Modern Wisdom - #080 - Stephen Wolfram - The At Home CEO

Episode Date: June 13, 2019

Stephen Wolfram is the founder and CEO of the software company Wolfram Research. What happens when you track every email, every keystroke, every mouse movement and every project for 30 years? Today we find out the productivity strategies, personal infrastructure and tracking analytics from the man behind Wolfram Language and Wolfram Alpha - the answer engine which powers Siri & Alexa. Extra Stuff: Wolfram Alpha - https://www.wolframalpha.com/ Follow Stephen on Twitter - https://twitter.com/stephen_wolfram Seeking The Productive Life - https://blog.stephenwolfram.com/2019/02/seeking-the-productive-life-some-details-of-my-personal-infrastructure/ Stephen's Personal Analytics - https://blog.stephenwolfram.com/2012/03/the-personal-analytics-of-my-life/ Check out everything I recommend from books to products and help support the podcast at no extra cost to you by shopping through this link - https://www.amazon.co.uk/shop/modernwisdom - Get in touch. Join the discussion with me and other like minded listeners in the episode comments on the MW YouTube Channel or message me... Instagram: https://www.instagram.com/chriswillx Twitter: https://www.twitter.com/chriswillx YouTube: https://www.youtube.com/ModernWisdomPodcast Email: https://www.chriswillx.com/contact Learn more about your ad choices. Visit megaphone.fm/adchoices

Hello friends, welcome back to the Modern Wisdom Podcast. My guest today is Stephen Wolfram. Stephen is the founder and CEO of the software company Wolfram Research. He is the mind behind Wolfram Mathematica and the Wolfram Alpha Answer Engine. This might sound like hyponur'd speak that you don't ever interact with, but Wolfram Alpha actually forms the basis for the answer engine behind Siri and Alexa. So his work is probably a lot closer to your life than you give it credit for. Now, just as interesting as what Steven does is how he does it.

He's tracked every email that he sent over the last 30 years, also tracked every mouse movement, every key stroke and has recorded all of these down using computer software that his company has built himself. His approach to personal productivity and analytics is probably without match on the planet and I'm so excited to get to present this fascinating insight into the life of an incredibly influential figure. Hopefully you'll enjoy it as much as I did. There is some cool experiments that you can do yourself on the Wolfram Alpha website. That will be linked in the show notes below. If you enjoyed this episode, please share it with a friend. It makes me incredibly happy. But for now, please welcome the very wise Stephen Wolfen.

Ladies and gentlemen, welcome back. I'm joined today by Stephen Wolfram. Stephen, welcome the show. Thank you. I am particularly excited to speak to you today. One of your blog posts that was released earlier this year seeking the productive life was shared around in a number of different group chats. And when that happens, when it appears in a few different spheres of awareness, I think it's usually a pretty good idea that it's going to be something interesting. So I wanted to talk to you today about your approach to productivity and personal analytics before we actually get into what it is that you do. The work you do is is interesting, but the way that you do it is almost as fascinating to me, which is okay.

I like to think it's interesting. I've been doing it for decades, so it better be interesting, or I'm should be embarrassed, but yes, the main thing is that I like to do the things I like to do and I like to not be distracted by things I don't need to be distracted by. And so I tend to build all these systems to try to automate as much as possible, to try to be as concentrated as I can and actually doing the work I want to do. And so I would say the number one tool, which is not for everybody that I've built to get. My work done is I built a company over the last 32 years that has 800 people in it, then

it's sort of intended to be a machine for taking ideas that I have and turning them into real things. And so that, but one of the things that is probably more sort of generalizable is one of the ways that is probably more generalizable is one of the ways that I tend to work. As an, you know, in any given day, I'm trying to create things and turn out have ideas and I'm trying to turn them into real things. And I tend to follow the sort of approach

of spending a lot of my time doing what I tend to call thinking in public, which means, you know, you're working with a team of people and some people would imagine that, you know, when you're going to go figure out what to do, you go off on your own, you hide away, you figure out what to do. There's not what I tend to do. What I tend to do is it's like I'm doing some meeting with the people who are involved, and that's the actual time when we figure out what we're going to do. It's not something which is happening sort of behind the scenes. And I found that, you know, I have been a remote CEO for 29 years now,

which is another bizarre feature. So most of my, you know, interaction with people is screen sharing plus audio. I usually avoid video. So like the experience we're having right now is unusual for me. I'm usually a, you know, I've got audio, I'm, you know, sharing the thing that we're both talking about, but I'm not seeing the people. And then, you know, what I like to do is to try and, you know, we're trying to figure something out like today. There were several different meetings

that I had about different kinds of things and we figured out some things. And that's always, you know, it's very satisfying and you know, one has to have a, you know, what I'm typically doing is I'm typing into one of our notebook documents and trying to, you know, set out what it is we figured out and so on and then notes get taken and so on and then it gets turned into something or something real can happen from it.

I understand. I like that. I also tend to, maybe it's an eccentricity, but it's turned out to be pretty interesting. We've publicly live streamed a lot of these internal meetings that we've had. So in the last year, we've probably live streamed 300 hours of these things. And that's a fascinating dynamic because I originally started doing it just because I thought these meetings were interesting. They range from very intellectual stuff to very gritty stuff about software engineering. I just think these are interesting and why not have other people be able to share the fun. But it's turned out we've ended up with people join the live chat and so on. And we get a lot of sophisticated users of our products and a lot of other people who are experts

in various kinds of things. And we get real-time feedback, which is pretty interesting. So you've crowd-sourcing some solutions almost? Yeah, yeah, yeah. I mean, there are things that have actually gone into our products that were suggested by people in the live chat. And it's a very fast process. I mean, we could go and we could say, you know, okay, you know, well, you know, here's what we're going to do. And a week later, people could respond to it.

But actually, this is like people are hearing what's going on. Really? Time. Time-thing things. And it's pretty interesting. And I think, you know, to me, being able to do those kinds of figuring things out live and in public, it makes, perhaps, egotistically, the things feel a little bit more meaningful to me. I understand.

