic packaging. So, to your question of what happens when people aren’t using the thing in the way that we expected, we’re like, great, that gives us so much information about what the actual need is and how to design it better. And we kind of really look for that information.

Olimpiu Pop: Okay, that’s cool. Well, because I went to another jeans shop and I asked for talking jeans that I saw them in a presentation. And they just shrugged and they just said, “Okay, dude, I don’t know what pills are you taking, but those don’t exist”. And I say, “Just wait for it”.

Savannah Kunovsky: Every time I give that talk and I talk about the talking pants, I ask for the phone number of the CEO in Levi’s and nobody has given it to me yet. So, anyone listening, if you have the contact number for the CEO of Levi’s, please reach out.

Jenna Fizel: Yes, pants can talk. It’s totally possible.

Olimpiu Pop: Yes. But that was really, really cool. I mean, it was such a nice way. You could’ve just put on the slide that, well, we have to be careful with what we’re doing. We are consuming so much of everything. But then you actually touch on a point that was really cool. Lately, a lot of the, I don’t know what’s the proper term for it, probably vintage clothes, the secondhand clothes are gaining popularity. I’m just thinking about one of the companies in Europe. It became a multi-unicorn just by selling used clothes. And that’s something that is quite nice. But that was quite an interesting concept, where you’re just taking technology, and put it in a proper place. You enhance the experience that a buyer has, and then you’re just thinking about the future as well.

And I can tell you that my daughter was very excited. She’s 10. And she was very excited about the fact and “Oh, are those really talking pants?” No, but it’s just things about the future, because at this point she’s just trying to figure out how she can convince her colleagues to make an impact for the planet. And she’s just brainstorming ideas. So, I’m just thinking that probably you have a huge warehouse where you have all the previous ideas that are stored there just for moving around, right?

Jenna Fizel: Yes. I sometimes call it a museum in a suitcase. Sometimes we put it in a bag and take around some of our more provocative ideas. I want to dive into the pants for a second. So, what we’re talking about here is this speculative piece that we created where we’ve encoded into the context of a large language model-backed chatbot information about a pair of vintage jeans and things about who wore them, how they were created, all of the information that an informed consumer might want to know about before purchasing. As well as some fun things, like what are its opinions about khaki pants. But part of the motivation for this design wasn’t just that large language models had become available. Though that was important. It wasn’t just the social trends of especially younger consumers wanting to shop based on their values more than brand loyalty, but also some regulations.

So, especially in the EU, there are important regulations about the traceability of things like supply chain, labour regulations, and all this other information that now by law needs to be tracked and stored somewhere. And that suddenly created a future world where knowing about your pants is not just a theoretical thing, but actually a sort of mandated, everyday thing. And so, we think about, okay, if that’s the case, what new opportunities are there to take that information and make it engaging, usable, and valuable to folks beyond just that regulatory environment?

And that I think, to Savannah’s point earlier about how we look for signals in our futuring work, that’s really important, because there are some things that will change about the world. And even some of the scarier ones mean that we’ll be living in a different environment in the future. And what sort of secondary consequences do those different worlds have on our daily lives? And maybe one of them is talking pants. We can hope.

How to embrace regulation when you are designing a global product? [31:12]

Olimpiu Pop: Okay. Well, I’m sure you can. But you said the EU word. And I have to ask you, because I’m in the EU. You are on the other side of the pond. And my feeling is that technology companies are not necessarily happy with the EU regulation. And a lot of people are just drawing interesting words towards the EU regulation. At points, I did the same, but now my optic changed a bit when I see also the benefit. For instance, the AI Act is really focusing more or less on the individual. And how do you feel as a design company? Because somehow my feeling is that the intention the EU legislation has and your intention as a design company is pretty much the same thing, to just make sure that the end user gets the most value and in the best place. Do you have customers that say, “We have to get to the EU market, that’s a pain in the back somehow?”

