YouSaid · the spoken record

Mark Chen

lines on the record: 77
first: 2025-09-25
most recent: 2025-09-25
sittings or episodes: 1
sources: podcast

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“Some of the greatest discoveries in science, especially in physics, have often come from a pair of collaborators often across universities, across fields. And it seems like you guys have not.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Itself, but then coupled with this great ability to lead and inspire teams and create an organizational structure that, you know, in this whole kind of mess of chaotic directions actually is coherent and able to gel together. Yeah, very, very inspiring.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Thanks, Mike. Yeah, yeah, I think the big kind of the first big thing that we together was like we started seeing like, okay, like we think this algorithm is going to work. And so, you know, I was thinking like, okay, like, how do we direct people at this? And we were talking with Mark, like, oh, we should establish a team that's actually going to make this work. And then Mark went and actually did this, right? Like actually kind of like got a group of people working on very different things, like got them all together and created a team with incredible chemistry out of this whole disregard group. And I was like such an impressive thing to me. And yeah, I'm really grateful and inspired to kind of get to work with Mark and kind of experience that. Yeah, I think this incredible capacity to both understand and engage and think about the technical matter of the research.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Do you think we started working together a little bit more closely when we kind of had the first seeds of working on reasoning? I think we At the time, you know, that wasn't a very popular research direction to work on. And I think both of us kind of saw glimmers of hope there. And we were kind of pushing in this direction, kind of figuring out how to make ROL work. And yeah, I think over time kind of growing a very small effort into increasing larger effort. And I think that's kind of where I really got to kind of work with Jakob in depth. I think he's just really a phenomenal researcher. I think any of these frank lists, like he should be number one, like just his ability to take any very difficult technical challenge and almost like personally just kind of think about it for two weeks and just crush it. It's incredible that he has kind of the wide.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“New thing and trying to reconfigure our thinking around the kind of new constraints and new possibilities that we're going to be faced with. And so I think that kind of creates this feeling of constant change and the mindset of always kind of learning the new thing. Well, you know, one thing that came up in our research about things that OpenAI that have not changed through a lot of the change is the trust that the two of you guys have in each other. Because I think there was an article or profile of you guys recently in the MIT Tech review, and that was also one of the highlight themes that your chemistry, your trust with each other, your opposed something a lot of the people at OpenAI have come to Treat as a constant. So, what's the backstory? How did you guys build trust there? How did that?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I think that the developer of technology is a driving force here where. Maybe we would kind of become comfortable after a few years working in a given paradigm, but we are always on the cusp of that, you know.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“It is a full time job to kind of stay on top of all of it. And that's just been very fulfilling. So yeah, no, I think that's a very accurate description. We just want to generate a lot of really high quality research. And it's almost a good thing. Like if you're generating enough that you're barely able to keep on top of it.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I think one of the clearest markers that we have really good research culture, at least in my mind, is I've worked at different companies before and there is a real thing which is a learning plateau, right? You go to a company, you learn a lot for the first one or two years, and then you just find kind of like. I know how to be fairly efficient in this framework, and my learning kind of stops. And I've really never felt that at OpenAI. Just like that experience you describe of all these really cool results bubbling up, you're just learning so much over week.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Very few startups can get to the scale that you have, both from an employee perspective, but also revenue. Secret sauce to doing that. And how do you continue to maintain this pressure almost to ship as quickly as possible, even though you're kind of on top now”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“More broadly than compute, there is physical constraints of energy, but also at some point not too far, like robotics will become a major focus. And so I think thinking about the physical constraints is going to remain important. But yeah, I do think on the... Intelligence front, I would not make too many assumptions.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“It feels like because of the unsort of completely unbridled base of progress that we've just spent a lot of time talking about. Lot is going to change over the next few years, right? It gets really hard to predict. I imagine 10 years out, let alone 10 months out. My question, I guess, is through all that change that the frontier of AI is going to bring, what are some priors that you actually think should stay constant? Is there anything? Well, one clearly is that we don't have enough compute. Is there anything else that you think doesn't change that you think would be strong, reasonably held priors as constants?