You take a process of figuring something out and you put a lot of effort into it. It's kind of fun if that effort is actually archived. And I haven't watched any of them. I made them, but I know other people have. And I think it's for me, part of the things I figured out over the last few decades about, particularly about software design and language design and so on. And this is my way of kind of helping educate about those things is, you know, you can actually see this happen and you can see what the process is. There's a term that's one of the guys behind the Modern Wisdom project George uses when he talks about evergreen content like that. So this is a discussion that I'm having with you. I've always said I would do this podcast even

if nobody tuned in because I want to have these discussions with interesting people However George describes it as you at scale and I think that that's a nice way to describe What it is that you're doing because that meeting would be going on anyway the only difference is the only difference is the fact that now other people get to benefit one of the things that you touched on right the beginning there some of the the listeners may be One of the things that you touched on right at the beginning there, some of the listeners may be taken away on the whirlwind that is Wolfram and what the company does. But one of the things you touched on that I thought was really interesting was that you are a remote CEO, which means that you do the vast majority of your work at home. I think you've cited that you're in the office for hours per year, as opposed to days or weeks per year. But contrasted with that, you have this

quite sort of crowdsourced, very interactive working style. I think when people think about the at home CEO, if you were to say that, you kind of think of this Tony Stark kind of down in the dungeon on his own tinkering and working away, especially when you then couple it with the fact that a lot of what your company does in as much as me as a good avatar for the layperson can understand is pretty hard core mathematics and programming. You think down in the dungeon working on their own sort of and then every so often revealing something to the rest of the team. Is this a quirk of your personality or is this simply how you've found to be the most optimal way to get stuff done? Yeah, I mean, I've done different things at different times in my life. This is a really good way to get stuff done, although it probably depends on my personality that it works. I mean, so for example, when I was first, well, after I started the company, for about

10 years, I kind of put myself on sort of pseudo-sabatical working on a basic science project. And that project I did in a completely reclusive mode. I wasn't talking to anybody. I was just, it was me, I happened to be in a high up room, rather than down in the basement. But other than that, it was pretty much caged. And I'm working on my own. And I was, you know, my schedule was sort of shifted around.

So I was working typically from, I would do stuff with the company in the afternoon, and then I would go off and start working on my basic science project, sort of, I'd go off and do things I, during the time when I did the basic science project, I had some kids and, you know, I was doing things with the kids for a while, and then I would go and starting at like eight or nine in the evening, work until six in the morning, doing basic science, basically on my own. And it was a, you know, that was a, definitely a tenacity testing process to go do that for a decade, basically.

And I got it finished. I produced this book called New Kind of Science, which has had all kinds of consequences in the world. But it was definitely a pretty intense way to work. So I changed the way I worked after that and decided that I would try doing this much more, you know, with my internal group kind of this thinking in public type mode. And it's great. Now, it depends on the fact that you have people that you're working with where there's sort of, I don't know whether it's good chemistry, but where people kind of know what to expect. And, you know, it's probably, it's probably, I don't know, one could probably figure it out. I should know the analytics of this from my live streams, but I'm guessing there's probably 150 people

who sort of make an appearance in some live stream or another. That's kind of the, out of maybe 800 people in the company. So that's probably the, you know, that's the set of people where they kind of are in the right flow to be able to be involved in these kinds of live stream type meetings. It's interesting that you say that they need to know what to expect from you and kind of you do vice versa. If you were, I think a lot of people have just come off a podcast with Robert Green and we're talking about inter office politics and people having to wear masks and all sorts of things like that.

Most people's jobs are a combination of the solar warrior perhaps, cubicle work, typical knowledge work, emails backwards and forwards, and then some meetings, some collaborative meetings. And for the meetings, a lot of people have to play the role of whatever it is, the boss, the subordinate, the this, the that, the the other. I imagine if you were having to play a role to 150 people over a live stream for hours and hours every day, it would be exhausting. So I completely understand what you mean that you're able to have sort of brain to mouth to screen with as little friction as possible. And I think that actually probably quite nicely

leads us on to your approach to productivity overall because having done as sophisticated an assessment as I can of the most sophisticated approach to productivity that I've seen. Lack of friction kind of appears to be one of the things that's a meta narrative about it. So would you be able to just explain your approach to your personal infrastructure? Yeah, well, okay. But I mean, just to say one more thing about what you were just referring to, because I think it's interesting.

I mean, the fact is, my company is sort of constructed to be a direct communication kind of place. So, you know, we've, another feature that makes the remote CEOing thing less weird or even more weird is that, you know, I set this example nearly 30 years ago of being a remote CEO, so that means that the majority of people who work at my company work remotely. I was at a home as well, or in a room, or a office, So whatever. All kinds of random places. I don't even know where they are. I mean occasionally there'll be some interesting things somebody will say well there's a volcano erupting. So the next to a shark or something like that. Yeah right and it's it's some and then

you find out where they are which I don't typically pay that much attention to. Yeah and you know but I think that's a the fact that one can develop a company culture where people are able to actually say what they think. On these live streams, they're very unvarnished. People will be saying, sometimes people get quite passionate about things. They'll attack me and tell me I'm a total idiot and so on. And it's it's some, but this is the way that I like to work because I found, you know, it turns out you can have the whole sort of posturing of that often happens in many kinds of business settings, but it's like a big waste of time.

And so long as the, yeah, right. I mean, so so long as you can handle directness directness is much more efficient. And also it helps people I think from a management point of view, you know, knowing where they stand, I mean, one thing is the question of what projects I do, because that's sort of the starting point of how one is productive. I mean, I've been lucky enough that I've basically been able to build a technology stack for three decades. And much of what I do is something that will fit into that technology stack. There are things that, you know, fortunately, it's a broad range of things, it's a broad range of kinds of different intellectual areas and so on.

But when I imagine, oh, I'll do something, you know, completely different. I'll, you know, write a play or something. Okay, if I did that, I have no idea, you know, that would be a big... Need a new system. No idea what to do with it. So, you know, the first step is kind of having a, you know, there's a set of things I like to do and I've sort of built these matrices into which to put the individual things that I try to do. Like, you know, I try and build these sort of computational intelligence systems where I got this big kind of thing to put that into. I like doing

kind of historical writing about historical biography and things like that. I have another kind of matrix into which I can put things like that. And I try to avoid doing things which are which don't fit into any matrix I have because I know that the kind of cost of getting something out if it isn't in some matrix is really high. So that's one step. In terms of daily life, I tend to be a very schedule that has very, it's very kind of structured, and I've built all these systems for prioritizing. In a sense, I cheat because I have a whole company that's dealing with things like prioritizing what I do. So this is not, but we've had to build these systems for, I would say, the number one

matter system is, I have all these ideas all the time, like I've had several ideas today, which will turn into, which have the potential to turn into lots of work. And the thing I like to do is to have ideas that actually turn into something real. I find it very frustrating just have ideas and not have anything happen with them. So it's a question of how do you build a system where you can make concrete those ideas

and then actually have the right project management and the right kind of flows to make that happen. But in terms of my own, like I like to work, the work I do is what I choose to do. I like to be doing that as much as I can. I also like to get exercise every day. If I'm set up a treadmill so that I can have a type of my computer while I'm walking on the treadmill, and that works fine.

I also typically do meetings. I usually try to get meetings that I think are going to be a bit frustrating, scheduled for the time when I'm on the treadmill. Does anyone know? Is anyone listening? Yes, I mean, he like plotting away. And they think that's a signal that Stephen thought

this was going to be a shit meeting. If there's anyone, if anyone of Stephen's executives are listening and you hear him plotting away on the thing, that's because he thought he was going to be a boring meeting. Well, it's not so much boring. It's usually frustrating. It's usually like something that's going to need to, you need to get a little bit of energy out. Yeah, yeah, right, because it's like, like, you know, why aren't we managing to do this? What's going on, et cetera, et cetera, et cetera, and then it's like, okay, I can increase by half a mile an hour. That's a much better way to manage my frustration that it could be to be prowling at people.