Jenna Fizel: Yes. I think there’s a couple of answers to that. We work for companies all around the world, and so they all live in different regulatory environments. And as designers, one of our responsibility is to understand the constraints of the business. So, we’re pretty often learning about new kinds of regulations or standards, based on either industry or location in the world, or both. I think from a design perspective, understanding different regulatory paradigms is really exciting, because you see this distilled thinking and understanding from at least some representation of a whole society or culture that’s been squeezed through their government and regulatory apparatus. And that’s gold.

Whether or not we’re necessarily designing to be compliant with the EU AI Act, for example, I think I’m personally really inspired by the framework of the different levels of regulation based on the impact of the technology. Whether it’s for entertainment, all the way up through something that might end up creating bio-weapons, and using that as a tiered understanding of harm reduction. That’s very interesting. So, yes, it is a bit nerdy, but I get excited and inspired by different regulations for sure.

Savannah Kunovsky: Also, we have a studio in London. And our studio in London is excited to work on stuff that is in that context and understands it well.

Olimpiu Pop: We don’t talk about London anymore. They decided to leave. So, no, I’m joking. Yes, I bumped in one of your colleagues who is in the London office. Great. I’m going to help you with the future and looking at the future. AI is important, so maybe you would like to look into the AI space and just think about how the people will interact with that, leaving the joke aside. Generative AI opened the box, even though as Savannah put it, AI has been with us for a long time. But now people understand it. And at this point, we are probably at the height of the hype when people are using it for pretty much everything.

How will the interactions with AI evolve? [34:17]

And well, my main concern is with the ecology of that thing, but that’s a whole different conversation. How do you feel about the current interaction that we have with AI? I know that Savannah, during her presentation, had a point on that, that we are at the point where we are between the horse and carriage and the automobile. We don’t call it an automobile yet. We are just calling autonomous horse or whatever. Do you have any thoughts on this?

Savannah Kunovsky: I think that we’re seeing some incredible potential and some incredible capability. And that is in generative AI and in many other parts of the AI space. And I think that we’re in many ways at the beginning of this precipice of having more advanced technology as a part of our day-to-day life. I think that we’re all used to social media algorithms and just having some level of personalization in a lot of the services that we’ve used. So, we’ve gotten the soft launch of these types of services. And there are definitely industries that have been much deeper in this space for quite some time. But from a commercial consumer perspective, I think that it’s becoming more and more explicit for us. And I think that as the devices that we’re using and as the services that we’re using get better, then people just come to expect those types of experiences, those kinds of advanced experiences.

And so, what is normalized happens relatively quickly, but I think that in order for us to get there, we have to be building and designing truly useful technology, and truly useful services that are mapped into what people want and need. And also, into the context of their lives, and their homes, and their work or whatever it is that we’re creating the device for. So, whether the interface is voice-based or brain controlled, or just sensory based on how you’re feeling or whatever kind of the input method is, feels like… I’m like, yes, all of that stuff is super exciting, but it has to be fit for purpose and fit for context. And the technology has to be good, because if it’s not good then people don’t want to use it.

Olimpiu Pop: I think it’s more than just don’t want to use it, because at that point you have a choice. But what I’m thinking now is that there is a startup in the place where I am. And we don’t have many that are that innovative. I’m going back to Star Trek, as we discussed earlier. These guys built a headset, some kind of LiDAR to help blind people. And that was nice, because that empowers people that usually live in a very narrow space due to the constraints that the society builds, willing or unwilling, around us. And then it’s just really opening new doors for a lot of people that otherwise will not have this chance.

And on the other hand, I was just thinking about what you mentioned about the social media algorithms. Well, that’s not necessarily a choice. Now, with the rise of LLMs, I think we have a choice where we can actually, even though it’s a paradox from my point of view, have more time and have better quality. For instance, what I’m trying to do now is to automate most of the things that I would normally do by hand. And obviously, I’d be fine behind my finger, saying that I don’t have enough time, but now LLMs allow you to do that. But on the other hand, I still have the privacy issue. If I simply drop it into ChatGPT or Claude, or whatever, what happens to my data?

