The Changelog: Software Development, Open Source - Python documentary companion pod (Interview)

Episode Date: August 27, 2025

Our friends at Cult.Repo launch their epic Python documentary on August 28th, 2025! To celebrate, we sat down with Travis Oliphant –creator of NumPy, SciPy, and more– to get his perspective on how Python took over the software world. Stick around for the twist ending! We set aside Python and dissect Travis' big idea to make open source projects financially sustainable through direct investment.

Welcome friends. I'm Jared and you are listening to The Change Log, where each week we interview the hackers, the leaders, and the innovators of the software world. We pick their brains, we learn from their failures, we get inspired by their accomplishments, and we have a lot of fun along the way. On this episode, we celebrate the launch of Colt Repo's epic Python documentary by sitting down with Travis Oliphant, creator of Numpai, sci-pie, and more. We get his perspective on how Python took over the software world. Stick around for the twist ending.

We set aside Python and dissect Travis's big idea to make open-source projects financially sustainable through direct investment. But first, a big thank you to our partners at fly.io, the public cloud built for developers who like to ship. We love Fly, you might too, learn all about them at Fly. I. I.O. Okay, Travis Allifant talking Python on the change log. Let's do it. What's up, friends? I'm here with Kyle Galbraith, co-founder and CEO of Depot. Depot is the only

build platform looking to make your builds as fast as possible. But Kyle, this is an issue because GitHub Actions is the number one CI provider out there, but not everyone's a fan. Explain that. I think when you're thinking about GitHub actions, it's really quite jarring how you can have such a wildly popular CI provider. And yet, it's lacking some of the basic functionality or tools that you need to actually be able to debug your builds or deployments. And so back in June, we essentially took a stab at that problem in particular with Depot's GitHub Action Runners. What we've observed over time is effectively get up actions when it comes to actually debugging a build. is pretty much useless. The job logs in GitHub Actions UI

is pretty much where your dreams go to die. Like, they're collapsed by default. They have no resource metrics. When jobs fail, you're essentially left playing detective, like clicking each little drop down on each step in your job to figure out like, okay, where did this actually go wrong? And so what we set out to do with our own GitHub actions

observability is essentially we built a real observability solution around GitHub Actions. Okay, so how does it work? All of the logs by default, fault for a job that runs on a depot GitHub Action Runner, they're uncollapsed. You can search them. You can detect if there's been out of memory errors. You can see all of the resource contention that was happening on the runner. So you can see your CPU metrics, your memory metrics, not just at the top level runner level, but all the way down to the individual processes running on the

machine. And so for us, this is our take on the first step forward of actually building a real observability solution around GitHub actions so that developers have real debugging tools to figure out what's going on in their builds okay friends you can learn more at depot.dev get a free trial test it out instantly make your builds faster so cool again depot.dev We are here with Travis Alephent, creator of Numpai and one of the founding contributors to SciPai, longtime member of the Python community,

and now a documentary star. You're in a documentary, Travis. How cool is that? Wow. Wild. Yeah, actually, they did a great job. It's impressive. a good media creator can produce.

Yeah, it's really cool. The Python documentary coming out soon. The trailer is out there if you're listening to this and you can't find the entire thing. The entire thing will be out soon. But I just think it's a strange world we live in where like a bunch of nerds who write programming languages are the subjects of documentary.

And there's no scandal. There's not like murder or anything interesting. It's just like, you know. There are some interesting things. There's some interesting things you can talk about. We didn't get into some of that. Yeah, there's some drama and stuff. Like, what kind of interesting stuff has happened?

Well, you know, there's, you know, people have different ideas about how community should be run and about how projects should be governed. And there's, you know, different kind of scandals. We had the, you know, donglegate at one PyCon that probably didn't make the documentary because nobody wants to talk about it anymore. We had, which is totally fine. Yeah. We had the introductions of, uh, so it's just some really, I mean, it's people, right? And there's some awesome people. But then people end up, you know, rubbing each other the wrong.

way a little bit. And then how do you deal with that? Well, like iron, sharpening iron, you know, that's how it works. It hurts to, uh, to do that work, but it's, it betters both sides, hopefully, for the best. Hopefully. And there's definitely ways to do it. There was the Python two, Python three transition. I'm trying to think of the dramas. I don't know what Dongo game was a big, yeah, well, that was just a Pycon, it's call it, it's called it, it's call it codes of conduct. Yeah, okay, I can guess what that one is. You can guess what it is.

Codes of conduct and how to appropriately have public events with lots of different diverse people coming and how to then, you know, just managing that and managing expectations and helping people feel comfortable and not, you know, making a safe space for lots of people. Then as you're making a safe space for lots of people, making sure everybody who is also still welcome because there's definitely people that end up not coming. There's the whole, you know, people being. You know, some of the original contributors, we get a little older, and then maybe we're not as, we don't choose our words well enough, you know, and so, and ultimately get, uh, maybe even from offending somebody to inadvertently to kind of the style of engagement being, uh, unacceptable anymore. And so there's definitely some of that that's going on under, I would put that under the, that's managed pretty well, but there's definitely, I talked to a lot of people. And there's some people who are feeling less well.

welcome in the community than they used to. And that's something that maybe is okay, or maybe it's like, well, there's room for other communities. There's places to have, I call Python an ecosystem at this point. Yeah, I was going to say it's like so big. It can't be a community even. No, it can't be a single community. And actually, that's one of the things for the major leadership of the Python, you know,

the Potter Software Foundation or the ecosystem facilitators understand. I think that's one of the primary things I could articulate this under is just as you get so big, you're actually encompassing many nation states, respectively? How do you be the UN as opposed to an organization that's running one country, county, city, like the skills and that what you have to do is different? And how do you do that without effectively making it feel like you're a bully or a totalitarian for one group, for other groups? Because that's what ends up happening is some people feel unwelcome. Not because they're intending to, but just because, well, you know, we're limited.

Every human is limited. And if you have an organization, it still has to be rid. People have to do work. They have to do stuff. If the stuff they do just isn't feel inclusive enough for other people,

then those people start to feel, you know, annoyed. So what are the patterns? And Python is definitely big enough for that. And you'll see issues on this over and over again, whether it be the documentary didn't cover this group enough. I'm sure we'll get that.

Sure. I'm sure it's true. The documentary, I'm just like excited to see anything talked about that emphasize a couple of great points about Python that it's been such a great group of people who have tried to bring their best foot forward and try to do what's best for each other and you know check ego at the door not perfectly of course because none of us can but but try and try to be inclusive try to bring other people in try to manage the growth and different

mindsets that are there I understood very well the difference between the let's call it the developer mindset, the person who's using Python to build a website and then from there a system prompt or a script and operating system or build an event programming system versus somebody who's building using this to run a scientific experiment or to do math or to run physics systems and now evolving into data science and AI. Like the kinds of problems they have and the needs they have are different than somebody building a website or a database or a Raspberry Pi. right or a web app all great all wonderful you know there's not a there's no judgment about which is more important it's just simply different and then as they come together how do you

how do you have a language support all of these use cases great question right I think it's challenging but the community is awesome I think one thing that comes out in the documentary is very true is people come for the language and stay for the community and that has to do with kind of you know the original group you know Gito his original personality approach he took to engaging with people and the group of people that came around him in the early days, and then how that spawned multiple subgroups, even from the very early days, they had these SIGs, special interest groups they created just to allow other communities to form instead of just all one mailing list in other places.

Hey, you could talk about that problem over here and not be, and everybody didn't have to chime in on that problem if they weren't interested. And so people have these special interest groups. And that special interest group is the matrix SIG actually that ended up giving rise to numeric and then Numpai and then the Sipai ecosystem came out of that special interest group. Then you had other special interest groups that gave rise to Django and Fast API. And then there's packaging. It's its own story that can go on about because there's still challenges there.

So I think that's one of the key things to understand. But each of those interest groups was infused with at least a general sense of, hey, here's how you treat people. Here's how you, you know, let's avoid kind of the, even though, you know, we want to make sure excellence is achieved and people do really good work and not just lowest common operator code gets in it's still how do you make it welcoming you know how do you make it so there's new people they don't feel scared away because they're not capable enough to or the people who they feel they're not capable enough how do you make it so that they feel welcome but then also you

respect the quality of the code and that people are attentive to that you know you sometimes in some areas I shouldn't be contributing code right the code I write should be tossed out. But I appreciate being listened to, at least if somebody tells me, you know, this is why. It's always better than just being ignored. So I think some of those elements of the Python community have been helpful. Not perfect. You know, each of these communities in the Jupiter community, the notebooks, you know,

the data frame community, pandas emerged from the kind of the Saipai ecosystem. SciPi was an ecosystem that gave rise to data, data science, AI, scientific computing, and each of those kind of have developed their own. own stories, you know, Jupiter, you know, one of the things we did early was, not early, 10 years in 2012, we created a nonprofit called Nunfocus. So I was heavily involved in creating that nonprofit, nonprofit, non-focus. And the purpose was because I wrote Numpai and it had no home, except in a company. I didn't, I didn't want, and the community didn't want a single company to own the domain and own the IP of NNPai. It needed to be a community red driven thing.

So where did not going to live? But I can go back on the history. before we get ahead of ourselves you want so you know love to kind of yeah i can talk about the different things that you think are interesting for sure adam where would you like this to go uh i don't want to dwell on the donkey but i do recall that stuff i think everybody's going to not i think every community's got a version of that i think you know what i'm going to say to is like don't apologize because it's going to happen not that we should allow it to happen but you know we've all got growth and growth matures with scars from previous battle wounds, whatever it might be.

I think it's all about trajectory, which is probably why Python succeeded so well, not just because it's a great language, but because, like you said, you came for the language, but you stayed for the community. You have to have a way to bounce back from things like that and handle things well.

And I think we've known Brett Cannon for years. We've never met Guido, unfortunately. Guido, come on the pod, man. Come on, man. Yeah. I know he's doing less of that. I actually asked him specifically. he's like oh brett's asked him for us it's a longstanding thing you know we have own drama around here

you know well you know keto's a great guy but he definitely uh has a lot of people oh for sure yeah for sure so appreciate him numpie take us back to the language for you like what were you doing for that what brought you to python why'd you like it why'd you pick it for numb pie exactly great great question so i am a scientist i was a electrical engineering student who went to the Mayo Clinic to study medicine because I wanted to help diagnose cancer and diabetes and instead of make bombs, right? I was, I knew, I was, I loved applied math, I loved electromagnetism, and I loved signal processing. And then I had this opportunity to go to the Mayo Clinic to study. And initially, when I was a master's student, I was measuring wind speed, I was sorry,

I was measuring backscatter radiation from the planet in satellites. It's called satellite scatterometry. and then from the information from that signal from the satellite, you could infer wind speed. You could also infer the things like vegetation coverage, ice coverage, and the lab I was in, we were doing those kind of Earth observation at the time. I was using, I was on a Vax VMS, actually, back in the day. We were using, it was programming C, Fortran, Matlab, and then some Pearl. So I just started to pull out Pearl.

And my experience with Pearl, in the back, this was back 94, 96. I would write it and like, okay, this is pretty cool. I can do the scripting. I can write some code. But then I'd come back three months later, a year later, and I had no idea what I'd written. It was like, it was write once, read never, right? And, you know, very interesting. Like, ideas were there and it was cool, but that was my experience.

And so as a domain expert who was using coding, I couldn't use it because I couldn't understand what I'd written past. So fast forward to 97. I'm at the Mayo Clinic doing work on Magnetic Residency, Elastography, trying to measure, I'd take a big MRI image and look at the phase of that image to infer motion. And from that motion, you could see a kind of a propering wave inside of tissue.

