Interview — 2026-09-02

Hey.

Hi, can you hear me?

Yeah, I can hear you.

Cool, cool. Thanks for agreeing to meet.

No, no, for sure. Yeah, no problem.

How are you doing today?

Good, good. How are you?

Pretty good, pretty good. Are you back at—

Yeah. I'm not, I'm not yet. We start September 8th now after Labor Day, so.

Oh shit, okay, that makes sense.

Yeah, yeah, we pushed it back a little. Yeah.

Nice.

So, so you're on a gap year right now?

Yeah, yeah, that's right.

Awesome. So what did you say? You were at Google or?

Yeah, yeah, I'm currently at Google. Um, yeah, just seeing how it goes for a year.

Awesome. Cool.

So.

Are you in California, Mountain View?

No, I'm actually in the YouTube office, San Bruno, but I usually work out of like the SF office just because I live in SF.

Oh, okay. That's cool. Nice. You like it? It's cool.

Yeah, yeah. Yeah, yeah, yeah, yeah.

Yeah.

I think there's a big difference between like student life and like work life. So it's been pretty interesting. Yeah. How about you, man? How are you doing? Like, what are you up to?

Yeah, that's for sure. Yeah. I'm doing good. Yeah, I'm doing good. I think right now it's just a few weeks after my— so I were this summer, I was— so I'm going into my junior year.

Okay.

Yeah, I'm going into my junior year and this summer I was working at a pharmaceutical company. They, yeah, I was in New York and they have, I guess what I was doing was it was pretty CS related in the sense that They have a machine learning team that is working on basically— so this specific company is a rare disease company. So a lot of the work that they do is sending out reps to find patients or like identify So they have a team that works with claims data and EHR data to try to identify patients that could like Yeah, yeah.

Oh shit, okay. Okay. Interesting. Wait, which, uh, which company is that?

It's called Kyowa Kirin. It's Kyowa Kirin, K-W or K-Y. It's Japanese. They're— well, I mean, their headquarters are in Japan, but they have a— yeah, they have a North North America, A-K-Y-O-W-A-K-I-R-N. Yeah, yeah, yeah.

Wait, what was it? I just bought it. See that? Oh, okay. Yeah. W-A. Interesting. Okay, well, that's super cool.

Yeah, yeah, they have their— so go ahead, go ahead.

So I guess like, yeah. No, no, you go ahead. No, they have their

No, no, I was going to say, yeah, it's just like some random— like, it's interesting because the company was formed like because they have the Japanese beer brand called Kirin and they merged with like their Pharmaceutical, yeah, because the pharmaceutical company has their headquarters in like Manhattan and then the North America Kyowa Kirin is in like Princeton and they like merged together. It was interesting. Yeah.

Yeah. Oh shit. Yeah, yeah. Wait, that's super cool.

It's cool.

Dang.

Yeah.

So I guess like the reason why I wanted to talk was because like I've been reaching out to a bunch of people who are in PLEME and also doing like other things. Like I know you're doing CS. I was also doing CS. I just wanted to hear about like what you're or where you're going with CS. Where were your heads at with like what you want to do in terms of like, do you want to go to med school? Did you want to do more CS-focused things?

Yeah. Yeah, honestly. I think I'm I feel like everyone's kind of thinking this right now. I actually spoke to like someone who was playing me, I think, who was also CS, and they were playing me a while ago. So maybe like 5 years ago, 6 years ago. And right now he's doing, he's in residency at MGH, but he's like, I was asking him too what he was thinking. He said back then it was a lot more clear because every, it was For SWE looked more like SWE used to look like, where it was like traditional stuff, not like the AI-driven development now that we have in like a lot of frontier labs and stuff. So people, people were a lot more Clear if they want to go into medicine or do sweet stuff, but now it's like different. I for me personally.

Sure. Okay. Yeah. Sure. Yeah.

I'm still leaning medicine. I still like the clinical aspect of it. And honestly, I don't think the— I don't know, what do you think actually? Because I worked in a, I guess, a not traditional SWE environment, but a corporate Environment for summer, and I didn't love it. Like it was interesting, but honestly, corporate just feels like a lot of. I think every job feels like this at some point, but it doesn't feel very people driven. I mean, or it doesn't feel, yeah, if it doesn't feel like the kind of problem-solving work that you do, like when you're learning, or it doesn't feel like people-driven, interaction-driven work that you do as a doctor. So it's like, it's like a weird middle ground for me that I don't absolutely love. I'm sure I could tolerate it, but like, I don't know. What do you think?

Yeah. Yeah. Yeah. Uh-huh. Yeah, I guess on my side, like, there's the aspect of like medicine that I like, which is, as you said, the people aspect. Like, you can have an impact on people. And then with the SWE side, It's like the upside of SWE and CS for me is that it's very scalable. The impact that you have can scale to a million people versus a doctor who you're seeing a patient one-on-one. For an hour, and then you can see like, you know, 10 to 20 patients a day. So I feel like the amount of impact that you have at scale, which I really like.

Yeah.

Um, but where my head's at is like, the reason why I want to do CS right now is because of how fast the field is moving, especially with AI. Like, I think the amount of impact I can have is extremely scalable compared to And then I think the downside of it is that it's not as fast as how it was before. Like, I think you brought up a good point about how, like, in the past, SWE was like, you know, just very like, oh, you have to code everything by hand. But now with AI, it's like everything's really fast. So I just kind of want to see the potential of, like, How we can use AI to impact as many people as possible. And that's why I'm trying to learn as much technical skills as possible and also potentially go into more medical AI or medtech spaces. So that's kind of where my head's at.