Fantastic. I absolutely love it. I think if you were a layperson and you were to think, well, I'm the sort of person who likes to work. I want to maximize my ability to do the work that I like to do. Not only does it feel like what I'm going to maximize my ability to do the work that I like to do. Not only does it feel like what I'm going to guess is close to your highest calling in life, but also something that's enjoyable as well. You would make it as easy as possible to do as much of that as possible, as high of a velocity as possible with as little waste. And reading through the blog post, which will be linked in the show notes below for the listeners who want to check it out.

And I suggest that you do because it's a real monster, but it really is. The particular setup that you have, which is, like you say, these matrices, as you've described them, which are kind of these systems, I guess, people would, in more sort of common terminology, where you have a desk which moves from sitting to standing

very easily at the touch of a button, you've optimized the ergonomics. I think I'm right in saying that you're left-handed and you've realized that you can, you use a older-style roller mouse, right, rather than a track-out. Right, usually when I'm at my desk, yes, because I've found that that's somewhat fast. I mean, you know, the point is because I record all this personal

analytics about myself, most of it, you know, for the last 30 years, I've recorded tons of things like, well, obviously, all the emails I send and receive. And then probably for the last 20 years, I think I've recorded every keystroke I type. And I record kind of an image of the screen that I've heard that I've been in front of me and things like this. And most of the time, I don't look at any of this. Most of the time, it just goes... It appears in a blog post at the start of the year. Yeah, yeah, right. And occasionally I'll look at it, but something like,

is it faster for me to use a left-handed mouse or a trackpad? I can answer that question, because just go look at the data, and it takes me, you know, probably 15 minutes to go answer that question because I've got different computers with different setups and I just can see how far I can compare the two. Yeah, I think I'm right in saying that you've done a third of a million emails since 1989 and more than a hundred million piece strokes. No, no, no, much more than that. I've done, let's see, I get a thing that shows me every month, so I've sent 850,000 emails. This blog post from 2012. Yes, right, right. Yes, yes, yes. You've really stepped it up. You've done half a million in the last in the last. Yes, yes, that's right. No, in fact, the number of emails that I've

Yes, that's right. Yeah, it's, no, in fact, the number of emails that I've, that I receive has gone up, the number that I send has gone up. Yeah. It's, yeah, I mean, that's another, you know, another feature of at least my life is, you need to learn to make decisions quickly. Otherwise, you just go totally bonkers. So, you know, I'm getting hundreds of emails every day.

And, you know, it's great, well, one of them is spam. It's pretty rare that it's spam spam because that's just a quick delete but you know most of the time their emails that I sort of should get in some sense and a lot of the time their things which are some kind of decision like do we do this do we do that whatever and you know one of the things I've tried to train myself to do is just make these decisions quickly and it it, you know, experience helps a lot. I mean, one of the challenges in the business that I'm in, so to speak, is what do you delegate? This is what you just do yourself.

And, you know, there's things where I just know pretty much what to do. It's going to take me 10 minutes to do it. I could delegate it, but it's going to take somebody a week to try and figure out what to do. And there's a chance that they won't do the right thing. And so what I tend to do, my solution to this is that I'll tend to do this kind of thinking in public way of doing it. I'll say, yes, I'll do this, but you're going to watch what I do. And so that way you learn how to do it for the next time. And that works pretty well. And it's something, also for me,

in running a software company or something, you might think that the CEO of a software company of our size would never like look at the underlying server code or whatever else. But the fact is, from time to time, it's just easier for me to just look at it. And it also, you know, the dynamic with the team, for example, tends to be, you know, you might think, oh my gosh, that's totally traumatic to have the CEO go look at some thing that some

junior person was supposed to work on. And, you know, and I suppose sometimes it is traumatic if something really stupid was done, but that's the rare case. It's usually it was actually hard. something really stupid was done, but that's the rare case. It's usually it was actually hard, and the main thing that is communicated is the CEO cares about what this junior person does, and isn't totally clueless about what's involved in doing it, and that's a positive message, so to speak. And I think this theory that you should, I mean, I tend to delegate whatever I can delegate. That's one of my principles of leading a productive life to delegate whatever I can delegate. That's one of my sort of principles of leading a productive life is delegate what I can delegate, but don't delegate too much. And there are cases where one sort of instinctively

delegates things. I mean, over the last decade, I think I've learned more about this. There are cases where it's like, oh, this is a trivial thing. This is something about some random network issue, whatever, let me just delegate that. And turns out that's just a bad idea because given the experience I have and so on,

I can solve it in 10 minutes. Are there any metrics that you use for that? Or is it just experience? You said you've tested it recently? Yeah, it's just experience. And I think one of the things that's complicated is because I'd been in the software business and so on for a disgusting number of decades now, Yeah, it's just experience and I think you know one of the things that's complicated is because you know I've been in like the software business and so on for a disgusting number of decades now

You know, I just know a lot of stuff and it's it's some you know And it's and I've gotten better at problem solving and debugging things and so on over the years and there's not really a substitute for an extra few decades of Debugging experience I couldn't I couldn't agree more So to draw a little bit of an analogy between two industries that I probably guessed you never thought would be analogous, I run club nights. So I'm a club promoter, running night clubs, late night industry, and stuff like that. One of the things that's interesting myself

and my business partner are the two MDs of that company, and there's a couple of other partners. But there isn't a person in that company who hasn't started out as a flyer boy at the bottom. And it means that I understand the craft of every single layer all the way up. And because the company is inherently quite flat, even now 800 members of staff for us

a lot of them part-time and a lot of them a lot less technical than yours. But because it's very flat and because our ascension through it required us to learn every step of the way and then model what we did and then distill that back down to the guys that are below us. If push comes to shove and I get asked a question about pretty much anything, the likely it is that I've either got a similar experience or the very experience that that person's talking about. And I think to any business owners or entrepreneurs in waiting for a listening, I think earning your craft and getting the bread and

butter of your actual business understood to a high fidelity is a skill that's super, super useful. And when you think about CEO, you think about this, especially remote CEO, if you're not the guy that's in the basement that's working in Tinkering, you're the guy that rocks up in the boardroom like on his private helicopter once every whatever for like the AGM, like picks up his like picks up his dividend and then goes back to the seashells or something like that. I don't think either of, there's not much romance in that person. It's cool. It's cool to have a CEO, I think, personally, to have one that gets stuck in like yourself. Right. I mean, you know, my principal about companies, I've told this to

many entrepreneurs is, you know, on day one, the CEO has to do everything. And gradually you understand more and more of what the company is doing, and then you can gradually hire people to whom you can delegate those things. But I know in the history of my company, everything, every area that I didn't really understand didn't get done very well. And that's partly, it's for two reasons. One, because I wasn't there, I think it's partly a question of how the motivation of people, it's like, oh, the CEO doesn't care about this, we're not going to put so much effort into

it, and it's partly just it's harder for me to kind of assess it and clean it up and so on. So, I think it's a really, it's a very good principle that one should understand every aspect of, I mean, I have a pretty complicated company, but I try and understand every aspect of what we do, and I also know very well that if there's some part I don't understand, that's the part that's going to get messed up. I mean, the one thing that happens in a company like mine, which is a tech company, is that I've also been pushing for another thing, which is automate everything I can. So we've got only 800 employees,

but, you know, the productivity that we manage to generate is a vast multiple of what you would expect from that number because over the years, you know, any process that I've seen where I can say, why do we have 20 people working on this for six months? This is something that can be automated and, well, it can take some effort to automate it, but once it's automated, you can just crank it out all the time.