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I think with every launch, we are trying to aim it to be something that's wildly successful on the product side. And I think from a fundamental research perspective, we're trying to create models with all of the kind of core capabilities needed to build a very rich set of experiences and products. And there are going to be people who have some vision of one particular thing they could build. And we'll launch it and everything we launch, we really hope it goes wildly successful. And we get that feedback. And if it's not, we'll kind of shape our product strategy a little bit. But yeah, we are definitely also in the business of launching very useful, wildly successful products.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“So we generally have some pretty strong convictions about the future. And so we don't tie them that closely to short-term reception of our products. Of course, we learn based on what is going on. We read other papers and we look at what other labs are working on. But generally, we act from a place of fairly strong belief. What we're building. And so, of course, that is for our long-term research program, of course, when it comes to I think the cycle of iteration is much faster.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“How does external perception, reception of a particular product launch impact how you prioritize something? Is that to the extent where, you know, Perception and usage in the case where they're married, obviously there's probably a clear directive there. But in a case where maybe they're divorced a bit, does that impact how you think about roadmap or where you emphasize resources?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I think maybe like one. Utter nice thing that you get to experience at academia is like, yeah, just like persistence, right? Of like, oh, you know, you have a few years and you're kind of trying to solve a problem and it's a hard problem and you've never dealt with such a hard problem before. And yeah, I do feel like this is a thing that's like, well, Currently, the pace of progress is very fast. Maybe also the idea tends to work out a little bit more often than they did in the past because deep learning just wants to learn. And getting your hands on a more challenging problem for a little bit, maybe being part of a team attacking an ambitious challenge and getting that feeling of what it feels like to be stack and what it feels like to finally be making progress, I think is also something that's very useful to learn.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I guess I personally started as a resident at OpenAI, and it's a program that we had for people in different fields to come in, you know, learn quickly about AI and become productive as a researcher. And I think there was a lot of really powerful elements in that program. And the idea is just like, you know, could we accelerate something that looks like a PhD in as little time as possible? And I think a lot of that just looks like implementing a lot of very core results. And through doing that, you're going to make mistakes. You're going to be like, oh, wow, like build intuition for if I set this wrong, like that's going to blow up my network in this way. And so you just need a lot of that hands-on experience. I think over time, you know, there have been curriculums developed at probably all of these large labs in like optimization and architecture.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Historically, the job of advancing fundamental research has historically been largely a mandate that universities have had, partly for the compute reasons you just described, that hasn't been the case for Frontier Eye. You guys have done such an incredible job kind of channeling the arc of Frontier Eye progress to help the sciences out. And I'm wondering when those worlds collide, the fundamental world of university research today and the world of frontier AI, what comes out.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, I think we've seen for long enough, like how. Much we can do with compute. Yeah, I haven't really bought that much into the will-pie data constraint claim. And yeah, I don't expect that to change.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I think it makes sense to talk about it for just a little bit more, which is compute sets so much of Computer's destiny in a way, right at a research organization like OpenAI. And so would you, a couple of years ago, I think it became very fashionable to say, oh, okay, we're not going to be compute constrained anytime soon because there's a bunch of CMs that are, you know, people are discovering and we're going to get more efficient and all the algorithms are going to get better. And then eventually, really, we'll just be in a data constrained regime. And it seems like a couple of years have come and gone, and we're still, this is sort of very compute constrained environment. Does that change anytime soon, you think?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, honestly, I do think kind of to your question of prioritization, right? It's like in a vacuum, any of these things, you would love to like go and excel and win at. I think the danger is you end up second place at everything and not. Clearly leading anything. So I think prioritization is important, right? And you need to make sure there's some things you're clear eye on. This is the thing that we need to win.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so I think that's a big part of both of our jobs. Just this portfolio management question of how much compute do you give to which project? And I think historically we've put A little bit more on just the core algorithmic advances versus kind of the product research. But it's something that you have to feel out over time. It's dynamic. I think month to month there could be different needs. And so I think it's important to stay fairly flexible on that.