In this episode of Founded & Funded, Madrona Managing Director Tim Porter sits down with Babak Parviz and Daniel Kelly, co-founders of NewDays, a platform purpose-built for older Americans living with cognitive change to help them reclaim abilities, preserve independence, and keep being themselves.
Babak and Daniel share how their experience at Amazon and Google led them to apply AI in the most human way: helping people with dementia and mild cognitive impairment (MCI) with scalable solutions.
They dive into:
- Why we chose to build at the intersection of AI and cognitive health
- How to translate clinical science into accessible daily experiences
- What “meaningful velocity” looks like inside an early-stage company
- How to balance mission-driven purpose with commercial viability
- Lessons learned from scaling startups and building impactful teams
- Why the next wave of generative AI is human-centered, not model-centered
Listen on Spotify, Apple, and Amazon | Watch on YouTube.
This transcript was automatically generated and edited for clarity.
Tim: Well, let’s start with the obvious. This is a massive problem, and it’s a deeply personal one. One in three people over the age of 65 in the US is dealing with some form of cognitive impairment, dementia, or early-onset Alzheimer’s. We all have someone in our lives, either a parent or a relative, an aunt, uncle, a close friend, and we know it’s heartbreaking because there’s really no treatment to date, there’s nothing you can do. You’ve now identified a treatment path that is actually validated, and technology, specifically large language models, has made it possible to go build a service to address this. But yet it’s a big step to decide to start a business. With that big problem, what made you say,” this is the right ‘why now,’ let’s go start a business to address this opportunity or this big problem?
Babak: Maybe to take a step back and share where this all came from. I was at Amazon for a number of years, and one of my roles was to figure out what the company should do next. So we ran many different investigations in many different areas, and one of the investigations that we ran was about aging and what happens to older people. We looked at this nationally and globally, and we surfaced many problems, and this was, I would say, one of the most daunting areas that we looked at. But it was really hard to find radically new solutions to these problems that we could believe or have ourselves believe that they could move the dial in a meaningful way.
And as you mentioned, if you think about the scale of the problem, today, if you look at the population over 65 in the United States, 11% of them have dementia and on top of that, 22% have something that’s called the mild cognitive impairment, or MCI, but that’s truly a euphemism. Someone with MCI is impaired enough that they may not be able to pay their bills anymore. So these are very substantial cognitive issues. So one third of people over 65 are battling with these cognitive changes. And we all know that our ability to remember things, our ability to reason about things, they really, to a large extent, define who we are. So once they start to go away, we feel like we are fading away, and people around us also feel that the person is fading away.
So there’s substantial emotional toll on the person. And after that comes financial issues, many health issues. So these are very, very serious things that we have to deal with. And even though we just say, okay, one third of people deal with that over 65, but if you think about any person living in the US today, they are very likely to have a spouse or parents or siblings, so with the likelihood of 90%, this situation would hit one of us sooner or later. So basically, it’s going to hit all of us.
And if you think about what solution is available to people today, if I go to a doctor and get a diagnosis of MCI, for the most part, the next step is good luck. There’s not much you can do. There is no drug today that can cure these diseases. There is no drug today that can even stop these diseases. So this is highly motivated both Daniel and I to do something about it. And the way that we went about doing something about it was to step back and see where it is that we have solid clinical evidence of an intervention that can help people? So we did all the background research to surface randomized clinical trials, and that’s the gold standard of medicine, that showed any form of intervention that was beneficial to people.
So we went after those, but we realized none of them have really scaled because they’re limited by the availability of trained expert humans. And then we realized that now we have also radically new technology available to us in the form of generative AI. So we put the two together. There was a massive need, unmet need, and there was a radically new technology available that could bring medically proven interventions to a large number of people, to put them all together and decided that this is the right time now to go after this problem and help many people that have no recourse otherwise.
Tim: Amazing. Babak. I was not aware of this research. And just in simplistic terms, these therapeutic conventions really boil down to immersive conversations frequently. And there’s a clinical rubric behind it; you guys should describe that more. How does that come together in a product?
So you had this insight, there’s real research that underpinned it. There’d been no ability to turn that into something that scaled before. Daniel, tell the audience what actually is this thing? I’m sure a lot of people are like, “My gosh, I have people in my life I want to introduce this to.”