Yeah, so would you say, because I also thought of the same thing, but I guess when I think about impact, you could, I You could also make the argument that like if you want scalable impact or impact that like is going to affect a lot of people, you could pursue medicine and you could have that like more like intimate relationship with patients. And you could also like, it's It's very feasible as a doctor to have a lab, even if you don't have a PhD or anything, or do, do a lot of research. Like even, yeah, even if you don't only want to do like clinical research like most people do, like just outcomes research and stuff like that, if you want to do wet lab research, you Could do that, and that could that that has the potential to impact a lot of people, especially if you're like on the drug discovery side or like surgical technique side. And then also, I guess.

Totally. Yeah.

Like, I guess as a counterexample for SWE, I would say that like, not to hate on big tech, big tech is really cool. They do a lot of good stuff, but like practically, I think when you work in Big tech, it's a lot more of just like a cog in the machine, or at least I've never had a job in big tech. But from what I hear, yeah, from what I hear, like you're working on a team and you're doing cool work. But it's like teamwork and it's like you're building a big thing, like maybe pushing out a new feature or like doing, running a new iteration on model, working on some infrastructure stuff, right? But like, yeah, it doesn't hit the same as like So, but I think a good point you have is that like right now startup scene is like crazy. It's like very, very, very bullish.

No, totally. Yeah. Mm-hmm. Yep. No, no, no, you thought. Yes. Yeah. Yeah. Yeah.

And if you do want to have like a huge impact in biotech or something like that, maybe making your own thing or like doing work that like you can kind of guide the development and maybe that's like A possible way to make impact. I don't know, that's just, that's just what I think. What do you think?

Yeah. Yeah. No, no, that's totally cool. I think you brought like 2 really good points. The first is like, even as a doctor, you can have like extremely big impact but super scalable. Like you're not just limited to seeing patients, you can also do research. I guess for that, the reason why I want to explore the technical side and SWE is because like I already did like a bunch of research in high school and in college, and so like the one thing I, I guess I don't want to say dislike, but the one thing that kind of deters me from doing research right now is just the fact that, like, with research, I think it's really cool. And like, if you really love the thing you're doing, It's a really good place to be at, but to impact people, like, you have to go through like so many rounds of like clinical trial. And like, it's not just that— it's not the— like, the product of your research isn't going to directly impact people. Yeah, yeah, yeah.

Yeah, yeah. Mm-hmm. So much stuff.

With like technical skills. Like, Jeffrey, where I was going with this, but I feel like that answers it. Sorry, what was the second part of your 3-dimensioning again?

No, because I, well, I guess the two parts was that like, I guess because I wanted to also, I was like maybe not truly devil's advocate, but maybe like another perspective. I was saying for the, I guess for the medicine side. Medicine is also scalable in some sense. And then for the SWE side, like most people end up in big tech. Yeah, right. Yeah, most people end up in big tech and like the impact there is quite limited. I mean, It's not limited, but I would say that every argument you can make for like how you have impact as working at Google could be made for how you have impact in medicine, right? So yeah, yeah.

Oh, you're a cog in the machine. Right. Yeah. Yeah. Totally. Yeah. Okay. Yeah. Yeah. So I guess like with that, like the reason why I'm in big tech is just because like I want to build up the technical skills first and then like go into like the startup scene. I think the startup scene is really Yeah, yeah. Yeah.

Do you think so though?

I think so. Yeah.

Oh wait, sorry. Yeah, I just want to like, I have a question here because like there's differing opinions on this and I have no idea how I feel about it. I'm just curious, but do you think, because you said To be in the startup scene, you really have to know what you're doing. Maybe that could be particularly true for medtech.

No, no, no, you're totally good. Yeah. Yeah. Yeah. Yeah.

But at least from what I've heard. I feel like a lot of people nowadays are just like, because what's that? What's the canonical advice is like the only way to learn how to make a startup is to make a startup, right? So like, yeah, so you can have like all the technical skills. But unless you want to do something, which you may, do you want to do something that's super science-driven? Maybe like BCI or something that's completely pure science?

Yeah, totally. Yeah. I don't know if it's like pure science, but I think something that like blends the two of medicine and tech, like I think BCI is extremely like science-driven, but there's some other like fields Like, oh, like if you've heard of like Open Evidence or like Try Discovery, which is focusing on like computational or like LLMs for doctors or like drug design, like those kind of work is pretty interesting. So.

Yeah. It is, yeah. Like, yeah. Yeah. So I guess, so tri-discovery would be like molecules and like pharmaceutical design.

Right, yeah.

Which is like, yeah, so that's, yeah, that would be pretty science heavy, right? So I would agree, like in those spaces though, but I don't know, I feel like at that point, like aren't the people who may try to discover, they're like PhDs, right? Like biomed PhDs and stuff. Yeah. So once you get to that point, I feel like it's like you have to have done the buds. You have to have the rigorous training and then it When you start going back and back from the super high technical stuff to, I guess, maybe Open Evidence, I think Open Evidence would be more in the realm of EHR integration and just like LLM queries and search.

Yeah. There. Yep. Mm-hmm. Sure. Yep.

Now that's more like it's free game, right? But also that's super competitive, right? Like, I don't know if you saw ChatGPT just integrated with Epic and like now they're like super, yeah, they're like super onto each other. So it's like, That's like super competitive now, right? So the incumbents are huge. So I don't know, what do you, how do you feel about that?

Yeah. I saw that. Yeah. I mean, I guess, like, are you talking about how I feel about OpenEvidence and ChatGPT competing, or which part?