Scanability, right? Yeah, right. That's been the story of what we've built. As a company, the products we built and so on help other people do that too, but the customer number one for these things is ourselves. I also make a point, I build a lot of systems. Sometimes I build them myself. Sometimes I'll prototype them and get other people to finish them. That are for my own personal sort of productivity of doing all these things. I don't know, for example, I have a simple system that monitors the history of my inbox,

how many pending emails do I have, how many unread emails and so on. Now you might think, well, it's just a snapshot you can get by seeing how many emails you have, but for me, it's very useful to see that time flow, to see this week that it's been growing. Oh, then there's a big cliff because I actually did a bunch of work

of processing these things and so on. I mean, that's a big cliff because I actually did a bunch of work, processing these things and so on. I mean, that's a whole other dynamic. I did want to get onto your very special travel clock, but before I get to that, there's one thing that I noticed in the article that you talked about your personal infrastructure. You use a term that says, any flat surface on your desk being a potential stagnation point for accumulating piles of stuff. And that is such a universal truth. And anyone who's listening, like, look, unless you're a neat freak, look at your desk. And if there's sparse, like, flat space, there's stuff on it. Like, I'm looking at mine now. I'm looking around you.

And there's like a set of airports, like a diffuser that I've not used in months, there's like a coaster, like an external hard drive. So your actual physical infrastructure in terms of the way that you have your desk set up is to minimize that as well, right? Yeah, yeah, right. Now, I have, you know, one of my little hacks there is I have a, you know, I have a fan's fieldale wooden desk that I've used for the decades. It's some, but it has these pull-outs that I had put in at the front. So, you know, there's the surface of the desk, which really just has keyboard and, you know, the monitors and things like that. And I admit it has a pile of books on it right now, which it probably shouldn't have. But, well, the problem with it, you know,

this is a problem, I happen to be working on some historical thing I was doing the last couple of days. And the problem with historical, you know, research is it tends to involve physical books. And you kind of have to put them somewhere, they're either on the floor of their own, your desk. So these ones are my desk.

The good news about these books is, once this piece is finished, which it will be in the next day or so, those books will go back in the code. But what I do to try and sort of minimize desk stagnation, so to speak, is I just have these pullouts in the front of the desk. And so, if I need to actually, well, eat my lunch or sign a document or look at a book actually, just pull them out of the front of the desk and do that, but I can't leave them pulled out because then I couldn't tell the way.

Yeah, in the way. Right. And so that kind of forces me to, after I'm done with it, clear it off, push it back in. Absolutely, yeah. And that's a nice, these kind of little hacks over time. I mean, another one that I tend to, which you alluded to, is kind of like, you know, I have a sleep clock that I have that is just a piece of code, well, from language code, that just puts up an interface

that I press a button that says I'm going to sleep now, it starts a count up timer that I can see, and it has the time and the count up timer, and then it also sends a message to, I actually, where does it send a message to? It sends a message to some system, which anyway ends up with a thing that lets my assistant know kind of when I went to sleep, and then if I'm in some weird time zone, ends up with a thing that lets my assistant know

kind of when I went to sleep and then if I'm in some weird time zone, they can kind of predict, oh, we'll be up again in eight hours or so. Or something like that. I mean, so it's just for me to hear that you have, obviously, I'm gonna guess, compared with some of the stuff that you guys do, that piece of code will be like two plus two equals four. Yeah. But the fact that you're able to create That will be that piece of code will be like two plus two equals four

But the fact that you're able to create you think I have this particular productivity problem in my life I also have either the personal capacity or the capacity within my company to fix this problem It must be a little bit like being a kid in a playground sometimes for you. Well, you're like, oh, I like this. It's a small problem that I've encountered. And what have we been talking about so far that when you do come up against things, we model the issue, create a solution, and then just scale. And the problem looks after itself. So I'm going to guess 20 years ago, you will have gone to bed in some weird time zone and missed a Morning meeting.

Yes, yes, and this was the fix. And now, you know, and this fix has been, I haven't had to touch this fix in ages, and that's the, yeah, I mean, that's the, you know, I think this is, look, maybe it's something that I get from being involved in the software industry, is that there are bugs in software, and one of the things if you're a software CEO is when you notice a bug, you report it and you try and get it fixed. I follow the same principle in my personal productivity and life and so on. These things that are obviously kind of goofy and take the time to think about it, see if you can come up with a solution, and then execute it if possible,

build a system that will keep doing that. The same thing, it's like my computer file system, for example. I've gone through, I think, four generations. I think I worked out, maybe it's five, I'd forget. In the last 40 years, I've gone through some number of generations of computer file system. And in each case, it's optimized for the way that I'm working at that time. And people are remarkably bad at organizing their file systems. I've discovered

I even discovered that after I wrote this post. I mean, you know, I should, I should explain that I'd been meaning to write a post about personal productivity, nerdiness for ages, but, but I actually, the reason I wrote that post when I did was that we were finishing some big new version of our, of language product and my job was done basically because, and it was just a matter of squashing the lost bugs and then the thing would get shipped out. And of course, you know, it's supposed to take only a week to do that, but it was taking a lot longer. And I was like, I've got to find myself something else to do.

Right. So I tap out this blog post. And I found that, you know, one of the things that happens, I'm a reasonably fast writer. And I really, I like writing stuff. And it helps me to think things through to actually write it. My team has noticed recently that I have this terrible tendency of converging to always write 13,000 word blog posts. And they actually have plots that show how long it takes and the fact that it tends to

converge to that number. I'm now that I know that. Oh, I got the observation selection bias here. Yeah, yeah. Well, I think 13,001 for all of the future ones. Yeah, no, no, no, no, no, no, they should be shorter., no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, a single writing process, and I'm not going back and revising it and refactoring it and so on. And for me, I hadn't really understood. Maybe five or ten years ago, I started writing a lot of blog post type things. And there's a lot of stuff I think about, and I was talking

earlier about these matrices to put things into. Back in the day, there were things that I was thinking about, but I had no place to kind of, no place to put things into, back in the day, there were things that I was thinking about, but I had no place to put these things. For example, I'm quite interested in history and philosophy and things like that. Now, if I get an idea about one of these things, I'll end up writing some blog posts about it, and people will find these blog posts hopefully interesting or whatever, but there'll be something that will come out of the work that I did. It's not something where I'll just say, well, yes, I'll go do that research and that's all very nice and I enjoy doing the research,

but it feels a lot more... I'll produce anything. Upward. Yeah, I think one of the things again to try and identify some of the larger themes that we're touching on here is that there's a lot of latent potential if you don't have the right system to allow whatever it is that you're doing to emerge. Because if you do have the system that was sufficiently low friction for you to write the blog post, you know, whatever your, for instance, whatever your capture for articles or offer tasks, offer for brain dumps, and then your review system, David Allen's getting things done, or a two-minute rule, or whatever version of the will from language approach I'm going to guess you have.