You could then try to figure out the elasticity, like how stiff it is, and make a picture of elasticity. So that was the problem I was solving, and I needed to find derivatives and compute them on essentially four or five dimensional data sets. So big datasets. And Matlab was, I was usually Matlab a bit, but I ran out of space,

and I didn't have enough, I couldn't change the precision well enough. So I was looking around for other ways to do this. I could just write C code, but man, when I write C, I'm spending a lot of time on pointer arithmetic and figuring out where memory references are. And I want to be thinking about my problem, which is, here's my volume of data, and I want to do derivative calculation. So if I have to write that, you know, if every line is like 10 lines of C, I lose track in

my mind of what I'm doing very quickly. So that's what a high-level language did, is give me a chance to be a, in my domain, writing some scripting or high-level conversations, but I needed to be fast, and needed to be efficient. So I was looking around for ways to do that in 1996, 97. And I came across Python. Python was pretty new. It had been around for still a little bit,

and it had an array library called numeric that I learned later had been written by Jim Hugganen out of this matrixig, which was formed in 94, right? And the language itself was written 91, but I came to it about 97, right? And it was still early, still nascent, you know, kind of his thing on the net that a few people were doing and it wasn't being broadcast or promoted by anybody, but the people who found it and then started to share their experiences. So I found it. I found, oh, this language actually feels familiar. It's like high level enough that they don't have to, the syntax doesn't get in my way.

I'm not worried about chasing pointers. It's just a straightforward language that also can be extended. So if I had C code that did something fast, it wasn't like, good luck, you know, run that a different process. It was, that's fine. You can actually load that in a shared library into the main, into this, into the language. Next, you could extend it. And numeric had already done that to make an array object. So if numeric hadn't existed, I would not have, I would not have come out.

I would not have started using it. I would have been using something else, very likely. So, you know, Jim Huganan and the Matrix Sig, Conrad Hinson, Paul de Bois, they were hugely influential in making that happen. And they don't get mentioned a lot anymore because, but they were, they were the OGs of array computing in Python. Paul, yeah, and I leave it off names, David Asher. I mean, you look at the, there's a NumPy book.

What I did early in 90, by about 98 is I made a chapter in the first, you know, numeric documentation that particularly covered how the C API worked. How if you're a C developer, how do you use numeric and make an extension using that? So that's what I became really kind of known for. And what I really, my super skill was, was blending Python and low-level languages. and releasing libraries that could do that. That's essentially what I learned to do as a grad student at the Mayo Clinic.

So fairly straightforward, very specific. That's what, but I had the opposite experience from Pearl because I started 97, I wrote some scripts to do some things. Fast forward a year in 98, I come back to the language, oh, that script, say, oh, yeah, I did that script to load those data and do this math. And I, wait, I understand what I did. Like, I can still read this.

This still makes sense to me. And so then I was kind of hooked. oh, this can work then. And so 98 was the start of my journey. And then 98-99, sci-pi really was really created in 99. You can see on the main list, the early mailing list there posts for me, like probably every two months. I'm like, here's a new module.

Here's a new library. Try this out. And just, you know, posting a tar ball. That's how we did it in those days. Here's the main list. Post a tarball on a web. And, you know, you can go to my website. My website was really dumb.

Just had a bunch of links, hyperlinks. not pretty at all and you could download it and they'd download it and you'd unpack it and then I would get patches I get patch files people started to send me patch files and I went oh this is cool someone from anywhere in the world is sending me code and yeah that's better yeah that's cool like all and then I decided to adapt or not adapt it so I did that for about seven different modules between 98 and 99 and then a few other people started the same thing one of the guys actually helped me he saw what I was doing because the modules I was writing it's things like ordering

differential equation solving, integration, optimization. It's things I needed for my research. I'm like, oh, where's the library for that? Okay, well, here's some Fortran code that does it. Then I just write the connector to Python to make that work, and then push that together an extension module, release it, and then tell people how to install it. But to install it, you had to literally compile it yourself on your code. Right.

So that's what I did. And then, you know, around me, people started to show up, right? sort of this people in the community started to show up one person showed up and said oh let me build a binary for windows installers and they did they wrote a binary installer for the predecessor to sci pi called multi-pack and then somebody could just go to the website and click and an exe they can install in their windows box and they could start using it right and that was huge so all of a sudden usage went up about a hundredfold right and that's actually why a guy like me ended up starting a company like Anaconda, right, which is all about getting the tools and the hands of people

easier, right? Because of that experience, like, oh, yeah, that was a big deal. Helping people have to get this stuff installed and used easily is a big deal. So, anyway, that's how I got started. It was that awareness of, oh, this works, and then the enjoyment of engaging with community-driven development. Of people, I share it, people come, they add things to it, and you have this community on the mailing list. And I finally, I think, went to a Python conference, probably, I think it was 2000 before I went to my first Python conference. I don't really remember, but then you go to a conference, and then we had, we started our own sci-pie conferences in 2001. So I'd gone to a Python conference before,

then we started our own sci-pie conference in 2001, and man, that just hooked me, right? You go to this, you go and you have these engagements with people, it's like, yeah, these are my people. This is, this is my crowd. And I had done a lot of scientific conferences. I've gone published papers and gone to MRI ultrasound conferences. And I like them. They're also very interesting, but a lot of those conferences, it ends up with people competing for grants

and for notoriety. And so there's not as much collaboration that goes on in those conferences. A little bit does, but a lot of times it's, you know, you give your presentation to an audience of people staring at you and not listening.

And then you get some questions, but people will come up and the question would be something like, this is interesting, but have you seen my work? you know why didn't you incorporate my way and it's like well okay that's I didn't mean to offend you but I'm just right so there's a lot of that going on and in the in the Python conferences I found a lot more collaboration how do we build it very proud and part of us because it's a practical problem solving a problem for people and they're using it they're scratching their niche they're solving problems they have and just created a space for that to happen and it was it was beautiful so the sci-fi community inherited a lot from the Python community but kind of organized its own story and So sci-fi came around in 2001 when Eric Jones and P.R. Peterson and Eric Jones and that's a separate story. But Eric Jones and P.R. Peterson have been also writing some modules.

And they said, hey, why don't we blend these together and make a single thing called SciPi that you could download? And SciPi was really a distribution of a bunch of these modules in one place. Masquerading as a library. We spent a lot of work kind of making the library work with different modules and different, you know, there's optimization, there was integration, there was special functions, there was a lot of things so that somebody could use Python instead of IDL or MATLAB or some other scientific computing tool. And initially, we were trying to get like plotting in there and a user interface in there, machine learning in there, statistics, statistics is in there. But eventually what happened in the side pie conferences, people started to go,

okay, this is cool. We really love this, but man, this is a big area. This is a big ecosystem. and having all these ecosystems trying to be managed from a single governing spot is going to be hard. Just bandwidth constraint. How are you going to decide what goes in and the government stays out? And so there was an emergence of the psych kits, not having at a sci-fi conference in 2002, roughly, 2003. And they basically said, oh, well, let's make a psych-kit learn and a psych-kit image. And sci-kit-learn became super popular. And then that was the psych-kits as a concept, they first started to call themselves psych-kit.

site kit learn second image then eventually it became why we have this extra layer of naming convention when we can just pick whatever name we want and then and then just have us you have different open source projects that are then just collaborating in terms of oh we'll use a similar documentation style or a similar pattern and so that that was the community I was deeply in the middle of from about 2000 until and I'm still I'm still in it but really active from about 2000 to 2013 timeframe um 13 years that's that's that's independent of the python community right and so then i kind of at about the time uh the sci pha was released the pressure came so then that was the sci-fi story and sci-fi came before numpy a lot of people don't realize that that my my baby was sci-fi and that was

this thing i was trying to make happen is makes python able to be used for scientists to do their work and publish and publish their work and have something that they couldn't uh they didn't have to rely on proprietary language for. I'm not against proprietary code at all. I'm not. I'm actually, you know, I think there's space for selling software. But I didn't want science, I didn't want scientists who are publishing their work. That needs to be a place. It's kind of, it's an open, it's a commons. There's an open technology commons that needs to exist. And science producing papers should exist in that space. And as a scientist, I don't want to have my scientific work be published. And then a consumer of that come in and say, oh, to use this, you've got to buy this

proprietary package before you can even understand my science. Like, science should be reproducible from, you know, I didn't want that behind licensing and IP barriers, right? So I'm very much for open science, open production. I'm not a big fan of actually the, you know, I understand journals, they have to have be funded to, but, you know, I want papers to be available, easily accessible. So that was really what drove me in this direction was the desire to be a scientist and and share.

And then I started to do that with software. And then I learned a ton about how software works generally beyond just doing scientific software. But that journey was because of my associate with the Python community. Because I was a young scientist writing scientific research code, essentially, and maybe some libraries and learning about, okay, data structures

and packaging systems and algorithms and high-level compilers. That came later. And when I became, what I would call one of the ambassadors for science to the Python community. Some of the early ones were Conrad Hinson, Jim Huguenin, Paul de Waugh. They were the ones who helped Gito add key features to the language.

And so I go into this in the documentary. I don't know how much of it's going to be in the documentary when it comes out. But I talk a lot about that, about how critical it was for those early science ambassadors to the Python community to have a voice, to be able to be heard. Because Gito's not, he didn't always know, like, why. He wasn't himself deeply involved in scientific computing, but he was open to hearing the input. He was open to changing things like,

okay, let's add extended slice syntax. Okay, let's add tuples can be constructed without formally creating the parentheses. You can create a two pole without just having the parentheses sitting there. And that was really critical for multi-index selection. And extended stride syntax enabled you to skip. If you had a big array, you wanted to skip elements. evenly, you could represent that simply.

Things like complex numbers. Like a lot of languages, they just say, oh, yeah, complex numbers are an implementation detail. Now, the problem is complex numbers are everywhere in science and engineering. They're so fundamental that, you know, really, when they're in the language, it matters. Otherwise, you end up with 15 competing implementations of them and nobody can agree. So having them in the language meant that they were there from the beginning. So I likely wouldn't have dropped to Python if complex numbers hadn't been there.

And as I looked into it, how did that happen? It was Conrad Hinson specifically, like him and other people who joined in the community and said, lovely language here, but we need a complex type. And then back and forth conversations with Gito said, okay, well, what letter do we pick for the complex representation, I or J, right? And the engineers won with the J. So, you know, those early conversations were that was possible by what I'm calling like scientific ambassadors to the Python ecosystem.

Yeah. And there's actually been very few of them, unfortunately. Like, we need more, honestly. I played a role, Nathan, you know, we had the Matrix operator added finally. That was a missing element for many, many years. So that's a bit of drama around how did Matrix operator get added. And Nathaniel Smith made that happen, right? And he was as an ambassador.

What do you do? Sneaking in the repo at night and slip it in there? Well, no, no, no, no, exactly. He didn't. Like, so I'll tell you how it works. Like, you have to actually go into these communities, whether it's a Discord channel, a public disgust channel now. You spend hours basically talking to people,

helping them understand why it's important, answering their questions, because a lot of them are coming from a space of, I don't know why this is important, and then kind of, so therefore I'm negative about it. Yeah. And as the language matures, of course, it gets harder and harder. Early on, the affect was, okay, I don't know about this,

but I'm a plus zero. So Python, this sort of story of negative one, negative zero, plus zero plus one emerged. You know, the early community said, okay, here's how we're going to vote on things. Right, plus one or minus one, but you can also do a plus zero minus zero. Okay.

It's kind of, I don't really care, but I'm leaning one way or the other. So help differentiate the different ways people might feel about it. That's still, it is actually very, it's very useful.

A lot of people use that actually to help kind of navigate this, you know, a lot of people paying attention, a lot of bike shed people, but like, who really cares? Right. If you don't really care,

why are we listening to your voice? Right. Because you're there. Plus zero. Yeah. Okay, well, plus zero, great. That's good to know. But, okay, let's figure out the plus ones versus the minus ones.