No, no, no. Yeah, that was like ambiguous. I'm just curious, like, how do you feel about like, so what, I don't know, because I was also thinking about the startup space and like, you know, the YC Startup School and everything. This summer, I went, it was fun. It was just like, I don't know, it was just like a party. It just, I don't know, just hang out with people. But talking to people there was kind of fun because it's like everyone has an idea and everyone's pursuing something. And it's, yeah, and I would just like, when I think entrepreneurial, it's like, you don't have to have a great idea, but like, I was wondering like where your interests lie, like in like specifically, you know.

Yeah. Oh, totally. Yeah. Yeah. Yeah. Mm-hmm. Yeah. Sure. Yeah, I guess like with the— okay, the YC Startup School, first of all, is like, that's like so fake. I went for— I just went to attend and then I got lunch and I just dipped because like most people were like, Really young or like even some high schoolers that I talked to. So I was like, okay, yeah, I'm not staying here.

Did you go? Yeah, yeah. No, yeah, it was so— I met a range of people actually. Honestly, I thought that like a lot of the high schoolers were straight LARPing. Like it was just, yeah. But some Some people were actually pretty interesting. And I think that I listened to the talk by Max Hodak. That was a pretty good one. If you— some of the talks were actually— yeah, he's a guy who does like science. The BCI company. Yeah, it's like, I thought it was pretty interesting. I thought some of it was interesting. It's like, I think it was like, it was just a networking event and it was like not really that good of a networking event, but it was fun. I don't know. Yeah.

Really? They would totally, 100%. Oh, okay. I didn't go, but Yeah. Yeah. Yeah, but I guess with the startup stuff, I don't really have a general direction of what startup I want to build personally, but there are definitely companies or startups that I would definitely join. Like, for example, like Open Evidence, like, yeah, they're competing with ChatGPT, but the reason why I think that like medical startups built by doctors are gonna beat these like frontier AI labs is because like when you're Yeah, I think that's a really good point. I think that's a really good point. I think that's I think Open Evidence for me is a really, really cool company. I would totally join. I guess like with Open Evidence, like if you didn't know, there's like a team of only 30 people and all of them are hyper-focused on like healthcare. So I think that's very unique and the kind of team they're building, the kind of things that they're doing there is very, very bespoke. I would say that those kind of companies are companies that I've definitely built an interest in.

Wait, yeah. That's really cool, actually. Actually, I remember I've read about Open Evidence when I was working at the pharma company because I remember I was speaking to the— well, I read about it earlier, but I read about it a little bit more at the pharma company because I was speaking to the Sales team there, and they were super hyper-focused on advertising on Open Evidence because they—I guess now this is a big thing for pharma companies—and it makes sense because if doctors are searching up stuff on Open Evidence, you want your drugs to like.

Yeah.

Be higher in like you can't modify, and I know Open Heavens has strict policy. You can't modify the actual generation LLM generation, but they'll have like cards, like sponsored cards after, and like a different model will be ranking like the. Relevance of a drug, and then like putting up the cards. That's interesting, I guess. But I was not—I guess the main thing I'm wondering right now is like what's the main?

Yeah.

What's the moat for open evidence right now? Because I would assume that it's not gonna be just like they're not like open code and it's like, oh, we use whatever model because I don't think doctors care about what model they're using. It probably is gonna be like something about About like, can ChatGPT? Like, do you know what the regulation looks like around research data and like how? Because is is it that open data evidence has better access to like research data and Like what's in PubMed, or like how do they how do they compete?

Yeah. Yeah. They partnered with the— what was it called? Was it New England Journal of Medicine or something? And some other sources that nobody has access to. So I think that's part of the remote. And I think that's because like, I think that like, in my opinion is that this is kind of a hot take. I was talking to some other like doctors in like the tech scene and like people were talking about how like the moat for a lot of these healthcare companies Is the fact that they care about medicine. It's their kindness. It's their altruism. Like when you actually care about that problem to that certain extent that other companies don't, you understand the kind of people that would benefit from it. And I think that's because Epic Science is a company built by doctors for doctors. But companies like ChatGPT or OpenAI, the reason why they're partnering with Epic is just because they have great partnerships. That's the only reason why. It's not because they have doctors in-house who understand the problem. And when you understand the problem so much, of course, Open Evidence is going to beat them out. So that's kind of the opinion that I've been hearing.

Oh yeah, yeah, yeah. Yeah. Yeah, that would make sense. Yeah. No, I agree with that. That's, that's interesting. And I think it's a pretty good take. Um, what was I thinking? Yeah, were you saying something else though?

Was I saying something else? I think that's pretty much it. But I guess I'm also curious why you're interested in CS and how you got into med kind of.

Yeah, I think I was pretty— I was always interested in CS in general because I think, I mean, I think it just starts like I was thinking about this earlier. I was discussing with a friend like how did it actually start? But I think it's always like you're good at math, you're kind of good at math as a kid, and then like you end up like just like people would just say that, oh, CS would suit you, and then like you start playing video games or something, and then like you just start working with computers. Yeah, that's pretty much how I got interested in CS, but I've always like really liked it and I've really liked the problem. And I think ever since, like, I've always been interested in modeling in general, like just training models, how that process works, like data Yeah, I was saying, I was doing like data collection. So I did that throughout high school. And I think I, my mom's a nurse, so I was always like, she would always tell me about medicine. So I was always, yeah. So in high school, I started shadowing doctors a lot. volunteering in medicine, and then that's how I became interested in medicine. And then in high school, I had a few internships at the med school.

Yeah. Okay. Yeah.

