Transcript

00:00:00 - Speaker 1: There just really doesn’t seem to be an effective concrete practice for taking like day to day insights and accumulating them, like rolling them up into a snowball of novel ideas.

00:00:16 - Speaker 2: Hello and welcome to Meta Muse. Muse is software for your iPad that helps you with ideation and problem solving. This podcast isn’t about Muse product, it’s about Muse the company and the small team behind it. My name is Adam Wiggins. I’m here today with my colleague Mark McGranaghan. Adam, and a guest today, Andy Matuschek. Hello, thanks for joining us today, Andy. I think you’re about as close as there is to Rockstar and the tools for thought space.

00:00:39 - Speaker 1: That’s a really distressing statement.

00:00:42 - Speaker 2: Yeah, we’ll, we’ll talk more about why this space is so small a little later on, but for those that might not know you that are listening, maybe you can briefly give us your background.

00:00:51 - Speaker 1: Sure, I’ve kind of a meandering background. It begins in technology. When I was a kid, I was constantly developing video game engines and kind of these tools for creative people. I, um, with a couple of roommates, I worked on the, the first native Mac OS 10 graphics app and did that for a bunch of years and then made some open source software for developing.

I was always really into tools for others.

Went off to Caltech and kind of got introduced to science, serious science. And uh kind of got my, my very pragmatic engineer perspective salted uh with all that.

But unlike all of my peers who who went off to get a PhD, I, I went off to Apple and got a different kind of, it kind of felt like a graduate program of studying at the, the heels of all of these people with like jeweler’s loops that they were using to to look at individual pixels of devices and There, there my work became much less about just programming and much more about kind of the intersection between technology and design. I, I got myself involved in in all these projects that it kind of the through line was that they, they were about what was central to dynamic media, uh, as opposed to just pictures on screens. So things like, you know, interactive gestures and like the 3D parallax effect and, you know, crazy page curls and And all this stuff we’ve talked before about.

00:02:07 - Speaker 2: Uh, the way that Apple’s environment maybe has less of that distinction between design and engineering or there were a lot of people that sat really on the intersection of those two things and it was part of what allowed them to do and continues to allow them to do really innovative things on interface and and maybe you’re a person that sits in that place as well, right?

00:02:26 - Speaker 1: Sure, yeah, yeah, it’s it’s interesting because like from an org chart perspective, there’s really heavy boundaries between engineering and design, and like I was on the engineering side of the house, like I sat with the engineers, but uh for several years, I, I would like Spend much of my day sitting in the human interface lab, like next to a designer, and we’re just kind of like tossing prototypes back and forth all day. And so it became this kind of mind meld thing where those people could tweak values in the prototypes I built and you know, I would end up tweaking design elements as I was building prototypes and it kind of just the titles fell away.

But over time, I kind of, I began to feel that these experiments we were doing with the dynamic medium, I would love to see them applied to things which had More, more meaning, more impact in the world. And so I, I got really interested in, in education research. I started writing about that. And uh the folks at Khan Academy reached out and asked whether I’d like to do that kind of work with them.

Um, so I joined Khan Academy and and took along, uh, one of my Apple colleagues, Mei Li Ku, who is a wonderful designer and, and together we started this like R&D lab, uh, at Khan Academy where we explored all kinds of uh novel educational environments from that perspective of like trying to trying to look at what the dynamic medium alone can do.

Trying to make these active learning environments and I did that for about 5 years and um I started getting a little disillusioned with institutional education and um I started getting really interested in the kind of knowledge work that people like you and me do every day, where you’re reading information, writing information, creating new things, pursuing uh novel ideas every day, and I’m wondering how we could augment some of that.

Uh, so now I have this kind of independent research practice where I’m pursuing oddball questions like what comes after the book? Can we make something that does the job of a book but better? Uh, it’s just been sort of a delightful experience.

00:04:12 - Speaker 2: And I think one of the uh pieces you’ve written in all your writing is delightful, and I certainly recommend everyone uh read it, but uh uh read as much of it as they care to. But when I’ll link to because I think it particularly illustrates maybe the place where you and our team kind of overlap and thinking is the transformational tools for thought article, which both describes sort of your current work around the the learning and the space repetition, which you can tell us about, uh, but also the kind of the meta elements of how do we develop these kinds of tools in the first place.

00:04:43 - Speaker 1: Yeah, that that was a project with uh my wonderful colleague Michael Nielsen, who’s also been investigating the space which we might label tools for thought. And people have defined this in different ways that the term stretches back some decades, but uh I like to think of it as tools or environments which expand what people can think and do. And you know, a great example of this is writing. Another great example is numerals. So there’s a tendency to, to think about, you know, kind of computer implementations of these things and of course there are instances which are very interesting. Um, I find it very powerful to reach back to you know, these, these cultural.

00:05:16 - Speaker 2: Uh, ancestry tools for thought.

Absolutely. Another great example of that is, I think Brett Victor has a piece about this, which is essentially the chart, is the charting numbers, you know, on an X Y axis or, you know, line graph or that sort of thing that we we take for granted nowadays where it’s easy to crank that out in a spreadsheet or whatever, but that was an invention that happened not even all that long ago. It’s, you know, a couple 100 years back or something like that and the existence of this new. Um, tool, or actually, I think as you argue in that piece, medium, you would even call it a medium for thought, might even be more accurate, basically allows you to have new ideas or see the world in a different way. So the tools shape the kinds of thoughts you’re able to have and the kinds of works that you’re able to create.

00:05:58 - Speaker 1: That’s right. If all you have is Roman numerals, Roman numerals, uh, then it’s very difficult to multiply.

Suddenly, if you have Arabic numerals, it becomes quite easy by comparison. So kind of in the what comes after the book space, one of the things that my colleague Michael and I had been exploring is just this observation that most people seem to forget almost everything that they read, uh, and sometimes that’s, that’s fine.

The thing that really matters in a book is, is the way that it kind of changes the way that you view the world for many books that really is the impact that matters. Uh, but for other books, for instance, if you’re trying to learn about quantum computation or some advanced technical topic, uh, it really is kind of a problem, uh, that, that you forget. Uh, most of what you read because these topics build on each other as the book continues. And so you end up starting reading a book in English, say, and then halfway through the chapter, uh, you start to see there’s like a word of Spanish and, and then by the end of the chapter, there’s like whole sentences of Spanish and then then like the whole second chapter is in Spanish and say that you don’t know Spanish as a language, you read this book and you’re like, well, I thought I was reading an English book. It’s like, no, it’s actually written in this other language that you have to. Learn, just as you would have to, you know, learn vocabulary, if you were trying to speak a foreign language, you need to like learn the vocabulary, both conceptual and declarative of this domain that you’re seeking to enter. Uh and so, and so the experiment is kind of been, well, can we make that easier? A project that that paper describes is this textbook called Quantum Country, which tries to make it effortless for readers to remember what they read. Um sounds like kind of a crazy thing, but It takes advantage of really a fairly well understood idea from cognitive science, about how it is that that we form memories. It’s reasonably well understood. There’s sort of a closed set of things that you need to do in order to form a memory reliably. Uh, it’s just that like logistically, it’s kind of onerous to do those things, and it requires a lot of coordination and management. And so most people don’t do it or it’s kind of difficult to do it. Uh, but it’s pretty easy to have a computerized system assist these things. And so, basically, as you’re reading this book, every 10 minutes or so of reading, there’s this really quick interaction where, you know, say you just read about the definition of a qubit, after a few minutes of reading, there would be this little prompt interface where it’s like, hey, so how many dimensions? Does a qubit have? And you try to remember like, uh, how, OK, it’s two dimensional. So you think yourself 2 and then you reveal the answer and it’s like, oh yes, it was 2, and so you say, cool, like I remembered that. And then we say like, OK, so a qubit is really a two dimensional what space? Like, how do we think about representing this? And say you don’t remember that, it’s this linear algebra concept. OK, it’s a vector space. That’s fine. Like you reveal it back, you didn’t remember that. See market is like, I like, I didn’t remember that detail. And um this is already doing something for you because it’s kind of signaling like, hey, maybe you weren’t quite reading closely enough or just seeing that answer that you missed, like as you read the next section, if that topic comes up. Maybe you’re more likely to remember because you were just uh corrected and you saw that correct answer. But somewhat more importantly, 10 or 15 minutes later when you’re looking at this, this next set of prompts, and you, you see kind of the new things from this section, that prompts about the two dimensional vector spaces that you failed to remember, that one will appear there. And so you’ll, you’ll kind of get another chance. And then once you remember it there, the idea is a few days later, we will send you an email and you’ll say like, hey, uh, let’s let’s remember these things about quantum computing that you were working on, let’s work towards long-term memory, and you’ll you’ll open up that review session and linked in the email, and you you’ll kind of do this interaction again, just, just a couple seconds per question. It takes about 10 minutes to go through the material. And that 5 days later will kind of reinforce your memory of that material about as well as the 10 minutes later prompts did, not, not exactly, but, but just roughly you get the idea. And then if you remember things after 5 days, then, you know, maybe you will next practice them after 2 weeks and after a month, after 2 months, after 4 months, and so it initially seems like this kind of onerous thing, like, oh, I’m gonna like be working on these like memory flashcards for this thing I’m learning, but Because the way human memory works is that it’s stabilized in this kind of exponential fashion where you can have successive exposures that are further and further apart. Uh, it only takes a few exposures before a particular idea can be remembered durably for many, many months at a time.