Understand that, understand that dichotomy and see if there actually is a compromise somewhere. Maybe it's a misunderstanding. A lot of times it absolutely is. A lot of times it's a misunderstanding. We get so deep in our awareness of something that's hard to be aware of another thing. I personally experienced that, bring as a scientific ambassador coming to the Python ecosystem, and getting some PEPs, except. did. So I became a Python core contributor by adding some Python enhancement proposals and going through that work on a few fundamental cases. And that was great. It was exhilarated. It's also difficult, right, because I was dealing with really smart people with knowledge in areas I was weaker in and I had to understand where they're coming from and then respond so they would listen and then understand how they needed to be communicated with. So they would understand where I'm coming from. Right. And we got, so one of the things about

NUMPI. So that was, that's how I got involved. And then 2004, 2005 time frame. So this was the state of the world until 2004, 2005, was SciPy on top of numeric with a bunch of libraries people were installing. Usually installation meant either build it yourself with a tarball or rely on a guy named Christopher Golki,

who was handling, like at that point, probably several hundred Windows.exe files on his own personal page. So there was no IPI. know, if you want to install this stuff, you've got the source code, you've built from scratch yourself, or you installed from this EXE page. And one time, I, in about, this is about 2000, when did we have this conversation? 2013? 2012, 2013, I talked to Gito at a PyCon.

And it's kind of just saying, so, okay, the packaging story, like, it's really bad, right? And he goes, yeah, I don't really care about it. It's sort of, it's not something he really worried about or thought about until later he did. But at the time, he's like, oh, you know, if I have a, if I have a project package I need, I just put it in the standard library if it's something I care about. That's got to be nice. Yeah, well, yeah, exactly. That doesn't really work for everybody. So anyway, that's kind of illustrative of part of the problem is that that wasn't sort of tackled from the beginning.

And we had a lot of challenges and trying to just, how do you, we have this great language for for getting the head of the person who just wants to solve a problem. and then they can think about their problem instead of the syntax. And super extensible. Like I can actually take Fortran code and make it accessible in Python very quickly. In fact, the guy named Piero Peterson who collaborated with me on SciPai,

he wrote a tool called F2Py. F to Pi would take Fortran code, analyze it, and automatically create the Python extension to allow that Fortran code to be called from Python easily. So he took what I was doing manually because I was basically manually doing that on a bunch of Fortran code. And he looked and said, what are you doing?

That's idiotic. And he basically built a tool to do that automatically. So he's far more of a computer developer than I am. I feel like I'm an integrator, an implementer, an agitator perhaps, you know, someone who can try to facilitate. And that's why it led to me doing more entrepreneurial activity than development activity over my career. But anyway, that's the story of SciPai.

When you're in an unpy, if you'd like, or if you have questions. about the sci-pie story and the ambassador to python and the kind of how did python become a space where science is welcome i kind of have a question that may not be directly related to python but more of the era because python and ruby kind of came out roughly in the same space yes they did and you said that you came for the language and state of the community and i think that ruby is just as welcoming as python has been to me personally and i'm kind of curious i've always been kind of curious why science related folks gravitated towards python the language and then even the community versus Ruby because that's a great great question both perfectly capable

yeah that's a great question a lot of this is timing i think like i found about ruby later after you know had already invested some in creating the scipa ecosystem right so and then new people essentially are just well what's there already right and like i said i was there when numeric already existed with ruby there where is the numeric ruby right who wrote that who wrote a numeric ruby ruby had a really really good community around web apps and they're there are ruby on rails for example phenomenal story for building uh you know quality like they're way ahead of the python community in terms of helping people build uh quality web applications on a python back on a ruby back end but where there was no numeric ruby maybe or if there was it was very nascent and so um it's kind of that critical mass

question uh and i think part of it being i think part of it also was of the language I mean I mean, Ruby had a, it was in Japan, a lot of, a lot in Japan, right? And I don't remember the name exactly, but Mots, Masaki, Motsat, Motsat, Mots. Oh, and I was Mats. That's all I'm all about Matt. Yeah, I just call him Mats, right. M-A-Z, Mats. Yes, yes, that's what I remember.

So he was really, you know, really talented. Then the community in the United States around Ruby was in a couple of companies, right? But they're like this, I think what happened with Python is Python because of this early cooperation impact from the Conrad Insight. the Jim Hugganin, the Paul Dubois, the David Asher, like that's what was needed for Ruby to really get that critical mass. And it just didn't happen for some reason or another. I don't know.

Maybe it did. Maybe those people got tired quickly because it's kind of people in academic settings that were able to pull that off. He's like, who's going to do this, right? It's going to be something like me who's a grad student in the Mayo Clinic, who's got more time than money and, you know, and then kind of ambition than sense to try to do stuff myself. And there were people like me, too.

Eric Jones, a grad student at Duke University. P.R. Peterson was an academic. So it's kind of an academic mindset. Ruby did a good job of tracking the scripting, you know, the web app builder, but didn't appeal to the science mind. Syntax is part of it. I think what appealed to us in the Python side is it didn't have extraneous syntax. We did, you know, there's all this white space arguments, right?

Well, the white space argument appealed to the scientists, right? just, you know, putting braces or you didn't need them, putting extra line noise that, that principle that Gito had, it really made a difference for people like me, right, who were like, I don't want this extra line noise. Because partly because of maybe the PTSD from the Pearl experience, Pearl, like, had all kinds of special characters. You couldn't remember what they did. Now, you know, Ruby's better for sure.

But I think that's a big part of it. But honestly, I think the question would be, why didn't the numeric Ruby get written? Right? Because that's what was there in 1994, 95. or did Ruby, does Ruby have complex numbers? Like, I don't think it does last I checked, right? And a lot of computer scientists go, yeah, who cares about complex numbers? And that's typically what happens.

You know, computer science building a language, and then the scientist comes in, cool, can we add complex numbers? And they go, you do it. That's on your own. It's like, well, okay, thanks. And then then 15 people do it. And then there's like, okay, which one am I using? Who knows?

Like, there's an aspect of leadership from the center that is required. to ensure that certain things get rooted. Now I can put a laundry list of things that didn't happen in the Python community that I wish would have that would have helped it even further. You know, packaging being one of them, having a really strong packaging story that's led from the early community

instead of like an afterthought later. I think self-like macro, like a way to not execute code. Like to pass on, you know, a back-tick operator or something that lets you put code, that is not immediately executed like delayed execution on code blocks with Python you can only do that

if you use like the width operator or you have to write you have to write a class or at a function like just being able to do that in line would have really helped in a lot of ways a lot of places and then I would love to see extended slice syntax available to be used as an argument to a function

instead of only within the list operator sorry that's just top of the head a couple of features requests but are really hard now to get in because you've got such a massive community. Yeah, you've got to convince a lot of people. Yeah, there's a lot of people. I looked it up while you were talking.

Ruby has complex numbers, but not until 2007. So back when you're getting involved. There you go. It's a little bit late to that particular game and probably because there wasn't demand for it. I mean, a lot of times you just build what people are asking for or what you personally need. You're not going to go out and say,

you know what this needs is something I don't care about, you know? Correct. So you need the people to show up and say, we want complex numbers, then, you know, Gaito says, okay, let's do it. Exactly. So it's a bit of a random walk.

Yeah, I mean, you don't know what's going to be important, right? You know, because that's why I say, look, it's because Conrad Hinson showed up and found the language and said, yeah, I want this and started to participate. And that isn't, that wasn't driven by, like, nobody budgeted for that. Nobody articulated that that Conrad did, right? Yeah. And so, and then other people like that, Paul de Waugh got involved. You know, then Jim Hogan, and as a grad student, he was a master's degree student at MIT.

He saw the Matrix Sig. He saw someone built a matrix dot pi in Python. He said, huh, I'll try my hand to build an array object in Python. And he did. He wrote kind of, and it was good. It was like a pretty, really nice array object with multidimensional arrays and some compute infrastructure. And he pushed that out there in 94.

And that was the foundation of, so that's what I would say. Where was the Jim Hugganen? And then later, I came in and I felt like, you know, I definitely added a lot, but I, I mean, I wasn't even been there if I haven't been for Jim Huggan. And some of these early people that have come on before. Snowballs. You know, things he was in. exactly yeah numpy came about because numeric was right was there and sci pi was like that was my baby i wanted

sci pi to get usage and adoption and people and more because i want collaborators right there wasn't so much the user that cared about it is i wanted collaborators i like my people to jump in and help build some really good computing tools i really got into loving the numeric computing like solving science problems with computers well that was a thing i really enjoyed so i want collaborators So that was for me, the driver. It was collaborators I could lean on. And then the Space Telescope Institute, Hubble, the people that shipped Hubble, they were starting to use Python and they're using numeric. They're using sci-py modules.

And they thought, how do I, I need a better array. They needed a better array. An array with more types, an array that handled memory a little better, was faster in certain circumstances. They had a couple of needs, right? And we were talking about that early as 2000. Right. And so fast forward two years, they started work on a project called Numeri. And they started to sponsor a project called Numeray, and they started to build it.

And they started to release it, probably 2003, 2004. So Numerate, and it had some really good features. It was nice. It did some things that were better than Numeric did. And that's fine. Okay, you could use it optionally. And then somebody, when it came, somebody released a medical imaging library called ND Image that had, and I was jealous, basically. They released Indy Image, and it worked for Numeray, right?

And so NDI image had something called morphology, and then n-dimensional convolution. They did a great job of implementing it, and it did it better than the ND-Colution algorithm I'd written that was in SIPI. And so, but it used Numeric. And so now there's Sipai on Numeric, and it's NMD Image Library on Numeray, and the two communities were basically, like, it was competition. It was competition, but it wasn't collaborative either. Like, if you were using numeric, you had to copy your data over to a numerate. Like, it was, and for a scientific and programmer, you end up using memory tons, like, because a whole other stream of thought would be, what about Pi Pi, what about the Jit compilers,

all that story, right? And we can get into that because I ended up in the middle of that later. But right now, in this point, it was, oh, how do I actually connect these two arrays? And I have to copy it. And I'm already struggling with memory. I'm using gigabytes of memory and I can't use another gigabyte to put it in a number array. So it was going to split the community and cause people the interoperability not to work very well.

So that's the problem I set out to solve in writing NUMPI. Well, friends, I'm here with Damien Schengelman, VP of R&D at Oz Zero, where he leads the team exploring the future of AI and identity. So cool. So Damien, everyone is building for the direction of Gen. AI, artificial intelligence, agents, agentic. What is AuthZero doing to make that future possible? So everyone's building Gen.A.A.A.A.A.A.A.H. That's a fact. It's not something that might happen. It's going to happen. And when it does happen, when you are building these things and you need to get them into production, you need security. You need the right cardrails. And identity, essentially, authentication, authorization, is a big part of those cardrays. What we're doing at 0.0 is using our 10 plus years of identity developer tooling to make it simple for developers, whether they're doing.

They're working at a Fortune 500 company. They're working just at a startup that right now came out of Wight Combinator to build these things with SDKs, great documentation, API-first types of products, and our typical OTH-ZO-D-N-A. Friends, it's not if it's when, it's coming soon. If you're already building for this stuff, then you know. Go to OthZero.com slash AI. Get started and learn more about OTH-FORgen-AI at OffZero.com slash AI. Again, that's off zero.com slash AI. So that's the problem I set out to solve in writing NUMPI.

And in 2005, I basically was a professor at BYU at the time and I said, ah, this is a problem, but who's going to solve it? Like, nobody's going to do this because, you know, it's complicated. And who knows enough to be able to do something like this? So I, there was a semester, a class fell through and so I didn't have any teaching load. And so I said, well, I'll just do this. I'll take the next three months and do this. I'd written a bunch of module for sci-fi, I'll do this.