Clinician-Guided Conversations, Powered by AI
Dan: Absolutely. I like to think of NewDays as a therapeutic intervention for people with MCI or dementia. And really, that comes down to, so it is a telehealth clinic where you meet with a clinician that has expertise in cognitive therapy and then we kind of amplify the ability of that clinician to work with you through these conversations that you do with a large language model.
As far as the product goes, there is just an ability… Well, really all of it is kind of based on these three different methodologies of cognitive stimulation therapy, cognitive rehabilitation, cognitive training. And I think that those methodologies really spell out a range of conversations that can be beneficial for people with MCI and dementia. On one end of the range is just casual conversations, long-form casual conversations. I almost think of this as like going for a walk. These long-form casual conversations are just good things for you to do to maintain your ability to continue to have conversations with the other people around you in your life.
And within our product, these casual conversations are a good way to promote reminiscence about past memories. They’re a good way to practice verbal fluency, so finding words that you want to use to express yourself. They’re also a fantastic way to reinforce the concepts that you’re working through with your clinician in the telehealth setting. Repetition is important for the memory of someone with MCI and dementia, and these kinds of casual conversations are a good way to promote repetition.
Maybe on the other end of the spectrum are more challenging conversations, so these are maybe like doing sprints. These are designed really as a stimulus to stretch your ability within a particular cognitive function, and then that stimulus becomes something that your brain has to respond and adapt to. And then ideally, those challenging conversations would happen in a context that is as close as possible to a real-life scenario, so that you are challenging yourself in these conversations. But then in your real life, there’s a quick transfer between realizing like, “Oh, I was just working on this same skill through NewDays, but now I find myself in a similar situation in my everyday life, and I can apply the same methodologies there.”
Babak: And if you think about all of them, they’re highly personalized and they’re delivered in a conversational form and they require someone who’s trained to deliver these therapies. So they’re highly dependent on the availability of that trained individual to work with a patient to deliver the therapy. And that has been the issue with scaling these interventions because we do need millions of trained professionals to deliver these therapies. They’re unavailable, and even if they’re available, the cost of the highly trained humans to deliver these therapies would be astronomically high.
Clinical Foundations of AI for Dementia
So that’s why these therapies did not scale, and that’s where our NewDays.ai comes in. We allow the scaling of these therapies that are highly personalized and conversational through the use of generative AI or large language models. So you mentioned some of the clinical trials that we have anchored our work on. One of the most exciting ones that we came across was a study that was led by Professor Hiroko Dodge. She’s a professor of neurology at Harvard University. This was a long study, took many years to run it, but the results are pretty fascinating.
What’s the most amazing result about this study is that they managed for the population that was participating, this is a randomized clinical trial, registered, they managed to increase, this is highly unusual, increase the cognitive score of some of the participants. And what this practically translates to is to push back the symptoms of cognitive decline by six months or more. So this is really incredible for giving people time with their cognition.
If you look at those conversations, they look like normal conversations that you might have about the particular topic. Let’s talk about the Second World War or something like that, but under the hood, they are designed to encourage reminiscence. They are designed to challenge the person’s vocabulary in a particular way, and they’re designed to challenge the person’s critical thinking. So even though on the surface they look like normal conversations, when they’re delivered, there’s actually a purpose for these conversations.
So we saw this, we got super excited about it. We licensed the clinical methodology exclusively for our company. So that’s actually one of the things that we deliver through our AI system is dual steps of conversations. So what we are building, as Daniel mentioned, is a system that has two parts. One is that the patient interacts with the clinician on video. That’s not as frequent, could be once every two weeks or once every month, but every day of the week, the patient is interacting with AI.
We still have the human expert in charge, but by using AI tools that are augmenting and amplifying the human expert, we can do 20 times more. So there is the patient-clinician interaction, there’s a patient-AI interaction, and very importantly for us, and that’s a lot of technology that Daniel is building, there’s also the AI clinician loop of informing the clinician and the clinician controlling the AI.
Tim: Great blend of empowering the human to do more, the therapist, and using AI and technology to create a great patient experience, great user experience. And everybody has played around or done more than play around with ChatGPT. It’s incredible, but it can also get off the rails. There are a bunch of problems with it. This is a lot more than just slapping a voice front end on ChatGPT in the background. Maybe talk about some of the things that were hard problems to go from, yes, you can go interact with ChatGPT to having a delightful and reliable exercise and solution you’ve built.
