Dec 18, 2018
My Guest this week is Adam Wiggins, the cofounder of Ink & Switch — an independent industrial research lab working on digital tools for creativity and productivity.
The topic of the conversation is the future of product-focused R&D, the Hollywood Model of work in tech, Ink & Switch’s unique organizational structure, and whether it can be extended to other areas of research.
Links
A presentation on Ink & Switch's Structure
Sloan Review Article on Applying Hollywood Model to R&D (Paywalled)
Transcript
How the idea came about
Ben: How did you come up with this idea? Like wait what what originated that I'm just really interested in the thought process behind there
Adam: sure, you know, I think me and my partner's we come out of the sort of the startup kind of school of thought on Innovation, I think.
There's a lot of way to think about there's the more academic research minded approach to Innovation. There's made which get a bigger companies. So yeah, we come out of very much from the yeah. I don't know what you want to call it ad Jolene startup y combinator or whatever that you know mix of elements is which is really about build a thing really quickly get it in front of customers minimal viable product innovate, but at least my thinking is that the startup model has been so successful in the last let's say decade.
Particularly with the kind of mass production of the startup that you get through groups like y combinator such that I feel like the problems the space of problems that can be solved with that kind of, you know group of 25 25 year old Founders spending three months to build a thing not say it's let's say saturated.
Yeah to some degree in that maybe the more interesting problems are like bigger or longer in scope. And so then we thought about okay. Well, what's a what's a model that is more possible for going after bigger things. And that's when I kind of fell down the rabbit hole of researching these Industrial Research Labs.
I know that you spent a lot of time on as well, you know, these big famous examples like Bell labs and Xerox Parc and arpa and so forth. And of course many other examples when we thought okay, well, You know, we're not at the we're not in a position to you know, be setting up a multimillion-dollar research arm of a government or commercial institution.
But what can we do on a smaller scale with a small Grant and it's kind of a scrappy band and people and that's kind of what led us to the Incan switch approach.
The Thought Process Behind the Model
Ben: can you go one step further where it's you have the constraint that you can't do a straight-up corporate research lab, but I think there are a lot of unique ideas in terms of a model that are sort of just unique and.
In that like how did you cope that Lee idea that like, okay, we're going to like have our principles. We're going to pull in people temporarily. We're going to build this network that that seems sort of to come out of the blue. So what was what was the thought process behind that?
Adam: Well, maybe it came out of the constraint of do it with very little money. And so part of that is we're trying to work on a big problem. Hopefully and I can talk about that if you want, but the in terms of the the model that we're using we came at it from do it with very little money and that in turn leads to okay.
Your big costs are usually sort of like office space and then the people right, but if we can do these really short term projects, we called the Hollywood model and I can explain about that if you want the basically we have like a four or six or eight week project. You can bring in some experts on a freelance basis and you don't necessarily need to commit to paying salary is over the longer term and you couple that with no office.
We have an all distributed team. We're not asking people they don't need to pick up. Move somewhere to even temporarily to work on a project. Right? And so we what we can offer them as a lot of flexibility. And so the I think there's certain there's benefits for the people to participate in these projects join, but from the lab point of view again, it was we were embracing this constraint of do it really really cheap.
Yeah and that basically boiled down to very short projects people on a freelance basis only no office and that that's kind of what what led us there, but I think there actually is a lot. Benefits to doing things that way there's some big downsides as well but there's some benefits as well. So the constraint led us to the model you might say got a desire to work on a big problem in the same with a longer time Horizon like you would for a you know, a classic R&D lab, but trying to do that with a lot less money.
Let us to this kind of short-term project model.
The Hollywood Model in Tech
Ben: There are three things that I want to take into from that the three things are going to be how the Hollywood model works and sort of the difference between the Hollywood model in Tech versus in Hollywood and then like those those pros and cons and then it feels like there's a tension between working on a really big long term projects via very short term sort of Sprint demos.
So. So let's let's start with the Hollywood model because in Hollywood I like after after I learned about. You doing that I sort of dug into it and it's it seems like the Hollywood model Works partially because all of Hollywood is set up so that even the best people work on this temporary basis.
Whereas in Tech, it feels like you sort of have to get people who are in very special life situations in order to get the best people. So like, how do you how do you juggle that?
Adam: Yeah, yeah, that is those are really good point. Well just to I guess briefly explain. The Hollywood model is please the idea.
There is I actually lived in Los Angeles for a time and have a lot of friends who are trying to break into that industry and got a little exposure to that. I don't pretend to be an expert but and you can read about this online as well, which is that most movies are made by forming a an entity usually an LLC for the duration of the movie Project.