And at Colorado, and we did work on healthcare policy and modeling and like ways that we can like model access to healthcare. So that's how I got more interested in healthcare. And then now I think AI is just really cool that it just captures my attention. It's like, it's just something that's like, it's, I can't ignore it. I like healthcare, but I can't ignore AI because it's just too cool. So now I'm just, I think I'm working. I'm also interested in neuroscience. So I do neuroscience research and I've done that for a while. So I guess a convenient little intersection for me is medicine, neuroscience, and AI. And maybe how like we can push science forward by using AI and how that can impact, like, I guess understanding, better understanding of the brain and better like healthcare. It's related to the brain. I think that's just a convenient intersection for me. It's not something that like, this is the one thing that I pursued this like niche the entire time. It's like I pursued all these things and they're like coming to this niche, I think. Like, how did it go for you?

Totally. Yeah, I guess like it's a similar story. Like in high school, I guess like my parents weren't nurses, but my dad was a professor, so he did a lot of research. The reason why I got into research so early on was was because I was inspired by my dad. And then that kind of transitioned into getting inspired to do actual medicine instead of just doing the research side. There's the bench side, and then there's the actual practicing side. Seeing how it actually impacts patients. So I thought that was pretty interesting. And the reason why I applied to Plimi was because I was like, you know what, like I was shadowing a bunch of doctors and I think that the impact that they can make is really, really cool and really unique. To that specific profession. And so that's why I applied to Plimi. On the CS side, it was kind of something like when I got into Plimi, I didn't actually do a bunch of CS before. I took like AP CSA. That's pretty much it. And I just wanted to explore something that obviously AI was really cool at the time. CS was really cool at the time. And I wanted to explore something outside of just biology. Like I want to take advantage of the play me program kind of thing. And I really love it.

Okay. Yeah. Yeah. Mm-hmm. Oh really? Okay. Mm-hmm. Yeah, yeah, yeah.

And I was kind of explaining earlier about the scalability that I found was pretty interesting, and that's kind of why I've been pursuing both sides.

Yeah.

So.

Yeah, no, that makes sense. Yeah. That's really cool. Yeah, it's like, I think that's— I actually, I'm wondering real quick before I like speak for other preliminaries, I was hoping like you could do that actually, because you said you— did you speak to a few other preliminaries before me?

Yeah, yeah, totally. Yeah, like quite a few actually. Yeah.

Okay. Yeah. Like, what was the sentiment there? Like, what were they saying?

Everyone has a pretty unique take, which is— so I can't really say like one thing. Like for example, there's this one guy I was talking to. He actually graduated from med school and now he's working at Google. Google, so I've actually met up with them like at Google, which is pretty cool. He his take is pretty interesting. I mean, I guess like the general consensus is that everyone is still really interested in medical. The medical side of things and the technical side of things, but the things that he's interested in is like I guess like the same with like scalability, but also he was I guess. With him, he was pressured early on to go into medicine, and he didn't really think that much about like becoming.

Really? Okay. Okay. Oh, okay. That's interesting. Mm-hmm.

Like. What kind of life he would have to go through in becoming a doctor, and that's why he didn't really like med school as much as like other plebees did. He kind of just went through that plebe route and without thinking, he's like, "Wait, like I might want to pursue something." He took a gap year in medical school to do an internship at Google, and he kind of liked the.

Mm-hmm. Mm-hmm. Hmm.

Technical intersection with medical better during that internship at Google, so that's why he like came back after medical school. There's some other plebees that are very like research focused with the CS side of things. So not really industry, but they're like, oh, I really want to do like comp bio kind of research or like drug design. So there's there's a whole range of people that I've talked to.

Yeah. Mm-hmm. Yeah, for that, for that guy that you spoke to, what is he like when he took his internship in medical school? What did he do at Google? And like, what does he do at Google now? I'm just curious.

Yeah. Like the the thing about him is like. He specifically requested for the Google Health team, so it worked out for him like perfectly. And I think he was working on like LLMs. If you're familiar with like the like MedGemma, I think he was working on that team. So he really loved. That, and now he's working on like multimodal integration. So working with like health data and making that making the models better through like a data pipeline or something. I'm not too sure the technical details, but.

Yeah. Okay. Yeah. Mm-hmm. So he's doing— okay, okay. I was gonna ask because like what Google has like Sensor FM and all that stuff for like what is it? That's for wearable data, right? It's like something like that. Is he working on like actual model training or is he like

Oh yeah, yeah, yeah, yeah. I think he's working the data side for model training, like the data infra.

Of, yeah, yeah, yeah.

But.

Yeah, yeah.

Yeah, he's not working on the wearable data.

Okay. Okay, okay, yeah, no, I'm sure Google has probably like a million teams doing like med stuff, but yeah, yeah.

So. Yeah, yeah. Yeah, a bunch of teams there. Yeah.

No, because yeah, my dad actually works at Google, so that's, yeah, but he doesn't, he's hardware, so he's working on the GCP U, so yeah.

Oh, really? Oh, nice, nice. Is he in like Mountain View?

Yeah. Yeah, yeah. No, no, no, we live in Austin. I'm in Austin right now. Yeah, yeah, yeah, yeah.

Oh, is it? Oh, okay. Nice, nice, nice. That's super cool.

So yeah. Well, he didn't always— that's also probably one of the reasons that I was interested in AI. He doesn't— he didn't always work at Google. I think he just— he moved like 2 years ago, but he used to work at— he used to work at a chip startup, not Cerebras. Yeah, yeah, yeah.

Okay. Okay. Sure. Oh, okay.

Yeah, yeah, yeah. So yeah, that's also, I guess, maybe, maybe you don't consciously recall it, but maybe a reason that I was interested in AI, but yeah.

Nice, nice. Yeah.

Um,

That's super cool. Like, your parents are— like, one parent is in tech and the other is in med, and now you're doing like some intersection. So I think that's really cool.