That was in 2005. So that's where NNPI came from. That's where NNPI came from. Okay. A big part of the strategy was actually, well, how long we get an adoption? Well, let me go talk to Gito. Maybe we make NUmpi and we put it into Python. So I started to talk to Gito around that time, about how do we make the Python community

more aware of the NUMPI ecosystem? And maybe by putting NUMPI into Python itself. met with them about 2005, we talked about it, decided against it initially, but that is where the idea of the buffer protocol and the memory view object came. So the memory view object and the buffer, the extended buffer protocol, there was one already, we made a better one, that came because of those conversations. And I would say we got the data structure of numeric of NUMPI into Python, if not the library. Right. So that was, that was the, and that's how I became like this deep embedded ambassador for a few years, probably about seven years.

I did that for a while. Did that solve the problem of this division and this competition? Yes. Yes, it solved the problem. It absolutely solved the problem. So Numpai was wildly successful, way more successful than I thought it would be, honestly. It blew me away. It was work.

And I actually ended up losing my tenure track position at university because I spent too much time on Numpi. Oh, really? Yeah. Now I know why you're entrepreneur now, you know? That's what I'm, yeah, exactly. No, there's a deeper story to that, but, you know, it depends on which version of the story you want to hear. It's all, you know, the little sound bites never get to the full story. But it definitely had an impact on my academic career.

Huh. So, you know, but it was okay. It was okay. It was something I really wanted to. You know, you're a Python martyr. You know, you're a Python martyr. Exactly. Hey, if that helps people, if that helps people launch their careers, fine, right?

Now what I do is I try to say, look, if I can be helpful to you to build a company, to build a Python organization, to build a project, I would love to help. Let me know, because I've been so benefiting from other people as well. I want to help you do the same thing. Let me know if I can help. And that's what I do now, right? So it's a long history of all kinds of stories. You can see there's all kinds of avenues and places where you can literally, you could have a, you could have like a Netflix series. Yeah, totally.

There's lots of different ways to go. With the right writers who can begin the drama, you know, because there is. there's drama, there's people, and there's conflict, and there's, there's, you know, I don't know if there's any love interests. I don't think we've had enough romance, actually. You can always write that into the script. You write that in the script. Based on a true story, doesn't mean it is a true story, you know.

You got lots of liberty. I've had romance. I've got a, I've got a wife, and we've married 30 years. We have a great time. Oh, congrats. That's a long time. Yeah. So that's a bit of the scientific side of Python.

Yes. your subgenre, so to speak, and it's rise to prominence or why so many people adopted Python because the early adopters came, they laid the groundwork, people like you came after them, built tooling. Really, it was like, this has the tools I need. It's a nice language, and it grows and it establishes, and, like, people just start to choose it. What about, like, the industry side? Why did Python grow through industry? My only guess is, like, because Google used it, and, like, people wanted to work for Google, but I don't know. question. It has this similar multifaceted story narrative that also coincides with individuals

using it. And those individuals then go get hired by the companies. So one of the very first was Google, because Google started to, very early on, they used Python as kind of a, oh, this is a way for us to find great developers because the only people using Python are people who are care enough to go and do this on their own. And so they kind of use as a selection filter to find great developers. And so, and then early on, okay, you're here. All right, you want to use some Python, okay. And they started to use some Python internally. But it was, it was more because of the people they pulled in who wanted to, who wanted to help Python grow. But they, you know, they've built it. They've used it quite a bit, but lots of languages were support or supported

inside of Google, right? They've, they've supported lots of this open source growth. I think initially it was the people that drove it. And then, like my experience personally has been in the financial industry and in the the scientific use of coding industry where it was they were trying to solve problems and the scientists need to solve a problem you know one one character for example a guy named carot sing in who was uh had made the rounds between Goldman Sachs and then JPMorgan and then Bank of America until they went to his own company and every time he was basically trying to build a system for derivatives management you know and many people will understand and know a little bit at least about the derivative

empire, the fact that, you know, we have these underlying equities, then you have derivatives on them, the derivatives value could get balloon up, and it led to the 2008 crisis, all that stuff. Well, about 2008, suddenly that's when, you know, all the investment banks said, we've got to get our handle around this. And so there was requirements to build a system that would manage their risk assessment or their understanding where they are. And Karat Singh was there helping them build that, and he went, oh, well, let me just use Python, rather than Goldman Sachs had been in their own language. In fact, if Goldman Sachs had actually released their language, open source back in 92 or 93 when they built it, we might all be using slang, right?

Because, you know, they had this, they had something pretty good inside of Goldman Sachs way back then. It's called slang. It's called slang. Slang and SecDB is a database. Never heard of it. No, exactly. You know there's anybody else.

Yeah, they should have released it. You might have if they had this is open source. It's actually a good story to enterprise. And so enterprise is starting to learn that story, right? This is also part of why I think companies start to come to Python because companies, the So part of it is just the developers, then part of his companies realizing that they need to rely on these open source projects, there's been building dependencies on it, and they should start participating in it, right? And how do they do that? And I think that journey is still with us. I think companies haven't figured that out yet. And that's one area that I love to talk to people about because I think I have some insight, having seen so many things in this direction, both inside of big companies as well as part of big communities that are there. There's some, where's the friction and where's the real opportunity? But, you know, these financial community, they all start to build these tools around Python, right?

Because really of these key connector people. Again, and people have written books about this. You know, the Mavens, I think, is the book that is the word they use to these key connectors, these influencers, I call it technology influencers. Yeah. And it's kind of, you know, it's people that do a bunch of work. And then because they do the work, other people go, cool, you've done the work. I'll use it.

Okay. Right. And so then they build from there. It's how open source is diffused throughout the world. But companies started to rely on it for risk assessments. And risk assessment is mathy. Like there's a bunch of simulation, there's a bunch of array math you're doing. And so all of that leverage, the NUMPI, side pie, and related ecosystems that were emerging pandas.

So West McKinney was at AQR, one of the hedge funds that was a heavy reliant on Python. He and every single other hedge fund, heavily on Python, built their own data frame object. or something like a data frame object themselves. Wes McKinney was able to convince AQR to let him open source it. And then he spent further time in 2011 and 2014 shepherding that early release to make Pandas what it is. And he was a friend, connection, part of the sci-fi community. We knew him.

He was doing this thing. There were other libraries. They're also similar for a while, but Pandas ended up dominating because of his effort and influence. But lots of other companies now are going, ah, darn, we've got to convert internally to Panthers. this because of that same issue. So companies have learned, oh, either I open source what I'm relying on or I risk

technical debt of having a code base to maintain that nobody cares about. And the new people are coming in with different infrastructure, different story. So that's something I think has happened with the AI world. And I know specifically what happened in the AI world because of TensorFlow and Pytorch. and then in 2018 when I left anaconda which a company I founded to help make packaging work better and then other data science better actually basically I saw oh my goodness

I wrote NUMPI to bring the array communities together and 2018 there were literally 20 others but they're all around this AI story there's MXNet there's PyTorch there's torch there's Tensorflow there's so many of these other array libraries effectively now fortunately we'd fix it twice in NumPy.

Not only do I create NunPy, the array library, but also created a buffer protocol so that even if new array libraries existed and showed up, you could still share data. So there's a fix-it-twice concept. And then that's what we did get in there, so that, okay, great, there are all these array libraries, but at least you can share data now. You don't have to copy data from one or another. Right. So that's at least the saving grace, but they're all over the place.

Each one of these companies, they did it, you know, primarily they wrote, like, PyTorRs start as a Lua library. There's a C++ Lua library, and there's three versions of it. TensorFlow is a C++ library called Disbelief. You know, each of these have their own internal organizational C++ stories. They started a launch of in 2015 time frame, 2014, 13, 13, 14, 15, started to put these libraries out there. People started to use it. Well, at this time, there'd already been 13 years, the Saipai ecosystem and the SciPy Conference.

And a lot of academics and the very first machine learning library, Theano, was right in the middle of sci-fi ecosystem. So a lot of these first early array, these early papers on machine learning were Python-based. And so when these big companies came and shipped their libraries, the community said, where's your Python interfaces? And it demanded their Python interfaces. And then, oh, okay. I mean, I've heard this story specifically from several of these people inside these organizations. So then they went back, okay, and they built the Python interface, sometimes badly, TensorFlow,

sometimes better, TensorFlow fixed their problem by buying Keros. Keros was a good interface. And so that's the interface for TensorFlow now. That's great. But Pytorch from the beginning, because they were in the research lab, they from the beginning tried to build community around what they were doing. And so because they did that,

they were actually able to get more scientific embedding. So a lot of this is how a company goes about doing open source. Matters a lot in terms of its longevity and how it's going to be, I think who's going to win. You can predict based on how they're approaching the open source ecosystem. And PITORCH did a better job than TensorFlow, even though Google invested in a group to try to make that happen. But the problem is it's not just having a few people do some podcasts and do some DevREL. It's actually how are you managing internally?

Like what is your story internally? Like do you like on the meta side, they had Pytor, which is a public thing. And then they had the meta application of PITORC that was separate. On Google, the difference between the TensorFlow developer development and their internal use. of TensorFlow was not very separate. So they really couldn't open TensorFlow to wide-scale, you know, input because they depended on it heavily. And therefore, they couldn't just allow, you know,

some random pull requests from a community upset their own internal usage. So you have to manage that. You have to manage your, if you're going to be serious about engaging with others in your open source community, you have to put a bit of separation between your community-driven sponsorship or community engagement and your internal development processes. If you don't, you're not going to be able to manage it. You know, some version of Conway's law, you know,

where the software resembles the organization. The corollary of that is if your organization relies on the software structure, you're going to hurt your organization because, you know, you can't have your development teams and your delivery teams dependent on a random pull request from somebody in Estonia that you can't, that isn't working for you. Like there has no, you have no ways. to kind of keep, hold them accountable other than just stop using their code.

So anyway, there's a lot to be said about that. Actually, as corporations started adopting open source, this is not well understood by the open source communities often, or it's better understood by the internal development teams because they have to. But open source communities sometimes don't understand that, and then they get a little confused by corporate actions. They make the wrong assumptions about what companies are doing and why. And that can lead to some friction, misunderstandings,

and miss, you know, people feeling like they shouldn't support something because they're reading into a corporate action that isn't true. It's just a consequence in the lack of a PR statement from somebody in the organization. That's a whole other topic, but we often get involved in conversations like that with the corporate side. But the open source community side, it's just a massive ecosystem. And corporations adopting open source because it helps them. Actually, Zuckerberg probably said it really well, most recently. I don't know how he feels about it right now with the recent AI changes.

He's kind of, but previously he said things like, and I think it's valid, by releasing open source, you can actually influence the direction of the industry's going to more align with your internal choices. So you don't have the slang moment at Goldman Sachs or the pandas moment at any number of unnamed hedge funds that had to adopt pandas instead of their own data frame because they actually recognize the open source the way to align industry to your roadmap. That's certainly one way to contribute it for sure. I mean, if you're if you're that far ahead to be a leader,

I think a good example was probably like Borg and Google and Kubernetes. Yes, yes, yes, yes, yes. But it was graded internally, but didn't make sense externally because Google is Google, right? But Kubernetes, an orchestrator engine made a ton of sense. And the whole story is different now because of that. Yeah, actually, Kubernetes, great, great point, because I actually knew the person who was in charge of both TensorFlow and Kubernetes at the time. And they wanted to kind of figure out how to, you know, get community involvement in those two.