Making Conversational AI Reliable
Dan: These days, I really kind of break down voice-based interactions with an LLM almost into two categories. There’s almost like verbal interactions with an LLM, and then there’s conversational AI. And when I think about verbal interactions with an LLM, it’s almost like I have a query in mind. I have an objective of why I’m coming to this LLM, and I know the result that I’m looking for. And sure, I’m choosing to use my voice to interact with it, but I’m really going to rate that experience based on whether or not you gave me the information that I was looking for in a relatively simple way.
When it comes to conversational AI, I think it’s just a much different problem overall. Users will come to it without a particular objective in mind, and a lot of the problem shifts into this space of having an engaging conversation. And part of it, there is really the semantics of the conversation, and there’s also the mechanics of the conversation. And so the semantics of the conversation is really the content of that conversation, and is the LLM responding in an engaging and interesting way?
I think LLMs are reasonable at this today. A lot of times, though, they can become quite repetitive, and this is in how they’re trained, and it’s also in that the conversation history can kind of shoot the model into responding with the same patterns every single time that it responds. I don’t think that’s representative of what a true conversation is like. I think there’s a lot of variety in conversation. I think that when you have interactions with an LLM where the content is kind of formulaic and repetitive, you start to lose a lot of those engaging characteristics that would make you want to have a long-form conversation with the system overall.
The other piece is the mechanics of the conversation. This is kind of how things are said. I think that there are just a lot more of both of those components involved. When it comes to conversational AI. The content is really important, the variety of the conversation is really important, the mechanics of the conversation are really important, and all of that is just a very different scenario than sitting down and bringing a query to ChatGPT, but just choosing your voice to interact with ChatGPT.
Tim: Very complex system to make it work reliably and really human-like. Babak, you mentioned earlier that there are a lot of clinical trials that underpin that this type of therapy works. You’ve actually licensed some of that research, and then that gets baked into the product. Maybe explain a little bit more about, it’s both interesting technically, how you take sort of this private data and incorporate it into this type of system, but it’s also just super important about the fidelity of what we’re doing. It’s not just having random conversations. It’s actually underpinned with the type of approach that a therapist would take with you.
Personalization, Memory, and the Clinician-in-the-Loop
Babak: So I was at Amazon when we launched Alexa. Daniel and I were at Google when we built the voice interface for Google, which started with, “Okay, Google.” Well, at first was, “Okay, glass,” and then became, “Okay, Google,” and everyone used it on their phones. But, so that the state of the conversation with an AI system up to very recent times was, “What’s the time?” It’s 8:30.” That was the end of the conversation. So multi-turn was very difficult. Now with the advent of the new LLMs, especially ChatGPT, that is widely available, you can have a multi-turn conversation with an LLM, but these are not really optimized to hold a meaningful half-hour-long or longer conversation.
So one of the core technologies that Dan has built is really to enable a long form, half an hour or longer conversation with an AI system that feels natural and engaging. This actually is extremely difficult. It’s done with many agents and many models under the hood. So the technical implementation is quite complex, but we’re at the point that we can actually hold long-form conversations, unlike any other LLM system, which is not really optimized for this purpose. The other point that’s important is that we need to get to know the person and personalize it as we have these conversations, because these are meant to be daily.
So, Daniel and the team have actually had to build a very specific type of memory for the system that begins to learn about the individual, which is very different from a generic memory. Especially for the population that we are dealing with, because as an example, we may hear from the person that, “I don’t have a brother.” Two weeks later the person might say, “My brother said X or Y.” So then the question is what would the memory do about this fact? Because the previous fact that we stored about this person to personalize is that our knowledge is that this person doesn’t have a brother. Now they’re saying their brother is saying something. Is this because of their dementia or is there something else going on?
So the memory actually that’s built for this system that’s optimized for the population that we’re serving is also very specific type of memory that gets to know the user and it sort of reflects on what the conversation is doing. So that’s the second big difference with something very general like ChatGPT. So long form conversations, very specific type of memory for personalization for this population. The third part is that we are having very frequent conversations with our users. We need to report back to the clinician what’s going on in these conversations.
So periodically, our AI system publishes a report to the clinician of what is really happening in these conversations. Is it something that they need to pay particular attention to? And that’s actually something that no GPT system at the moment has. And then our clinicians also give guidance back to the AI of what kind of conversations to have. So at the moment, this is the only system that we know of that is under direct supervision of a clinician. And what our team had to build the ability to deliver these conversations while maintaining the particular therapeutic reason behind these conversations. So those are the things that we are doing right now. Super exciting.