You know, I might be a year or two. Here's whatever the shooting time is and everyone from the director or the camera people the whole cast the entire crew are all hired as essentially short-term contractors for whatever the duration of time their services are needed. But even someone like director who's there throughout.
It's essentially a one or two-year gig for him it yeah, and everyone's fired right things right expanded and it's and it's an interesting accounting model because it means the sort of earnings from the movie in the and how that connects to the studio. And then the way the studio is invest is almost more like maybe Venture Capital invest in startups to some degree.
So that's that's my understanding of it. So we kind of borrowed this idea for saying okay part of what we like about this is you get a situation. Any given person and a cameraman a crew member a member of the cast doesn't isn't guaranteed some long-term employment. They don't sign on for an indefinite thing.
They sign up for the duration of the project. Right and the end everyone leaves. But what you see is that the same directors tend to hire the same crew the same. You probably noticed this most dramatically in directors that bring the same actors on to the same onto their future films because if working with them before worked, why wouldn't you bring them back?
Right and so it's but it's it inverts the model of instead of we're going to keep working together by default. It's more every time a project ends. We're all going to disperse but the things that work will kind of bring back together again and just inverting the model in a subtle way. I. Produces better teams over the long term.
But yeah, you get this sort of loose network of people who work and collaborate together to have more of an independent contractor gig mindset and I think that was yeah it was inspired by that and like you said, can we bring that to kind of Technology Innovation?
How do you incentivize the hollywood model?
Ben: Most people in Tech don't do that. So, how do you sort of generate? How do you get the best people to come along for that model?
Adam: That was definitely a big unknown going into it and certainly could have been a showstopper. I was surprised to discover how many great people we were able to get on board maybe because we have an interesting Mission maybe because me and some of the other.
Core people in the team have you know just good networks good career Capital. Yeah, but actually it's that more people are in between spaces and you might guess so quite a lot to work with us on projects. Certainly. There's just people who are straight. You know, they made freelancing or some kind of independent Contracting be their business, right so that those folks are to work with a lot of folks that do open source things, you know, we work a lot of people from the DAT Community, for example, a lot of folks there.
They actually do make a livelihood through some degree of freelancing in this space. So that's an easy one. But more common I think is you think of that. Yeah full-time salaried software engineer or product design or what have you and they. You know, maybe they do a new job every few years, but they're expecting a full employment salary HR benefits, you know the lunch on campus and the you know, the massages and you know yoga classes and so I was worried that trying to you know compete to get Talent like that when all we have to offer these very short term projects would be difficult.
But as it turned out a lot of people are in some kind of in-between space. We're really interesting. Project with an interesting team good sort of in between things maybe a palate cleanser in a lot of cases turned out to be quite interesting. So we got a lot of people who are you know, they're basically looking for their next full-time gig but then they see what we have to offer and they go oh, you know, that's actually quite interesting and they can keep looking for the next job while they're working with us or whatever.
Yeah their Habits Like do this thing is like an in-between thing onto the way that are to their next. Employment or we have situations like, you know one person we were able to get on the team with someone who is on Parental. Leave from their startup and so basically wanted to be like getting the mental stimulation of a project but couldn't really go into the office due to needing to take care of an infant, right?
Um, and so by working with us was able to get some nice in that case part-time work and some mental stimulation and a chance to build some skills in the short term in a way that was compatible with. Needing to be home to for childcare. So the a lot of cases like that. I think so it granted, you know people that are looking for full-time gigs.
We can't give them the best offer in the world. But there's a surprising number of people that are willing to take a weird interesting kind of cool learning oriented project in between there. May be more conventional jobs.
Building from scratch with the Hollywood Model?
Ben: Yeah. Because one of the things that I'm constantly thinking about what I'm asking these questions is how do we have more things using the same model in the world? Because I think it's a really cool model that not many people are using and so it's like what like could there be a world where there are people who just go from like one to the other and then would be an interesting shift in the industry to be a little more gig oriented or Independent. Contractor oriented versus the sort of the full-time job expectation that folks have now. Yeah and another sort of difference between I think Hollywood and Tech is that Hollywood you're always sort of Reinventing things from scratch. Whereas in tech there is code and and things that sort of get passed on and built on top of .
Do you do you run into any problems with that or is it just because like every every experiment is sort of its own its own thing. You don't you don't have that problem.
Adam: Yeah, the building on what came before is obviously really important for a lot of our projects. We were pretty all over the place in terms of platforms.
And that was on purpose we built a bunch. Projects on the iOS platform we bought built from on the Microsoft Surface platform. We've done in various different web Technologies, including electron and classic web apps and so in many cases there is not a direct, you know, even if we had written a library to do the thing we needed in the other thing.
