THE OMNI SHOW

Yong-Yeol (YY) Ahn: You can just grab the whole file content and then just copy paste in Tommy Focus and you have a date and destination and several placeholders. Basically the script asks me those questions like, where are you going? When are you going? And if I answer those questions, it fills in that information and then copies it to my clipboard.

Andrew J. Mason: You're listening to The Omni Show where we connect with the amazing community surrounding the Omni Group's award-winning products. My name's Andrew J. Mason, and today we learn how Ahn Yong-Yeol uses OmniFocus. Welcome everybody to this episode of The Omni Show. My name's Andrew J. Mason, and today we have YY. He is a quantitative foundation distinguished professor at the School of Data Science at the University of Virginia. And we're getting to dig into his Omni Focus setup a little bit today, but so grateful to have you join us today, YY.

Yong-Yeol (YY) Ahn: Yeah, thank you so much for having me. I'm an avid listener for this podcast, so I'm very happy to be on the show. Yeah, nice to meet you.

Andrew J. Mason: Oh, absolutely. And great to be met, and thanks for spending some time with us. I know that you're probably a pretty busy person. And when I say the phrase, "Quantitative foundation distinguished professor," there's probably somebody scratching their head saying, "Okay, number one, what does that entail? And then number two, how do you end up there?" My goodness.

Yong-Yeol (YY) Ahn: So, quantitative foundation is actually the foundation that established the School of Data Science. And it was invested by basically local business people, to donate $150 million, I think. That initiated the process of creating this school. And they have so-called this endowment for bringing professors to the school. I was lucky enough to be one of them and have this, a long title in front of me.

Andrew J. Mason: And talk to me a little bit about how your career track took you in this direction. If somebody happens to pop over to your LinkedIn page, they see MIT on your journey, University of Indiana in your journey. It's a winding but very pointed road to land up over here, which is really exciting.

Yong-Yeol (YY) Ahn: Yeah. So I did all my study in Korea. I actually studied physics, but then I got interested in data science and network science, and that pulled me into very interdisciplinary research areas. So I moved to Boston after my PhD at North Eastern University to do my postdoc research. And after that, I moved to Bloomington, Indiana to become a professor at Indiana University. And after spending 14 years, I recently moved to Virginia.

Andrew J. Mason: Can you talk to me a little bit about, in your role at the University of Virginia, what are some of the projects that you're involved in? What are some of the things that you're working on day-to-day? If you're allowed to, or as much as you're allowed to. Give us a bit of an overview as to what you're involved in there.

Yong-Yeol (YY) Ahn: Yeah. So I started from physics and I would say my main area of research is network science. So you can imagine Twitter, social networks, Facebook network, or even biological networks, neural networks. Those are all networks. And I'm really interested in how those structure of those networks produce this, which behaviors. And another important topic for me is machine learning and AI, and especially I love to bridge these two areas. So thinking about how to represent these networks using new machine learning models, for instance. And I study how information spreads, how communities form, and how AI models work, and then how to use those model to model complex systems, like how science progresses and how our society works essentially.

Andrew J. Mason: Any unusual or interesting findings that come out of your work that you think maybe aren't necessarily widespread or wholly adopted as opinions? Any amazing one-off thoughts about how stuff spreads, or how that behaviors transform over time? Or anything that shows up there for you that you would say, "I don't necessarily see this in a lot of research, but this is something that I'm finding"?

Yong-Yeol (YY) Ahn: Before that, maybe I should mention this. I'm still very proud that one of my research project was featured on VisOS, one of the VisOS videos, and it was about so-called flavor network. So it's about the network between ingredients based on how much flavor they share. And the idea is that if you have ingredient pairs that share a lot of flavor compounds, you can enhance that and they pair really well together.

Andrew J. Mason: That is incredible. Okay, that absolutely does fit the bill of what I was asking, yeah.

Yong-Yeol (YY) Ahn: So that was a fun-

Andrew J. Mason: I will say it was unexpected, and that's exactly what I was asking for.

Yong-Yeol (YY) Ahn: Yeah.

Andrew J. Mason: That's perfect.

Yong-Yeol (YY) Ahn: The fun side of it. And regarding how things spread, so we've been studying basically spreading models. And one of the interesting insights from those studies, not necessarily just my studies, but the field, is that there are two types of very different contagion dynamics. One behaves more like a disease spreading, like COVID and so on. The other one is very different. It requires this reinforcement. So technology adoption can be one example. If you need some critical mass around you for you to adopt certain behavior, beliefs or product, like Omni Focus. And these two contagions behave very differently and I think people are not really aware of that difference much. And one of the big implications is that people use influencer marketing, targeting all these celebrities, right?