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“How does that translate just to build on Anja's question into a concrete framework around resourcing? Like, do you think about, okay, X percent of compute resources will go to longer term, you know, very important, but maybe a bit more pie in the sky exploration versus there's also, you know, obviously current product inference, but sort of this thing in the middle where it's achievable in the short to medium term.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, absolutely. And the real answer is we don't discourage someone from being really excited by that. And it's just if we're consistent in the prioritization and our product strategy, then it just will naturally fall in. And so it's just for us, we do encourage a lot of people to be excited about building this, or building kind of like agentic products, whatever kind of products that they're excited by. But I think it's important for us to also have a separate group of people who you protect that their goal is to create the algorithmic advances.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I think there's definitely a question that we've been kind of thinking about for quite a while at OpenAI. I mean, if you look at GPT-3, right? Once we kind of saw, oh, this is kind of where language models are going, we definitely had a lot of discussions about Well, clearly, there are going to be so many magical things you can do with AI, right? And you will be able to go to this extremely smart models that are out there pushing different tiers of science, but you will also have this incredible media generation and this incredibly transformative entertainment applications. And so how do we prioritize among all these directions has definitely been something we've been thinking about for quite a while.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“And have there been any moments where those things have been in tension at all recently? Well, one provocative example could be recently this new image model came out, which was Nano Banana, right from Google. It's extraordinary value shown that lots of everyday people can unlock a lot of creativity when these models are good at understanding editing prompts. And I could see how that would create some tension for a research program that may not be prioritizing that as directly. If one of your somebody talents on your team came and said, Guys, this thing is so clearly valuable in the world out there, we should be spending more effort and more energy on this. How do you reason about that question?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Bottom up idea generation for fundamental research on various domains, but we are always thinking about how do these ideas come together eventually. We believe, for example, that reasoning models go much further and we have a lot of explorations on things that are not directly reasoning models, but we are thinking a lot about how they eventually combine and what will this kind of innovation look like once you have something that is out there and thinking for months about a very hard problem. And so I think this clarity of our long-term objectives is important. But yeah, but it doesn't mean that we are prescriptive about, oh, here are all the little pieces, right? Like we definitely view this as a question of exploration and learning about these technologies.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Our state of goal for our research program has been getting to an automated researcher for a couple years now. And so we've been building Mosaic projects with this goal in mind. And so this Still leaves a lot of room for.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“One of the things that you guys have done is let such a diversity of different ideas and bets flourish inside of OpenAI that you then have to figure out some way as research leaders to make it all make coherent sense as one part of a roadmap. And you got, you know, people over here investigating the future of diffusion models and visual media. And over here, you've got folks investigating the future of reasoning when it comes to code. How do you paint a coherent picture of all that? How does that all come together when there might be at least naively some tension between giving researchers the independence to go to fundamental research and then somehow making that all fit into one coherent research program?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“One thing I think is also helpful is that our product team and broader company leadership is bought into this vision where we are going with research. And so nobody is assuming that all the product we have now is the product we'll have forever and we'll just kind of wait for new versions from research. We are able to think jointly about what the future looks like.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, I think it's about kind of delineating a set of researchers who really do care about product and who really want to be accountable to the success of the product. And they should, of course, very closely coordinate with the research work at large. But I think just kind of people understanding their mandates and what they are rewarded for, that's a very important thing.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“To pull on that thread more unprotecting fundamental research, you guys are obviously one of the best research organizations in the world, but you're also one of the best product companies in the world. How do you balance, and especially with you've brought on some of the best product execs in the world as well, how do you balance that focus between the two? And while protecting fundamental research, also continue to move forward the great products that you have out.