Co-Design for deeper user understanding across groups [37:52]

And looking at the way how the world evolves these days, it feels that you want to have your data in a safe space, if possible in a suitcase, as you mentioned the museum in my suitcase. That’s also quite important these days. People are more and more aware. And that pushes me towards the other concern that I was having. A lot of the presentation that you had during your keynote, Savannah, was about the Gen Z generation, and the way how they interact with the technology, because they were constrained to use it more and probably a lot of them prematurely.

I’m just thinking about my kids; my daughter just started school. And then two weeks later, she had to interact with a laptop. It was the first time for her to interact with a computer to do her studies, even though she didn’t know her colleagues. And, actually, a couple of minutes ago, you mentioned older folks. So, how does design vary from this spectrum? I’m not familiar with all the generations. I’m thinking about the boomers, and I know the Gen Zs, and I know the millennials because I’m part of that generation. But how did the interaction change?

Savannah Kunovsky: It’s a super important question, because a lot of the time, the people who are making the technology are from one or two generations, or the people who are designing the technology are from one or two generations. And the people who are using and benefiting from that technology or being harmed by that technology are sometimes from their generation, but also from others. And I think that there’s this thing of different generations liking to rag on each other. It’s like, oh, Gen Z is… Every generation is like the one before it; they’re lazy and whatever. There are all of these just stereotypes that we make up about other generations. And millennials are ragging on boomers. And that’s a thing.

However, if you’re designing products for other generations or I think we can broaden this out into designing products for communities that are just different from your own, using the process of co-design is incredibly important. And an oversimplified definition of what that is is that rather than you just designing something for another group of people and then dropping it on them and being like, “Cool, hope this works. And it’s imbued with all of my values and perspectives on how I think that this technology should serve your community”. Using the process of actually designing with the communities that will be using or benefiting from the technology you’re creating is essential. And getting input and actually giving folks a seat at the table to come with their ideas, and to come with their lived experiences, and perspectives about how that technology might fit into their lives.

So, one of the first things that we did, and specifically IDEO has a play lab where we do toy invention, and we bring the principles of game design and play into everyday objects, including toys, but also extending out into other things. One of the first things that they did when generative AI came out was go to a bunch of Gen Z folks and say, “Hey, how do you actually want this technology to fit into your lives? You’ve been so oversaturated by technology through the pandemic. And that was a really key part of your social upbringing and the formation of how you’re experiencing the world. So, we’re on the cusp of this other technological revolution, and what do you want from it, and how do you want it to fit into your lives? And it’s going to change your work and your social dynamics. And so, how do we build it in healthier ways with you, and for you?”

And the principles that came out of that work were really like, we have had so much technology over-saturating our world that we’re okay with technology, we just want to make sure that it helps us be more human, and stay connected to other people, and connected to ourselves. And those principles I think, are just incredibly important for any form of designing technology. So, there’s this Gen X millennial mentality around tech, that it’s for efficiency and for making things faster and more streamlined. And I don’t want to think, just kind of make the decisions for me and take care of it.

And as much as I think that sometimes it is wonderful, it also takes away some of the friction in our day-to-day life that is actually really important for us in ways that we don’t necessarily expect, and in ways that help us stay connected to ourselves and to other people. So, I think just making sure that we’re getting outside of our own heads, and talking to experts, and talking to people, and working with folks who are going to be potentially using the services that we’re creating is the way to go.

Jenna Fizel: Yes. And I think one thing to add on to that, especially because this is for a more technical audience, is doing that first step of identifying who you actually are designing or building for. Sometimes maybe you’re working at a giant tech company and you have billions of users, and then that can be tricky. But for most folks in most applications, you do have an audience or at least you have an aspiration of meeting a certain set of, I don’t know, behavioral characteristics or place in the world, or some other way that you can define who in particular you’re designing for. And a process I really enjoy is this algorithm bias checklist by the Brookings Institute, that you can run before you start a project. That gets pretty serious and granular about who you’re designing, who your end users actually are, and what your intended impact on those users might be.