Yeah, I know, I know. Someone made that connection for me. I can't believe I never did. But yeah, one of my friends told me that. I'm like, oh, I guess.

Yeah. I guess with the neuroscience side, like what kind of things are you doing with that? Is that like more wet lab or is that like do some tech comp bio stuff?

Yeah. No, I'm like Yeah, right now it's, I guess it is a little wet lab because I'm working at the, at a lab at the Dussauds Lab. It's a pretty big one at Brown. And basically He's working with— he's a neurosurgeon and he takes— he records whenever he cuts. I guess when he does procedures on epilepsy patients, he uses intercranial stimulation to collect data. And we're basically analyzing that data and using it to like help make better like models and try to understand how to better model epilepsy.

Okay. Okay. Yeah. Mm-hmm.

Patients and like their, their reaction patterns so that you can have better surgical techniques and better surgical like strategies for isolating like reactive sites.

Yeah. Okay. So I guess there is some wet lab, but also some technical side with the data analysis as well.

So that's, that's basically Yeah, yeah, yeah. I wouldn't call it real wet lab because like, I guess real wet lab is when you're sitting with a bunch of cells and you're like, I hope they don't die. Like something like that. But like, yeah. Yeah. So I guess I'm doing a little bit. I find it interesting. I think it's interesting. I could definitely see myself when I do med school, like continuing that kind of research. Well, do you plan on going back to do med school? Like, do you have any clue if you're going to do that or?

Yeah. Right. Yeah. That's kind of the debate that I'm thinking about right now, like whether to go back, whether to take another year. I do plan on like, I think the general goal for me is to do some kind of intersection of med and tech. It's like a question of whether do I need to go to med school to do that kind of work is the big question for me. So I can't really give you a concrete answer, but I'm still trying to figure it out.

Yeah. What did— yeah. Yeah, what did, I guess you said the coworker that you have at Google, did he say, did he feel that his like med school education helped him or like, Did you feel like it was like, oh, not, not like the marginal gain wasn't worth the 4 years or like something like that?

Yeah. Yeah. Yeah.

Like, what did he think?

I guess for the things that he wanted to do, just because like he was kind of not really forced, but he wasn't really thinking too much about what he wanted to do at the time and then went to medical school to realize that like he didn't want to treat patients. Yeah, yeah, yeah. So I think it's just like, I think it depends on the person. Like, I think if I was to do it with Ryan, like, we would do it one-on-one. He felt like it wasn't that worth it for him, but like, obviously he still had an interest in med. So I guess like that's kind of different. And he did tell me for his use case that it wasn't that useful. Just because like he just has a better understanding of the medical things than a lot of other people, a lot of other colleagues that he works with. But I guess I need to figure out the thing for me So I think the big question for me is like, oh, what do I want to do in the future? And would med school kind of unlock that for me? So I think it's a completely different question.

Oh, okay. Yeah. Mm-hmm. Yeah. Yeah. Yeah. I think right now, I think it's hard for me too because I think there's like a real weird balance right now with like doing stuff and like learning stuff. And it's like you can learn stuff by doing stuff. But you also need to like learn stuff to do stuff. So it's like, it's just, it's a little bit difficult. And I think from med school, there's like a, I think a lot of what you'll gain from med school will be a lot of like clinical Yeah. I think that's the most important thing.

Or yeah. Mm-hmm.

There probably is more time than people think. Like, I think, yeah, I think maybe 4 or 5 years is like totally— because the thing with medicine is it moves slow and for a good reason because it needs to be really safe. So I think there'll be a lot of time before there's adoption.

Totally, 100% agree. Yeah.

And like, I think once doctors or like physicians and like systems are more used to like, like a lot of doc— I've actually been speaking to physicians in general at like Brown just out of curiosity because I'm trying to decide on a I was trying to decide on a specialty, which I'm not like decided, but like I want to have some sort of like idea of like something, you know what I mean? So like when I start like thinking about it, like I have a little more to go on. And most of them don't use AI. Like, they're not big fans. They like, they'll use it to like, they'll use it for notes. But even like, I thought like bare minimum everyone uses a medical scribe. Like, what is it? Like a Bridge or something. I think that's the main company. Yeah. Yeah. So I was like, oh, everyone has to use that. But even at Rhode Island Hospital, a lot of doctors said that like, I don't want to use it because I feel like If I do use it, it allows me to skip over details. And I think that's like something that's like a lot of doctors are like, I think, I think you're right that like the med school makes a huge difference because I think tech is a little bit blind.

Oh really? Oh, that's super cool. Yeah. Totally fair. Yeah. Yeah. Yeah, bridge. Yeah. Interesting.

To like what doctors are really care about, and it's for to me it seems like they really care about the humanistic aspect. Like they really care like because they're like oh if AI does describing that means that I didn't have to write it down myself, meaning that. There's a possibility that like I just skipped over details. So like they don't, sometimes they don't even see it as busywork, right? So I don't know. I feel like once there's more adoption and like things are a little bit like dust settles a little bit more, it'll be a lot more clear like what people actually want.

Yeah. Yeah. Yeah. Totally. Yeah.

So.

Yeah.

I don't know. That's why I feel comfortable saying that like, hey, maybe I'll just go through med school and if there's something I really want to do after that or some technology I really want to pursue, then I'll— actually, I have one question for you. I like, do you, you said you did science in high school or maybe did you do any in undergrad research?

Yeah. Yeah, go for it. Like research? Yeah, yeah, I guess like in undergrad I was more like wet lab. I did a lot of like microbiome research, and then coming into college I was more focused on like whether it was like comp bio or I also did like pure CS research, so.