Andrew J. Mason: Yeah.

Yong-Yeol (YY) Ahn: That makes sense in the case of more epidemic spreading because that just spreads from the hubs to the [inaudible 00:07:00]. The other contagion we call a complex contagion, that kind of flows in the opposite way. It starts from a very tight-knit community and you need those communities to trigger the initial adoption. And once the periphery adopts enough, then the hub adopts.

Andrew J. Mason: Wow. Oh my gosh. That is awesome. Okay, well, I had a tall order for you to blow my mind in about 30 seconds and okay, you delivered. Geez. That is really cool because the assumption is just that if it spreads, it spreads. And so the idea here is that actually, no, it challenges that assumption, especially in the adoption of ideas. Remember the adoption curve, the early adopters and then the laggards and everybody. And so you're saying there's a tight-knit community that begins and reinforces itself, almost like it feels like a nuclear reactor kind of a thing that's happening here. And then once the hub gets it from there, that's interesting. Wow. Okay. Well, that was perfect. That was perfect, YY, thank you. That's exactly what I was asking for.

Yong-Yeol (YY) Ahn: [inaudible 00:08:18]. Yeah, so you want to, say, promote some product, it's not the hub you may be targeting, you maybe should targeting. It can be just these niche communities. That can work better, potentially, yeah.

Andrew J. Mason: And it shows the flaw in a lot of people's thinking too. You think if I can just hit this critical mass of just spreading it in enough places, then that's okay, but it's diffused in that model. In this model it's-

Yong-Yeol (YY) Ahn: Right.

Andrew J. Mason: That is cool. Wow. Okay. Well, I will sit with that for a little while to think about what that means for me, man. Talk to me a little bit. We'll take some parallel tracks here so we have your story arc happening here. Do you have any recollection as to when you first came across the Omni Group or OmniFocus as software? Was there a moment where you're like, "Oh yeah, I've heard of that"? Or was it just a growing awareness over time? Eventually you just ended up knowing about the software and who we were?

Yong-Yeol (YY) Ahn: Yeah, so I've been really into productivity systems throughout my career, starting from, I don't know, my PhD and David Allen's book, [inaudible 00:09:32] and CGP Grey. I've been listening to all those people throughout. So I was very much aware from... Even before OmniFocus, there was the Kinkless GTD system. There were so many apps around. So I was just trying out a bunch of those apps. And I think I remember trying to use OmniFocus. Many people were saying that, "Oh, this is the app and it's so good." But it was expensive. I was not a professor yet and it was a little bit expensive to buy, so I was really struggling. I want to use it, but yeah, it's expensive. But then later I just jumped the gun and since then I just kept using it. It was not just a smooth journey because I kept trying out different apps all the time. Yeah, I don't know how many times I moved my whole to-do list set into another app and came back and just hopping through these different systems.

Andrew J. Mason: It's amazing. There definitely seems to be some... I don't know what you call that, technical debt or some sort of thing where it's like, "Oh man, I've got all of my data in one system and then I'm moving it out into the other." And then you try that one for a while, but you need to know whether or not this new system is going to give you a full return on your investment. So you really have to go all in on it.

Yong-Yeol (YY) Ahn: I think there is a trap. Once you start using a new app, it's fresh and clean. There's not a lot of things to do and you feel much more productive in that state until you accumulate a whole lot of to-dos. So I think there is a trap of just hopping through those apps. You feel productive for a while and then you get stuck and then you find another app. "Oh, this will solve my problem."

Andrew J. Mason: You hear people call it the shiny object syndrome.

Yong-Yeol (YY) Ahn: Yeah.

Andrew J. Mason: And I think David Allen said at one point, "Sometimes people get angry at me for what's on their lists. They get upset at me because of all the things. It's your list. It's the things that are in your list." How do you advise somebody who finds themself in that space where they're like, "You know what? I try to get some momentum, but every time that I really feel like I'm making headway, something new shows up in a different app and I want to be at the cutting edge of technology and there's the coolness factor of all of that." What would you say to somebody who maybe finds themself in that space?

Yong-Yeol (YY) Ahn: Yeah, I think it's so easy to make that mistake. So my biggest advice would be, go slow. Try to tweak your system one at a time here and there, not to try to just re-haul the whole system at once. It may make you feel more productive for a brief moment, but you'll come back. You're not changing. Your system may be changing a little bit, but you are not changing. So I'd say tinkering is probably the right approach for most cases.