We actually couldn't bring that over in that kind of build it all from scratch each time or or the the mic slate of it. I think is part of what makes it creative or forced to rethink things and not just rely on the. Previous assumptions that said. You know for certain tracks to research you might call it a big one for us is this world of like CR DTS and essentially like getting a lot of the value of getting a lot of capabilities that you expect from cloud Solutions real time collaboration Google Docs style of being able to do that and more peer-to-peer or less centralized oriented environment.
And so we in an earlier project. We built a library called Auto merge just in JavaScript and it was being plugged into our electron app and. And in future projects, we wanted to build on top of that and we have done a number of subsequent projects some of which were but obviously they needed to like use the JavaScript runtime in some ways.
So if we were doing another electron project, yes, you can do that but that and then another case, you know, we wanted to go with tablet thing. All right. Well that limits us because we can't use that library in other places. And in one case is we chose to build for example in the Chrome OS platform because we can get a tablet there and partially because we already had this investment in kind of.
Script ecosystem through these libraries. But yeah again that comes with comes with trade-offs to some degree. So so we're always trying to balance build on what we made before. But also we're really willing to kind of start over or do the blank canvas because we really feel like at this. Level of early Innovation.
What matters is the learning and what lessons you learn from past projects and you could often rebuild things in a fraction of the time in some cases we have actually done that is rebuilt an entire project sort of like feature complete from what on a completely different platform. But if you can skip past all the false turns and you know Discovery process and to build what you where you ended up it's often something that can be done in just a tiny fraction of the time or cost
Knowledge Transfer in the Ink&Switch Model
Ben: Got it. And do you have a way of transferring learning between different groups of temporary people that things like would be one tricky piece.
Adam: Absolutely. Well an important thing here is we do have core lab members both. We have some principal investigators who are people that are around long-term and are the people that drive our projects and their, you know, carry a lot of those learnings both the Practical ones, but also like culture.
Cultural elements and then a lot of the folks we work with they'll come back to work for a future project. But yeah, absolutely every given project is a new combination of people some existing people in the lab. They carry forward some of those learnings and then some people who are new and so we've had to do we tried a variety of approaches to kind of.
Do a mental download or crash course and you know, none of it's perfect. Right because so much knowledge. Is that even though we take a lot of time to do a big retrospective at the end of our projects try to write out both raw notes, but also like a summarize here's what we learn from this project even with that and sharing that information with new people so much of what you learn is like tacit knowledge.
It's somehow, you know more in your gut than in your head. And so to some degree we do count on the people that are more standing numbers that go project project in some cases. We do have to relearn small lessons each time. And again that that somewhat is a you know, if you start over from scratch and you kind of start from the same premises then you often discover some of the same same learnings.
I think that's okay as long as we get a little faster each. Each time and then yeah combine that with learning documents and I don't know for example, we're actually the point now we have enough projects under our belt. We actually have a deck that is like here's all our past projects and kind of a really quick crash course summary, at least here's what they're called and least when people reference.
Oh, yeah. That's the way we did things on Project number five right was called this and you can be like at least have some context for that. And so short answer is we haven't solved the problem but here's some things that at least have helped with that. Yeah, and how many projects have you done in total?
Yeah. Well depends on exactly how you count. But when it comes to what we consider the sort of the full list called formal projects, which is we spend some time kind of wandering around in a in a period of time to call pre-infusion named after the the espresso machine for the sort of record time.
You put in the water to kind of warm up the grounds. So the version of that and once we have basically a process where once principal investigator finds a project with egg, I think there's a really promising area and we should fund this. Okay. Now we're going to go actually hire experts that are specific to this area.
We're going to commit to doing this for again six weeks or eight weeks something on that order. There's a project brief we present basically present that to our board to basically give like a thumbs up thumbs down. I'm so if you count stuff that has been through that whole process we've now done 10 projects cool.
That's over the course of about three years.
Ink&Switch Speed vs. Startup Speed
Ben: Yeah, that's that's really good compared to. Like I start up where you do one project and takes three years.
Adam: I need to maybe feels sometimes it feels slow to me. But honestly, we spend as much time trying to figure out what it is that we want to do as actually doing it and then suspend a really good bit of time again trying to retrospect pull out the learnings actually figure out.
What did we learn? You know, we usually come out with strong feelings and strong Instinct for kind of this work. This didn't work. We'd like to continue this. There's more to research here. This is really promising. This was a dead end but actually takes quite a bit of time to really digest that and turn it into something and then kind of the context shift of okay.