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Especially now that there's so much spotlight on open AI, so much spotlight on AI in general and the competition between different labs, it would be easy to fall into a mindset of like, oh, we're racing to beat this latest release or something. And there's definitely areas that people kind of start looking over their shoulder and starting about, oh, what are these other things? I see it as a large part of our job to make sure that people have this comfort and space to think about what are things actually going to look like in a year or two. What are the actually big research questions that we want to answer and how do we actually get to models that vastly outperform what we see currently rather than just iteratively improving in the current paradigm?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“So I think actually the most important thing is just to make sure you protect fundamental research. I think you can get into this world with so many different companies these days where you're just thinking about, oh, how do I compete on a chat product or some other kind of product surface? And you need to make sure that you leave space and recognize. And also give them the space to do that, right? Like you can't have them being pulled in all of these different product directions. So I think that's one thing that we pay attention to within our culture”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“And say a little bit about what it takes to make a frontier sort of winning culture that can attract all kinds of shapes of researchers and then actually grow them, thrive them, make them win together at scale. What do you think are the most critical ingredients of a winning culture?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I mean, I do think Researchers, they don't just fit one shape. We have certain researchers who are very productive at OpenAI who are just so good at idea generation. And they don't necessarily need to show great impact through implementing all of their ideas, right? I think there's so much alpha they generate in just kind of coming up with, oh, let's try this or let's try this. Or maybe we're thinking about that. And there's other researchers who, you know, they are just very, very efficient at taking one idea rigorously exploring the space of experiments around that idea. So I think researchers come in very different forms. I think maybe that first type wouldn't necessarily map into the same bucket as a great engineer. But we do kind of try to have a fairly diverse set of research tastes and styles.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“As you were talking, I was thinking back to when I was a founder and I was running my own company and we would recruit for great talent engineers. Many of the attributes you described were ones that were on my mind then. And Elon recently tweeted that he thinks this whole researcher versus engineer distinction is silly. Is that just a semantic? Is he just being semantically nitpicky or do you think these two things are more similar than they actually look?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I think one thing that we look for is having solved hard problems in any field. A lot of our most successful researchers have started their journey with deep learning at OpenAI and have worked in other fields like physics or Computer science, theoretical computer science, or finance in the past, strong technical fundamentals coupled with the intent to work on very ambitious problems and actually stick with them. We don't purely look for who did the most visible work or is the most visible on social media.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I was chatting with a researcher recently, and he was talking about wanting to find the cave dwellers. These are often the people who are not posting on social media about their work for whatever reason. They may not even be publishing. They're sort of in the background. Doing the work. I don't know if you would agree with this concept, but how do you guys hire for researchers? And are there any non-obvious ways that you look for talent or attributes that you look for that are non-obvious?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“In the business of discovering new things about the deep learning stack. And I think we're kind of building something very exciting together. I think beyond that, a lot of it's creating very good culture. So we want a good pipeline for training up people to become very good researchers. We, I think, historically have hired the best talent and the most innovative talent. So I just think we have a very deep bench as well. Yeah, I think most of our leaders are very inspired by the mission, and that's what's kept all of them there. Like when I look at my direct reports, they haven't been affected by the Talon Wars.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Biggest, I think, things that OpenAI has going for it in terms of keeping the best people motivated and exciting is that we are in the Of doing fundamental research, right? We aren't the type of company that looks around and says, oh, what model did Company X field or what model did company Y build? We have a fairly clear and crisp definition of what it is we're out to build. We like innovating at the frontier. We really don't like copying. And I think people are inspired by that mission, right?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“As leaders of the research org, how do you think about what it takes to keep the best talent on your team? And on the flip side, creating a very resilient org that doesn't crumble if a key person leaves.