Andrew J. Mason: It's so funny because that kind of goes against a little bit of the fundamental makeup that I feel like I have because you spin faster iterations in your life, you feel like you have more going on and you think, "Oh, well, if I throw everything into the new system, then I'll be able to keep going that quickly." But if there's a bump in the road, just like your tire hitting a rock, it can just start throwing you off a little bit faster too.

Yong-Yeol (YY) Ahn: And also there is this thing where you imagine a system that will work for you. But in fact, if you once implement that, it may not work for you. The best system is the system that you actually use, but what you imagine may not be what you actually end up using.

Andrew J. Mason: That's right. So you romanticize the idea. You fall in love with the idea of a system. Oh my gosh, that's right. I've never heard that before. That's really good. What do you say to somebody that's maybe on the other end of the tinkering spectrum? So there's those that really try to stay at the forefront and figure out, "Is this next new feature going to work for me?" What do you say to somebody that maybe knows they need to be doing something to keep track of their commitments, but a to-do list leaves a bad taste in their mouth. But you're growing in responsibility. Maybe you've got a new role showing up in your life or expanded responsibility. How would you advise somebody that is maybe just getting started in that direction saying, "Okay, I need to do something, but what?"

Yong-Yeol (YY) Ahn: Yeah, so I think an important starting point is starting really simple. Don't try to over-engineer the whole thing from the beginning. Say if you are starting out OmniFocus, maybe just use the inbox and nothing else, and then the system may gradually emerge. And I think one thing to really try out if you don't have any system is at least do this brain dump. Try that, because that's really powerful to dump everything from your brain into the paper or system, and then experience the moment where your head is clean. You have a very clean head-space. I think it's a good experience to have.

Andrew J. Mason: Talk to me about your day-to-day. Do you mind placing OmniFocus in an overall context? What types of things do you use it for? Is there corollary software that has data flowing into it or out of it? Just maybe walk me through a little bit of what your setup actually looks and feels like in the day.

Yong-Yeol (YY) Ahn: Yeah, so I think it's interesting because now it's a transition period for me due to the whole AI systems emerging. So everything is changing. And also over time, one of the, I think, important lessons I learned is that the system that works for you doesn't necessarily stay the same. So at one point the system may work perfectly, but that doesn't mean that that will keep working for you over time. So over time, I more and more accept the idea that my system will be, keep changing. And having said that, I think right now I'm using OmniFocus at the beginning of the process and at the end of the process, more or less. So at the beginning, I use it mainly for a capturing tool. I find some interesting paper, I just immediately capture into OmniFocus inbox, or I may just type out some random ideas. Or if I'm driving, I may be recording some voice memos on OmniFocus, and that all goes to inbox. And then sometimes I just open up new project and then just sketch out the whole task list, basically a checklist for that. And after that, I start using Claude Code and those AI agent tools more and more. And one of the reason I build this [inaudible 00:17:44] focus project is because these coding agents work really well with those command-line interface tools. So I use that to process my inbox. So basically, if it finds a YouTube link or paper link, it automatically finds all the metadata from the web and then uses that to create a page in my Wiki and then just file all the information there and then connect to relevant pages. So that's automatically done in the background, and I think that makes inbox cleaning very easy. Yeah, so that's the process of [inaudible 00:18:33], yeah.

Andrew J. Mason: And just to bring maybe some folks that aren't as familiar with the LLM stuff up to speed a bit, what you're describing is some add-on stuff that you've created that will allow you to use one of these command-line tools like Claude Code to be able to conversationally interact with your OmniFocus inbox and just something that performs the agentic behaviors that you're interested in having show up for yourself and automates in a way that makes sense to you. Is that kind of the idea?

Yong-Yeol (YY) Ahn: Yeah, yeah. So for instance, I may have 10 different paper links in my inbox. I need to click each one of them, open the webpage, grab the page, title, authors, abstract, all the information. I need to open up Obsidian, put that information into a new page. So there's no real brainpower needed throughout the process. LLM agents are really changing how to handle these tasks because it understands the natural language and it can use all the tools, it can access to the web, it can access to my Wiki, it can access to my OmniFocus. So it becomes a really nice agent that I can just tell.

Andrew J. Mason: And you also mentioned the idea of templating. Talk to me a little bit about that. I know it's a bit less agentic than we're talking about, but I also know we have a wide spectrum of people. Some are comfortable with hooking their data up to something that's internet ready, and then others maybe are a little bit more closed-system minded. Talk to me a little bit about how you use TaskPaper and templating as well.