Yeah. Okay. Okay, are you like, I don't know, have you spoke to your dad about this? Like as like a professor, but like I'm curious because I've been reading a lot or like I've been seeing a lot about scientists and how as I think Anthropic specifically because they're super bullish on this, but like about how like we need Claude to accelerate science research and like they are very adamant on figuring out ways to like make sure that science Starts moving quicker because like that's something they really care about. So like, are you are you curious in any way about like maybe trying to be a scientist and trying to be like on the tip of the spear when it comes to? Applying AI to make science better or like making sure that like we have the tools.

Yeah. Yeah.

To allow AI to like make us move quicker, right?

Yeah, this is a really good question because I think that was one of the things that it kind of interested me. Like one thing that I was looking into was like autonomous like labs, and I didn't even know this existed, which Yeah, yeah, yeah. And then I also went to a lab, which was super cool. Like they're making these— I think it was Ginkgo Bioworks or some other like biotech company that's making these like autonomous labs, which was really interesting to me. There's also a bunch of like— I'm gonna be honest, like a lot of the YC companies Yeah, yeah, yeah.

Or something like that. Yeah. Yeah, yeah. Yeah, yeah. They are. Yeah.

It is something that's definitely interesting to me. I'm not sure if that is something I want to pursue for a long time. It doesn't have that much medical application. For me, it seems like it's more of a robotics, physical AI problem, so I'm not sure if I want to go into it.

Yeah. Yeah. Yeah, I guess it could be, it could be like more of a physical AI problem. Maybe, yeah. It could also be like more hypothesis forming and like how can we make like a good like method and structure. I think that's what like Discovery Loop is doing. But yeah, it's like a lot of companies are working on it, but I think trying to Make like a one size fits all thing is like a good goal, but like just from like.

Yeah, I saw that.

History, I would say that like. It's not. It's not going to work in the sense that. Every, like, you're not going to be able to copy and paste it onto every single problem, and there's always going to have to be like actual scientists that are working on the problem that like kind of like reach up and say like, how can I attach this tool to what I'm doing, right? Not like this tool is just going to like swallow everything underneath it, right? So maybe.

Yeah, the more verticalized you are, the more helpful you'll be to that specific vertical. Totally.

Yeah. Right. Exactly. Yeah. So I guess, what do you think about like, so do you think, are you leaning on the side of like another year at Google, see how it goes, or what do you think?

I guess like with Google, like if I'm being completely honest, I'm at Google right now, so I can't really speak that loud. I don't want to stay for a super long time unless like I switch to like a health team. Just because of what we kind of mentioned with like, oh, you're kind of just a cog in the machine. I see it more as like a stepping stone in potentially opening up other doors and also building up some Technical skills. So yeah, I'm not gonna stay for super long for Google, but if a different opportunity comes up, then I guess we'll see what happens. Yeah.

Yeah. Yeah. Yeah. Yeah. Also out of curiosity, so I did like, I'm still thinking about what I should do next summer. I'm like completely scattered out. Do you think, did you do an internship at Google? Is that how you went full-time? Okay. Did you feel like it was worth it? Did you like enjoy your time? Do you think that like the process was

Yeah, I guess with Google, I will say if you don't join the right team, which I don't want to say I didn't join the right team because it was interesting to do some kind of AI-related feature. I've done translation. But I will say there are some people that I know that joined really boring teams, like they did some like front-end things, and it's like, you don't want to do that.

Mm-hmm.

So. I will say definitely apply, but if you don't get a good team, it's not super worth it from what I think.

Yeah.

Are you looking for— yeah.

Yeah. And also for your app.

I guess like for— are you looking for like roles for next summer or like roles in general? Like are you looking for SWE roles or like what kind of things are you looking for?

Yeah, go ahead.

Okay.

I'm kind of open to it, like, because I'm thinking about it and honestly, it's like

Okay.

Like you said, technical experience is like especially useful and like especially for when you think Plimi summers, it's like you're a lot more free than most people. So it's like the freedom I think You should use it. I think I got my fair share of pharma. I don't think doing that again has like low marginal gain at this point. So I don't think I want to work anymore in pharma. I'm also looking at startups, so maybe like I think a startup could be like interesting, but like I think big tech also is like they're also working on very unique problems and it's a different type of technical experience. So did you?

Yeah. Totally. Yeah. Yeah. Okay. Yeah. I will say if I had to go, yeah. I will say if I had to go back to like where you are, I would probably lean towards like the startups because you can probably learn more. And like if you can find like a med-related startup that you really, really love, then you're going to learn infinite Yeah.

Yeah, go ahead, go ahead. Really? Okay. Mm-hmm.

Like a lot of my friends that interned at like, I think I had a friend that interned at Chai or something and I just felt like his work was a lot more interesting than what I did.

Really? I'm sure Chai is brutal though. I'm sure like getting an internship there is not like an easy task, but.

Yeah. Yeah.

Yeah, did for did for your applications like I'm just wondering like how did you go about applying like when it comes to like startups in general or big tech I'm just.

Yeah. Yeah, I guess like the thing with big tech is like they don't really care about like whether you're a plebe or not. Like they're not going to appreciate it because like these recruiters are just like mass sending these like, I don't know, like, oh, do you want to apply to like everyone? Like they don't actually care.

Like if I wanted to, yeah. Yeah. Yeah.

I will say for those roles, just don't put your plebe— you don't have to talk about your medical background. Just talk about like your technical experience and like it's kind of a luck of the draw for those, to be honest. Like I just got super lucky, I'll be honest. Startups though, I think that like if you talk about how you have a medical background and you're literally a plebe, you got into med school, like that like stands up or stands out from everyone else. So I think you should mention that for those applications.