Tim: If you put it in the perspective of the company, and what are the moats that you’re creating, or a little bit, what was the investment thesis? You guys are an amazing team. This is a really big, important market. You’re building really hard tech that somebody else can’t go build. You have proprietary data that’s getting incorporated into it.
And then there’s this human piece about having an actual, the telehealth part also, we decided that was really important and that’s a big lift. You’re operating in three states right now. You’re seeing patients in those. Maybe say a little bit either about other parts of the what’s hard moats or just like why the heck do this human part of it? Why not just launch this AI app out there? That sounds easier.
Why Humans Stay in the Loop: Care, Safety, and Trust
Babak: The human part is really important. This is actually a major part of our thesis that these types of interventions, for the foreseeable future, they should be supervised by human experts. So we don’t want to just run the AI open loop without supervision. We’re always going to maintain the human supervision for this. It gives us confidence that we’re doing the right thing. I think it also gives our users have more confidence that-
Tim: Big time.
Babak: Yeah, the right thing is being done for them. So there’s a pilot in this plane, so it’s not an autopilot.
Dan: I think I see what there’s this saying within the healthcare industry for startups that services save lives and software improves efficiency. And so I think when you’re in healthcare and you’re dealing with someone’s cognitive decline and they have now been diagnosed with that condition, just having a person to speak to about that condition is amazingly and powerful versus, “Hey, I’m just going to go interact with a piece of software every day without any sort of oversight from another person,” I think would just never be able to get off the ground in the same way.
Tim: You all, the product’s live so people can go try it. You can tell others in your life to go try it. Newdays.ai. You built an incredible amount in a short period of time, you’re barely six months into this, and the product’s live. This isn’t the first time you’ve done that. You’ve actually gone from an empty room to astartup before. We’ve referenced Google and different things here in the conversation. Maybe back up, talk a little bit about how did you all decide to work together? What was your history before that’s made you say, “Yeah, let’s go jump into this big problem and do it together as co-founders”?
Dan: Babak and I have known each other for 17 years now. It’s been a while. We’ve worked together a bunch of times. That part of it is absolutely fantastic. I think that the reasons to go do this company, we saw cognition as this huge problem that we should try and go make a difference in that space. We saw LLMs and generative AI as this transformative technology that could be very beneficial there. We both have, Babak has family histories of the disease, I have family histories of the disease. It kind of made a very personal connection for both of us as well to something that we would be just invested in working in because we know how much of a problem this can be for patients and families within the space.
And then, yeah, I think that as far as co-founders, there are aspects of both working at Google, Google X and Amazon Grand challenges. I mean these were very much startups within these giant companies anyway, so in some ways Babak and I have worked together within startups for a long time now, but I can also say that doing a startup and co-founding a startup with somebody that you know so well and you just trust 100% is fantastic because there’s so many things to go do, there are so many problems to solve.
And that if you just know that the other person is capable of getting those things done, it just makes the whole process that much more seamless because you trust each other and you just say, “All right, I know that these are the problems you’re working on and these are the problems I’m working on and we can chat about those problems, but I also 100% trust that you’re getting these things done,” and that makes… Startups are always a journey, but that makes the journey just a little bit easier.
Babak: Plus one to everything that Dan said. I would say both of us are highly motivated, not to do something that’s cool and interesting, but to do something that’s meaningful. So something that’s not a niche product, something that’s genuinely good but also can help millions of people. That really highly motivates both of us,, and we both like velocity of execution because we’ve built a number of things from the ground up from robotic surgery to Google Glass to e-commerce services to human-machine interfaces.
So many things, many times from really the grounds up, like an empty room with nothing. And we’ve built these products, launched them. Some of them have been quite successful, some of them have been less successful, but we’re not afraid of building from the-
Tim: Like all startups.
Babak:Yeah, So we are not afraid of building from the ground up. We love velocity, and we love working on something that’s meaningful. I also have to add that we want to make this a successful business. Because what we’ve learned, I actually do believe in philanthropy and I think in our personal capacities we are engaged in that, but I just put that aside. In order to truly actually change the world with a solution that does good for people, we need to make it financially viable. That’s the only way for something to scale. So we’re building this, even though our intentions are as we mentioned, is really to do something good for the world first and foremost, but we know that we need to make this a successful business in order to have the impact that we want to have. So that’s equally important for us because otherwise it’s not going to have the impact.