00:10:11 - Speaker 2: And this is a space repetition systems you’re talking about, um, which I had some exposure to through Onki, which is this little kind of I don’t know, uh, it’s definitely a tool for thought, but it is, uh, very nichey, I would say more than a little clunky to use.

You have to be really motivated to do it. And so you can use a tool like this to increase your retention or understanding of something you’re reading a science paper, a book. Something you you do want to get a deep grasp of, but you got to really work hard at it, right? The tools are very taping it all together yourself in a way that requires pretty big commitment and investment.

And one of the things I think is really interesting about the work you’re doing is whether you can take that and build it in a way that’s fun, relatively low effort by comparison, maybe even you know, sleekly designed and just more, more enjoyable overall.

00:11:06 - Speaker 1: Yeah, one thing that characterizes, I think a lot of opportunity in this space is that there are many exciting ideas which have been explored by technologists or by academics, which are promising at some foundational level.

The underlying mechanic of Aki is fundamentally the same as the underlying mechanic of quantum country if you look at it from a certain angle, but there’s this core design piece missing, that’s kind of keeping that idea from really having the transformative impact it could have.

By that, I don’t mean the fact that Aki is like hideous. I mean, it is, and, and it will kind of like turn off basically everybody who looks at it for that reason. But there are deeper issues to your point, it’s really hard to write good prompts. Uh, both in the sense that people start by being bad at it, and so they’ll write prompts that don’t work very well and that are boring and onerous to review, and they mostly won’t realize that that’s what’s happening. They’ll just think like that’s what this is. And then also in the sense that even if you do know how to write prompts well, it’s quite taxing. It takes a lot of effort. It’s a context switch from the experience of reading and it’s valuable insofar as kind of reflecting on material that you’re studying and synthesizing it, distilling it and turning it into a question actually does. go quite a long way to enforcing your your understanding of the material, but maybe you’re only going to do that for like the most important things in your life. And it’s pretty interesting to wonder like, OK, maybe you do that for the top 10% of the stuff that you ever read, but what if it was like really pretty easy and low effort for you to remember the top 70% of the things that you could read. You could save that special effort for the stuff that really, really matters. Um, that’s kind of what quantum Country is pursuing. One of the main things it’s wondering is, can we make this something. That it basically everybody who’s reading it and is serious about the topic can take advantage of and really see the benefit of.

00:12:49 - Speaker 3: I think this thread also reflects one of the challenges in developing new tools for thought, which is you actually need a lot of different skill sets. It’s not just a matter of engineering or computer programming, you need engineering, products, design, writing, marketing, community, often you need at least all of those things. And I see a lot of people approach the domain as basically pure engineers and they they. Tend to kind of bounce off or the products don’t stick because they’re missing a lot of those aspects.

00:13:15 - Speaker 1: That’s right. And I’ll add one more actually, that that’s kind of Michael’s in my hobby horse here, which is that you probably also need some kind of domain expertise.

So many of the, the projects in this domain, even if they do actually have the design skills and the technical skills involved as well as some of the other peripheral skills, they’ll be doing things like trying to make a tool to do math better or something like that, but no one on the team is a serious mathematician. And so they’ll make something that seems really cool and it makes for a really good like product presentation, but no mathematicians really going to use it to do serious work.

Maybe it works in an educational perspective, but it’s fundamentally limited. It’s it’s like a toy in some fundamental fashion. And so to that list, I would add, you need some kind of deep domain expertise too for a product like Muse, maybe that is somewhat diffuse. So anybody working on a product, the domain expertise that’s relevant there might be like, you know, the visual design of a product or like doing this kind of conception stages of a product.

00:14:11 - Speaker 2: Well, our domain is thinking. So luckily we have a domain expert on that, and that’s Mark, right?

00:14:15 - Speaker 3: Yeah, I feel like a sort of secret that we have, we had with the lab and now we have with use this understanding of the creative process and thinking and a lot of it actually comes. From the study of how this stuff happened historically. And you mentioned reaching back in history and learning from that something we’ve done a lot of.

00:14:29 - Speaker 1: Yeah, it’s fantastic. I think it’s just really attractive to build tools.

It is built into my DNA like I grew up that way, and it’s actually a liability for me.

My tendency when I see an opportunity or I see a problem space, is like, oh, wow, like I’m going to make a tool to like help with that.

And that’s like a useful tendency, it’s a cool tendency.

But often, I’m not like really solving a burning problem, or I’m solving an abstract problem that isn’t connected to something that is like concrete and intrinsically meaningful and that like actually is about doing the work. So like the analog and muse would be if maybe I’ve done like one serious creative process that was about like a concrete thing, and then I. Like, wow, like I’m really interested in the creative process. Like I’m going to devote, you know, the rest of my days to working on building tools for the creative process, which I like, I’m never really using to do any subsequent serious creative process. Like I’m I’m doing it in order to make the tool because I’m fascinated by tools. That’s a tendency that I have that I have to actively combat.

00:15:24 - Speaker 2: The other thing that comes with it, if you come into building a tool with the domain knowledge.

Is that over time you get focused on building the tool and maybe you actually know the domain less well.

So there’s there’s quite a parallel for me personally between uh Hiroku and Muse in that both are some kind of creative process.

Hiokku’s web development, um, which is one kind of one kind of creativity, one kind of creation, act of creation with Muse’s, it’s thinking and reading and making decisions.

In both cases, there is a process where a thoughtful professional sits down and they start in one place and they end with a solution or a result or or an output.

And studying and understanding that process both it’s fun for me to introspect for myself, but then the the ethnographic research aspect of going out talking to in the lab and in the build up to Muse, we talked to hundreds of creative professionals about their process, which was always an interesting thing because of course it’s this very private and intimate thing and also I would say 98% of the time people are vaguely embarrassed because they feel like it should be better.

It’s like, oh, my notes are really messy, or yeah. Yeah, you know, don’t look at my office. It’s, you know, things are, I, I should have some, I don’t know, some they have some idealized version of what it would what it would look like the reality I think is the creative process is messy and that was something we we fed into Muse was sort of embracing that a little bit.

00:16:46 - Speaker 1: I think it’s critical that you all not only experience that ethnographically but also personally that you have this deep personal experience of that process. Otherwise I fear it’s too detached.

The insight from the last year that I’m most excited about is is kind of this nugget in the middle of the the paper you you referenced, Adam. I call it like that the parable of the Hindu Arabic numerals. I hope you don’t mind if if I kind of recap it here because it just seems to bear.

It’s this observation that if you are the Roman royal accountant and you’re just struggling through these tables of numbers and you find it very onerous and it’s kind of taxing and it’s error prone, imagine if There was like Roman IDEO and you could go to them and say like, hey, please help me like with my accounting process, please redesign this. You know, IDEO’s process is pretty amazing in a lot of ways. They’ve helped make a lot of really powerful products, and they have this process that is really interesting where they go and they they embed, they will like sit with the accounting departments and like interview extensively as you talked about interviewing people about their creative process and like really try to internalize it, they’ll do all this like synthesis and diagramming. And they’ll come up with words to describe what people are doing, and it’s all great, but I think there’s just no way that Hindu-Arabic numerals would be the result of of that process if, if what you’re starting with is Roman numerals, because the transition requires the deep insights of a mathematician and also deep insights of a designer. So just for instance, place value, this notion that like if I have a 6 and it appears in the right moment. Spot, then it’s like a one digit, but if it appears in the second or rightmost spot, that 6 is still 60 in certain fundamental ways, and you can still perform the same fundamental operations on it, like with addition and so on. It still works the same, but it has this alternate interpretation of being like 60, it’s in the tens place. That is a profound mathematical insight that depends on deep intuition of like commutivity, the laws of distributivity. Uh, it’s not something that somebody just like doing some ethnographic research in the field is going to come up with, yet simultaneously, it’s also not something that most mathematicians are going to come up with. And so it’s a great example of how you like, you really have to have the same, the people on the same team.