Now, let me reorient and switch gears to a new project is really a whole skill, too. To be doing such a rapid turnover, I think and I think we've gotten decent at it over the last few years, but I think you get a lot better if you wanted to keep at it.
Ink&Switch's Mission and Reconciling Long Term Thinking with Short Term Projects
Ben: Yeah. And I've actually like to step back real fast to the bookmark in terms of a the big picture long-term thinking like what is in your mind the real Mission here and B.
How do you square these? Like, how do you. Generate a long-term result from a whole bunch of short term projects.
Adam: right. Yeah, really cool problem. Absolutely. Yeah. Yeah and one again, I don't pretend to have answers to we're still in the middle of this experiment will see if it actually actually works.
Yeah, let me start by just briefly summarizing our our mission or a theme. I like to think of it a little bit right like typically these and these great examples of successful Industrial Research Labs, you know for Bell Labs or theme was this Universal connectivity that has Bell had this growing Communications Network and they wanted to like solve all the problems that had to do with trying to tie together an entire nation with Communications technology or Xerox Parc.
Of course, they had this office of the future idea. It's. How many papers and copier what is it going to be? I think you need a theme that is pretty broad. But still you're not just doing a bunch of random stuff that people there, you know think it's cool or interesting new technologies. It's tied together in some way.
So for us our theme or a research area is Computing for productivity and creativity. Sort of what the digital tools that let us do things like write or paint or do science or make art are going to look like in future and we were particularly drawn to this and. And our investors were drawn to this because so much of the brain power and money and general Innovation horsepower in Silicon Valley certainly the tech industry broadly and even to some degree in Academia computer interaction research and so on it really pointed what I would call consumer technology.
Right, it does social media It's Entertainment. It's games. It's shopping. Yeah, and and that's really a phenomenon just the last five or ten years, right the successful smartphones the fact that sort of computing has become so ubiquitous and mass-market its health and fitness trackers yet wearable, and you know, that's all great, but.
I think that the more inspiring uses the more interesting uses of computers for me personally. I things that are about creativity there about self-improvement there about productivity and when you look at what the state of I'm going to look like a spreadsheet, right if you look at Excel in 1995 and you compare that to Google Sheets in 2018 the kind of looks the same.
Yep, you know, it's at a Google Sheets as real-time collaboration, which is great. Don't get me wrong. But basically the same kind of program, right? Yeah. And I think you can say that same thing for many different categories Photoshop or presentation software note-taking software that sort of thing.
There's some Innovation to give me to go get me wrong, but it just feels very out of balance how much again of that Innovation horsepower of our industry broad. They could go into Super Side. So for us the theme is around all right. We look forward five or ten years to what we're using to be productive or created with computers.
What does it look like and you know, the reality is desktop operating systems or more and more kind of advanced mode because that's not where apple or Microsoft revenue is anywhere. But at the same time I don't think it's you know, touch platform particularly, you know are built around phones and consumer Technologies and sort of the pro uses of them tend to be kind of attack on afterthought.
And so it sort of feels like we're in a weird dead end which is like what are we going to be doing 10 years from now to yeah do a science paper or write a book or make a master thesis or write a film script? It's hard to picture and but actually picturing it is that's that's sort of our the job of our research here.
Ben: and that is a really long term project because you sort of need to go back down the mountain a little bit to figure out what the what the other mountain is.
Adam: Absolutely. Yeah the local Maxima of some kind and so maybe you need to yeah be a little. Out of the out of the box and go away from basically make things worse before they get better.
Aside on AI Enabled Creativity Tools
Ben: Yeah, just aside on that. Have you been paying attention to any of the sort of like a I enabled creativity tools? This is just been on my mind because Neurosis is coming up and there's some people who have been doing some like pretty cool stuff in terms of like. Enhance creativity tools were like maybe you start typing and then it starts completing the sentence for you and and or like you sort of like draw like a green blob and it fills in a mountain and then you sort of like just adjust it.
Have you been paying any attention to those tools at all?
Adam: Yeah. Absolutely. Some of the follow sir pokes on Twitter that post really interesting things in that vein that hasn't been an area of research for us partially because maybe we're a little contrarian and we like to kind of look where. You are looking and I feel like Ai, and that kind of Realm of things is very well.
Or I should say a lot of people are interested in that that said yeah, I think to me one of the most interesting cases with that is usually we talk about with like generative design or things like. Sot great Target Range Loop last year by an architect who basically uses various kind of solvers we plug in like here's the criteria we have for like a building face, you know, we need the window has to be under the, you know can't because of the material dimensions and the legal things and whatever it can't be here's the constraints on it.