Kubernetes succeeded. TensorFlow did not in that regard. And I think you had a big of a great point. And part of it was because they didn't really depend on Kubernetes internally. Right. It was just a thing that came out of their story, whereas they did depend on TensorFlow. Yeah. Is part of what you're saying, and maybe this isn't the point of this conversation in the grand scale,

but it's part of what you're saying is when corporate control permeates into the development life cycles of the software, it begins to mimic what the corporations want versus what the community and the technological folks need. Yes. Yes. It's actually that juxtaposition of corporate constraints and therefore corporate control and community needs, which is broader. It's kind of, it's kind of, because the community needs includes other corporations,

but it's basically the broader set of infrastructure needs, that everybody needs. And how much of that is the corporate willing to give up for the benefit of other people contributing, right? Because, you know, why would a company do this? It's the 80-20 rule, exactly, exactly. because a company could just do it themselves. Great, just do it yourselves. They have their own story, who cares.

In fact, a lot of companies have often, I've given talks at organizations where they want me to talk about, how do we adopt some of this open source ethos in our 100,000 develop, I mean, we have 100,000 people here. And we would love some of the energy that happens in the open source ecosystem to happen here in like a private mini, you know, open source enclave. Just even if it's not to the full world, but at least it's inside of our company, people are more aware of it. Like, how do you do that? So we've gotten into some of those conversations about what are the incentives that drive open source? How do you mimic those

inside of an organization? Can you? One of the critical things to me, and this is also why goes back to the people stay for the community, it really comes down to respect and ownership and accountability. And do people feel that in the community? Do they feel like their voice matters? They feel like when they contribute, it's not just ignored, but it's heard. And then And furthermore, do they do something that they feel pride in? Because, like, this is the thing I built. And I show it to the world, right? And that's what open source enables for engineers that inside of a big company doesn't

happen as well. You know, you go to get another job and you're like, cool, I did all this great work. Well, can I see it? No, it's over there on their repo. I can't show you. Whereas if it's open source, here it is. I can show it. And I see a lot of developers, a lot of engineers have felt like, oh, this matters to me

in my career. I need to do that. Now, what's what I'm finding is that it's actually, some of the, of that spirit, that energy, that ethos is not there among the early, among the new, new developers coming in that there used to be. And so, you know, a lot of people new to the new to programming are like their GitHub repos aren't great. They haven't really contributed open source communities. They're kind of, let me just get that job. And, you know, my advice to a young developer is go, go find a few open source communities you love, you get excited about

and start participating in them. Just show up, you know, hear what the problem is contribute something to it. If it's documentation, even if it's just, you know, oh, read me for a new, a newbie. Like everybody, if you're new, great, you have a power nobody else has in the community is you're new to it. Everybody else has been there a while. They don't know what the problems are for someone new adopting it. So great.

Document your journey and write a story for a new person, how to make this more accessible. There's a lot you can do, anybody can do to participate in open source and do that. Okay, maybe you can't do it 20 hours a week, but do it for five hours a week. Do it for an afternoon. Do it for a weekend. That will have more impact on your career than sending out resumes. Because it just helps, there's a correlation between your participation in open source communities and your ability to contribute to a corporate community.

Now, it's not one-to-one. It's not identical. And the reverse isn't always true. There are also people who struggle to participate in open-source communities because it takes a bit of, you know, thick skin, a bit of, I can work remotely with people. I can communicate via text or email or and maybe you're not good at that you're better in person, you're better at, and so there are, it's not the only way

but if you do, if you can participate it's easy. Well, you can always just go practice that leak code problem you know, that's what they're doing with their time too. That is true. That is true. It's like which one do I do? I don't know. No, I've had that conversation with someone on LinkedIn who was asking me, how do I do it? I said, well, okay.

But you know, I can just share my experiences, right? I mean, you know, some of my experiences might be relevant for the future and, you know, some might not. You know, it's because things do change. But I'm happy to share my experiences. And if anything, if anything is helpful to somebody, I'm more than happy to share. I'm super eager to help people. Like, I want to see a world of more owners. I want to see a world where there's distributed opportunity to collaborate.

What I've loved about the ecosystem I participated in is when people come to the table, like it's a round table. Like I like these roundtable. I understand the role of hierarchies. They're helpful for certain things. But I love when you're in a room where people feel like they can contribute. And they have skin in the game and they have something they're trying to contribute. I've definitely seen the decline of the GitHub resume emphasis. Yeah, I wondered about that.

I don't think it's gone. I think it's declining. But that being said, I don't actually disagree with you. I think that people should do that. but maybe do it a little bit more I'm not saying you have applied intention but like maybe do it for the love of the game and I think maybe like your

portfolio your resume whatever could be a nice side effect of you but actually it's fun it's fulfilling thank you Jared yes pay it forward there that really is satisfying yes nothing I've done would have been possible if it didn't love it

yeah the only reason I did it because I loved it it was actually something I really loved doing I didn't know if I mean it wasn't because oh, I get a job if I do this. Right. The opposite, sometimes. Like, actually, I lose my job if I do this. Yeah, I've seen a lot of people that they're like asked about their open source work

and they don't really have any. And so they think, oh, I need to go have some. And if the goal is to, like, have, you know, the green dots on your contribution graph, well, of course, that can be gamed. But if your goal is like to have some open source because you need to have some open source, that's ultimately going to be empty and not very fulfilling. That's kind of the same thing. And not very impressive either because you're like, oh, cool.

I open up a PR on some meaningless thing. So like, if the right intentions are there and stuff, it all works out. If not, and then it is, you might as well practice your lead code. Yeah, a thousand percent agree, Jared. Yeah. Very well said. Side tangent, you were talking about all of these, the tensor flows and the pandas and then like all these things that were like kind of competing or burgeoning out of

in his messy way on the scientific side of Python because of machine learning. needs and because of industry driving these things and that got me thinking about mojo and i just wonder your opinion on mojo which is the pythonic language that's like right in that wheelhouse yes yes so i'm excited by this kind of innovation right uh in 2012 uh when was it 2011 2012 i started a project called numba at the same time there was a language called julia that was emerging. And Numba was a Python compiler that took a subset of the Python language

and made machine code to make things fast. And we actually, by 2013, we're targeting GPUs. So you could actually write Python code that ran faster than any C++. Like we were showing that in 2013 at the GTC conference at the NVIDIA because you could basically write Python code that would run on GPUs directly.

So I love that whole space. Like this is something that it took me a while because I was a, this is when I finally learned how to write compilers. Now, I wrote the first version, then quickly found other people to make it better. But, but I took a, I actually took a pilot class from my friend David Beasley in Chicago to try to understand, at least have something besides just what I picked up in the internet. Right. And that helped me see the vision for, oh, Python can be actually orchestrating compiler tools. And there's no reason you can't just write syntax that's

pythonic, looks pythonic, and then have it compiled the machine code. There's a zero reason that can't happen. So there's no reason you have to use C++ or Ross to write machine code. You can totally write a subset of Python and have very fast code. And Numba proved that and proved it pretty well, actually. And so

since then, since then, there's been like 20 other versions of that. Like right now, there's a if you go to L-Python.org, L-Python stands for L-L-V-M-Python. It's a example of a compiler for Python, LPython.org, and a table there shows a list of other

similar projects. Some of them are a little bit more like Mutica, where they're translators from Python to C++. Others are like Python is another one. Codon's another one that's out there. Like, they're literally a dozen, all right? And so. Yeah, I'm looking at the table. It's probably two dozen. Two dozen. Yeah. Now, you know, all of them are kind of this example of scratch your own niche, something that's, you know, that's built. You know, Numba has a team that Anaconda still working on it. And so it's actually received a lot of support. And so it's kept up to date with the latest releases. And there's a lot of every time the bytecode changes, Python, Numbus got to change because it goes from the bytecode on. And you can actually write, there's also a tool called

Scython out there. Scython was in the same, it's not exactly the same, but it was like, oh, write it in this language, and then you can write extensions quickly. And even something like F to Pye might be considered in that category. But Scython, Numba. So I love this space, right? I would say so Mojo is great because Christian was one of the original creators of LLVM. And Numba depended on LVM. Like so I've been an LLVM fan for a long time. So I'm like, well, this is awesome. We get kind of the OG kind of bringing Python to compiled languages.

Awesome. What's going to do? Let's make that happen. I think what I'm hopeful for, and I know he's got funded and there's a company structure there. So some of the same concerns about, okay, corporate capture of communities and how does that work? I don't think he's actually even had those conversations yet. I think those are, you know, so right now I'm very hopeful and excited by the technology innovation that will occur.

And I'm cautiously optimistic about what that might mean. I know that he wrote, I think one, very concretely, he transformed objective seed of Swift, essentially with LVM. And so I think part of his thing, and I talk to Christian, so I know a little bit, but I don't know him 100%. But I've had a couple of conversations with them. about what does he think? Where is he trying to go with this? I think his experience making Objective C users moved to Swift was pretty easy, right?

Because Objective C, it's kind of all the Apple community. Right. Python's much, much different. If you're not going to have the same experience, you're not going to be able to take the whole Python ecosystem and move them to Mojo in maybe in a decade. You could pull that off, you know, or billions of dollars. Like, you know, money might be able to do it,

but that money has also got to be able to hire the right. people to have the right connection points so you're interacting with the right communities because you can't just you can't just have great tech and then and then push it on people and then but so I'm eager I'm open I'm really eager to see it but I'm okay is is Mojo open source yet is it you know is a community driven how are decisions made and it's all early days so I don't I don't I don't I don't these are hard things so I'm right now I'm of the attitude I'm excited I love seeing what he's going to come up with because he's a brilliant guy and I want I want to see an explosion of languages that are Python-like that enable the Python ecosystem to actually make

run time, make fast run times starting from Python syntax. I know there's a lot of enthusiasm around Rust, and I don't need to dampen that enthusiasm. I like Rust, too, but I think there's far more low-hanging fruit in just having statically typed Python. In fact, I call a little project we're working on at Open Teams, but it's very early, and it's not, you know, it's not a Petitor Mojo by any means. It's called, I call it Post Python. Performance optimized, statically typed Python. Okay.

And it's basically saying, oh, Python now has type, annotated types, optionally annotated types, right? Now, you can use them for lots of things, but if we just, with this post-Python language definition spec, so post-Python is about creating a spec and a definition with lots of runtime implementations. So in my ideal world, you know, Mojo, Numb, cython, codon, all these, and then Jax, PyTorch, these are also, you know, compiling subsets

of Python. PyTorch does it directly, jacks does it directly. If these could all have, oh, here's the syntax for a statically type sub-language that if you write, if you format this way, then you can compile it, and then these become compilers. So my world, you have a standard that allows people to, and then you have implementation of that standard. You can almost see it like SQL. So will we get there or will Mojo become that by de facto or will pie torch? That's a good question. I don't know. Yeah. I would love to see more cooperation here. One of my concerns is these these are challenging problems. And so the communities in them end up being siloed pretty quickly. And they don't look at each other very often. And so because you've got, I'm just naming a few. There's many,

many more than I've seen over the years. And they're all siloed. And they all don't really talk to each other. So hopefully we get cooperation between them. Do you think VC funding is the reason or promotes the silos or no? I think it's been promoting the silos primarily. I think where we've gotten the funding from the strategies, from the corporates have helped break them down, like the big funding, but VC funding has encouraged silos.

I've actually been an outspoken critic, not that outspoken, but I am a critic of the GitHub star funding model of VCs, right? For a while there, it was like, oh, you're GitHub, I see your GitHub here has many stars. Here's $5 million. Right. And the trouble with that is there is not a one-to-one GitHub repository to company mapping.

You can't just trade those in for dollars? Yeah. I don't mind. In fact, we could have another conversation. I think I've got a way to actually create a market for that. But it's not as simple as – because I have a VC fund too. I've started a VC fund, right, for this purpose of helping entrepreneurs create. Okay.