00:18:57 - Speaker 2: That is a great example of the domain knowledge, and I wonder if that connects to something.

I feel like I see the trend of people with design as a skill set. I feel like are more often drawn to what I would call consumer or sort of end user things. So they’re more interested in working on social media, you know, let me get a job at Instagram or Facebook or something like that. And I wonder if that’s because then they only need to be an expert in the design domain, and if they’re working on something that’s more um for an end user that’s not really a specific domain, you don’t need that knowledge or the things that you need. To understand the problem space of Instagram is not deep specialized professional knowledge. It’s just being a person with a smartphone that likes to take photos and post them on the internet.

00:19:40 - Speaker 1: They can certainly be a lot more successful in that way.

People are sometimes surprised that Apple doesn’t really engage in anything that looks like design research, and here I use that word to to kind of mean that the ethnography that you’re describing user interviews, the walls full of sticky notes where you’re trying to like describe user behavior.

And summarizes your quotes. The Apple designers don’t really do that.

But they’re primarily designing products that solve problems in their lives. Like I use email, like, let me make this email a little nicer, and so like they can do that.

But I think as soon as you leave that domain, things start getting hard, like Apple iBooks, there aren’t a lot of like really serious readers on the design team. I think that’s part of why Apple iBooks is not good.

The various attempts at social music platforms, that’s something that requires like a set of ideas that have been pursued by various products. It requires like, you know, kind of a landscape review, understanding people’s social interactions really deeply, that’s also not part of the process. The Instagram designers, I think they are doing something that the Apple designers aren’t, they’re talking to users a lot about how they feel when they’re interacting socially, and that’s a piece that has always been missing from Apple’s process, but to your point, they’re not this like goal of of taking and sharing photos. That’s something they already like.

00:20:52 - Speaker 2: Well, we’re already pretty far into it here, but I feel like I should um stick to our format, which is introducing the topic. Maybe I’ll do that here and Andy, you, you suggested this one, which is uh environments for idea development, particularly idea of development over time. I thought it might be interesting to compare what that phrase brings to mind for each of us.

00:21:12 - Speaker 1: Sure. So one of the hobby horses I’ve been thinking about recently is, I’ve been reading this literature on deliberate practice. Eriksson is maybe the prominent individual there and there’s this, this extensive research on the practices of dancers, musicians, athletes who have these very formal and intense. Hence preparation and practice structures that stretch from youth into eminence. So touring international pianist is still working on these like fundamental skills and activities. And I think it’s fascinating that by contrast, knowledge workers really don’t seem to take their fundamental skills all that seriously insofar as kind of like improving them in a deliberate daily ongoing way.

00:21:51 - Speaker 2: Yeah, I’d be curious to even just enumerate what we think are some of the foundational or some of the core skills for a knowledge worker.

00:21:59 - Speaker 1: I was about to try to do that because I think it actually connects to this to this phrase. I’m sure that y’all could add some more, but I think reading effectively is is one of them, writing, communicating effectively is one of them.

But taking an inkling and developing it over time effectively seems like another just really important idea of creative work.

And so that that’s what made me suggest the topic that if I speak to people and ask them like, hey, so you know, this kind of interesting notion comes out of a conversation, and you think like it might be worth pursuing, then what? People’s answers are uh. They’re not good, you know, and like people do come up with things, they managed to develop ideas in spite of this, but it’s clear that this is very haphazard, and it doesn’t always feel like haphazard in a good way.

People will say things like, well, you know, maybe I write it down in my notebook. It’s like, well, and then what? Well, uh, maybe later I’ll like flip back through and see it, like, no, no you won’t, uh, or, you know, you can like you can schedule time, you can like put aside time to like think about that idea, and maybe if it’s like a really important idea you’ll do that. But you won’t for like, you know, something cool that comes out of a conversation that seems like it might connect to something later. There just really doesn’t seem to be an effective concrete practice for taking like day to day insights and accumulating them, like rolling them up into a snowball of novel ideas over time, except insofar as, you know, they kind of happen to accumulate in your awareness.

00:23:17 - Speaker 2: Yeah, that makes sense and obviously connects very well to the To the Muse story for me, it’s become because of this product that I now obviously have been using in the process of our team developing it.

Because it for me represents the place I go to do my deepest thinking. There’s almost not quite a ritual, but let’s say when I, when I go to make a muse board for something that I feel like is something I need to do a deep dive on, I know I’m really getting into it. That signals it to myself.

Almost to the point that sometimes I’m, it’s an idea I’m excited to explore exactly what you described, like the team is having a conversation, something serendipitously comes up. I think I should really dig in on that.

I think there’s something there. I put it in my notes to do that. So that can be like.

A fun, exciting opening a new door, opening a fun Pandora’s box kind of thing.

But it can actually also be the other way around, which is I know it’s maybe more of um something important to insult to research or understand deeply that maybe has is a problem in in my personal life or like a government paperwork thing or some other something like that.

And I just know, OK, I’m going to really get into it.

This is not shrugging it off. This is not quickly jotting down a couple of quick notes in my notebook and moving on by creating this board. I’m kind of mental. Making myself a commitment to follow this rabbit hole as deep as it goes until I feel like I have my head around the problem or or I’ve solved it, which is sort of an interesting effect, mental effect that the product seems to have on me.

00:24:36 - Speaker 1: It’s really interesting. Can I ask the and then what? Like something comes up in a team meeting and so like you add it to the muse board. What’s the and then what? How does that idea grow?

00:24:45 - Speaker 2: Yeah. Well, importantly, I wouldn’t add it straight to muse from the meeting. I would put it more into my kind of like inbox GTD style. Like just stop it’s the same it’s the same list where I put down, um, you know, we’re out of we’re out of milk, you know, get more, it’s just like little notes here.

Another way I’ll think of it sometimes uh in team meetings is realizing we need kind of an internal memo to pull together diverse thoughts on the topic and like really articulating what the problem is, um, and really trying to lay it all out so that not just for my own thinking but so we can all sort of be on the same literal page about.

Something, particularly maybe something that’s a long time ongoing problem and there’s people that weren’t on the team before and they don’t have some of the past contexts you want to put it all together.

Yes, so then what for me is deciding I want to devote a chunk of time to this, you know, maybe it’s 20 minutes, maybe it’s an hour, maybe it’s more to really dig in, to really just face whatever this is head on and see where it leads me.

And you know, maybe it’s something like an idea for a new product feature, for example, which again tends to be more on the fun. Uh, the fun side of things. And so then, then there’s this whole process around, you know, let me assemble prior art and get together some ideas and sketch some things and all this kind of stuff.

The output varies, but sometimes there’s just a clear insight of like, oh we should do X, it’s a decision basically, and then I will go and take action on that, but other times it’s realizing, wow, this is a really much deeper hole than I thought and You know, it needs more thought or it needs more whatever.

And then maybe I want to, for example, it’s a team activity, maybe I want to bring it back to the team and say, we thought we could, I thought I could think about this briefly, have a solution, and then do it. But actually it’s a lot deeper than that. What do we want to do? So I think it’s, I think it’s just like understanding or not quite enlightenment, but getting to this new place of understanding about whatever the thing is, and then that in turn implies a next action.

00:26:38 - Speaker 1: One of the questions I’ve been exploring in this space is what to do when it’s not really possible to make a lot of progress in one session.

So talking with people about their practices, one common approach that I hear relates to what I just heard you articulate, and that’s that something kind of reaches a threshold of interestingness or apparent importance. And at that point, you’re going to like carve out some time and sit down and really think about the thing.

That’s cool. And sometimes that is enough. I noticed that for a lot of the most interesting ideas that I explore, one session doesn’t often really doesn’t yield all that much. In fact, often it doesn’t necessarily feel like that session really produced a significant increment at all. Uh. You’re just kind of like manipulating the terms of the equation, so to speak, getting a better handle on it. And so one element that I noticed often really seems to be lacking from people’s processes, because it’s kind of it’s hard to orchestrate is marination, where it seems like sometimes what ideas need is just kind of consistently returning to them over time and asking like what do I have that’s new to say about this difficult question? OK, I can say a few sentences about it that seem kind of new, like it’s interesting, but it’s still not. Something. So I’m going to leave this for 2 weeks and I’m going to come back and like, what do I have that’s new to say about this? And maybe if you do that, you know, 6 times, something starts to emerge. That seems really difficult to orchestrate.

00:27:58 - Speaker 2: It makes me think of a great article called Solitude and Leadership, which basically is describing how you need to carve off this.

You basically need to disconnect from the opinions and influence of others in order to have original thoughts.