But here's what we want out of the design. You can plug that in and the computer will give you sort of every possible permutation. And so it's a pretty natural step to go from there to then having some kind of. Algorithm whether it be here a stick or something more learning oriented, which is then try to figure out from that superset of every possible design satisfies the constraint which of them are actually sort of the best in some sense or fit what we said that we like before where we use, you know, the client or the market or whatever it is you're looking for.
So I think there's a lot of potential there as I think it was more of an assistive device. I get a little skeptical when it gets into the like let's get the computers to do our thinking for us. Yeah realm of things. I would say, you know, I think you see with the fit and of the sort of auto complete version of this, but but yeah, but then but then maybe I you know, I love that artisanal Craftsman, you know, some kind of unique vibe that humans bring to the table and so yeah tools as.
Assisting us and helping us and working in tandem with us and I think yeah, there's one probably a lot of potential for a eye on that that said that's not an area where researching.
Ben: Yeah. I just I wanted to make sure that was on your radar because like that's that's something that I pay a lot of attention to him very excited about.
More Reconciling Long Term and Short Term
Ben: Yeah, and so for the long-term Vision, the thing that I always worry about in the modern world is that we are so focused on what can you do in a couple months these little Sprint's that if there's a long-term thing you just wouldn't be able to get there with a bunch of little projects.
So I'm really interested in like how you resolve that conflict.
Adam: Yeah, well you could say it's one of the biggest Innovations in Innovation, which I know is the area your study medication to get into this iterative mindset this what he called agile whether you call it. Yeah, iterative that the idea of kind of breaking it down into small discrete steps rather than thinking in terms of like I don't know we're going to go to the moon and let's spend the decade doing that.
But instead think of and I didn't even see that difference in something like the space program right the way that the modern. Space exploration stuff that's going on is much more in terms of these little ratcheting steps where one thing gets you the next rather than that one big Mega project. It's going to take a really long time the super high risk and super high beta so I in general.
I think that's a really good sort of shift that's happened. But yes, it does come at the expense of sometimes there are jumps you can or need to make that are not necessarily smaller steps. And so I certainly don't propose to have the answer to that. But at least for what we're doing the way I think of it is, you know, starting with a pretty Grand Vision or a big Vision or a long time Horizon.
If nothing else and trying to force yourself first and foremost into the bigger thinking right? But then going from there to okay, if that's you know, where we want to go. What is the first step in that direction? What is the thing that can give us learning that will help us get there and one of the metaphors I always love to use for I guess research in general or any kind of Discovery oriented process is the other Lewis and Clark expedition, you know, this was commissioned by the Thomas Jefferson was president at the time and it to me was really crazy to read about.
Holly you know they hadn't explored the interior of the continent they believe there might still be willing - running around and actually one of the things Thomas Jefferson Wander from the he's like, I really loved a, you know get a while you're out there they just had no idea they knew that the Pacific Ocean was on the other side that had ships go around there.
But other than that it was this dark interior to the continent, but they sat out you know that expedition set out with the goal of reaching the Pacific Ocean and find out. What's on the way right and they did they took their best guess of what they might encounter on the way and put together Provisions in the team to try to get there.
But then the individual sort of you might wait, you might call the iterative decisions. They need to make along the way to be go up this mountain rage. And we divert this way to be cut across this River. Do we do we follow this for a while do we try to befriend these tribes people who run away etcetera.
Those are the sort of the iterative steps for the important thing is keeping in mind that long-term strategic goal. Um and defining that goal in such a way that it doesn't say go west, you know, it's not a set of directions to get there because you can't know that you have to start with here's what our vision is.
Let's connect the two coasts of this country and then we're going to take whatever whatever iterative steps seem to be most promising to lead us in that direction. Also realizing that sometimes the most iterative step leads us in a way even away from our goal. So hopefully that's what we're trying to do it in can switch is picking individual projects.
We hope carve off a piece of the bigger thing that we think will increase our learning or build our Network or just somehow illuminate some part of the this problem that we want to we want to understand better again, what is the future of you know, productive and creative Computing and then hopefully over time those will add up in the trick is not to get lost for me.
I think the trick is not to get too lost in. Detail of the project right? And that's where the Hollywood model is. So important because you got to end the project and step away to truly have perspective on it and to truly return to looking at the bigger thing and that's what you don't get in my experience working in a startup that has operations and customers and revenue that you know goals.
He need to hit us according to those things which are absolutely you know, the right way to run a business but then. Keeping that that that bigger picture view and that longer term mindset is very difficult. If not impossible in that setting. So that's our approach. Anyways, see how about in longer term?