If you don't have that, there is so much latent potential just sitting behind you, and I think one of the things I'm working very hard on at the moment, and listeners will have heard Tiago Forte's episode, which was a guide to digital productivity, touching on many of the things, albeit a slightly lower degree of sophistication, that you do yourself. One thing I wanted to touch on to before we actually get into the nitty gritty of all from itself, you have a, you've mentioned about your treadmill desk, which I think is fantastic, and everyone needs to have a look at the way that it's set up with the mouse pad and the resting thing. But you also do a outside laptop setup where you're able to actually get some vitamin D and get

out in the air. Absolutely. So one of the things I wanted to ask was firstly, how do you find that effect your productivity? Because I'm going to guess that you'll be tracking that as well. And then secondly, overall, your motivation to work, that must come and go. And that must actually in itself be difficult to track. It's difficult to track where your headspace is at. And are you able to explain to the listeners how being out and about whether that refueles you, whether that actually turns to take away from your work or how that kind of all plays in? Look, this whole question about being instantly on and able to be productive quickly.

Over the years or decades, I've gotten incredibly much better at that. So, for example, after I spent that 10 years being kind of reclusive and so on, I would try to set up meetings, but I wouldn't have them back-to-back and things like this. And I would find out, I get into some meeting about some topic, and it will be like the first 10 minutes I'd have to be telling jokes because my brain wasn't set for the actual topic. And gradually over the years, I taught myself to basically be able to, I have meetings scheduled back to back. And after I finish one, I'm going into the next one, I'm looking at the agenda, and then I'm on, and I'm able to launch into it. Now,

I also know that I have certain memory decay times. So, for example, I know if there's some meeting that has complicated stuff we figured out and we didn't get it finished, I know I have about three days to get the follow on. And then I have, in three days, I'll still have the complete mental state remembered. If it's more than that,

I'm gonna have to go look at the notes and things like this to be able to figure out what was happening. And I think that's, for me, in terms of productivity, the ability to just go into some meeting and immediately be, yes, I'm on, I'm understanding what's going on. Now, in terms of personal motivation, I think by most people's standards, I'm a very even tempered kind of, however, I consider myself a procrastinator. I think others would probably not. But, you know, there'll be things where I would say that I do

rational procrastination to some extent. In the following sense that there are things like, I don't know, they'll be, let I'm going to give a talk somewhere, let's say. And there's a question of how long in advance do I prepare something? And the answer is, I leave it until the absolutely last minute. And why do I do that? Because for example, if I'm giving a talk somewhere and the more I know about the environment in which I'm giving the talk, if I've seen the audience, things like this, the more likely I am to be able to do a relevant job than if I'm sitting two days earlier trying to prepare what I'm doing.

There's forms of procrastination like that that I tend to. Sometimes I will break my own rule and end up preparing something further in advance or another case is product releases. And the question is, you're working very hard to do a product release, and it's like, when do you write the marketing materials for the product release? Now sometimes I like to write them before we even start building the product, because then I know why anybody would be expected to care about this. But often, it's like, you have to wait until the thing is done, basically,

because otherwise, you can to wait until the thing is done, basically. Because otherwise, you can waste a lot of cycles, inventing things which, oh well, actually, it turns out once you've done it, you understood something different and so on. But I think in terms of this personal motivation, look, the number one, the zero-other feature of my personal motivation is the things I do, the things I really like to do. Now, when you build, I do big projects. I do projects that last decades, and it is not the case that every micro-piece inside every project is as fascinating as every other one. But somehow, I managed to average that out. I think different people tend to be at different times in their lives, actually, optimized for different lengths of projects.

Like I find at our company, for example, they're people who are like, optimized for the 15-minute project. And those people, if they're in technical support, for example, it's fantastic. They'll come in, some issue will come in, they'll solve it in 15 minutes, everybody will be happy on they go. And there are other people who are optimized for the three-month project. And if you feed the three-month project person, the 15-minute project, they'll spend the first week preparing the structure that they need to do the project.

And it's all a big disaster. You could have done it half way before lunch. Yeah, yeah, right. So I mean, I think, you know, I, it's one of these things where, you know, you have to be picking projects which are sort of optimized for your, you know, for, I mean, I wouldn't claim that every single thing that I do every single day, like this morning, I was working on some stuff that it was like, yeah, it's kind of, you know, I, it's not, I don't consider it the most thrilling, but yet, you know, the end kind of justifies the effort spent on it. And I find that, you know, almost

anything done sufficiently well is interesting. And, you know, people are always saying, oh, this is such a boring area. I can't, you know, I can't study them, whether it's in science or in technology development. You know, this is just so boring and it's like, no, if you actually try and think about it and you try and really understand what's going on, it will be interesting. And you know, that's also a piece of self-motivation that I use because it's what my experience has been. And you know, sometimes when you do things when you think, oh, this is kind of boring, I'm just going to skate over the top of it.

Then it is boring. But when you actually dive in, and you really understand what's going on, turns out it's actually pretty interesting and pretty intellectually challenging or whatever else. But in terms of in terms of walking outside, you know, I am my wife had been saying for probably 20 years that it was a good walking outside, it was an outside was a good thing. I was like, I ignore that. It's who cares. But I finally realized through some analytics that I did to be fair.

Of course. Of course. That it was having that when I happened that I was spending time outside, it happened that my resting heart rate was lower. And that was a good sign that that was worthwhile. And I found, there was the challenge, I had been thinking about this for like 20 years. How can I be just walking around

and typing on a computer? And I thought back, oh, sometimes the 90s, I was thinking, oh, I'd use augmented reality and I was trying to figure out how I could use a one-handed cord keyboard type thing and so I had all kinds of fancy stuff. And the technology wasn't really there for that. And then it was about a little bit more than a year ago. I was some, at some very, some fancy tech event and actually an event. The scenario was just really kind of funny. It was an event that put on

by Jeff Bezos and he had a photo op that involved him walking with this robotic dog. So I happened to be right there. I think I just been talking to him and there he was with a photo up in the robotic dog. And the robotic dog wasn't that exciting but what was really interesting to me was there was a guy just outside the frame of the photo who had this walking desk and a laptop who was controlling the robotic dog and that for me was the, you know, that was the winning piece of technology in this picture. So I hadn't really internalized this idea that you could really have a walking desk where you just put a laptop on a thing with a bunch of straps that look like somebody who's selling popcorn or something.