One way that the author talks about it is in that first session, like you described, at the end, everything that you’ve come up with a written. Down is really in a way just the thoughts of others that you’re echoing back. And that’s fine. That’s a starting place, but to truly get to something original or new or potentially breakthrough, you need to push past that.

Yes, he claims that he can sense when he’s sort of like sort of cross from the more mundane thinking and into the more excuse visionary for lack of a better, better word or just original, uh, when the thoughts start to not just be an echo of what he’s read or seen or heard someplace else.

And that always requires multiple sessions.

00:28:49 - Speaker 3: I think this also points to the idea that you can’t always expect to sit down in a series of sessions and then kind of one step after another, produce an idea all kind of in the forefront of your mind.

When we think about thinking and ideas and tools for thought, we have this very conscious perception of it.

It’s like I’m sitting down, I’m going to come up with something that’s better than Roman numerals. At the end of the session, I’ll have, you know, Arabic numerals. I think that’s just not how it works. Usually, sometimes you can get away with that, but often it’s more of your, like you said, marinating on stuff. That’s becoming this fodder for your mind and then in the background, you’re having an unconscious process of ideas, connection forming, inspiration, and then when you come into a later session, you might be better prepared to have a new idea. So I think it’s like you said, it’s really important to find ways for the tool to support that marination, chewing, ruminating, going over, rearranging without the expectation that you’re going to be explicitly building up your new idea.

00:29:39 - Speaker 1: It’s really easy for tools to accidentally build walls for that.

One of my favorite novel reading tools is this. liquid text, totally fascinating set of interactions for manipulating PDFs, excerpts, things like that. One very interesting design decision is that by default documents are kind of a workspace and so you extract excerpts into like this canvas and you can manipulate them, but documents are kind of separate from each other in that sense.

So you can have a set of insights about a document, but if you’re going to have inter-document insights, that’ll depend on your memory.

Now there’s a fix for that, which is that you can create multi-document workspaces.

You can say like, well, this is like my thinking about the this. Problem, you can kind of like bring several PDFs into it and kind of like make your notes and make your excerpts and whatever. And that’s cool because then you can have insights between them, but it still requires this intentionality of saying like, cool, I’m gonna like bring that PDF into this workspace and then like the notes and excerpts and whatever like they live there. But if you’re working on several interesting questions and ideas at once, it’s not at all clear that you’re going to have interactions between those workspaces that are necessary.

00:30:40 - Speaker 2: Yeah, liquid liquid text is great, but I think as a coming back to the environments for idea development. That creating room for serendipity without just total chaos is maybe a subtle and tricky thing.

00:30:53 - Speaker 3: I’ve thought about ways, by the way, to do this not subtly. One notion I have for an experiment is the idea collider. So you have something like your, your notes or your wiki pages, and every morning it just gives you two random pages and it’s like write a third page, which is the synthesis of these two things. Oh cool. I’d love for someone to do that experiment. Have you tried it? No, no, it’s kind of a it’s open. Request for research. So if anyone listening wants to develop it, let us know. That’s great.

00:31:14 - Speaker 1: It connects to a set of ideas that I’ve been exploring for the last year or so.

I’ll share it, maybe that’ll generate some more.

I’ve been doing this kind of strange note taking practice that really came out of trying to solve this problem of like, how, how can I make marination effective? How can I, how can I make a process where I can like do something every morning and cause there to be increments on my understanding. of some ideas or some problems I’m trying to solve.

And so I have something that’s kind of like a personal wiki basically. The technology is not really important. It’s more about the practice that’s important and the practice is that I try to write these notes that are densely linked to each other where each note is about a particular atomic idea.

Sometimes the note is a question like what are the most important design considerations when writing prompts for the mnemonic medium like one country and sometimes for Since the children of that note are declarative statements like space repetition memory prompts should focus on one idea, and then that note will kind of accumulate not just in one session, but over many sessions, all of the things that I have to say about that.

And sometimes I’ll learn that the title was wrong. It’s like, oh, actually they shouldn’t always focus on one idea because sometimes it’s really good for, you know, these memory prompts to like synthesize multiple ideas and these things kind of evolve over time, a term that some have used is is gardening.

Uh, I call these like evergreen notes because they’re trying not to be fleeting notes, like notes from a meeting that you’ll never really return to, but rather uh notes that you water and which grow over time.

And just to get back to your idea, Mark, one of the practices that I found most rewarding here is this notion of a writing inbox, where when something seems interesting or juicy, I have a place for it to go, and I start my writing most mornings by looking at that writing inbox and and training. those as a set of provocations or prompts and asking like, which of these things do I feel like writing about this morning.

In this way, ideas which seem promising, even if there’s already a lot written about them, I can kind of throw them back in the inbox and then it’ll like it’ll appear for consideration on upcoming mornings. But I think that inbox gets even more powerful if you start to introduce fancier orchestration methodologies into it. So one possible orchestration methodology is like the one that you just mentioned where like maybe the inbox this morning. contains these like pairs of notes. Uh, so it’s going to kind of combinatorically like walk my tree here. But another thing that seems pretty interesting and that I’ve been playing with is this idea that I had this interesting idea in a conversation with someone. I don’t really know what to do with it yet. It still feels promising, like, I don’t want to lose it, but I also don’t really have anything more to say about it right now. So I can like kind of snooze it for a while. It’s like, OK, I can go out of my, my writing inbox for a while, and it’s familiar from Gmail. And then It’ll like come back in a while, but in a modification on the snoozing functionality that I’ve been finding very interesting is the parameterless snooze. Normally you have to say like come back in a week. I think that kind of overhead is unhelpful and is often counterproductive and it’s better to just say like, no, not today. And to say like, well, if I’ve said that 10 times, then like, probably this should just go away a long time.

00:33:57 - Speaker 3: Yeah, does it like exponentially back off and reminding you. I think by the way, that snoozing or moving things out of you is really important. It’s actually a big difference in just having a big pile of to dos because there’s a limit to how many things you can have in your head at one time. And often we have new ideas that we want to bring in, but there’s no space. And the only way to do that is to actually kick stuff out from your working memory, and something like a snooze can help with that.

00:34:21 - Speaker 1: Muse is really Interesting in this regard because the the constraint of the screen as a surface, it encourages users to keep stuff to the quantity which they can see at a reasonable zoom scale on a screen at a particular time. I like part of the design?

00:34:36 - Speaker 2: Yeah, well, certainly constraints are potentially great for creativity. Post-it notes.

One that I reliably come back to both in my own work, but also just as just this kind of very workhorse tool for thought analog world thing and part of it is you just can only fit so much you can also use index cards for this as well, yeah, maybe with an index card and a Sharpie and that sort of limited amount that can be on each card.

Of course you can have any number of cards.

So yeah, obviously with Muse, you’ve got the, you’ve got the expanding boards and you’ve got the sort of the 3D nesting, but certainly there’s I feel a desire to make what’s on the screen at the time kind of fit together as a collection of things that feed each other and when I start to have a section. Of the board that starts to feel like a rabbit trail, then I want to make a subboard that and so it feels like you’re going deeper down the rabbit hole or something like that.

00:35:30 - Speaker 1: One of the things I wanted to ask you about is kind of muse relates to this note writing practice I’ve been doing is the practices of refactoring or revision, polishing, gardening.

Uh, something that’s been very useful in my practice is kind of having ways to think about writing at different levels of fidelity.

So I’ll kind of have a place where daily notes go that are quite fleeting and kind of scraps will start there. And when something is titalable, there’s some, some atomic unit that I can point to and say like, OK, that’s that’s the thing. Now it can get its own notes and it can be linked to from places. But almost, it’s almost like the goal over time is for these things to adhere and Crete into larger elements. So a a note that’s a single claim is like not that useful. It’s kind of this ross, but eventually some number of notes that make a claim will become like a, like a theory or like a noun phrase, a coinage or something. And that larger note that, you know, contains references to all these constituents, it feels like an increment that’s meaningful. And so the pressure in the system to like over time refine, refract. To create ever higher order abstractions is very helpful in my writing practice and I’m curious how you think about that.

00:36:38 - Speaker 3: I would say that Muse supports that, but doesn’t require it. So you can certainly use Muse as a persistent corpus that you’re accumulating over time and building up to these pristine and complete notes that are basically publishable.

But you can also use it in complement with other tools. So maybe you’re doing it in your head, maybe you’re writing stuff out in notion, maybe you’re using an authoring tool like Final Cut Pro, it’s more flexible on multi-purpose maybe.

It’s very important. It was a very explicit design decision that boards and cards in general do not require titles. I think that one of the kind of original sins of of file systems is in order something to exist, it has to have a name, but a lot of things just aren’t named yet.