And then you can check again after you’ve done some of your work and see, are you living up to your aspiration or have things drifted? And if so, why? And I think using techniques like co-design and having that intentionality when you start can really improve your outcome, not just from a market fit perspective, but actually improve the value that you’re making for the people who use your product or service in the end.

Focus on behaviour patterns rather than traditional personas [44:00]

Olimpiu Pop: And a follow-up question on this. You mentioned just making sure that you know exactly who is the target that you’re addressing. What was going on in my head was at some point I was listening to a design podcast book, I don’t remember exactly what. And they were discussing about personas and how faulty personas can be. And they were providing an example. He lives in a castle, he drives a Rolls-Royce, and he’s in his ’60s and he lived in the UK. And then everybody was like, “Okay, you can either choose Ozzy Osbourne”, or at that point, Prince Charles, currently King Charles. So, that can be really far-fetched. And then I think looking at the way how environments and cities look these days, more than just generational sampling, I think it’s important cultural sampling. How can you manage to get to that particular point of view in such a heterogeneous environment?

Jenna Fizel: Yes, it’s a really good question. And I will say that we relatively rarely use traditional personas in our work. We much more often focus on behavior patterns. So, are we trying to serve people who commute by bicycle or like to spend time with their elders, or sort of like more action-oriented, or behavioral characteristics, rather than demographic ones. Because often a more fruitful site to get inspired when you’re designing. But you’re right, these are not substitutes for understanding your actual in-real-life customers. And that’s why ultimately we basically always talk to individual people while we’re designing.

And even though you can’t talk to every possible customer, you can identify folks who exemplify some of these behavioral characteristics that you’re particularly interested in. You can be inspired directly by Ozzy Osborne or by King Charles, by talking to them and learning a little bit more about their full lives as people and how that might intersect with your design problem. I mean, that’s one of the core tenets of human-centered design, I’d say.

Olimpiu Pop: Great. So, what I hear you saying is not to go after stereotypes like demographics or culture, but rather look at the habit of the product you’re developing. So, go after the tribe, rather than whatever people living in a given city or something like that.

Prioritize observing user actions over listening to stated needs [46:26]

Savannah Kunovsky: Yes. To an extent, we’re looking at behaviors and we’re looking at actions. And there’s also a lot of the time a big difference between what people say versus what they actually do. And so, a great use of emerging technology in the process of design is to be able to create simulated environments or to create digital experiences that replicate some sort of physical, or digital experience that people might be having in a product that you’re creating. And then, actually, you can talk to them about it and hear about their habits. And hear about how the thing might fit into their lives, but then actually prototype that thing and watch what they do and see what happens. Because oftentimes, those two things are actually quite different. There’s something that we talk about, which is the say-do gap. And so, we try to lead with bringing prototypes all the time and actually getting people to walk through or move through those prototypes, so that we can map their behaviors to what we make.

Olimpiu Pop: Let me see if I follow your idea properly and I understand it. So, first of all, you go and discuss with them and you ask them nicely about their intent. And then you go on your IDA to come back with a bunch of prototypes. And you just come and say, “Okay, this is it. Play with it”. And then you’re observing how they’re actually interacting with the prototypes. And that allows you to use the observations, and iterate over what you have, and then narrow down to a more perfected prototype, let’s say. Do you have something like a stage where you’re iterating over the finished product? Like we have currently in the technology space, a very fast iteration, where you have looking like continuous deployment, and observability, and you’re creating that kind of behavior as well?

Jenna Fizel: Yes, definitely. And I guess I’ll maybe nuance your description a little bit. We try to always bring some kind of a prototype, but not a finished one and not one that’s necessarily related to that sort of final outcome. But rather a prototype that lets us ask a question more deeply so that we can learn something about a preference or a behavior that then informs that final design. But when we’re lucky enough, we get to take it all of the way. So, I’ll tell a story from a few years ago now about an AI product. Not generative AI, though. Good old-fashioned AI, about predicting labor and material needs at fast casual restaurants around the City of Chicago.