Loops around Loops: The Explicitly Temporary Nature of the Whole Lab
Ben: and in terms of of your approach and ending things is it true that you're actually going to at the end of a certain amount of time. You're going to step back and look reevaluate the whole. Is it like you're sort of doing like loops loops around Loops
Adam: indeed? Yes. So individual projects have this sort of you know, we'll end it and and step back and evaluate thing.
And then yeah, the whole thing is basically, you know, we have a fixed Grant when that's how it's out and right and it's up to us to deliver invest to investors the learning you might call the intellectual property. We're not patenting things or whatever, but the. See protect the things that offer commercial potential and could potentially be funded as startups.
Basically. Yeah, that's you know, that's that's what we'll do. And actually that will happen next year. Wow. And when that does happen will hopefully do you know will do the same process? Like you said that the the bigger loop on the smaller Loop which that we've done on the smaller Loops which is retrospect at the end write down everything we've learned and then we do go ahead and let the team.
Part of that may be when you've done put all this hard work and getting a team together, but my experience is that if there's really some great opportunity there. You'll recall us it in some new form.
What Comes out of the Lab?
Ben: I can see it's going multiple ways. Where you. You ended and then you could either say there's another five-year research thing in this or there's some number of sort of more traditional startups to come out of that to try to capture that value are those sort of the the two options.
What what do you see as the possibilities that come out of this?
Adam: Yeah, those are those are both pretty key outcomes and they're not mutually exclusive right so it could be that we say, all right, great, you know we generated sort of five interesting startup options one of them. You know an investor decided to pick that up and you know, maybe take a team that is based on some of the people in the lab that worked on that and those folks are going to go and essentially work on commercializing that or making a go to market around that but then some other set of people who were involved in things and want to come back to this.
He's promising tracks research and we're going to take another grant that has another time duration, I think. The obviously money is your ultimately all of them in limiting factor it yeah in any organization, but but I like the time boxes. Well, I think we use again we use that for our short-term projects and and some degree.
We used it for the lab overall. I think thinking that it's like that Star Trek, you know, what is it or three-year Mission our five-year Mission, whatever it is. It's something about the time box that kind of creates clarity. Yeah, maybe in some is and yeah, you might decide to do another time box another chunk of time.
In other chapter actually investors do this as well. If you look at something like the way that Venture struck funds are structured they often have sort of multiple. Entities which are you know, it's fun one fun to fund three. Yeah, right and those different funds can have different kind of buy-ins by different partners.
They have different companies in their portfolio, even though there is like a continuous. I don't know if you want to call a brand or culture or whatever the ties them all together and I think that approach of like having these natural chapter breaks time or money based chapter breaks in any work is like a really useful and valuable thing for.
Productivity and I don't know making the most of the time.
Human Timescales - 4-5 Years
Ben: I completely by that. I have this theory that human lives are kind of divided up in like these roughly five year chunks. We're like that's that's the amount of time that you can do the sort of the exact same thing for the most time and if you if you like if you don't have.
You can reevaluate every five years but it's like you look at like school. It's like you really like maybe it's like five years plus or minus like to but beyond that it's really hard to like sustained. Intense and tension on the same thing. So that makes that makes a lot of sense
Adam: agree with that. I would actually throw out 4 years as a number which does I think Max match the school thing it also matches the vesting schedules are usually the original vesting schedule and most startups is a four-year window. And if I'm not mistaken, I think that is the median length of marriages think there's something around.
Well, you know, maybe it's something around, you know, there's renewal in our work life is what we're talking about here. But there's also renewal in a personal life, right? And if you're yeah if your employee at a company. Maybe something around for years as a feels like the right Tour of Duty. No not say you can't take on another Tour of Duty and maybe with the new role or different responsibilities, but there's something about that that seems like a natural like you said sustained attention, and I think there's something to goes about as well as inventing.
Or Reinventing yourself your own personal identity and maybe not connects to you. Marry. Someone for years goes by you're both new people. Maybe those two people aren't compatible anymore. Yeah. I don't know. Maybe that's figure that's reaching a little bit far. I mean the other yeah
Investors, Grants, and Structuring Lab Financing to Align Incentives
Ben: that makes a lot of sense and you mentioned investors a couple of times but then also that it's a grant so how did you something something that I'm always interested in is sort of like how to.
He's up. So the incentives are all aligned between the people like putting in the money the people doing the work and people setting the direction and so like how did you structure that? How did you think about sort of coming up with that structure?
Adam: Yeah, I've used maybe investors and Grant sort of a little Loosely there again, the model we have is a little different.