Yeah. Yeah. Yeah. Yeah. Yeah. Mm-hmm. Mm-hmm. Yeah. Okay. Gotcha. How did your, like, for Google, was your application process just like completely normal? Just like LeetCode, everything, just like nothing too special? Yeah.

Yeah. But I wonder how much things have changed because when I applied, I guess AI was still there, but it wasn't like— it was still like the LLM, like you talk to ChatGPT kind of era. It wasn't very agentic, I guess is the point. Now I know like companies like Meta are doing like agentic interviews or something. I wonder if Google's doing that now. I'm not sure.

Yeah. Like bad LLMs. Yeah, yeah, yeah. Yeah. Yeah. I heard something about that. I don't know too much about it, but like, I guess it's interesting. I don't know. Let's see. Yeah. So I don't know. I'm still thinking about it. I guess I'll look out for startups. Do you know any, like, besides OpenEvidence, like, do you know any particular startups that you think are, like, interesting, like, worth looking into?

Yeah. I can actually connect you with some because I have friends working there. Let me, let me see. I think I made like a list of a couple companies. Actually, there's a funny thing is that so I was at a Brown event and I met this person who Works at YouTube and is a Brown alum, and her husband is like the CEO of a company called Genesis. And what they do is essentially like, okay, I'm not too— yeah, is it therapeutic?

Oh really? That would be amazing actually. I'm very curious. Yeah. Mm-hmm. Mm-hmm. Mm-hmm. Oh. Therapeutics.

Is it Genesis Therapeutics? I'm not too sure, but it's like they do drug discovery or something like that, or like for small molecules.

Yeah, yeah. I think so.

I don't know the gist of it, but their company seemed pretty interesting to me. I'm probably gonna talk to them soon, so I'll let you know how that goes. The other companies that like you should probably look out for, there's actually a company that's like, are you familiar with Voyo?

Okay. Okay. Yeah, that'd be awesome.

Like I put in the chat, V-O-I-O, like it's basically founded by a PLEME and it's a frontier AI lab for radiology. That's like definitely something like I can actually connect you with them. I'm not too familiar with them because like I know that he was the ex-chief of staff at Voyo, but he knows everyone at Voyo, so I know them pretty well.

Oh yeah. No, I haven't heard. Really? Okay. Oh.

What else is there?

That's awesome.

Like obviously Neuralink is cool, but I'm not sure if you want to join Neuralink. There's also obviously Abridge, TriDiscovery, Hippocratic AI. I saw Heidi. I think Heidi's pretty similar to like a bridge, like they do like medical note-taking for doctors. But yeah, if there's any connections I can make, I can— I'll definitely send it over to you.

Yeah. Yeah. Yeah. That'd be awesome. Yeah. I really appreciate it. Actually, are you— I was, again, another curiosity question. Are you interested in transitioning to a startup before medical school maybe? If you end up going to medical school, whatever you end up doing, but do you think that path from like Google jumping to a startup would be like something you'd be interested in?

Yeah. Yeah, totally. I mean, if it fits with my North Star and like kind of the things I want to do and it seems pretty interesting, I would be like totally down to just jump ship.

Yeah. Yeah. No, that's cool. Super interesting. I'm sure living in SF is great though. Like the connections you can make. It's like, yeah.

It is. Yeah. You just talk to people on these events just randomly. You're like, oh, you also go to Brown? And then you have a conversation only to figure out their husband works at like, or is the CEO of some huge company. So I think it's pretty interesting.

Great time. Yeah. Yeah. No, it's good.

Yeah.

I've met like a bunch of MIT people at startup school and like they were all like hardware people. So it was like, it was interesting. Like I think a few of them work at Etched and then like a few of them did hardware stuff at Google. Yeah. Yeah. It was pretty cool. Yeah.

Oh shit. Okay. Interesting. Do you also know about these like FTE rules?

Very interesting.

I think one thing you were talking about was like, you like, I guess as a Swede, you don't really get that much experience or exposure to like how things work outside of Sweden. Like you're just like in front of a computer coding. But do you know about like FTEs, like order boards? Yeah, yeah, like a lot of us, yeah.

Yeah. Mm-hmm. Yeah. Yeah, like the forward deployed engineers. Yeah, yeah, yeah. I, what do they? Sorry, like let me just give you my like perception of what they are and like you correct me when I'm wrong because I don't really, I don't really know what they do, but I was assuming that it's more like sales roles that like work on integration, right? So like an example would be like if you're working at a company, like you go and like you go to like a company that could be a client and then like you're basically trying to pitch them, but like in a way that like helps them with integrations. So you're like more technical about it. Is that how it works?

Hold on. Yeah. Yeah. Mm-hmm. It's— that's pretty correct. I think it's like a blend of like consultant and SWE. Like there's actually 2 different roles that like people typically go into, 2 different buckets. Like there's like— so there's like 4 Forward deployed strategist, and then there's like the FDEs that you're familiar with. The difference is that the first one, so it's like both of them are 70/30 splits. So the first one is more like Yeah, I think it's like 70% consultancy. So what you're talking about with like they go into the company, I don't think they sell too much. They're more about like they're talking to the customers because they're trying to develop solutions that are very specific and bespoke to that company. So the strategists basically spend most of their time doing that and try to understand the problem better. And 30% of the time they're developing. The FTEs are more technical. They integrate into a company 30% of the time. And then 70% of the time they're doing development work. That's the way I kind of think about it.

Okay. Yeah. Okay. Mm-hmm. Yeah. Yeah. Yeah. Yeah. Gotcha.

There are a lot of FTEs in healthcare like opening up, which I thought was pretty interesting. So yeah.