Tim: In these early days, I think you’re really focused on initial users getting lots of people to try and experience the product and we’ll come back to that aspect of it, but I think in healthcare, there’s always this, how do you get distribution? There’s multiple ways. It’s early days, but maybe how are you thinking in a really customer-centric, user-centric way about ultimately how do you go to market to use that startup term here for this type of service?
Babak: Yeah. I would say our GTM is still a work in progress. We haven’t exactly nailed it.
Tim: Absolutely.
Babak: We have two things that we are doing. So we’re doing D2C, so we’re trying to remove all barriers for people to access us as fast as possible and with a minimal amount of effort. So there’s a D2C flow to us operating and there’s partnerships that we’ve had a number of conversations with different entities for partnerships that would not be of a D2C type. It would more be of some form of enterprise. So they’re both in progress. We’re trying to figure out which one is the best way.
We’re pursuing both at the same time because they’ve both shown promises and they’ve both shown challenges for us. So we’re learning and we are experimenting with. What I would say is that something that has been highly motivating for us is we recently exited our beta, is the feedback from our beta users. Because as you know, a startup has lots of ups and lots of downs, and every time we get feedback from our beta users is really having a shot of espresso for the whole team because we actually see that we’re helping people, and this has been really meaningful for us. Just in terms of-
Tim: Let me break in on that because I want to talk about this. I mean, Amazon’s famous for work backward. From the customer, I’ve been super impressed by how you’ve gone about it, not just like, of course, we need to go get user feedback, but you’ve had a real process leading into the beta and now the GA is going to lots of different users. Maybe just talk about how you’ve approached that around being really customer driven and getting feedback on how the product’s working as well as any aha moments from hearing this feedback from end users.
Babak: I would say that’s both. Daniel and I have spent a number of years at Amazon, and that’s something that Jeff is amazing at drilling into people, to be customer-obsessed, and that’s really a superpower of Amazon, and that’s learning directly from Jeff of how to be like that. So we tried to.
Tim: I think it’s been a superpower for NewDays too.
Babak: Yeah. So we’ve tried to bring basically that part of the Amazon culture into the company and some of the mechanisms that Andy and Jeff have built at Amazon. But yes, from day one we have been very customer and user obsessed and maniacally basically ran user studies, ran beta tests, measured CSAT, customer satisfaction score, to make sure that we are building something good for people and people actually like it. And I’m happy to report as of now our, CSAT is really high, so it’s measured in the scale up to five. For our AI exercises, our CSAT at the moment is 4.55, which is very high. For our full clinical service is 4.8.
Tim: Wow.
Babak: So people love this service. So that’s the numerical measurement but also the anecdotal, what we are hearing from people is that they are actually seeing really meaningful results. So that has been extra motivating, an extra motivating factor for us to continue. And encourage us to exit beta and make the service more widely available.
Dan: I do agree, as MCI and dementia progress, people tend to socially withdraw a little bit. They don’t seek out social interaction the way that they used to. And there was one participant that was engaging with the exercises and he used to be this really outgoing, gregarious individual and has definitely pulled away from that, but as soon as he started interacting with the exercises, all of a sudden that aspect of his personality came out all over again and his care partner was there with him as he was interacting with this system and her mouth just hit the floor because she had not seen this aspect of her husband in a very long time.
And was almost like these exercises are just kind of a safe space. They can interact with them without all of the social pressure or other potential drawbacks to the kind of fear and worry that come from interacting with other people. And just hearing that sort of feedback and seeing those sorts of things is incredibly empowering.
Tim: So powerful. For me, just thinking about it, it’s like, okay, is someone going to really want to have this in-depth conversation with an application? And not only have you seen they do, this idea of maybe you’re self-conscious in groups of people and unsure of yourself a bit, but that hey, there’s no downside here and then that kind of really builds on itself that you’ve seen that multiple times with your early users.
Dan: Absolutely. I think that there is a certain amount of interacting with another person where there’s some amount of concern that you may repeat yourself or you may not just come across as the person that you think of yourself as. And so that may lead to the decision to just refrain from the conversation and not participate in the same way you would’ve. But when you have a system like this, there’s no judgment there. You can make mistakes. It’s the place that you’re supposed to practice in order to continue to have those interactions with the other people in your life.
Babak: Again, to complement what Daniel was saying, we’ve heard this multiple times now from our users that they feel like this is a no-judgment space. So when they talk to Sunny, our AI character is called Sunny, they feel like they could just talk and they’re not worried about being judged. And we love that because we want them to have these conversations because we kind of know the therapeutic results there, but we want to encourage them also to socialize more.