You could actually type on this. I should have realized this 20 years earlier because it's a trivial solution. It's a baby carrier. It's a baby carrier turned around to the front with a laptop. It's similar to the story, which actually a audience member, I used this in a podcast a couple of weeks ago, and one of the listeners messaged me and said that it's wrong, but it's the only useful example that I've got. And it's when the Americans wanted to try and develop a space pen that would write upside

down in zero gravity, and the Russians just used a. And it's like one of those things where you think sometimes the simplest solution, I find it so hilarious to think about you around Jeff Bezos and this robotic dog, which is obviously supposed to be like the focus, the focal point of attention. And you've been like, yes, excuse me, you smooth the dog out the way, excuse me, mate. You remind me what that strap around you next made of, please, it's carrying your, this carrying your laptop. Right. I think the photo op, it looks like an autonomous dog, but the most interesting thing was the guy controlling it. It turns out, to my surprise, it's perfectly straightforward

to type on a, if you've got this thing in front of you, I didn't know it would be straight forward to do that. Now, you know, what I found is I kind of have a hierarchy in if I am writing something which is really all about writing and I'm really trying to type the maximum number of words per minute, so to speak, then sitting at my desk is always standing at my desk is going to be the all, is always going to be the winner. then sitting at my desk is always standing at my desk is always going to be the winner. Tribunal is a little bit less effective in terms of how fast I can type for a long period. I'm walking outside is again a little bit less effective. But the typical scenario for me when I'm walking outside, I'm usually using screen sharing and I'm in some meeting and I'll be typing a certain amount of stuff, but I won't be, it's

not like when I'm writing some blog posts, it's been when I'm just purely typing. And I find, I mean, you know, what I tend to find is, if I'm really in gear writing a blog post, then I can do it when I'm walking on a treadmill and even sometimes when I'm outside. But when I'm kind of still just getting warmed up and I haven't quite, you know, gotten into the, into the swing of it, then I have to be sitting at my desk or it doesn't really, I end up at... A lot of cognitive efforts to do that. I mean, just avoiding walking into things. I'm

going to guess you must have to curate the root that you actually walk to and share those no obstacles and stuff. Yes, I do. So before we move on to, I'm conscious of time and I know you're a very busy man. Before we move on to a couple of cool things that I want to do with Wolfram Alphron, an explanation about the Mathematica as well. Final question I wanted to ask about your productivity. Do you think that there's much more left in the system for you?

Like do you think that there's more that you can squeeze out of the lemon of your life in your daily routine at the moment or Or do you think you're working as close to capacity? That's an interesting question. I mean, I think, hmm, you know, well, it's interesting because I think about what the next projects I want to do are. And I'm actually a little frustrated because there are a couple of really big projects. So I mean, one thing to do for like 10 years or more.

And I really want to get the time to do them. And so for me, it's important to figure out, can I, you know, squeeze the other stuff to the point where I can get these done? And one of the challenges, sort of a lifetime challenge is, how do you end up doing new stuff? Because, you know, it's something like me. I built a bunch of things, you know, I've got people who depend on the things I do. It's like we've got a lot of, there's a lot of stuff that's just flowing forwards. And so I think one of the, one of the sort

of personal challenges and the, the attitude challenges is, can one do new stuff in the light of that? Because it's very easy to say, well, I've got all this stuff. I could spend all my time just, you know, maintaining and turning the crank on things I've already built and things I've already done, sort of products we built, et cetera, et cetera, et cetera. But for whatever reason, I kind of have a great urge to go do new stuff as well. And you have to be just a little bit irresponsible to be able to do that. You have to decide, you know, I'm not going to put 100% time into this thing. I'm going to try and push it, squash it a little bit so that I have time left over to go do new

things. So it's a, it's some, yeah, I mean, it's an interesting question. I mean, I think that there are probably You know, one question breaks into two pieces. One is are there things that I'm doing that I shouldn't be doing And the other is the things that I am doing can I do the more efficiently and? I'm good way to frame it right and so you know the and know, in the things I'm doing that I shouldn't be doing, it's, you know, that, that's a complicated thing because, you know, you say, okay, there's some meeting that I'll be doing that's reviewing something or other, okay? I can like not do that. And then there is a decent chance that, that project will keep running okay. But there is also a certain chance that project will keep running okay,

but there is also a certain chance that it will go off the rails. And so that's a, you know, so you have to kind of try and figure out. And and some, I should I did a big refactoring recently of project review meetings of figuring out, you know, how to aggregate different pieces so that it's one meeting that's an hour every week or two that used to be three different meetings and so on. So I mean, there's this some, but in terms of the, yeah, so I, it's a good question. I have to think about that question. I don't, you know, if I knew, to be honest, I'm, I'm unembarassed in answering this question in the following sense that if I could say to you immediately, oh, there's this obvious inefficiency, I would be a bit embarrassed

because, um, you know, it's, uh, why is it not sorted already? Yeah, right. Um, but so, so that's, um, but so, you know, I think, yeah, right. I, I, I mean, there's, there's, um, uh, as I work on two new big projects, um, they will have a slightly different rhythm than projects I have previously done, and so they will have their own kind of, I'll, it will take, you know, I know that when I work on, when I start doing some different kind of project, there's a certain amount of turbulence at the beginning, as things aren't well understood, and you know, gradually I understand what the systems are and get into the swing of it, and then it can flow nicely. I have to say for someone who works in what to most people would feel like a very transactional, well-controlled, himmetically sealed environment that is cold and maths. The way that you speak about the overall philosophy is a lot more the way that an artist or

a musician would speak about it, to do with the sensations and the understanding, the experience-based conception of what is going to happen, which is emerging from all of this past experience that you've had. I think there's a lot to be said, as we've touched on already, that just spending time on detention, as you'd refer to it in the gym of just getting to grips with the bread and butter and then beginning to slowly add more and more on and expand that domain of competencies is something that's very useful for a lot of people. So, final thing, Wolfram Alpha is an answer engine, not a search engine. Would you be able to explain to the listeners who don't understand what an answer engine, not a search engine. Would you be able to explain to the listeners who

don't understand what an answer engine is? What that means, please? Well, we usually like to use the term computational knowledge engine. That's our fancier term for it. But what it is, is a thing where you ask it a question in natural language, and it will try and compute the answer to that question. So you might ask it, I don't know. And you know, you can use it. It provides computational knowledge for Siri and for Alexa. Oh, yeah, it's the basis of Siri and Alexa, right?