And we did some of that exploratory research and prototyping first. But eventually, we actually built a machine learning model, a deployed frontend, and installed it in several actual locations that were serving customers around the city. And then had continuous check-ins with the frontline workers and the managers at those locations to evolve the design, until it got to a place where everybody was seeing the kind of information that was appropriate and actionable to them, and that our predictions were working well enough to be useful. And we were actually running the model on one of those old Mac Pros that looked like a black cylinder, basically, which was, by one of the data scientists fraud-named the trash machine.

And so, people would wonder, did the trash machine make the new predictions this morning, or did it fail for some reason? And do we need to restart the trash machine? So, that one just really has stuck in my head, both as a fun and exciting moment for us as designers to go all the way through that process, but also just a really compelling and fast process of doing that iteration, making some code changes, deploying the front end, and then immediately seeing it out in the market within seconds. Which is not so unusual in a lot of software deployment practices these days, especially for web apps, but a little bit different for us than our usual iteration cycle.

Generative AI can help with product co-design, but also as a fast prototyping tool [50:27]

Olimpiu Pop: Okay. Nice. And this leads me to probably my final question. Everybody’s using generative AI. How do you use it? Because it fits for me. What was nice, it was quite easy to build prototypes. It’s a matter of minutes, half an hour to just have something ideating, doing something in practice. Okay, it’s not ideal. It needs a lot of polishing. But how do you do it? I know that Savannah had at least one example in her keynote. But what are the lessons learned? Does it work and what doesn’t?

Savannah Kunovsky: I use it, and I see our teams using it in a lot of different ways, because we have so many designers who are working across different crafts and methods. But I think the general message is that we use it to add rigor to our work and to our research. And so, if there are ways that we can create either more accurate or higher fidelity concepts and prototypes earlier on, or more personalized prototypes earlier on so that we can get more accurate information from our research, then oftentimes we use it in that way.

So, whether that’s vibe coding a prototype or creating a short, scrappy experimental video, or having a bunch of different concepts that we can generate on the fly and pull in based on the preferences of specific people who we might be testing with, all of those are great. And then I think that there are the more obvious day-to-day things that we’ll use it for, where we’re just asking it questions and helping it co-create assets with us, whether that’s written materials or other things.

And at the end of the day, I think that it’s in a place where it’s really useful for some of that scrappier, and more experimental stuff, and sometimes for more later stage polished stuff. But all the time we are coming in with the creative vision, and the creative direction, and trying to use it more as a thought partner to us. But our designers, and their vision, and their agency in the process is the thing that’s the most important. And I think if I could make an ask of generative AI toolmakers, it is to center the human and the process that people are going through as they’re trying to create something. And create experiences in the tools that allow them to more clearly and more easily articulate that vision of what it is that they’re trying to make. And to be in the driver’s seat of creating those assets so that vision comes to life.

Jenna Fizel: I’ll maybe add one more aspect here, which is an aspect of learning. So, I’ll talk about vibe coding, because that’s in many ways closest to my heart. And certainly, I have I think three Cursor projects open right now at various levels of completion. And I use these tools as an extension of my existing skill set. But we have a lot of people who work on digital products at IDEO who don’t necessarily have direct experience with building digital products by putting their hands on a keyboard and writing TypeScript. But we now have this ability, and honestly, this, in some ways, companion who wants you to learn and to know more about processes and expertise that you didn’t get from your schooling or maybe even from your work experience.

And so, we have a few folks, including Neil, a person who works in our play lab, who’ve gone really deep and have built pretty complex pieces of software without that background technical knowledge, but with a ton of curiosity. And a real willingness to put in time and hours to understand the problems, and to understand really basic and foundational ideas, like debugging or building a backlog. And not coming to understand these things by reading articles, but by actually making them in collaboration with these AI tools. And now when I talk to Neil, for example, I can use some of the shorthand and the basic ideas of software development and of digital product design in a way that I couldn’t have a few weeks ago before he started staying up until 5:00 AM to build and rebuild the Slack bot that he’s been working on.