And we've got 14 companies invested in. I've got an idea of how to actually create a – marketplace where you can actually have GitHub stars be a market driving question and investors are actually looking at, okay, this project's going to be used, great, I'll invest there, and then have that investment dollar go to support the development of the project while also having to return at some point from somewhere. Because that's the thing you've got to figure out. You've got to build an instrument that drives the return to the investor from the risk they

took to invest in that project early. And, you know, a company is one way. Yeah, just have a company and ownership in the company and the company sponsors. that is. But can we do it in a way that actually allows many companies to collaborate and still have the benefit from that, from those, the time that somebody spent investing on that project, iner to them as the companies that rely on it develop? I think I've had an answer to that, actually. It's, it's my BHAB, my big-haer audacious goal is to bring that to market in the next five to 10 years. Really? Behab, can you say that again?

Be-Hag, big, hairy, audacious goal. Oh, B-Hag. B-Hagg. It's a dumb acronym, but it's, it's, it's kind of like dreaming. It's kind of, it's what I'm dreaming about now. It's like, how do you actually make open source intimately connected to the growth of market, of companies? And how do I, how do I make more owners? How do I contribute to making more owners? Obviously, I'm not going to do it myself, but how do I contribute to a world where there become more owners? That's one of the problems of my lifetime is our, our Western societies, especially the United States.

have decreased ownership. There's like fewer, there's more and more money and fewer of your hands. And that's not great for society. I don't say your phrase. You will have, what is it?

You'll own nothing and be happy, Adam? Yeah, as you say that Adam. He brings that one up a lot. No, it's true. You'll find yourself owning nothing and being happy. And okay, yeah,

there's a pill you can take for that happiness, but. I mean, I would love to hear this idea. What do you think, Adam? I mean, are you sharing this idea right now? Are you just building it? No, it's out there.

It's out there, but I'm building it privately. It's under, but it's been incubating. I, the challenge is I can't, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's, it's, the beginnings of that idea, which we, we, we, we, we, we started a couple of several years ago and now we're just resting on because I don't, I know what to do, but I don't have the money. I need about $5 million, right? Right.

So if, if somebody, but that $5 million, dollars can't have a bunch of strings attached that, that the guy that basically say, here it is, I'll check, check, check back with you in five years, right? That's what I'm looking. for it's um yeah it's not how investment work no exactly i like to go on the record i'm also looking forward for that yeah yeah i know that's not how it works exactly check back in five years yeah exactly this is why well you can check back in there you know every we can read reports but i know what you mean we're just but you know it's like you know this is going to like and and really for the five million to return money on it is going to take five years it'll have impact before then but like

you know, it's seeding an ecosystem and seeding a story. The idea is pretty simple, right? Effectively, you just have an organization that, on the one hand, it works with open source communities to document their dependencies, both their dependencies on code and their dependencies on people. So essentially, I call it a, it's their end dips, their millibips table, right? And they basically have a basis point, and if you do it a thousandth of a basis point, you basically have 10 million units to give out for every project.

And a project governance essentially gives out basis points for dependencies. Like, oh, I'm Numpi. I depend on Python a lot. So we're going to give, you know, 40% of our cap table to Python. Right. And then from the rest of it, we're going to give, you know, award it to people. And you have someone reserve and as people come in and make contributions, the governance can actually go, oh, here you go.

here's you know here's ownership here's um so you basically have one side helping people organize that because there's a specification you stick in the GitHub table and it's there and you can say oh this is you the project have decided a cap table basically you've constructed a capitalization table for the project right and it's it depends on the governance you know it's not our decision now what we can do is to drive that as ferroSS could essentially have a default approach to doing that so it says well this is what we'll use if we if you don't tell us what not to use this is how we're going to do it and then of course to encourage them to do that so we don't wait we're not gated by whether they preficit or not so you build that and then and then to the companies you go to companies and say hey you're missing from your cap table

your employee option pool your investor group the warrants you're given out to partners because this happens all the time you're missing all the open source ecosystem from that group and so let's get on your cap table. So we get on the ownership table of a company. And of course, you know, we can't get a million open source contributors on the cap table. Okay, great. We put an entity on the cap table. And the entity on the cap table represents the open source you depend on. So you have an entry on the cap table and Ferrosus maintains your dependency, like their Milibs table, like what do you depend on? Right. And it's and then as equity returns happen, which is distant usually. It's like as a venture capitalist, I know how this works. And you basically, over time,

value will flow. Now, if you want quick value, it could be maybe you're not going to give up equity. You're a mature company. Equity is hard to come by. But we'll do a dividend agreement, like anaconda's and dividend agreements with an agreement where we'll just allow some of this to come. Our venture fund, for example, we already do this with our carried interest. Like we have carried interest, which some of you know what that is. It's the, it's the motivation for the partners to find good deals to invest in for their for their LP's money and then they get a percentage of that growth and so we our general partner some of that carried interest already goes to fund open source right and so it's the same thing we can formalize it through that process you got all these

now you have all these inputs right you have equity deals you have dividend deals you have carried interest deals that are going through this instrument that becomes the funding source for all the open source dependencies and then as opportunities arise you're just streaming it out distribution style to the cap tables and it flows down the cap table tree is oh you're you're dependent on pandas well pandas looks like oh it's dependent on python and numpy and then it flows down until you end up at the leaf nodes where there's individuals who are basically getting participating so that's the basic idea and then what i did i tested that out with a few companies because i actually get these agreements could i get people to agree to that and yeah and i thought i'd have to have a venture fund actually

the whole reason i started a venture fund in 2019 so i thought i would have to go go to startups and say, yes, I'll invest in your company, but you have to do this. You have to put open source on your cap table, right? Because I knew they would say yes to that deal. What I found is I actually got people to say yes without the money. They understood the problem. Yeah. And so I went, oh, okay, that's good because, you know, it's like reg X.

You know, you use reg X to solve string parsy. Now you have two problems. You have the problem I was trying to solve and then understanding regex. Same thing was starting a venture fund. Same thing was starting a company. I started anaconda as a company to solve the problem. How do I fund Numpai? How do I fund Sipai?

How do I fund Sipai? How do I build this thing? So my whole life has been like, okay, here's a problem. How do I solve that problem? Here's the meta problem. Here's the next problem. How do I solve that problem? And they're just trying to learn along the way. And just try to figure out ways that are learning from other people, trying to organize.

Because what drives me is I want to create a world where open source is a meaningful way to live a life. You can be an open source contributor and still pay for your kids and still have it. That's a job. And it's meaningful. It's not just the thing you do on the weekends and nights and when your day job is doing something else. So this is why I've been thinking about this. And fair OSS is the epicenter of this? Yeah, it's the first version of the organization we've created to do this, right?

And it's an idea of how it could be done and we've tried it and enough to know that I know it will work. But for it to work and to create the vision of where you can actually have investors, Because eventually we'll have, you have a ticker symbol for every open source project, literally. You have a market where, oh, how's this open source project doing? That's going back to your stars. Your GitHub stars literally could translate to a value, a fair price, a fair market value for that open source project. And investors are looking and going, oh, yeah, I want to buy some of that. Right?

Because it could. They could say, oh, I'll put in my portfolio that project because I think that's going to go somewhere. And how is it going to go? Because people are going to depend on it. And therefore, enough of these agreements are in place where value will accrue because of those agreements. in place. So FerroSSS puts the instrument together. It's responsible of creating the instrument that connects the dots

between the investor money and the open source communities. Well, you need is a dependency graph versus the GitHub stars. I understand the analogy. No, no. You have to have the dependency graph. But that's also what FerroSSS manages is the dependency graph of those milibibib stables. But that's the

evidence to show the, you know, should or should not be on the cap table, right? Like that's the that's not a star, which is I like this, or this is cool. Correct. That's not what gets you on the cop table. What gets you on the cop table is one,

it's just one entity. So, you know, a company is not going to put a thousand people on a cop table, but they might put one entity on the cap table that represents those people. And you're saying that at some point for an open source project that may be of that caliber,

they should have or might have either their own foundation representation or FerroSS is that representation. Maybe, yeah, VerroS could be that representation. Maybe they could do their own. Ultimately, it's, it's a net it's a market right so it's a there's a markets are very complex with lots of parties right but the the project itself all they do all they have to do is just track their millibibs table

they just have to put and document and record well who who gets what like who who's who's accountable for this it's like a thanks file but it's like a thanks file with a number next to it like a percentage yeah it's their own cap table it's their own and they manage that that that is old that is used to build the dependency graph that allows the flow through to happen from the entry point, which is just the company that puts FeroSS in the cap table also submits their own high level millibus table. Like, well, this is what we care about. And then FeroS also, there's stuff around here to support that. What you need is to be in the IRS, you know, the tax code to make this have some serious incentive behind it because at that point, every company would actually do it.

This is a separate question. I potentially, I agree. I'm trying to avoid creating a ministry of open source. Like, yes, some of this could be facilitated with government as long as it's automatic and rule-based and not bureaucratic. Well, not even so much IRS, but like recognized by the business nature of the United States, right? Like LLC versus S-Corp versus C-Corp. There's a reason why companies form one of those because they're recognized.

No, 100%. In fact, in fact, the way this would be implemented is actually. through an series LLC. Like, because essentially what you'd end up with Ferrisus doing, like what it does, it says, okay, we have an LLC representation for you, project, or your corporate, or whatever it is, that's representing your,

because some products have one and some don't. Right. And so, anyway, yes, I agree with all that. I would say to your point about the IRS, what I would love to see, I would love to see the United States actually as a separate thread, have a sovereign wealth fund, and allow deferred taxes to be paid.

Instead of you have a tax, you just give a part of your equity to the sovereign wealth fund in the United States. If they could allow that to be used for, there's a ton of places where it's the tax code. Like, I've been looking at this a long time. And so much of the inhibitions, the problems we face are because of outdated SEC code, outdated tax code

that was meant for a different time that's now stopping innovation in the business world today. There's so many lawyers, so many people get paid, so much effort is spent, you know, essentially preserving yesterday's infrastructure, yesterday is business infrastructure. It's hard to innovate in. And there's no legal precedence for it.

Like there hasn't been a case. Correct. So you can't say, oh, yes, we should or shouldn't do this because there's no case law that represents how the courts may or may not lean in proceedings. So a big part of the challenge is figuring out how do you fit in that existing case law, but still do something innovative, right? Which leads to a lot of challenges. It really does.

Are you doing this? Yeah, that's why it takes $5 million at least to get the. this going. We've done it already. We'll get this $5 million.5 million bucks. Let's get this money. Well, if someone wants to buy anaconda shares, they can buy them from me and I got the money. So that's what I'm doing with my next tranche of anaccia shares. You need some liquid, man. I can get liquidity if someone just wants to make a bet on anaconda.

I'm happy to share that bet with them. So just, you know, if you hear this, contact me. And maybe you want to fund this, but you want a hedge, great. You can own anaconda shares, let me take the risk. I'll do it. Okay. So that's an option. I like that offer. Yeah, anyway. So that offers out there to anybody who wants to talk. I like this idea thinking about it slightly more deeply. It seems like there's a bit of a impedance mismatch between

the value provided by the open source projects and the companies that would then adopt because you're basically relying on you're going to be adopted by winners and you might not be. Yes, correct. But you're still valuable, but just to losers. You know what I'm saying?