So when I you know went to pitch the private investors on what we were going to do with this, I basically said look. Me and my partner's we had been successful in the past producing commercial Innovations. We want to look now at something that's a little bigger a little longer term and wouldn't necessarily fit as cleanly into some of the existing funding models including things like the way that the academic research is funded and certainly Venture funding and so take a little gamble on us.
Give us a pics. Amount of money a very small amount of money by some perspectives to deliver not profits, but rather to deliver again this kind of concept of learning intellectual property in the loose sense not in the legal sense, but in the sense of intellectual Capital, maybe might be another way to put it and more explicitly.
Yeah spin out potential right but the but but no no commitment to make any of these things. It's just we've evaluated all of these opportunities. Here's what we think the most promising ones are and that includes both. Let's call it the validated findings. We think there's a promising opportunity here at technology.
That's right to you know, serve serve some marketing users well, but also some things that we got negative findings on we said well look we think there's a really interesting Market of users to serve right here the technology that would be needed kind of isn't ready yet and still five years out or maybe the market is actually tough for an early not very good for sort of early adopter type products and so in some way that would be valuable to.
There's as well to have this information on why actually is it is not wise to invest in a particular Market a particular product opportunity. So that was that was what we asked for and promised to deliver and obviously we're still in the middle of this experiment so I can't speak to the whether they're happy with the results.
But at least that's the that's the deal that we set up.
Tension between Open Knowledge Sharing and Value Capture
Ben: I just I love the idea of investment not. Necessarily with a monetary return and it's like I wish there were more people who would think that way and. In terms of incentives. There's also always the question about value capture.
So you you do a really good job of putting out into the world just like all like the things that you're working on and so it's like you have all those the great articles and like the code. Do you hold anything back specifically for for investors? So that because I mean it would make sense, right because you need to capture value at some point.
So it's like there's there's got to be some Advantage. So like how do you think about that?
Adam: Yeah. I don't have a great answer for you on that, you know, certainly again, you know, there's conventional conventional ideas there around yet Trade Secrets or patents or that sort of thing, but I kind of.
Personally, I'm a little bit more of a believer in the maybe comes back to that tacit knowledge we talked about earlier, which is you can in a way. I feel like it's almost misleading to think that if you have the entire project is open source that somehow you have everything there is to know I feel like the code is more of an artifact or an output.
Yeah of what you learn and the team of people that made that and the knowledge they have in their minds and and again in. To some degree in there. There are sort of hearts and souls. Yeah is actually what you would need to make that thing successful. Right? And I think a lot of Open Source people who work on open source for a living rely on that some degree, which is you can make a project that is useful and works well on its own but the person who made that and has all the knowledge about it.
They have a they have a well of. They have a lot of the resources that are really valuable to the project. And so it's worth your while to for example go hire them. And so that's that's the that's the way I think that we think about in The Way We pitched it to investors. If I were to do this again, I might try to look for something a little more concrete than that a little more tangible than that.
The other part of it that I think is. Pretty key. Is that the networking? Yeah, and so you could say okay. There's the knowledge of the people who worked on in their heads. It may be that that kind of ties together. But there's the knowledge we transferred directly by like here's a here's a document that tells you everything we learned about this area where we think the opportunities are but then it's also by the way, we had a bunch of people to work on this some of whom are now in some cases where we were pushing the envelope on a particular Niche e sub technology.
We end up with people on the team who are in many cases of the world's experts or we're in touch with the few experts in the world on a particular topic and we have act we have that network access. And so if someone wants to go and make a company they have a very easy way to get in touch with those people not the really impossible for someone else to take that.
Bundle of information or take even a code based on GitHub and pick through the contributors list try to figure out who worked on it and go contact them. You know, I think that's possible Right, but I think it's quite different. You would be the pretty substantial disadvantage. There's someone that actually had the worm Network and the existing working collaboration.
Extending the Ink&Switch Model to Different Domains
Ben: Yes, the I like that and in terms of using the model in different places. Have you thought about how well this applies to other really big themes the things that you're working on our nice because it's primarily software like the capital costs are pretty low. You don't need like a lab or equipment.
Do you think that there's a way to get it to work for maybe in biology or other places where there's higher friction.
Adam: Yeah, I think the fact that we are in essentially purely in the realm of the virtual is part of what makes the sort of low cost. By all remote team and not asking people to relocate that's what as part of what makes that possible. We do have some cost. We've certainly purchased it quite a bit of computing Hardware over the course of the of the course of the lab and ship those to whoever needs it.
But that said, you know, we can do that. I think this model would best apply to something that was more in the realm of knowledge development and not in the realm of you have to get your hands physically on something. Whether that's a DNA sequencer or a hardware development or something of that nature, but on the other hand as certainly as cameras get a more of the quickest and high-speed internet connections get better and certainly we've learned a lot of little tricks over the time.