And I don’t want everyone to stay up until 5:00 AM every night, but I think that there’s something to this companionship, this encouragement of learning and exploration that are baked into some of these tools at least. And I would echo Savannah’s sentiment. I hope not only that the designers of these tools help to put the users in the driver’s seat, but also to have that, a nice little, I don’t know, gremlin on your shoulder that encourages you to keep going and keep exploring.

Olimpiu Pop: Thank you. Well, to be honest, rigor and accuracy would’ve not been the two of the words that I would associate with generative AI, at least not in this particular point. But yes, I understand the benefit of… And I’m also using it and my colleagues are using it as well. And just for our closing, I’ll just have to ask you, do you have any plausible scenarios for the technology in the future? I think that was the term that you use, plausible future. So, any, not predictions, but directions that we might expect in the upcoming years maybe?

Savannah Kunovsky: I am excited about more ambient, humane technology in general. I think that there’s the possibility of us having more everyday robotics, and just smarter devices and capabilities. And I think that they could be really cool and really interesting, but I don’t think that they need to be these crazy sci-fi, futuristic or attention-grabbing objects. I think that they can just be super functional and work really well and look really beautiful. And fit nicely into the context of our homes and our lives. And be healthy, and help us stay more connected to other people. So, if I get to put a vision out there, it is that.

Olimpiu Pop: That’s nice. It sounds like an Italian village where everybody’s connected without technology. So, I would second that. Thank you. Thank you, Savannah. Jenna, how about you?

Jenna Fizel: Yes. I think mine’s fairly related. So, there’s often this really strong barrier between the technical interface, I’m puppeting, basically, and then the world around me. And one thing I’m really excited about at the sort of intersection of AI, and robotics, and XR, is that there’s more and more opportunity for our digital interfaces to understand our physical contexts and for our physical context to influence our digital interfaces. And we see that in lots of different ways already through things like wearables, like watches that have been around for many years now, through to things like the Snap Spectacles, which are not a commercial product, but a real AR headset that you can wear around outside.

And I think that this sort of blending and this kind of neither privileging the digital experience, not making you stare into your black rectangle all day, but also acknowledging the value that showing otherwise hidden information can bring to your life as a unified experience is really exciting to me. Maybe not totally new, but I think an experience that we’ve been walking towards for decades and that I think we’re going to see a real acceleration in.

Olimpiu Pop: That sounds like the humans are taking their head out of the rabbit hole, the social media and the internet provide to them and then getting back to the environment around them using the technology in the right space. So, that sounds like an evolution from what we currently have to something closer to what we need to improve our lives in some way. Thank you for your time. It was an absolute pleasure and I’m looking forward to following more of your work. Thank you.

Savannah Kunovsky: Thank you so much for having us.

Jenna Fizel: Yes. Thank you so much.

Mentioned:

Oppenheimer & Co. Inc. reduced its position in MongoDB, Inc. (NASDAQ:MDB – Free Report) by 49.8% during the 1st quarter, according to its most recent filing with the Securities and Exchange Commission (SEC). The institutional investor owned 4,614 shares of the company’s stock after selling 4,579 shares during the period. Oppenheimer & Co. Inc.’s holdings in MongoDB were worth $809,000 as of its most recent SEC filing.

Other institutional investors have also modified their holdings of the company. Vanguard Group Inc. lifted its stake in shares of MongoDB by 0.3% during the fourth quarter. Vanguard Group Inc. now owns 7,328,745 shares of the company’s stock worth $1,706,205,000 after purchasing an additional 23,942 shares in the last quarter. Franklin Resources Inc. boosted its holdings in MongoDB by 9.7% in the 4th quarter. Franklin Resources Inc. now owns 2,054,888 shares of the company’s stock worth $478,398,000 after acquiring an additional 181,962 shares during the period. Geode Capital Management LLC boosted its holdings in MongoDB by 1.8% in the 4th quarter. Geode Capital Management LLC now owns 1,252,142 shares of the company’s stock worth $290,987,000 after acquiring an additional 22,106 shares during the period. First Trust Advisors LP raised its stake in shares of MongoDB by 12.6% during the fourth quarter. First Trust Advisors LP now owns 854,906 shares of the company’s stock valued at $199,031,000 after purchasing an additional 95,893 shares during the period. Finally, Norges Bank acquired a new position in shares of MongoDB during the fourth quarter worth $189,584,000. Hedge funds and other institutional investors own 89.29% of the company’s stock.