So it’s not really meant to be a substitute for socializing with other people. It’s meant to be a safe place to practice and get better, so they feel more confident, so they can actually socialize more. So the more they socialize, the better, and this is a place for them to practice and build confidence, and hopefully they feel overall better about themselves and their abilities.
Dan: The other place where we’ve heard really great feedback is from the care partner as well, and that the person with MCI or dementia can sit and have a conversation with our system and it’s almost half an hour to 45 minutes of respite care for the care partner where they get a break and they don’t have to be so involved in the care and management of their loved one.
Tim: You mentioned earlier you’re building a business, people might be wondering, it’s early days and this point of, which I’ve really encouraged too, is to reduce all friction to getting users to experience this thing, wanting to come back, and then those positive references I think build on the system. Eventually, you’ve got to make money. It’s early days, you’re experimenting, but how do you think about pricing a product like this? Some days as an insurance could pay for type thing? How do you think about that aspect of the business?
Babak: So we have two components now. There’s access to AI and all the exercises overall, the AI platform. And then the other one is the clinical visits. So we already accept insurance for our clinical visits. Then that really helps lower the cost, the actual cost to people that participate in the program. The AI access part is out of pocket and we have a subscription for that. There’s a cost associated with that, at the moment is priced at $99 per month, which appears to be fairly affordable for the population that we are targeting. And every day actually you can go in and do another free conversational exercise and then if you’d like, at some point you can upgrade to become a full member of the clinic. But we’ve definitely tried to make it easy for people to access the system.
Dan: Maybe one thing I’ll add on to that is that an additional feature that we think is really important that we’re building towards now is just providing people feedback about their cognitive health. We have to do this. There’s a lot of UX associated with providing feedback, but I think one benefit to the feedback is, or maybe my general impression is that I’m not totally convinced people just want to go sit and have a friendly conversation with an AI for no particular reason. It’s not like you’re walking down the street and you see a stranger and you just stop and talk to them for 45 minutes for no reason.
I think that there is, you want to know what is the motivation or justification for me participating in this particular program. And I think one thing that’s top of mind for all of our users is, is this helping? How am I doing? Et cetera. Feedback along those lines? And so if we can provide feedback, it’s just another piece of the puzzle as far as going from casual conversations to complex conversations, all of that overseen by the memory and the things that we’re learning about you to make it very particular to your cognition and your life experiences. But then also using all of that information to provide you feedback to continue to give you justification for coming back to these exercises to understand that process overall.
Tim: I mentioned how fast you’ve built the service and the company and you’d never do that without a great team. And part of being able to move fast was that you hired a great initial team quickly, and hiring is hard. Maybe talk a little bit about how you were able to do that and the type of culture overall you’ve tried to instill in NewDays here from the inception.
Dan: I mean, we definitely leveraged as much of our personal networks as we possibly could in order to find people that were interested in this space. It’s nice having-
Tim: The mission’s important though.
Dan: Yeah, the mission is kind of one of the big selling points for coming to work for this company, is that if you are the type of person that wants to take your technical expertise or your business expertise and apply it towards making a real difference in someone’s life, then this is just a fantastic company for you to come look at.
And so yeah, leveraged personal networks to the greatest extent possible. And have also just been super scrappy about finding fantastic talent to help us go build things as fast as we possibly can. And we leverage, we have people here in Seattle, we have people in New York, we have people in Argentina, we have people in Indonesia, and they have all just been… Every day I’m impressed with the work that they’re getting done. And so yeah, I think it’s just a fantastic team so far.
Babak: I think that’s an accurate statement that every single person that we tried to recruit, we actually successfully recruited. So that has been our track record. And hopefully we can-
Tim: Knock on wood.
Babak: Knock on wood. Hopefully we can maintain that. But pretty much everyone that we wanted to get, we got. Because I think part of it is because they really found not just the technology exciting because this is obviously cutting edge technology and AI, but the mission is meaningful so that both components to work on cutting edge technology, which is the hottest technology of the day, but use it to do something that’s very meaningful and humanly relevant. I think that the combination of the two has been a good combination. As Daniel mentioned, our team is quite distributed. We try to fly people in with the regular cadence, so we physically actually get together with the regular cadence and that has been helpful in building the company culture.