It's just one part of the funding fabric. First of all, I don't think it's the answer to everything. Sure. But it's something that should. exist. And it's also the investor class. That's the part that we, you know, it's not just the companies, but when I realize there's at least $100 trillion of investment money out there looking for alpha, which is like looking for return. And that's in people's retirement accounts. That's in investment accounts. It's all the world. All that money is looking for investing. Where are they going to put it? And so a lot of times they, you know, property values go way up. Stock values get

way overvalued. They can need a place for that to go. So you have that investment value. Then you have open source where innovation's happening because you look at the past 10 years and innovation that's occurred from AI to cloud to data right it's open source communities that have been at the heart of that but yet there's not great connection between the investor class and the open source community class okay so imagine a world where ferro SS is running okay yep yep and there's it's active and it's vibrant yep and I'm an investor and I want to put 10 grand on numpie yep exactly what happens there's a site you go to and it's like it's traded on a public market maybe it's crypto maybe there's a crypto token associated with it that's what i was hoping that crypto would actually help this emerge

quicker onto public markets yeah like there should be a place you just call your broker or you go into your own online thing and go yeah i want to invest in numby cool it's a ticker symbol you just put it there great now at the moment that's going to buy somebody else's position but the project numpy could say you know what we're going to make a release we're going to we're going to authorize you know more ship more of our millibips table to investors. And they funnel that up through and say, we've got now $10 million that can be purchased by new buyers. It's a kind of IPO.

Then you're buying their upside. And you're buying their upside. Exactly. So again, the NumPi community and Ferrosis would mediate the relationship between the community that has to essentially go, yes, we're willing to take investor money because they're the ones that have to take it and do something through their own governance or however they're going to do it, right? There's somebody that has to take that money.

Ferroassist just facilitates the connection between that and the market. And actually, that particular entity would be a different company that would be actually the broker, the broker dealer between the projects and the market. Yeah. That's a separate activity. The current thoroughassist organization is intended to be the arbitrator of the millibibs tables. The middleman.

Yeah. And then kind of the negotiation of the contracts with the companies. Right. And then you'd have a broker-dealer that would connect the two and make a market. It's long-term, you have a marketplace. The Chicago Mercantile Exchange exists. Why? Because somebody put the idea of an option in a future out there and started selling them.

Right? It's just that. Like, New York Stock Exchange exists because the idea of a corporation was created. Then somebody started to sell them. So you make a market for it. This dog could hunt. How much have you been able to convince these companies? So I have, so I haven't really, the problem, when I left an account, I had to build this whole other thing.

And so my time has been spent building. including KwanSite, Open Teams Incubator, my funds, and then Open Teams now. And so I've been sent so much time there, but this has been in the back of my mind since about 2019, 2020. So I've had conversations on the side with multiple companies, enough to get dividend programs. Like Anaconda has a dividend program. You know, lots of companies are willing to the dividend program. That's an easy way to fund it.

And then I've got a few conversations with funds to say, hey, you've carried interest. And then startups, I've had 100 startups willing to put, put, Ferro assist on the cap table. That's been super easy, actually. Well, it's good question. So the highest is like 10% of their company they'll put on the cap table. 10%?

Mm-hmm. That's a lot. It is. It must not be worth very much. It's really dedicated. It's startup land, right? Because startup gets deleted, right? And it's like, and the argument really goes like,

hey, here's a way to get. And for that, they're going to want more, what they're going to, what they want is connection to the open source communities. They want for their hiring pipeline and for improving they're, because the startup, your most important thing is the people you hire. So if Ferroset can provide an opportunity to hire, then it's worth that. Right.

So it's worth, so that is high. Mostly it's like one to two percent. It's pretty easy. And as the company matures, you know, maybe a big company like Anaconda, it ends up being like 0.1% is all it is, right? Or 0.5%, right? But that's like, you add that up and that's a lot. If you actually took, you know, and you only have, let's say, a few basis points on every company.

And a lot of companies, they're throwing, I mean, they're putting more of that in their option pool for employees. And that's kind of where you're, that's where you're arguing. You're saying, okay, here's your option pool for employees. You need to recognize that there's a portion of this that you're not either taking advantage of and you're missing. And that's where I've had the best conversation with people.

They go, oh, you're right, that could help. Now what can, and then what they're looking for is, well, how do I, the company wants to know, well, can I connect that to feature requests? Can I figure out a way to kind of connect this to community connections or hiring? or, and that's where we can talk about that, right? Because it could be a milestone-based vesting on that pool. There's ways to negotiate that.

But that's what FeroSS does, is create the negotiation to create them to increase the side of the instrument market. That's why I couldn't, it was my view is that has to develop, and then we can build the marketplace for the broker-dealer where you can actually get investors to come in. But you have to build this before the investors will come in. Anyway, that makes sense. Anyway, that's my big hair audacious.

goal and what I'd really love to work on next. You just need some liquidity, man. This needs some liquidity, yep. Anacana's not going public anytime soon? Not soon, but they just have their series C. It's actually doing really well. And they're very, you know, it's a good example of a company. I can tell that story numerous times.

A lot of people can tell that story. I, of course, have my own version of the story. It's doing well. It's doing really well. But I don't know if it's when it's going to go public. I'm out of that. I'm out of the loop on that. You could ask Peter.

you could ask the board, I could ask them. What I've heard is they're not really anxious to go public quickly, but they did just get Serie C and got a new people. Actually, I shouldn't announce that. I'm sure they're doing very well, but I'm not authorized to say that they've had that. Vannecona is doing very well. Anything else?

This has been a wide range in the interesting discussion. Adam, you have any either follow-ups on fair OSS or something else before we let me go? I mean, I'm just going to scrutinize it more, really. I want to say it happened, but I want to scrutinize it more because I'm like, Yeah, scrutinize. Give us feedback because it's still early, right? And so the idea was, let's get it out there. Let's get talking.

Let's see how to make it, how to adjust it. Well, I mean, like, I'm easy to please with it because I want it to happen. But then if you take Jared's example where he says, hey, I'm a venture capitalist. I want to put it on Numpai. What happens was this question? But like, what do I get? What is the incentive for that venture capitalist to put 10 grand on Numpai? They get the returns that later come.

So remember, if you get on the cap table, have you ever, are you on a cap table? Have you been an owner of a company? If you're like, you basically, thorough assess has ownership of a company, but that ownership is tied to flow down through the dependencies, right? So basically, thorough assess is the arbitrator helping as people use NUMPI more and more. Now all of a sudden,

Netflix and Amazon and OpenAI and Google, they all basically depend on NUMPI in some way. And even if it's like, you know, a millionth of a basis point, of the value of that company is now flowing through FerroSS to the NUMPI community. But an aggregate, it could be 100, it could be hundreds of millions of dollars, actually. It's sort of people have told me, people said, you know, NUMPI has had billions of dollars of impact on the economy.

I'm like, great. Where do I see that? Right. Measure that. How does that show up for a second. So back to the venture capitalist with a 10 grand that puts on Numpi. Well, it would probably be an investor. I mean, venture capitalists would probably put more than 10 grand.

They'd probably want to put a million. a million in early, right? Okay, well, pick a, pick a number. Just telling you with the Robin Hood app. You know, everyone's asking the Robin Hood. Yeah, that's later, the Robin Hood app is what I want to get to, but that's going to take a little bit of time. Totally.

But then you have 10 grand. You put it there. What are you going? Well, one, you have other buyers, right? Because every market, you know, if you think about stocks in general, why do you put money in stocks? Well, maybe they'll give a dead end someday, but no, because you're going to sell with someone else.

Right? So it's the same thing here. Is there a buyer for this later? And the answer is, sure, if the market's real. and why would the market be real? Because there is an eventual value. What exactly are they buying? Help me understand that.

They're buying ownership. They're buying ownership in the Milibis table that Numpai is governing. And remind what the millibs table is? What does that consist of? So Milibbib stands for a million, a thousandth of a basis point. So there's 10,000 of them per percentage, or 100,000 per percentage point. So it's a percentage where you're buying is a percentage of the Numpi project. So, and then, okay, cool, I have a percentage of the NUMPI project.

What does that get me? It gets you any value that flows from the FeroSS infrastructure to that project. So let's say in the future, $100 million is flowing to that to NUMPI from companies whose value either FeroSS sells the position it has and flows it through or it earns dividends or there's a, basically there's numerous ways FeroS is creating actual transactions, the market that flows money back to the open source community. So it's aggregating that. And then downstream, some of that aggregation is coming to the Numpai project. And as an investor, you have a right to a percentage of that. Okay.

That's what you're buying. It's like buying a stock in a company. It's the same thing. Why do you buy a stock in a company? I'm tracking now. I'm tracking the whole cycle. But we've had to create the instrument to enable the flow to happen. And so an investor could see, because that's what investors are going to see.

Before the market can develop, investors would have to look and say, okay, wait a And how is this going to work? And so that's what takes work to develop that market. It takes work to develop the relationship for the companies, the flow through from their value to the rest of the market, and then the aggregation. And it's a technology problem. There's stuff to do because you basically have, you know,

there's like five million open source projects. I kind of think 500,000 or a million of them are probably, you know, so you have to onboard them. You know, Farrow assess will have, okay, we have 10,000 projects we're supporting. Now it's 100,000 projects we're supporting. You know, it's going to be a pipeline there. And the same sign, FerroaSet is going to have to build, we've got 1,000 companies participating. Now we've got 10,000 companies for Spain. Now we've got 100,000 companies for Spain.

The market's growing in both directions, right? You're going to build both sides. Which side do you build first? It's a combination. Like, you have to do both kind of, it's like every bootstrap problem. You have to do, you have to attack both at the same time. And so it takes work and it takes, you know, a lot of conversation, selling, communication, communication, you know, trust building.

Let me be more clear with Jared's question. What is the most clearest form of a good next step to make this happen? $5 million. For me is the money because we already did. I already spent as much as I could. I probably spent about somewhere between half a million and a million on this already. Just from, you know, the consulting company I had and we were just taken from, you know, money we didn't send back for investors instead invested in this idea. So we've taken money already to invest, but, you know, hiring people because you got to, you know, I hired people and they did work on some things and it takes resources to do that.

So the next step is to, is that money. That's right for me the next step is to get that pocket of money. And five million is really two millions like the minimum, but I'm kind of, I like five, like I'd like 500K to invest in this company for 10 years. That's why five million. Because I want to, it's got to be funded so that there's people who are hired to pay attention to this problem and are working towards it. And it's going to, and I want it for 10 years because this is not something that's going to be solved in three years, three months or six months. It's something that will need time to develop. And the company is the Farrowsess S company.

FerroSS is the FeroSS company. Yeah, it's investing in FeroSS. And why will it be valuable someday? Well, it's the broker-dealer ultimately that will create value of FeroSS. That's why FeroS itself is a public benefit corporation. Because I don't know if it's going to have value or not. It's purpose is a public benefit. It's to build the market of open source.

And so whether it has value intrinsically or not, who knows. But the broker-dealer will at some point, because it'll be the same reason. It's a transactional, right? It's there basically brokering conversation for investors and their money. These are public benefit corporations remind me the structure of that. Is that a C-Corp that has a different classification? Correct. It's a designation, and there's a few version versions of this.

The public benefit corporation is in Delaware. You can basically tell in the articles of formation, this is a public benefit corporation, which means you've told the Secretary of State, as well as every other investor who might invest in this company, this company exists not only to maximize shareholder value, but to also achieve some public benefit. So you can't later, a shareholder can't invest in the company to later come back and say,

hey, you didn't have a fiduciary responsibility to me and maximize my investment, which is kind of the default corporate law. They go, well, actually, you have to prove that we weren't supporting the public benefit that was told you from the very beginning. It was in the short of corporate shodder. So it's an innovation. I like it a lot.

It's actually a really good innovation. Because even though, even companies that don't have it, they still benefit the public. Like a lot of people have this idea that some of corporations are somewhat inherently evil. They're not. They're just an organization to kind of pool money together so you can do stuff, do stuff. Their motivation is different than a human. That's the problem. They're motivated.

And it definitely is true. Definitely is true. There's an agency problem. They're capitalistic by nature. I mean, by design. It's the whole point. It's the capitalism by nature. Yeah, exactly.