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“And identifying them can be a very meaningful breakthrough for your research program. But also kind of bugs in the sense of like, well, you have a particular way of thinking about something and outweighs a little bit skewed, which causes you to make the wrong assumptions. And identifying those wrong assumptions, rethinking from scratch, I think both for getting the first reasoning models working or getting the larger pre-trained models working. I think we've had multiple issues like that that we've had to work through.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Think on the path there, right? Like along the sequence of models, like above the pre-trained models, and there is a models, I think one very common theme is bugs. And both just like, yes, silly bugs in software that can kind of stay in your software for like months and kind of invalidate all your experiments a little bit in a way that you don't know.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“And in the development of doing the training phase of GPD-5, for example, were there any moments where There was a hard problem, the original initial attempts that were being made to crack that problem weren't working, and yet you found somebody persisted through that. And what was it about any of those stories that comes to mind that worked well? That you wish other people and other researchers did more of.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“You're always thinking about what is really the barrier for the next step. If you're going after problems that you really truly believe are important, right? Then that makes it so much easier to find the motivation to persist with them over years.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, to be clear, I don't think conviction and truth seeking are really in a zero-sum tension. I think you can be convinced or you can have a lot of belief in idea and you can be very persistent in it while it's not working. I think it's just important that you're kind of honest with yourself, like how much progress you're making and you're in a mindset where you're able to learn from the failures along the way. I think it's important to look for problems that you really care about and you really believe are important, right? And so I think one thing I've observed in many researchers that inspired me has been really going after the hard problems, like looking at the questions that are kind of like widely known, but like not really kind of considered tractable and just asking why are they not tractable or like, you know, what like what about this approach? Like, why does this approach fail?”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I was in grad school, you know, there's a big part of a failed machine learning researcher. I was in grad school for bioinformatics. But a big part of my research advisor's thrust was about picking the right problems to work on such that you could then sustain and persist through the hard times. And you said something interesting, which was there's a difference between having conviction in an idea and then being maximally truth-seeking about when it's not working. And both those things are sometimes intention. Because you kind of go native on a topic or a problem sometimes that you have deep conviction in. Have you found, is there any sort of heuristics you found are useful at the taste step, at the problem picking step that help you arrive at the right set of problems where that conviction”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I think there are just very few shortcuts for experience. I think through experience, you kind of learn what's the right horizon to be thinking of a problem, right? You can't pick something that's too hard or it's not satisfying to do something that's too easy. And I think a lot of researchers managing your own emotions over a long period of time too. There's just going to be a lot of things you try and they're not going to work. And sometimes you need to know when to persevere through that or sometimes when to kind of switch to a different problem. And I think interestingness is something, you know, you try to fit through reading good papers, talking to your colleagues, and you kind of maybe distill their experience into your own process.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“Is different about research when you're actually trying to. I think a special thing about research, right? Is you're trying to create something or learn something that is just not known, right? Like it's not known to work. You don't know whether it will work. And so always trying something that will most likely fail. And I think getting to a place where you are in the minds of being ready to fail and being ready to learn from these failures. And, you know, so, and, you know, and of course with that comes creating kind of clear hypothesis and being extremely honest with yourself about how you're doing on them, right? I think a trap many people fall into is going out of the way to prove that it works, right? Which is quite different from, I think like believing in your idea and thinking of it as extremely important, right? And you want to persist persist that, but you have to be honest with yourself about when it's working and when it's not so that you can learn and adjust.”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source
“I have a question about that, which is what makes a great researcher, right? When you say vibe researching, there's a big part of vibe coding is just having good taste in wanting to build something useful and interesting for the world. And I think what's so awesome about tools like Codex is if you've got a good intuition for what people want, it helps you articulate that and then basically actualize a prototype very fast. With research, what's the analog? What makes a great researcher persistence is a very key trait, right? I think what”
2025-09-25 · a16z Podcast · From Vibe Coding to Vibe Researching: OpenAI’s Mark Chen and Jakub Pachocki · IDENTIFIED FROM THE TRANSCRIPT · source