Like one of the departments. Well, the knowledge components, yes. Yes. So it's the thing that's answering, it's not the thing that's saying, play this song. It's the thing that's answering the question, you know, what's the population of such and such a place? Or, you know, if you type in a good party trick with Wolfmalfa, is type in a first name, and it'll give you the mostly US data, there has some other countries as well. It'll give you the number of people with that name who've been born every year in the last 100 years. Okay? So, but then what it has to do because it's actually computing things,

is it knows the mortality curves for people. And so it can figure out, you know, what is the distribution of people alive today who have, you know, first name, Chris, for example. Yeah. Right? So then a good party trick is you type in some of his name and they'll give this distribution you'll say most common age of a person with that name and just because of the way statistics works there's a pretty good chance that the person you're talking to has that name is of that age. So that's some. That's frustrating.

That's frustrating. I mean, so you know, and what we're doing in Wolfmalfa is we've been for the last few decades we've been accumulating kind of knowledge about the world in computable form. So, you know, you can say, where's the International Space Station? Okay, so that's something you actually have to compute. You can't just, there's not just because it moves all the time and you have to be working out, you know, what it's orbit is and so on and then computing the answer to that question. So what we really, the thing we've done is mostly translating human natural language, the kinds of questions people ask, into a computational language, and then using the knowledge

that we built up in our knowledge base to be able to answer those questions. I mean, kind of the goal in the end is there's a bunch of systematic knowledge that our civilization has built up. You know, my goal, which to be fair I've had since I was probably about 12 years old, is kind of to accumulate that knowledge in computational form and have it be the case that any question that can be answered on the basis of knowledge that's known in our civilization, we should be able to automate answering that question. That's kind of the goal. And we've been able to do that in more and more domains. And that's some, so that's the story of Wolfmalford. I use it like, oh, I'll use it probably today. I'll go type in sunburn, and it'll tell me because it knows where I am, and it knows the UV index stator, and so on. And it knows, you know, I can look up for my skin type.

It'll tell me, you know, it's whatever it is, 35 minutes to sunburn if I don't put on sunscreen or a hat or whatever else. Yeah. And that's, actually, I've been doing QA of that particular function now for probably eight or nine years. And I can say that the only times I've gotten sunburned at the times when I thought I was smarter than it was.

Oh, it's the same as when you try and go, you don't listen to Google Maps, and you think, no, no, no, this way home's always quicker, and it knows that there's the traffic jam there, and sure enough, you sat in the traffic, kicking yourself and not listening to Google Maps earlier on. So yeah, to any of the listeners who want to go and play some of these games, Wolfram Alphar,

WolframAlpha.com, and just type in where is the International Space Station, or type in someone's first name. Are there any other cool things before we go? Oh, gosh, there are lots of things. I mean, there are lots of kind of people who always enjoy these estimate type things. You know, how many soccer balls fit in a 747 or something? These kinds of things, or one that I was trying to figure out, actually took two steps to do this was if you took all the water and all the oceans on earth and you rolled it all up into a ball, how big would that ball be? And it's, which is relevant because I was trying to understand something about the origin of water on the earth.

Of course it was relevant. Yeah. on the earth from the Cal State of Israel. Of course it was relevant. Yeah, it's, I mean, this is, you know, the, I mean, just to, to, to fill in for a second, the, the, the main sort of intellectual thread of what, what I've tried to do for a long time is this thing we call orphan language, which is an attempt to make kind of a full-scale computational language, which means, you know, you have programming languages where you're kind of telling step at a time, you're telling a computer what to do. The goal of our computational language effort is to have a language to represent things in the world computationally.

In a startup programming language, you might have something that says, there's the value of variable, something like this. But in our language, full computational language, the town of Newcastle is an entity, and you can compute things about it. I can say, what's the geodistance from Newcastle to Boston or something? It's being able to have a language for expressing things in the world in a way that you can compute from them. I've been working on this now, well, kind

of for 40 years, actually, altogether. But I've only, I steadily understand, you know, that this is an important thing because, well, it's the thing that people use, they use our products in, well, lots of R&D and education kinds of settings our products are really widely used to figure out new things. But there are what's interesting about this process. So just to tell a sort of historical tale, there was a time when people like 400 years ago or so people were doing math and they did math by writing everything out in words. So there wasn't a plus sign, there wasn't a time sign, that was only invented 400 years ago. And so once that had been invented, then things like algebra got invented and calculus got invented and so on.

But while you were still kind of writing out all your math in words, that was very hard to invent. There wasn't a good way to kind of express mathematical ideas in a kind of language that was convenient for people. Well, we're in the same situation with computational ideas, and that's kind of what we've been trying to solve is to create a computational language that allows one to sort of express computational ideas in a way that both computers can read and humans can read. And this has been a pretty

successful thing and we're kind of seeing, you know, all these different fields you can call, you know, computational X, where X is, you know, archaeology, zoology, whatever else. All these fields, they need kind of a computational language to express the computational ideas that come up in these fields. And that's kind of what I built. I think you've touched on something there, which the listeners may be thinking sounds a little bit esoteric, but when you actually think about it, the fact that the democratization of knowledge as it is, kind of in the way that Wikipedia, I suppose, works in that you want to find something out and then Wikipedia

gives it back to you. But the thing that you want to find out has to be searched for in an incredibly specific way in the right language for the correct thing that is that you want it to do and it will feed out a very narrow range of results based on what it is that you want. But obviously with Wolfram language, taking natural language, converting that into computer code that then feeds back out something legible by a human who has no training, no special understanding of this, and then gives them the answer that they wanted

or potentially an answer that they didn't even know that they wanted, but is the one that they wanted. And then I think I'm right in saying that you're looking to even step this up even further and allow lay people to create computer programs. I want a program that will do this for me. Yeah, right. You want to then be able to create natural language to compute a program to understand it to then create a computer program to

then do what the person wanted. Well, here's the issue. The issue is that natural language is really good if you have a quick question you're asking. If you're trying to say, let me define how this really complicated thing works. That's not something where natural language is not particularly good at that. That's where computational language is really good. The trick is to have people be able to think in this computational language. And that's what happened when mathematical notation was invented and so on. People started being able to think in mathematical notation. They started being able to actually think through the math that everybody's taught these days.

After 400 years, everybody gets taught this stuff. Probably too many people get taught some aspects of it. But when it comes to computational language, we're just at the very beginning of people learning this and learning it early in their lives when they're 10 or 11 years old or whatever. Once they learn it, then they get to take the sort of computational thinking that they might be doing and put it in some concrete form that both they can read and a computer can also go execute. And that's a, you know, for, you know, from a sort of big picture point of view, in a sense what one is doing by creating what I've been trying to do and creating this computational language, it's giving people a language in which to think computationally, which also happens to be a language that computers can execute. But it's one of the really important things I think is that it provides a way to kind of

formulate your thoughts computationally. And that's something, you know, when we talk about making, you know, personal productivity and so on, a lot of, I suspect, I can't necessarily trace all the connections, but a lot of what I end up doing in trying to sort of formulate how I want to set up systems and so on is informed by the fact that, you know, I've spent a large part of my life sort of inventing this computational language to try and take, sort of general thinking about things and make it computational. And once you've made it computational, you have it in a sort of more streamlined, concrete form. So that, for example, you can automate it and get a computer to do it.