Yong-Yeol (YY) Ahn: Yeah. So I remember learning that I can paste TaskPaper into OmniFocus and it was mind-blowing to me. And I think it's probably one of the, I don't know, not so well-known perks of the OmniFocus that more people should know. So TaskPaper is another to-do app. It has a specific plain text format to describe basically hierarchical to-do items with the tags and everything. Basically, if you have a template pre-organized into TaskPaper format, you can just grab the whole file content and then just copy paste into OmniFocus and you have a new project with the exact same hierarchy and [inaudible 00:21:31] and everything. So I keep these template files in plain text where some of the key elements are... How do you say, encoded into special strings that I can replace. And then I have a Python script that asks me a bunch of questions. For instance, I have a travel checklist and it has date and destination and several placeholders. Basically the script asks me those questions like, "Where are you going? When are you going?" And if I answer those questions, it fills in that information and then copies it to my clipboard. And then I just open the OmniFocus, paste it, and then I have a new project with a, I don't know, a hundred item checklist. Yeah, so that's how-

Andrew J. Mason: That's incredible.

Yong-Yeol (YY) Ahn: Yeah.

Andrew J. Mason: That's incredible. And I think this sits in the space between somebody that knows they need some automation happening in their lives, but maybe it isn't quite as predictable as a repeating task or repeating project, but that kind of tear one off and have it. So you know it's going to show up again at some point, but when? That's a great use case for that, I think.

Yong-Yeol (YY) Ahn: Yeah, I think I use the travel checklist the most open because it's very structured and you have always the same tasks. So now, because I've gone through so many iterations on the template, once I've done all the checks, then I'm super confident that I'm ready to step outside of my house.

Andrew J. Mason: Yeah. I'd be really interested in, you mentioned a little bit of the shiny object syndrome, the finding something new that shows up somewhere and being tempted to jump over to a new feature. Is there anything else in your journey as you're handling more and more responsibility as your career has morphed and grown over these years, that you look back on and you say, "Looking back, I don't know if I see it as a failure or a misstep or anything, but if somebody else is looking at what I do, they're like, 'Wow, wow, I really would love to be where you're at in my life one day,'" Is there anything that you see in your journey that they could take as instructional when it comes to productivity or how you manage the flow of your life's work?

Yong-Yeol (YY) Ahn: You mean lessons that I learned?

Andrew J. Mason: Yeah, anything prescriptive that you would say, "You know what? This showed up for me," and either, "It was a win and I'm really proud of it." Or on the other side of it, "If it were you, maybe just skip that part and you'd probably be the better for it." Yeah.

Yong-Yeol (YY) Ahn: Yeah. So I think the biggest pitfalls are definitely over-engineering, trying to optimize too early and then just chasing new, shiny apps and objects and systems, expecting that, hoping that this new tool will solve my issues. But those are definitely very, very common pitfalls for those who are getting attracted to this type of systems, I'll say. Regarding things I'm happy about and proud, but with this failure, you just keep learning about yourself.

Andrew J. Mason: That's right.

Yong-Yeol (YY) Ahn: And you understand yourself better. So that's, I think, really important aspect of it.

Andrew J. Mason: Sure.

Yong-Yeol (YY) Ahn: And then over time, I've been accumulating systems around me that can ingest a lot of information and juggle so many different projects at the same time. I regularly work on, I don't know, dozens of research projects at the same time. And I think these systems help me manage across those many areas of responsibilities.

Andrew J. Mason: Well, I love this conversation, YY. And if anybody's interested in really staying in your orbit or connecting to your work or finding out more about the research that you've done, the work that you've done and being a part of that, where can they connect with you? How can they find out more?

Yong-Yeol (YY) Ahn: Yeah, so I have my homepage. It's just my name.com, yyahn.com, Y-Y-A-H-N. And if you go there, you can find a bunch of social links over there. And I'm still proud that I was YY on Twitter, just two letters. But now I'm not on Twitter anymore. But I'm still YY on GitHub and on many sites I'm either either YY or YY Ahn, like Bluesky, Thread, Mastodon, LinkedIn. Yeah, you can easily find me. I just started two newsletters, one about more on the research side, one more about more of urbanism and local advocacy site, so you can find the information from my homepage as well.

Andrew J. Mason: That's fabulous. I do appreciate your time with us. Thank you so much for hanging out with us today.

Yong-Yeol (YY) Ahn: Yeah. Thank you so much having me, yeah.

Andrew J. Mason: Hey, and thank all of you for listening today too. You can find us on Mastodon at the Omni Show at omnigroup.com. You can also find out everything that's happening with the Omni Group at omnigroup.com/blog.