Cool, cool. Mm-hmm. Really? Okay. That's interesting. Yeah. I'm sure, yeah, I'm sure there's gonna be a lot more of those like type of roles, especially for people who would have graduated med school. Like you're sending them to like maybe hospitals or sending them to like physician. Yeah. Okay. That's really cool. Yeah. Interesting. I guess maybe that, like, the possibility of that role, like, tips it in the favor of having more exposure to medicine, maybe. I don't know.

Exactly, yeah. Yeah, like obviously like you want people who understand the medical problem and can under— like have that kind of speech or talk to doctors, talk to nurses, talk to like key stakeholders. Like I feel like a normal software engineer can't do that, so.

Yeah. Awesome. Sounds good, I guess.

Um, not really, but, um, I can definitely like put you on with like some people I know if you're interested in like recruiting, so.

Did you have any other like questions, anything else that you want to talk about? Yeah. Honestly, that'd be great. Yeah. Super, like, I'm super open to like learning more, just exploring next summer. And yeah, that's awesome. Thank you. I appreciate it.

Okay. Cool. Is there anyone else that you know that you like in PLEME or like otherwise that

Uh, have you, have you spoke to Sid?

Sid— what's his last name? I don't think so, no.

Sid Naredi? Here, I think I can send you his. He is also CS, believe me, right? He's— this summer he was a data science intern at Stanford, so.

Oh wait, that's super cool. Is he still at Harvard or is he, or is he still like in the Bay?

Yeah. It's just LinkedIn. He was just in.

Okay.

I don't— I actually don't know. I'm not sure. I think he may have come back, but you can— yeah, maybe you'd be able to meet with him. Yeah.

Okay. Oh, he was a TA, a CS15 TA. Awesome.

Yeah, yeah, yeah.

Interesting. I like how every year in Plimy there's like 2 people that are doing like CS in Plimy, which is like so interesting to me. There's always like 2 or 3.

Yeah. Interesting. And then, uh, Yeah. Hey. Yeah, I think this year we have a few— actually this year, I don't know if this— we have a few people who are working at like McKinsey Bain next year.

Yeah. Oh wait, what was her name? Ananya was her name, I think. I talked to her. Yeah, yeah.

And Ananya, yeah. Yeah, but was she like— I don't— is she into tech? I don't think she's a— is she CS?

She's actually CS econ. So like she was telling me how she's going to intern at McKinsey, but she's also interested in like technical roles. So I was like, huh.

Okay, okay. Yeah. Yeah. No, I think she started just econ or public health econ and then she transitioned.

Oh, what?

Because I remember that, yeah, yeah. Because I remember freshman year during like the ice cream social and everything, we're talking and I think she was just econ then, but she moved into the technical parts. Yeah, yeah. I, that's what I'm saying though. AI just captures your attention, right? It's just too cool. But yeah.

Oh, interesting. That's cool. Yeah.

I guess other than that. I hope like it was, I guess. Do you have like, after all these talks, do you think that you have like a little more clarity or like you're a little more aware of like what people are thinking and like what you want to do or like do you feel like you're just more confused now?

That's a good point. Like, I will say that it's like when you have more options, the decision gets harder. And when you understand so many different, like, perspectives, you're just like, well, Like, like nobody's going to be the exact same as me, so I can't just like copy what other anyone did. I think like Abdullah, the guy I was talking to at Google, he put it perfectly about how like we're all all going, like undergoing a very unique path and nobody's going to undergo the same exact path as you.

Genuinely. Yeah. Yeah.

So you kind of just have to figure it out on your own. But obviously, like, having a network of people would obviously help. And honestly, we should just create a group chat of everyone. Like, I feel like that would probably make it easier if you want to like contact. Yeah, but I think just having each other would be great to just, you know, make the connections. I can obviously introduce you to people. So yeah, that's— it's just something I have to figure out on my own, which would be pretty interesting.

Yeah. Pretty much. Yeah. Yes, please, that'd be great. Yeah. Yeah. Yeah. I mean, that's so true. It's like, I guess now that's the thing with like, I guess the American dream, right? You can do whatever you want, but like whatever is a lot, a lot of things, right? So yeah, that's awesome. I feel like it's in some sense is a good problem to have and it's like, yeah, for sure.

Yeah, exactly. Yeah. It is. There's no bad decision to make, but yeah.

Exactly. Yeah. Yeah, for sure.

No, yeah, totally.

Well, I guess. Thank you very much. I appreciate it. Yeah, yeah, let me know what you end up deciding about med school and everything. That would be very interested to hear. Yeah, I know where you're going. Let's stay in touch.

Yeah. Yeah. Totally. I think it's great to hear. Totally. Wait, I'll drop my number down, so just like text me.

Oh yeah, awesome. Yeah, I'll text him.

But yeah.

Awesome.

Awesome. Yeah, I'll probably have to head out in a bit, so.

Yeah.

Yeah.

Thank you. I appreciate it. Yeah, it's great to hear other opinions, honestly, because like this is, it's a very unique like way of thinking and a very unique problem to have. Like not many people could relate or haven't thought about it at all. So it's like, yeah, it's good to hear.

Yeah. It is. Yeah.

Awesome.

Cool, man. Yeah.

Well, I appreciate it. Thank you.

All right, just text me whenever. And also, if there's anything that comes up in terms of like roles, I'll definitely let you know.

Yeah. Thanks.

So. Yeah, of course.

Yeah, that'd be awesome. Appreciate it.

Yeah, definitely.

Yeah, and let me know if you ever need anything.

All right. This way.

Sure. All right.

You too.

See ya. Have a nice day. Yeah.