00:37:11 - Speaker 2: That was one of our design goals with Hiroku was that you’d be able to put an application online without giving it a name.

00:37:17 - Speaker 1: Oh, that’s great. I didn’t know that.

00:37:19 - Speaker 2: That’s wonderful. The original implementation was Apps by default were untitled some long.

00:37:25 - Speaker 1: They have cute names.

00:37:26 - Speaker 2: I recall. This was, I think one of the, one of the really lovely pieces of work my partner there, James Lindenbob did, which is what we now call haiku names, which I think have been fairly widely adopted, which is sort of taking an adjective and a noun that were carefully selected so that they go together and they convey a certain vibe that kind of connected to our brand or whatever, plus we eventually had to add some numbers on the end just because there was enough of them. Um, but the idea is something that looks nice. It doesn’t look unfinished, it doesn’t look like untitled, but it doesn’t also require you to figure out, wait, do I want to call this my wiki or is it the team wiki or is it Team Wiki 2 or is it the, cause it’s like an idea I wanna pursue an unfinished thing and I don’t quite know what it’s gonna be yet. I have this hunch that I’m exploring and then yeah, you get all hung up on the name, um, and yeah, for for sure I see the file system. Uh, world of things having kind of that same problem where you use his names are important when we know that we sense that and so if you have to give it a name to even get started on whatever it is you’re creating, that can be a bit of a, a bit of a hold up. Now it’s nice, it might be nice to title something or label it later. Muse has labels for that reason, obviously rename your Hiroku app. There’s lots of other examples of that, but being able to just start with, it doesn’t have a name and eventually actually the act of naming it is you’re sort of upgrading it from Random tidbit of of random idea, random tidbit of knowledge may not amount to anything to, OK, this is a thing now.

00:38:47 - Speaker 1: Yeah, I really like this word upgrade. It accesses a design direction or a design space that I’m curious about with this taxonomy of notes, taxonomy of creative work. Taxonomy is too too rigid a word. It’s obviously much more fluid than that. Almost the ceremony of giving something a name, giving some. A coinage, and that that feels that the object feels more complete when it has a name, almost like it wants to like it wants to have a name. It’s OK with not having a name, but it’s in a happier state when it has a name.

00:39:19 - Speaker 3: This is a feeling that resonates very strongly with me. When I’m doing a project, a huge milestone is when I come up with a good name. And I don’t know why it is just, it feels so much more. Real when that happens.

00:39:29 - Speaker 1: In designing tools for thought in general, I think this is a powerful practice to avoid the tyranny of formality by saying like, OK, there are 6 types of notes. There’s the fleeting note, there’s the claim note, like, that’s terrible, screw that.

But you can still have an opinion about process.

People ask me like, what software do you use for your note taking? and it’s like totally the wrong question.

What matters is kind of the methodology, but having the methodology and Mind, I can’t readily like communicate it or install it into others' minds except by having them read like thousands of words of notes.

And one of the things that Tools for Thought can do is to encourage a particular methodology, not by imposing formal structure, but by implying certain kinds of structure, by making, for instance, objects on a canvas feel somehow more complete when they have a title. You’re not imposing the necessity of a title, but you, you’re suggesting that one’s work should perhaps culminate in a title.

00:40:24 - Speaker 2: My creative process is always heavily oriented around finding patterns, which is why it’s important for me to have a lot of I guess raw material and input.

Uh, you can call it data, but it might be something like user interviews or it might be something like looking at some other products in the space that I want to compete with or improve upon or something like that.

Um, it might be a series of bug reports, and I’m trying to get to the root of what this is in some kind of complex system in order to do that. I want to, you know, it’s been very difficult to track down, but if I could somehow kind of look at all of it together and extract out what’s the, what’s the pattern here? That’s, that’s the place where insights come from me. I, I glean that’s not necessarily the case for everyone, but for me it is this process and if I can somehow get everything together, I can get all the relevant stuff in one place, that’s half the battle.

00:41:12 - Speaker 3: Uh, one last idea and tools for thought before we transition into the meta, and the, the mummonic medium can be thought of as a way to optimally position you to remember things.

There’s this point where if you’re at as a learner, you’re, you’re best position to recall vocabulary phrases. It’s like just as you’re about to forget, basically, you get prompted again and as that happens more and more, those times become longer and with a system like space repetition, you get this software-based support to help you remember things.

I’m curious if you think that technique can be applied to Skills. Uh, this is an idea that I’m really intrigued by because yes there’s a lot of interesting things that are like facts and figures, but there’s also a lot of things that are our skills and abilities, and I wonder if we could apply the same technique to learning how to play chess or how to use a video editing program or something like that.

00:41:57 - Speaker 1: I do think that’s possible. I’ve spent a few years experimenting with it now, and so is my colleague Michael, and it begins with this observation that it’s possible to use spaced repetition memory systems for more than just recall. So the the typical way to use them is like, OK, what’s this term? What’s this definition? And that’s cool. I mean, that’s useful. But you can also use them for, for instance, applying an idea. And in fact, in quantum country in the final chapter, we have these questions that look a little bit more like lightweight exercises from a textbook or something like that, that share the property of the recall prompts that you can kind of, you can do them in your head, they’re quite rapid. They’re semi fungible, they’re lightweight, but they’re things like what would the output of this circuit be? And these are different from the recall prompts and that they’re not the same. Every time you see them. So you’re actively not trying to remember the answer, but you’re trying to like go through the work of producing the answer.

You can also write conceptual prompts, concepts distinguish themselves from declarative knowledge by focusing on how things relate to each other and kind of systems and structures.

You can ask questions like for instance, when I was studying the history of philosophy, contrast positivism and existentialism.

Now we’re making a connection, but in terms of developing a skill, like maybe you want to like learn to think in a Danological fashion or something. So you can also write a prompt that says, take a decision that you made this morning and it could be as simple as like deciding not to exercise when you normally would have and justify it or condemn it from a dentological perspective. And so this is like a task.

So zooming out, I think space repetition becomes most powerful when we think about the items, not as flashcards, but as micro tasks and what the system is doing is batching. The transaction costs, which would normally be associated with orchestrating all of these tiny micro tasks that you could use to practice a skill or develop a worldview or self-author in some way, and putting them together so you can say like I’m going to do 10 minutes of like my self betterment session very broadly construed, and that’s going to involve remembering certain chess moves and also practicing this line of force motion in chess and also reflecting on logical positivism in a certain way. Uh, and so on and so forth.

00:44:06 - Speaker 3: Yeah, that’s really interesting, and I’m, I’m wondering if you can extend it even further. So I think one element of space repetition is it’s kind of helping you with the mechanics of, OK, you commit to spending 10 minutes a day on this problem and we’re going to use the software system to make that really productive.

You’re gonna see a lot of cards, for example.

But I think another element is basically identifying what you need to get better at. In the case of memory, it’s pretty straightforward. It’s like the, the question. that you answered incorrectly last time or something like that, are the ones that you need to see now.

But in the case of chess, for example, it might be that your endgame is weak, or you don’t know how to handle attacking knights or something, and that is potentially much harder to identify programmatically.

But it seems like it’s also within reach. And so I’m curious about systems that both um help you mechanically, but also in kind of the same system, identify your weaknesses and where you can improve.

00:44:48 - Speaker 1: There’s a lengthy history. of people trying to solve that particular problem, going back, I think now almost 5 decades.

For me, the most promising kind of subfield or sub approach is called intelligent tutoring systems.

There are a few systems in the wild that have been commercially successful.

The most notable is called Alex ALEKS. It’s an algebra tutor which has some fairly clever mechanics for identifying your weak points and then focusing practice time on on those.

I would say that none of these systems has been wildly successful and the field as a whole has not been wildly successful.

I don’t fully understand why.

I’d like to spend some time studying that because it seems like a somewhat obvious progression once you kind of get into the space repetition space of trying to schedule stuff more efficiently, choose construct cards more effectively, perhaps dynamically. I have read some papers about people in the fields theories about why it hasn’t worked very well. They center on things like the non-regularity of topics. So an intelligent tutoring system on algebra will often share very little in common in its implementation with an intelligent tutoring system on geometry. They can share, you know, some kind of fundamental like modeling, the learner primitive type stuff, but the representation of the ontology is first off very difficult to construct and second off very. difficult to like systematize and encode in a consistent way across fields. My like personal hunch, and again, I haven’t read deeply into this, but my hunch is that part of why these systems have not been more effective in my practice is that they’re universally incredibly dreary. They, they have this intense feeling of being in a skinner box, like you’re a rat in a wheel, you are being fed. These like morsels of problem, and you like swallow, and then, OK, true, like, here’s another morsel, like, do this one next, and I think it may be possible to like, to recuperate the underlying conceptual ideas without the the interaction framework that they all employ.