And that’s something that I got to confess that that’s different post-COVID because I guarantee that before COVID, if Dan and I were building this team, we would’ve insisted everyone to be in the same building in Seattle. This is different. So the post-COVID world is different. We are learning how to operate in a more distributed way. So this has been in a sense liberating because we can recruit from all across the US and globally. As I said, we have people in three different continents right now, but we also, we have to be even more intentional about building the culture of the company to build trust and build velocity. And part of it still relies on flying people in to spend some time physically together every month.
Dan: I agree that it’s the post-COVID world is just totally different. Babak and I chatted a lot about this and we both agreed, we’d been part of a hundred percent remote teams during COVID and agreed that that didn’t work. We’ve also been part of teams where everybody’s in the office five days a week and you almost get some of the most toxic environments, competition between different teams. And so it’s not just like being in the office all the time is the solution either. I think ultimately the solution is you have to put work into culture, the company culture, just the same as you have to put work into the technology you’re building or the business you’re building. And if you’re not doing that, then probably the culture’s going to get away from you.
Tim: You raised a nice round of funding early on to start the company. Madrona was, we were grateful to be able to invest in General Catalyst. Holly Maloney has been an amazing board member and investor, lots of healthcare experience, but still the amount of resources paled compared to doing this inside Amazon, doing this inside Google where you did start with an empty room, but there’s more resources there if you need them and can make the case. What other learnings generally, advice for other founders, how to get going, how to move fast, have you learned? Probably some things you’ve learned the hard way here, even in these first months.
Babak: If you get a no from a VC firm, do not necessarily get totally discouraged because that, premiere VC firms see a lot of pitches and the success rate in these firms is 1% or below. So that no doesn’t necessarily mean that your idea is bad or you’re a bad entrepreneur. That no might actually mean that the answer is no at that particular time, and maybe next year the answer is yes. Or there’s a lot of things going on inside the VC firms that might actually result in a director saying no. So I would say to an entrepreneur, if you hear a no, don’t get discouraged. So continue if you’re convinced that your idea is good.
But the other thing that I would recommend is to maintain execution velocity. Because if I think about the startup, Daniel and I have been also part of one of the biggest companies in the history of the world actually. Big companies have a lot more money, they have a lot more resources, they have a lot more people, and actually good and smart people. So they have everything going for them. They have more access to customers. Everyone they call will pick up the phone. The only thing that the startup has is the velocity.
So as a founder, if you find in a situation that your velocity is starting to stall, that’s a major red flag. So we have to have the velocity. That’s the only way actually to be able to be competitive in a place that you don’t have massive amount of money, you don’t have massive amount of infrastructure, people, all that. So I would say paying attention to velocity is super important and that’s part of the culture building in the company that we have to be intentional. The company actually incorporates velocity of execution as part of the core of the values of the company early on.
Dan: I was having this conversation with Trevor, our CTO the other day, and we were talking about moving fast. And I gave this example of there may be a problem that’s posed where someone says, “Which one of these two objects is bigger? The bus or the motorcycle?” And our engineer instincts are like, “Oh, I know how I can figure this out. Here’s my process description of how I’m going to do it, and I’ve calibrated all my measurement instruments, and I know exactly the experiment that I’ll do.” And then someone else walks up and just says, “Yeah, the bus is bigger,” and you move on.
And I think that when you’re doing a startup, there are a lot of times where you’re facing those sorts of problems. The bus versus the motorcycle, it’s just harder to recognize because you’re working in a brand new space. But there are just a lot of times when you almost have to turn down your engineer instincts a little bit just to move faster when the solution is actually obvious. And it would just help you to move faster and go figure those things out quicker rather than dialing up all of the engineer processes that you know how to do and have been beaten into you for a long time.
Tim: And then jump on the motorcycle.
Babak: So I would add also one thing that might be counterintuitive, but I would say a bad decision is better than no decision, because a bad decision would allow us to proceed and figure out the problems, and the decision was incorrect and course-correct and get to the right decision, but indecision and making no decision would basically torpedo the operation.
Tim: Well, thank you both so much. So excited about the future of NewDays. It’s early days, but the results point to a future where AI for Dementia complements clinicians and restores confidence. Appreciate the opportunity to work together and build this service. So congratulations and thanks.
Babak: Thanks so much for having us.
Dan: Thanks, Tim. This is great.
Learn how AI for Dementia supports patients and care partners at NewDays.ai.
Related Insights