That's their focus. So the public benefit corporation allows you to insert an incentive structure. It's a communication. So every share share management, management, management can go, oh, we're attuned to this public benefit, not just maximizing shareholder value, right? It's actually this public benefit, too. And so it's a nice innovation. There's also something called a B corp. A B corp is a different thing.

You could have both. A B corp is you get a license from a firm. So a B corp is a branding thing. You basically pay a fee and get a license from a firm. and the firm has ways you can show that you're a benefit corporation. Whereas a public benefit corp is just an institutional infrastructure thing. You publish, you record this in state of Delaware is where I've done it. Other states you can do it too.

That's the thing about corporations are state by state. Delaware is just the close thing we have to kind of a, you know, everybody, a commonplace people do it. But that's what it is. It's a public benefit corp. And, you know, several companies have been doing this, particularly around open source because people go, wait, as open source contributors realize, okay, how do we use the mechanisms of institutional capitalism to support our mission. And that's what I, that's what I like to do. I'm not, I'm not, I'm going to call myself a capitalist, but I definitely am a, I like people, and I like distributed ownership, and I like people to be able to be free

to work with each other. And I like decentralization. So, and so I'm just like, how do we use this infrastructure to further the means of our open source desires? And so that's, that's at the heart of what's basically driven me for the past 20 years, basically. and, you know, had some success, but some failures, and I'm still trying, I'm still trying to find other collaborators, other people that are similar interested. And, you know, Open Teams is the latest one that's launching right now. Anaccona was with them first. I did some consultancies before that. I've done some consultancies as well, and I then talked to a lot of people.

I'm very eager to collaborate with anybody else thinking along these lines because honest, this is something I would love just to exist. I'm like you, Adam, basically. I'd love it to exist. So, okay, well, kind of like NumPy. I'd love it to exist. Well, nobody else is doing it. Maybe I should do it. Kind of the same way.

Okay, I love it to exist. Nobody else is doing it. Maybe I should do it. And we'll see. Okay. So I got to imagine that as part of this, we'll drum up some interest to something. Okay. We do have some various.

Contact me. Variance of influence. So you need roughly $5 million. To fund Fair OSS. And that will be used for the next 10 years. for the next 10 years. So half a million dollars. It'll need more than that,

but that's enough to make sure, that's enough to make sure that we can hire people. Because, you know, I'm going to allocate and I'm going to hire people and I'm committed to people. Then it'll self-fund. You'll hire some people to bring on projects. You'll have a,

let's say, 10 or 20 or 100 of your initial pool of projects that will, you know, show off there. What did you call it again, this table? The Mips, what was it called?

Millibips. Millipips. The Milibis tables. Is there a different name for that? Yeah. Yeah, please come up with one. Yeah. I do like it.

It's just forgettable. Yeah, I hear you. And easy to confuse with something else. Yeah, fair enough. Fair enough. I like the idea, though, because you're selling access to this table, which is not truly ownership in the, in the project, but future value it can create. It's future value it creates.

And so it's a separate file. Like, you have their thanks file. It's separate. And it's the responsibility of the governance team. to update it. Like FerroSS when it onboards a company will have one, right? And basically we're like, okay, here's the table we're going to use for your project. And who gets to, and you can change it any time.

The governance of that project gets to change it. Well, I think it's more important then, right? I mean, it puts a heck of a lot more importance on like, it does. Right. Just really, nearly open source. It does. And that's also I'm aware of that. So I'm also like, huh, because I also seen projects when, when money starts to get involved,

your culture can change very quickly. Yeah. I mean, motivations totally change. I mean, if I feel like I put my work out there and somebody else is getting the downloads from my work, I'm feeling. Then you're going to create, then you're going to show up.

Exactly. I talk to why I feel like, I feel like fair OSS is going to need to have like almost a, like an omnibundsman office, right, whose whole purpose is to, is to help resolve disputes between governance questions. It also feels like a license to. Fair OSS reminds me of like the license movement.

Yeah, I kind of, it's why we kind of have a ground water. Exactly. If you look at the site, we've kind of, we've got the groundwater program. Like, it's like, you have this idea and then you get a label. So the project could say, I'm participating in this groundwater program. And then companies could also say, I'm participating as a means to attract developers. Because for companies who participated, they're basically like, why do they do it? Well, they want to hire great developers.

And they see there's a way to do that. They recognize the problem of they're going to bit dependencies on open source that can't maintain. And they want to figure out a way to, you know, pay ahead for that or figure out how to, how can I reliably rely on an open source ecosystem when that old XKCD graphic of the, of the dependency that's in the middle, it disappears. Then what? A lot of companies are realizing this is a problem. So there's, but there's more to do there. Like, this is going to, like, it's why I say it's going to take effort and consistent effort and the right kind of people. Like, you'll have to have dev rels. I want to hire ambassadors. I want to, you know, all the people

involve in open source for multiple cycles. I want them to tell their stories and they come and talk about it and then there's a podcast that will have to have to promote. I mean, there's lots of things to develop here. But my perspective is, you know, if and when Anaconda actually becomes

not just paper, not just paper value, but real money, what am I going to do with that? Build this, right? Build a way to give back to everybody else. It's got a shot. It's got a shot, I think. Well, I appreciate that, Jared Adam.

That's kind of be, yeah. Yeah. It reminds me a little bit of the T.X, Y, Z conversations we have, but not like exactly one-to-one, but similar nature. Yes, similar nature. And I've seen a few emerge. I have, I spoke to him, yes. And that's what's excited to me recently is I've seen a couple of these.

We're like, oh, okay, we're on to some here. This is you guys have a similar concept. And I would be happy to join forces with some of these folks, too. Okay, this is not a, like, there is zero desire to be the only founder. Like, I've been a founder. I know what that is, and I'm fine doing it, but I don't, not. I'm doing this to support a concept. If there's other people that want to take the, like, I'm happy to be a spokesman.

I'm having to just be somebody that promotes it and that negotiates people and encourages them why. And I'd love other people to own it. I'm going back through our chapter markers. And when we're talking to Max, we talked to Max last end of last year at all things open. We got all things open every year. Oh, yeah. Yeah, yeah, yeah. Love that conference.

Yeah, anybody there. I would love to talk to people there too because I did talk to T. and I think they were the closest of the ones I've seen. I need to revisit that again. Yeah. That's actually who I'd love to talk to. Collaboration is key to this. I don't know what my idea was, but at one hour and 12 minutes of that conversation,

it says, Adam shares an idea. I don't know what the idea was. It may have been a really terrible idea, in all honesty. I'm sure I had a lot of single. I would go back and listen to that. And I would definitely circle back on Max because you got similar. desires, different implementations, but similar desires. I will.

Thank you for reminding me about that. I will, because I do remember, I will. Thank you for that lead again, that reminder. You guys are great. I think what you do is actually very valuable because it gets people talking and then listening and reaching out to each other. We listen a lot. We talk very little sometimes, sometimes a lot.

Sometimes I share ideas that are bad. Apparently, we'll see if it is. The chapter title did not say Adam shares a bad idea. That's true. And I'm pretty sure I wrote that chapter title. And I would have put that in there if I thought the idea was bad. It was a good idea. Jared liked again.

It was a great idea. I mean, we care about funding open source. And I think the mechanics around have always, to some degree, have been ambiguous or flawed. I think it's hard. This idea did not come to me until I'd spent time in open source, time in Wall Street, working in investment banks. And then time as an entrepreneur, then finally as a fund manager. Essentially, all these different things have led to, oh, here's how we can put it together. right because it's like all these different facets of a big of a big problem here's a big idea

for you guys let's see this this this chapter's titled adam shares an idea it could be a bad idea uh is like i i'm thinking i'm in this mindset personally where i'm thinking about my family bank and i'm not talking about like infinite banking i'm i'm talking about like ways i can set my family up then i can be the one who does the hard work to establish a foundation for which my future generations can borrow and lend against build wealth, have assets, etc. And I'm thinking like, gosh, I love software enough at this stage of my life and at this point of my life for the future family and destination and the sentence would come from me that I want to say this family cares about software. And so much so that it's open source software,

I would want my family bank if this was a thing to invest into the pool of open. open source for these things. And it sure be great if my foundation I start as a part of it or whatever can benefit because of the value that I invested in in open source. Like that'd be kind of cool. I think you need more of those kind of movements where you have people's long-term generational wealth or lack of. Totally agree.

I totally agree. I totally agree. So I've actually right this summer, I've been setting up a family office, which is just a company that holds the investments. instead of them, you know, basically asset protection, et cetera, yeah. It's driven honestly by the fact that my taxes have gotten complicated

and they're breaking me. And so I'm like, oh, I just need to push that to another organization that handles that. And so, but it's exactly that. And then that's gotten me in the family office community. There's a big community out there, family offices, family banks, right? We're in similar circles then

because I'm doing the same thing. I'm trying to figure out that stuff. Exactly. Well, we can share notes on that on the side. I'd love to connect. I'm trying to view. And there's just a lot of ways to do it. But I agree with you.

It's a big world. out there and why not as people become prosperous have a way to kind of extend and help the world be better. The AI revolution is here. It's coming. The AI transformation is here. I want it to make more people wealthy and not just a few people, but like a lot of people. And then pass that on. I want a world of peace and prosperity. I'm naive enough to still have that dream, but I actually believe it's possible with good ideas, with the right ideas. But there's also, you know, there's roadblocks and there's potholes and there's bad directions to go. And so that's why information matters.

That's why cooperation matters. That's why I think open source communities can be a part of it. Because in open source communities, you have real people working together to do something. And that's how anything great is done is real people, real communities. And how do you then help them and allow lots of them to flourish? Yeah. So, yeah, this is really good. And you're exactly right.

It's like art. The family banks, right? Yes. A lot of family offices invest in art for obvious reasons, right? Yes. open sources art right it's an asset class we've never been able to invest in yes but I believe in it you're 100% right

you're 100% right 19 years of my life chasing it exploring it sharing it you know have you been to Italy and into the Florence and seeing the great artists of that era and you realize how when I went two years ago I finally realized oh it was concentration

of these patrons that sponsored Michelangelo they didn't come out of nothing it came out of a concentration of wealth that was distributed to the people to an it was patronage that enabled that right and you're exactly right we need the same kind of thing but not just with a few wealthy people but how do we do it for millions of people to participate as the patrons yeah and in return their benefit it's got a function first so I think that's where the hard part is you need to get that half a million per year for the next five or whatever it is and

do it's right that's right figure out how to get past that because you need that first I totally agree with you that's what drives me right now is okay doing these other things I still got to make a living myself. I'm not quite at the point where I can just focus on this. I've got to figure out of, you know, I've got clients and other people I'm supporting so I can, you know, support my family. And then, but you see the idea of, oh, eventually I might have some means to invest. Cool. What am I going to do with that? And that's where this came from. Awesome. Awesome. Awesome. You guys are awesome. This was great. Let us know as you make progress. I will. Stay in touch. Be part of it. It helps spread the word. Definitely stay in touch.

Cool. Definitely stay in touch. Love talking to you. you all. All right, Travis, thanks so much for being on the show, man. Okay, take care of my friends. You guys have a great day. Bye. Well, I don't know if Fair OSS will take off quite like Python did, but I appreciate anybody and everybody putting work into helping open source maintainers do their thing. So, I hope Travis succeeds. If you are listening to this, the day we ship it, the Python documentary comes out tomorrow. If you're listening to this anytime after, August 27th, 2025.

It's already out there on the YouTube's for your enjoyment. I've been previewing a rough cut and it's pretty awesome. Our friends at Colt repo do amazing work. Speaking of amazing work, shout out to our partners at fly.io and to our sponsors

of this episode, depo.dev and off0.com and thanks, of course, to our beat freak in residence, the one, the only, the mysterious, breakmaster cylinder. That's all for now. But we'll talk to you again

on change logging friends on Friday. I'm going to be able to be.