00:46:39 - Speaker 3: Yeah, very interesting. I check out that literature.

00:46:40 - Speaker 2: So if we come to the meta side Of how tools for thought get developed.

We all have some familiarity with the human-computer interaction academic field and dabbled in that in various ways, even if none of us are career academics.

Then Andy, you ran a corporate R&D lab, which is sort of a one commercial approach to tackling innovation.

We, uh Mark and I were part of An independent research lab, which was an experiment in that, uh, and then all of us in various ways have been part of either classic Silicon Valley startups or bigger innovative companies like Apple.

And despite all of these, I feel like we still don’t have the level of attention, funding, and just people who are passionate about.

Yeah, computers and more broadly information tools that can help us be smarter, more thoughtful, make better decisions, be self-actualized, all of that bicycle for the mind stuff. I’m still trying to figure it out why that is. What’s the, what’s the gap there?

00:47:41 - Speaker 1: This is an ongoing mystery and a topic for discovery and discussion because in my mind, the wind condition for my work is not creating a particular tool for thought that that’s really powerful, but causing this to be a field. I view it as not a field right now. It’s kind of like this proto fields like some people doing stuff. We don’t have the Maxwell’s equations. We don’t have a powerful practice, but it kind of wants to be a field. I would really like it to be a field.

00:48:04 - Speaker 2: And in order to get there, no one graduates from design school and says I’m going to go into Tools for Though.

00:48:08 - Speaker 1: Well, I mean, some people have that intention, but they mostly don’t, and they mostly can’t.

00:48:11 - Speaker 2: Yeah, can’t is a really good point. I we got a lot of emails that can switch with people saying, hey, I’m about to graduate from this design school or I’m working in a startup over here. How can I get into To this field, I kind of said, well, what field? I didn’t have, I didn’t have anything like an answer for them.

00:48:27 - Speaker 1: I don’t think there is a good answer.

Almost everybody who’s been successful, it’s difficult actually to say that anybody’s been terribly successful recently in this space, but anybody who’s had even moderate success has something weird going on.

They’re like independently wealthy or they have some cash cow that they’re like milking in order to let them do this essentially economically unproductive activity, or they have like a whole bunch of connections that they’re using.

I have been helped in my thinking on this recently by reading uh Nadia Eggbal’s new book Making in Public, which analyzes the economics of open source production, and there are some connections between the the challenges of trying to provision tools for thought, work and also the challenges of trying to provision work on. Open source. They both seem from an outside view to be kind of economically unproductive activities.

Nadia’s insight that really helped me and that seems to have some analogs and tools for thought is that it makes sense to separate the way that we think about the economic model of consumption of open source from the economic model of production of open source. So when one consumes open source software, that is a non-excludable resource, so the code is just, you know, it’s available online, you can’t readily charge tolls for it. Uh, it’s also non-rival risk. So you downloading the code doesn’t really like make it more costly for me downloading the code. There’s very near zero marginal costs.

The analog and tools for thought is once I like publish that paper. On the great idea I had in Muse. This is a non-excludable resource out there, and it’s also mostly non-rivals, you know, the 100th person consuming that paper and consuming those ideas. It doesn’t really cost any different from the 100th person.

But the production looks pretty different. It’s a it’s a small country of people. It’s perhaps excludable, and there are some rivals elements in open source, for instance, Nadia characterizes it as being about attention. The scarce resource for the open source maintainer is their attention, they’re being bombarded by these like requests and like well-meaning people trying to contribute code and so on and so forth and it’s very draining and this actually makes the resource rival risk because the 1,000th contributor to the repository doesn’t cost 0 additionally relative to the 100th contributor. And so one way to think about this that she suggests for open source that I think applies a bit for tools for thought and relates sort of the strategy that I’m pursuing now is we should think about funding production. Than funding consumption.

Normally with media goods, we think about funding consumption. Like you go to the store and you buy the shrink wrapped package of software, and see like you’re buying a good, you’re buying an artifact. And when we think about commercializing or monetizing software, likewise, we think about the good or the artifact, or perhaps the services associated with it in the modern world, like I’m going to sell support services if I’m red hat or something, modern models might sell cloud services, but a different way to think about all this is to think about kind of verb instead of noun, funding the process of production rather than funding the The output of the production. This is more common in the arts, somewhat more familiar in the arts. Like if there’s a musician you really like, your contribution to buying their albums or whatever, like it’s probably not earning them very much money, but increasingly it’s a popular thing to like be part of their their fan club or sponsor them or something like this. And when you do that, when you sponsor the musician, it’s not really that you’re like buying a particular song or like buying an output, whatever. It’s more like, I like what you’re doing and I I I want you to keep doing it. I recognize that you need resources to keep doing what you’re doing. And I want you to have those resources. So like here I am funding your process.

And that’s roughly a model that I’m exploring for tools for Though presently, wherein I’m soliciting funders to cover the production of what are typically public goods. So I’m going to sit here and like do this work and think about space repetition systems and the most prominent, the most useful long term results of that is going to be an essay, or even if it’s instantiated in software, and even if that software is proprietary, it’s going to be a set of ideas, interface ideas, which are instantly stealable. And so those are public goods, and it’s probably a lost cause to try to monetize either the essay or the like interface ideas in the software, yeah, file a patent on it, but like that’s not gonna work. And so instead, maybe we can think about supporting this stuff in terms of uh recently I’ve been phrasing it as like funding a grant, like an ongoing grant akin to the way that you would for an academic research lab, which also produces public goods.

00:52:33 - Speaker 2: And it it sounds to me like you’re describing somewhat of a patronage model and you talked about this on a past podcast. in what’s happened with indie games, Steam Early Access and Kickstarter being the two channels there, um, and that that’s maybe a good example in a lot of ways, even though games are so different.

It’s the upfront production is where the cost is. You do have to do it upfront. There’s several years of development by these, by, you know, whatever size team there is. And when people invest in that, yeah, they’re getting some things like access to a community and ability to influence the game and ability to play an early buggy one that probably isn’t very fun. And maybe that feels good for the person or it’s fun, but ultimately it’s more about wanting to support something they want to see exist in the world.

And I see a similar thing happening with the boom and subscription newsletters. We’ll see, you know, whether that’s a bubble that will pop or something sustainable. I I hope closer to the latter, but I think it’s a similar thing, which is that people think this is someone and and probably that personal connection is part of it. When you get a subscription to I don’t know what the New York Times, there’s a maybe a similar thing there you’re saying, I want to fund good journalism. There’s something more powerful, I think about that individual creator, whether it’s the musician, whether it’s the indie game creator, uh, whether it’s the newsletter author where you you feel like you sort of know them as a person and what their work is and you’re really funding them because you believe in them and their worldview resonates and you’re sort of saying, I want, I want more of this in the world.

00:54:00 - Speaker 1: This leads I think, to a significant challenge. It’s comparatively difficult or it seems comparatively difficult to fund teams with this model.

Like a lot of the advantage does seem to be from this personal connection, you know, if you like go to my Patreon page, it’s it’s like it’s personal in a lot of ways. Like I’m writing like, here’s what I’m thinking about. Here’s what I’m anxious about. And you’re also perhaps there because of my presence in other places like you heard me on a podcast or you, you saw me on Twitter or whatever.

If now this is like the team for the something game, it’s more diffuse. And then there’s also simply A matter of funding amounts.

So it seems at this point pretty likely that Patreon is going to be able to raise an amount of money that can basically support me, which is exciting and kind of surprising to me, but very nice.

Assuming that persists, I can continue producing public goods of this kind, but it seems unlikely that it could support a team.

I really don’t see that happening. So I, I don’t quite know what that model is. And one of the things I’ve been thinking about is that if the main useful long term output of this kind of tools for thought research is not The specific software that is created, like we don’t use Ivan Sutherland’s sketchpad anymore, but rather the insights, then maybe it’s actually OK for some or all of software components of these elements to actually be proprietary.

If you’re my patron, maybe what that means is that you’re funding my work, you’re funding my research. So that’s going to include essays, which are, you know, freely available and perhaps software which is used to produce the insights, those core insights that are captured in those essays. And if you’re a patron like that software is also freely available to you.

But otherwise, The software is perhaps proprietary and perhaps generates revenue, which can then support a team.

One of the other problems I have here is, is that I can’t do all the engineering work myself and also do great research. I kind of need long term, I need staff.

00:55:44 - Speaker 3: Yeah, I do think the patronage model is really promising a few comments there.