And that's kind of the, that's a big piece of sort of the intellectual effort. And I suspect that when it comes to, I don't know, making the sleep time a clock or something. Yes, that's very easy to do in the language that we have. But it's also something where probably certain aspects, it's always a little bit hard to introspect and understand this, but certain aspects of how that works are probably because I thought about it in a sort of a computational way of this is how to structure it. And it's not just like, oh well, I'd like to know when I, you know, how long I've been

asleep to, I think. It's kind of, there's probably a little bit more to it, which is a little bit hard to introspect and see through. But I think that's the... There's a mode of thinking that you have internalized that is your work, which sounds really weak. As a layperson, again, I don't, I don't code, I don't understand how code, but I would have thought that the transfer from screen to real world would have been really limited. But what it actually appears is that you want to define the things as

clearly as possible, have a number of variables that you can control and then have as little friction and then bugs in the system. And then you've created a lifestyle, a productivity, a work cadence out of that and all of these other solutions. See, I would think so one of the directions is creating computational contracts. So, people, blockchain people talk about spot contracts and so on. So, the generalized version of that is computational contracts. That is, I'm sure in your work life, it's full of contracts, one kind or another. And those contracts are written down in legalese.

They're written in sort of a version of English that is a little bit closer to code, because you're trying to be a little bit precise about, you know, this is what we mean exactly, etc. But, you know, what we will achieve with this sort of computational language direction, you will be able to write contracts in code. And that means that the importance of that is, you know, sometimes that contracts as they're currently done, you know, you actually want some wiggle room in some place or other. But, you know, when the contracts as they're currently done, you know, you actually want some wiggle room in some place or other. But, you know, when when contracts are being executed automatically by machines and things, it's, it's really, you can't really do that. And that's where, you know, if you can express sort of a human, what you want to have happen

and you can express it in computational language, turn it into a computational contract, have it automatically executable, then that's an interesting thing that makes, you've talked about friction, that's a great friction reducer is to be able to say, no, it doesn't need a person in the middle of saying, this is how this should work, it's just automatic. You have some contract that says, I don't know what, you know, based on the number of, you know, if you're promoting something, maybe,

you know, you have some PR firm or something, based on the number of media mentions they'll get, you know, some, you know, commission, some such other thing. And, and but then what does that mean computationally? Well, that means computationally you have a program that says it's going to go search the web, it's going to have these criteria for deciding if it's a mention of this thing, and then there's just going to be some formula in there. Maybe it's going to use some machine learning classifiers that decide if it was a positive sentiment mention or a negative

sentiment mention. But in the end of it, it's just a piece of code code and nobody has to go figure anything out. It's just the code runs, somebody gets paid $100 or something or they don't. It kind of makes the world a more efficient place. There's going to be, so this is everywhere all over the globe just tearing the hair out at the sounds of this. Even your terrifying everybody in law at the moment here. You know what? It's going to be the other way. It's like the paperless office, right? When everybody said the paperless office, it's going to be, you know, nobody's going to have anything printed out and so on. At least for a while, at least for a few decades, there was a lot more paper around because what will happen in this case with computational

contracts is there'll be a lot more contracts in the world. And because there'll be a lot of things where there was no point in having, right now, is too much friction to have a contract. But it's like many things that people do, there'll be a little contract that says, and things will happen automatically based on that or whatever else. And a lot of the, I mean, I know from, because we've interacted with a lot of law firms and so on, that the sort of big, more sophisticated ones are like, we want to get involved in this. We want to be writing computational contracts. And we want to be the ones creating the intellectual property that is all those weird clauses that get added,

that's like, well, we'll sell you all these clauses that will take care of what happens if it rains when you're doing some event or something? Yeah, of course, because you're going to have to have someone who understands the law to interpret it into the programming language, and that particular, in the same way as I want to make, I want to process a document, I need a word processing piece of software, you also require this recipe almost. Yeah, yeah, right. So that's the anyway, this is the kind of thing I think about for a living, so to speak. And you know, these questions about personal productivity are the way that I manage to

get to think about stuff like that. And maybe, you know, one of the things that I've learnt because I've been interested in mentioned personal analytics and so on and I've tended to store sort of everything I've done. And then the real question is can you put together your personal history because there's I've got millions of emails and so on. It's like what is the arc of history that that corresponds to so to speak? In other words, you can look at each individual one. And I wouldn't say it's a project of mine actually right now is to try and make more automation to finding these kinds of arcs of history from individual documents

and so on. But the thing that is always interesting for me to understand, I think it's something that is an interesting introspection for people is when you've done something, can you figure out how you actually got to be able to do that thing? And so, for example, a lot of the stuff that I end up doing that ends up being not the typical thing

that everybody else does, you know, there's usually some whole chain of things. And for example, this whole, you know, spending a lot of my life developing this computational language is probably the reason that I end up getting to do a bunch of personal productivity things, and I haven't quite joined all those dots. Sometimes doing this history and understanding, for example, the Wolfmalfa project, I had thought about doing that project when I was a kid.

I thought this project is too hard, and I thought, among other things, to be able to ingest knowledge about the world and so on and be able to answer questions, you're going to need a complete AI, you're going to need a brain-like thing. And so that was, you know, I came back to it every so often, but I kept on saying, making a brain-like thing is really hard. Then I did a bunch of basic science that I won't term in that that has all kinds of implications, but there's a thing called the principle of computational equivalence

that comes out from that. And one of the implications of that is, it's a piece of basic science and sort of philosophy of science, but one of the implications is there's no kind of bright line between intelligence and mere computation. And so that sort of philosophical point made me realize, gosh, if I'm taking that seriously, then this thing that I now call with malphur that I've sort of wondered, could it be built?

Well, if I take my own theory seriously, then yes, it could be built. And so then I started building it. But it took, you know, in a sense, a very secuartous route, because it takes understanding this quite philosophical thing to realize that yes, actually, if I know what I'm talking about about that philosophical thing, then I should be able to build this practical thing. It needs to at least be able to exist in concept before it can exist in reality. Most things get constrained by reality. People's dreams tend to be bigger than their achievement, and the same thing goes for most stuff. But yeah, if you've got the backup that you, as you've alluded to there, and I will link to some of the blog posts

which have been illuminating to me, which, for the listeners who want to find out a little bit more about your philosophy on that, but Stephen, I'm aware that you are an incredibly busy man and I do want to let you go. Before I see we've got you in trouble and Ed is going to be emails pinging all over and your assistance, it'll have been automated at least. Yes, it has been, I've been getting chipmings and I know I'm supposed to start a live streamed designer of you meeting, so, so, let me go see the beginning of that will be late, but it's amazing. Final thing, where can people find you online if they want to find out more? StevenWallfrom.com.

There we go, that's all that we need. Steven, thank you so much for your time. I really appreciate it. No, interesting stuff, thanks a lot. Yeah, I'm fed.