MongoDB Stock Performance

MongoDB stock opened at $209.92 on Monday. MongoDB, Inc. has a one year low of $140.78 and a one year high of $370.00. The company has a 50-day simple moving average of $190.83 and a 200-day simple moving average of $216.65. The firm has a market capitalization of $17.15 billion, a P/E ratio of -184.14 and a beta of 1.40.

MongoDB (NASDAQ:MDB – Get Free Report) last posted its earnings results on Wednesday, June 4th. The company reported $1.00 earnings per share (EPS) for the quarter, beating analysts’ consensus estimates of $0.65 by $0.35. MongoDB had a negative net margin of 4.09% and a negative return on equity of 3.16%. The firm had revenue of $549.01 million during the quarter, compared to analyst estimates of $527.49 million. During the same period in the previous year, the business posted $0.51 EPS. MongoDB’s revenue was up 21.8% on a year-over-year basis. As a group, sell-side analysts forecast that MongoDB, Inc. will post -1.78 earnings per share for the current year.

Insider Activity at MongoDB

In other news, insider Cedric Pech sold 1,690 shares of the stock in a transaction on Wednesday, April 2nd. The stock was sold at an average price of $173.26, for a total transaction of $292,809.40. Following the completion of the sale, the insider now owns 57,634 shares in the company, valued at approximately $9,985,666.84. This represents a 2.85% decrease in their position. The sale was disclosed in a legal filing with the Securities & Exchange Commission, which is accessible through this hyperlink. Also, Director Dwight A. Merriman sold 820 shares of the business’s stock in a transaction on Wednesday, June 25th. The stock was sold at an average price of $210.84, for a total value of $172,888.80. Following the sale, the director now directly owns 1,106,186 shares in the company, valued at $233,228,256.24. This trade represents a 0.07% decrease in their ownership of the stock. The disclosure for this sale can be found here. Insiders have sold 51,202 shares of company stock worth $10,576,696 over the last quarter. 3.10% of the stock is currently owned by company insiders.

Analyst Upgrades and Downgrades

Several equities research analysts recently issued reports on MDB shares. Stifel Nicolaus dropped their price target on shares of MongoDB from $340.00 to $275.00 and set a “buy” rating on the stock in a research note on Friday, April 11th. Monness Crespi & Hardt raised MongoDB from a “neutral” rating to a “buy” rating and set a $295.00 target price on the stock in a research report on Thursday, June 5th. Truist Financial cut their price target on MongoDB from $300.00 to $275.00 and set a “buy” rating on the stock in a research note on Monday, March 31st. Scotiabank increased their price target on MongoDB from $160.00 to $230.00 and gave the company a “sector perform” rating in a report on Thursday, June 5th. Finally, Redburn Atlantic upgraded MongoDB from a “sell” rating to a “neutral” rating and set a $170.00 price objective on the stock in a report on Thursday, April 17th. Eight investment analysts have rated the stock with a hold rating, twenty-five have assigned a buy rating and one has issued a strong buy rating to the stock. According to MarketBeat.com, the stock presently has an average rating of “Moderate Buy” and a consensus price target of $282.47.

Check Out Our Latest Stock Report on MDB

MongoDB Company Profile

(Free Report)

MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premises, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.

See Also

Want to see what other hedge funds are holding MDB? Visit HoldingsChannel.com to get the latest 13F filings and insider trades for MongoDB, Inc. (NASDAQ:MDB – Free Report).

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