One is I tend to agree that it’s harder to find large teams with the model. I do suspect that small teams are actually possible.

Another thought is, I think some of the most interesting work in this area leans a lot into community.

So again, to draw a somewhat simple example from the gaming world, often if you support these gaming creators at different levels, you get access to like correspondingly elite Discord channels, which seems like it’s a small thing, but it’s actually a huge human needs, like be a part of community and and to believe in something that is important to you and to participate with your peers. So there’s actually a lot of um kind of community goods that one can provide as an independent creator or as a small team.

Another interesting example there is Pladium Magazine, which is doing really interesting work on political economy. And they have different tiers for supporters and as you become a more substantial supporter, you can participate in things like salons or even interact directly with the team.

Another idea to address the funding a team problem is, I think people don’t like to put money into big mushy pots.

Yeah. Like you think about donating to some huge institution, you like, what’s it going to go to? Is it like going to go to some, I don’t know, like random building or like cutting the lawn? I don’t know, it’s not very exciting. Whereas with an individual creator, like I’m funding, you know, this work on the neonic medium, that’s awesome. And I wonder if you can get a little bit of both by having an institution, but also supporting more targeted funding. So it’s almost like you’re having a two-side marketplace for funding as an institution where these are the 5 projects that we want to potentially do research on and you can back individual projects, and once it’s reached a critical threshold, we’ll go ahead and do it. So if it feels like you have more agency over what your money is supporting.

One other example there is you mentioned the work potentially being proprietary. This is actually well precedented with keyboards of all things, folks, you got to look up this, this. Crazy world of custom keyboards.

00:57:27 - Speaker 2: Oh, it’s so you’re talking about the mechanical keyboard.

00:57:29 - Speaker 3: Yeah, they’re usually mechanical and they do things like, you know, someone says, I’m going to make a keyboard. It’s going to cost you, I don’t know, $500. And if I get 200 orders for them, that’s enough money for me to do a production run in China. So I’ll do it. I mean, people pay 50 $500 for a keyboard, maybe they’ll pay $50 for, you know, a better note taking app or something, right? I think it’s it’s very possible.

00:57:45 - Speaker 1: And and do those people also have patronage or or is is now just the product they’re selling?

00:57:50 - Speaker 3: Yeah, I think it’s kind of both. So you’re. Yes, you’re covering the production costs, but also there’s this huge creative and entrepreneurial element where you have to ask to pull together the keyboard, like find the right key caps and get the right producer in China and arrange it all right. And so you’re also paying for that. It’s kind of an entrepreneurial activity in a way.

00:58:04 - Speaker 1: And do they like open source the like CAD files and stuff? Is there like a public goods component at all in that world?

00:58:10 - Speaker 3: Um, that’s a good question. I’m not sure.

00:58:12 - Speaker 2: Yeah, I’ll link both the mechanical keyboard and subreddit, which is just fun to scroll through for the great photos.

Uh, but also kind of relative to the what people are willing to spend side of it.

There’s an article by Kevin Lainoff, if, if I’m not mistaken, that is basically an exercise in what could you price this out and, and they actually end up with a price that’s over 1000 or something like that. And again, it relates to people who are really, really into a very specific hobby. They like the fact that it’s this one time run. It feels very authentic. It’s just someone in their community, you know, it’s it’s not a ongoing commercial entity. It’s just a person in the community that has an idea for a unique thing to make that they want to share with everyone else. To your point, they’re willing to put down a lot of money to do that. And yeah, I think there’s a, it’s a very different kind of calculation when you think I’m supporting something I believe in. With the community I want to be a part of is a different, very different kind of transaction than I’m purchasing a product, I’m going to, you know, shop on whatever comparison sites, to get the lowest price I can. I’ll never ever meet or even have any idea who was. Behind making this product in the first place is very transactional, mechanical, just give me the cheapest, simplest thing that will solve my problems so I can move on with my life.

00:59:28 - Speaker 1: Another related problem seems to be the arrivals to working on this kind of work have gotten more appealing.

And this is kind of a different angle on your point about Instagram.

When you look at PARC, it’s not so much that people there got paid a huge amount, actually, that the total budget for the projects that produce personal computing was not that large, but relative to the rivals, uh, relative to the universities that essentially would have been the employers for that staff, PARC was offering more than anybody. And so they were able to assemble basically all the really great computer scientists that existed uh in that period. It’s a bit of Overstatement, but they got a huge portion of them. Whereas now this work is competing with, you know, fairly lucrative jobs in the tech industry and in more than one way. So like, yes, it’s true if you’re young and you, you know, go work for Instagram, you’ll maybe make a quarter million dollars a year or more, but also in this kind of uncapped upside way. So if you are the kind of person who’s entrepreneurial and agenttic enough to pursue this kind of original technological work, you could probably be working on a startup and you could be getting uncapped upside. Whereas it seems fairly difficult to uh pursue a course of action that could yield uncapped upside in the tools for thought space nominally speaking. Uh, because of the kind of public goods elements, like the, the hardest thing that you do will be to come up with the elements that is novel, unique, and immediately stealable. And like, yes, you can start a startup around the, you know, the, the kind of the software around that, but uh you feel like you’ve shot yourself in the foot a little bit.

01:00:56 - Speaker 3: I certainly think there’s a lot of truth to that. I just want to jump back to the absolute amounts and comment that I think that the amount of money you need to find really interesting projects in this space is in the scheme of things very.

Small. It’s gonna be a fair amount to any individual person or any normal individual person, but just the absolute amount in terms of what we spend on random funded startups or what our various levels of government spend is just quite small. That, that makes me optimistic that there’s a way to make this work.

Um, on the opportunity cost thing, I think that cuts both ways. Like, yes, it’s the case that people can go to the Googles and the Facebooks and earn a lot of money, but we’ve also seen with the lab that people really value doing this rewarding, interesting, unique work and it’s accessible to a broader set of people.

So like, is remote because we have a broader hiring funnel and so on. I also think there’s a time and a dynamic element here where you don’t need to spend your whole career doing research.

Actually, one of the ideas behind the lab, use the spin out and kind of the whole group there is that we expect people to rotate over time. So it’s not just you’re not just a career researcher or a queer entrepreneur, you actually get a lot of dynamism from going back and forth. You get different benefits in each world and then actually going all the way back to our conversation about full-time toolmakers versus practitioners. you help solve that problem. You spend maybe 4 or 8 years in one domain and then you switch over and you get that hybridization.

01:02:10 - Speaker 2: I’ll fill in that I think the funding it through commercial products. We said the paying for the for the result rather than the process.

01:02:19 - Speaker 1: Sure, yeah, yeah, kind of paying for the output of the artifact rather than paying for the production of it. Yeah.

01:02:24 - Speaker 2: Obviously we’re pursuing the paying for the artifact path with umm that we’re we’re selling this product commercially if you want, kind of, but like it’s subsequent.

01:02:31 - Speaker 1: To the paying for the production element of I and Switch.

01:02:36 - Speaker 2: That’s right, yeah. Um, well, I almost wonder if there’s a progression there a little bit, which is ink and Switch was very much just a small amount of money, grant money that was people that want, you know, some people that wanted to see this thing, see a certain kind of research done in the world and very much public goods, we published everything as we open sourced as much as we could. That was the whole point of that.

And then the spin out commercial entity now we’re in a state where probably we’re close. to that kind of patronage Kickstarter level, which is, you know, I think a lot of the people that purchase the product, now they’re thinking it’s less about does the exact feature set that exists today, you know, how does is that exactly what I want or is that that, you know, worth the price and more that they’re thinking, I believe this team over the next period of time that my subscription covers is going to make great things and it’s going to make this product even better into something that fits into my workflow into my life, enhances things for me, enhances things for others.

And you can imagine fast forwarding a few years when the product is much more complete, uh, that at that point maybe it does come more transactional.

No one cares about funding the the team or the long term thing, it’s just more about now it’s a good product, it’s very full featured and has been developed over a long period. Time and so they’re going to spend money that the price they pay is, is much more of a transaction to just get this thing that does solve an immediate problem for them and they’re not worried about the future or the team behind it or the community element. So you can see that as sort of a three stage progression. Uh, at least I hope or imagine that could happen here and I could also imagine it happening with, with other things including something like the pneumonic medium or other uh research work that I’ve seen in process, but the making that transition step to step to step that I think is another place where Mark and I talked about that in our HCI episode that that I think is another weak point in the the field if we can if we can call it that.