I think we were talking about the start of the call there about. Our use of document cameras is basically screen screen sharing for tablets doesn't work great because you can't see what the users hands are doing. So we learned pretty quickly that you got to invest in document cameras or something like that in order to be able to kind of effectively demo to your teammates.
One of the quick or as a kind of a sidebar but related to that is one of the learnings we had in making the distributed team thing work is you do have to get together in person periodically so we can to support early team Summits got it.
Making Watercooler Talk and Serendipity Work with a Distributed Team
Ben: I was actually literally just thinking about that because one of the things that I always hear about.
Great research places like whether it's like Bell Labs or DARPA is sort of like the the water cooler talk or the fact that you can just sort of like walk down the hall and like really casually hop into someone's office. And that's the problem with distributed teams that I haven't seen anybody saw well, so so you just do that by bringing everybody together every once in a while.
Do you think that generates enough?
Adam: Yeah. I mean the to your right like. That problem is very big for us. And there's there's a number of benefits we get from the distributed team, but there's also a number of problems. We haven't solved and so I'm not sure how this would balance against the sort of the spending the same amount of money on a much shorter term thing where people could be more in person because that water cooler talk you get some of with a slack or whatever but.
It's just not the same as being co-located. So yeah, the the one of the mitigating things we have that I think is works pretty well as about about quarterly or so. We got everyone together and it's actually kind of fun because because we don't have to go any place in particular. There's no central office.
We try to pick a different city each time someplace that's creative and inspiring we tend to like interesting Bohemian Vibe, you know in some cases urban city Center's been in some cases more historic places or more in nature. Ideally someplace close to International Airport that it wouldn't fly into and for really a fraction.
I mean offices are so expensive. Yeah, and so our fraction of the price of maintaining an office. Actually fly everyone to some pretty interesting place once a once a quarter and so for a week, we have like a really intense period where we're all together in the same physical space and we're working together.
We're also getting the human bonds more that casual conversation and we tend to use that time for like a lot of design sketching and kind of informal hackathons are also some bigger picture. Let's talk about the some of the longer term things lift our gaze a little bit and that helps a lot. Again, it is not as is demonstrably not as good as being co-located all the time, but it gets you I don't know 30 to 40 percent of the way there for, you know a fraction of the cost.
So yeah over the over the longer term again, I don't know how that would Stack Up Against. Collocated team, but that's one good thing to getting product review so far.
Where to find out more
Ben: I see that we're coming up on time and I want to be very respectful of your time. I'm going to make sure people know about the website and your Twitter.
Is there anything else any other places online that people should learn more about and can switch to learn more about you and what you're working on.
Adam: Ya know the the website and the Twitter is basically what we got right now. We've been really quiet in the beginning here not because you know, I'm a big believer in that, you know that science approach of Open Access and you know, it's about sharing what you've learned so that humanity and can build on each other's learnings that said it, you know, it's a lot of work to to package up your ideas, especially when they're weird and fringy like ours are in a way that's consumable to the outside world.
So we're trying to do a lot more of that. All right now and I think you're starting to see that little bit to our to our Twitter account where in including publishing some of our back catalogue of internal memos and sketches and things which again very itchy things you got to be really into whatever the particular thing is to find find interest in our internal memo on something as well as taking more time to put together demo videos and longer articles that try to try to capture some of the things we've learned some of the philosophies that we have some of the technologies that were.
So yeah, there's she spots a great
Thinking About Extending The Model
Ben: So freaking cool. the. That I'm doing is just putting together the ideas and trying to almost make a more generic description of what you're doing so say like, oh, what would this look like if it goes into biology or it goes into something?
What would this look like for nanotech? could you do the distributed team using University resources? Right? Like could you partner with a whole bunch of universities and have someone in different places and they just like go in and use the lab when you need to I don't know like that's one Bay action item based on learning about this is like oh, yeah.
I think I think it could work.
Adam: That sounds great. Well, if you figure something out, I'd love to hear about it. I will absolutely keep you in the loop.
Ben: awesome. Cool. Well, I really appreciate this. I'm just super excited because these new models and I think that you're really onto something. so I really appreciate you bringing me in and going into the nitty gritties.
Adam: Well, thanks very much. Like I said, it's still an experiment will we get to see? But I feel like I feel like they're more Innovation models than just kind of start up. Corporate R&D lab and Academia. Yeah, and if you believe like I do that technology has the potential to be an enhancement for Humanity then you know Finding finding new ways to innovate and a new types of problems and you new shapes of problems potentially has a pretty high high leverage impact the world.