01:04:25 - Speaker 1: Totally. I think that. Progression is, is likely to happen in my work. And one of the things that seems to create the weak points and is likely to create them in my work is that it’s not always the same people who want to be working on these, these different things. That’s both a weakness and the strength. Maybe I don’t feel like doing the production maintenance of a commercial piece of software like that that’s just not what gives me joy to today.

01:04:55 - Speaker 2: But there’s like a lot of people who really like just like churning through task lists, and they love like the feeling of like, check, check, check, check, and Those people will be like really well suited to be on the engineering team for, you know, long term I’ll note you even reveal your proclivities by saying turning through taskless, because some someone that has more of the mindset of wanting to keep a real existing thing running and serving people’s needs, they would say, I don’t want to just think big floaty thoughts about something that could exist in the future. I want to deliver real value today by building production software and shipping it to customers, right?

01:05:17 - Speaker 1: For sure. And and so if you’re someone who values the big floaty thoughts, and you want this, this big floaty thought that you’ve kind of tethered to earth to actually live long term, you got to find somebody who enjoys the other stuff to come and pick it up and take control. That seems like a weak point in the process. Reminds me of tech transfer in universities, tech transfer.

01:05:36 - Speaker 2: I don’t know if I know that concept.

01:05:38 - Speaker 1: It’s how many of the top tier research universities actually get most of their funding these days. Uh, my alma mater, the plurality of its funding comes from this.

I think it’s true of Stanford too, but essentially, uh, the model is that professors are paid for mostly by public grants, and IH NSF, things like that in the sciences anyway, and they produce mostly public goods. They publish papers and so on, but also sometimes they They file patents on those things when they are patentable things or they do spin off startups or their advisors to startups or something like that and the university gets a cut.

Uh, and so a great deal of Stanford’s wealth, for instance, comes from the patents which underlies gene tech for recombinant DNA and uh Google as well.

01:06:18 - Speaker 2: Another piece of the funding spectrum. Is corporate R&D labs, which Xerox Park famously was Bell Labs and the one I often use as as inspiration. Now that was quite unusual in that it was a corporate R&D lab for the largest monopoly business, I think that is certainly ever been in information technology. But Andy, you had your, your at least brief run at doing uh on the corporate R&D side. How do you think that fits into this?

01:06:43 - Speaker 1: It’s really challenging. I spent a lot of time studying the players in this space and mostly came away with a pretty bleak perspective.

My own work at Khan Academy was kind of weird because Khan Academy is a nonprofit. So that the motivations are somewhat different there.

But even just looking at the for-profit space, it’s difficult for me to get excited about corporate research labs as an institutional model, speaking to some of the people involved in setting up and tearing down Microsoft research, that really was not terribly successful for the company and indeed was like successful in these other ways of creating a sink that could keep talent from Going and starting startups in Seattle, for instance, is like actually a useful and positive effect that made it worth funding for, you know, Bell Labs had it was this kind of this chaff to dodge antitrust litigation seems to be the prominent reason it got so much funding. It did actually generate a ton of value for the parent company.

And Park, you know, I mean, there’s this fumbling the future phrase that goes around. The fun thing is that Park actually was profitable for Xerox, just barely because of laser printers, not because of personal computers.

Yeah, Apple’s corporate research uh was really not successful. Um, I’ve been having difficulty learning as as much as I would like to about Dolby. Uh, which does actually seem to be pretty successful. But another fairly successful example is Pixar. And one thing that I think really distinguishes Pixar’s corporate research is that there’s cutting edge graphics research that goes on there, but it it is very much in service of these creative films. They are huge money generators.

01:08:08 - Speaker 2: Well, maybe that creates the connection and is always one of the challenges is the disconnect between the uh the mad scientists off thinking the big thoughts and the real world problems that those can be applied to and Yeah, having the the graphics researchers need to turn around and produce an algorithm or even work code for the new movie that’s coming out on a particular deadline and there’s a lot of money at stake for maybe that creates some realness or or as a way to, as you said, tether the the thought balloon to the earth a little bit.

01:08:38 - Speaker 1: One of the challenges that seems to exist for all these labs that Pixar manages to avoid the mechanism you just described and also existed at Khan Academy, which is a nonprofit so it had, you know.

Interestingly different funding issues is just this, um this challenge of tech transition.

So even the lab comes up with an idea, we came up with the laser printer, we came up with a personal computer, we have the Alto, we have the star, you know, whatever. And like, we want to get it out in the world and have it be a major corporate strategic priority. This is often the point where things fall over because if if the research really is cutting edge, often it will mean at the highest level shifting the company’s strategic objectives to really Capitalize on that technology. It’s difficult to find organizations that have done that consistently. Pixar makes use of their research, but I think in general, capitalizing on really great like water rendering technology or whatever doesn’t require shifting the highest level corporate strategy.

01:09:25 - Speaker 3: Yeah, Ben Reinhardt has done some really interesting research on this topic in the context of DARPA. I highly recommend checking out his work and one of the insights from the world of DARPA and military.

Or dual use technology transfer is that it’s extremely dependent on thick social networks that are formed largely because of DARPA’s work, and this I think points to another gap or opportunity, which is the kind of institutional and community side, where if you have a place for people to congregate and to gather and to form social connections, it can really fertilize the creative work of the industry.

And we saw this a little bit with ink and Switch, you know, we had a very modest community effort.

It was Slack channel. We had some articles published, we would tweet some things, but even just that got all kinds of amazing people to come out of the woodwork and say, you know, I’m working on this too, or this idea or what do you think about this or how can I contribute? And I can only imagine if someone invested a lot more in something like that, you’d see correspondingly more results.

01:10:17 - Speaker 1: I’d love to make that happen. It was briefly a kind of a high goal for the year until I realized that I couldn’t really achieve the other things that seemed important if I pursued that. So one thing I observed is that these kind of community efforts do seem to be like the result of times of plenty. DARPA, uh, especially in its heady days with just like excessive funding, is able to devote resources to this in a way that seems difficult.

01:10:39 - Speaker 3: But I think DARPA is also an interesting example of how, again, the absolute amount needed is not that big. Like the number of people at the very core of DARPA is quite small.

01:10:47 - Speaker 1: Yeah, maybe I’m just thinking too small here.

01:10:49 - Speaker 2: The time of plenty point, I think seems right, which is what we’re talking about is investing in the future.

Our particular niche and interest is this, this tools for thought. Um, but in general, being willing to invest in the longer term, 5 years out, 10 years out, and more.

There’s a few things that drive that.

There’s military is just a huge one because that’s just always an existential question for a nation. It’s also things like and of course, the space race with a lot of the stuff that led to the internet and a lot of those technologies was at its core connected to a sort of a military dominance or perception of that uh between the world superpowers at the time.

Or you have something like Bell Labs, which, as you said, you know, this antitrust thing, this, this huge monopoly with so much money to spend and so sort of in their interest and and government funding generally, the larger pool to draw from potentially and a willingness for longer time horizons.

And corporate R&D labs are always tough because they’re always when times get a little tough and there’s always the up and down, you’re going to look a little shorter term, of course, the first thing to go is the dreamers that are that are looking further out. And that’s fair enough. I don’t, I don’t think that’s a very pragmatic and reasonable choice, but then that that comes back to well, is that a is that a way to fund our future and at least the evidence seems to be despite some a few cases, a few exceptional cases like PARC, uh, that that’s not really very. sustainable or repeatable.

01:12:14 - Speaker 1: It’s interesting to look at HHMI’s funding practices versus the NIH’s funding practices of targeting specific researchers and trying to give them consistent funding over longer periods of time. What I feel differently about spending a lot of time right now on like community organizing, if I had something like an endowment. Um, I probably would, and it’s weird because like I’m not, I’m not really bleeding. I am in the red, but it’s, it’s not so much that I don’t want to do it because it feels like ultra ultra urgent to resolve that. It’s more that there’s a feeling of not being on steady ground. Yeah.

01:12:49 - Speaker 3: I think the future is still, I’ve written here, we’ve talked a lot about structural issues like funding and things like that, but a huge element is just the individual will and passion to see something change in the space. And I think Andy is a great example of that. There’s all kinds of currents that make that kind of work very challenging, but he’s succeeded because of his will and talent and persistence. I would invite more people to just try to take that on.

01:13:14 - Speaker 1: It’s very kind. Thank you, Mark.

01:13:15 - Speaker 2: B like Andy, I like that. Well, if any of our listeners out there have feedback, feel free to reach out to us at @museapphq on Twitter or hello at museapp.com by email. We always like to hear your reactions to anything we’ve talked about and we’d like to hear your ideas for future episodes. Andy, thanks so much for joining us today and talking about these areas of mutual interest. Thanks y’all.

01:13:37 - Speaker 1: This was a really fun conversation. Thanks, Andy.