Jerod Santo: What I’ve learned from jj

Jujutsu (“jj” for short) is an up-and-coming version control system that many smart people are saying many nice things about. Nathan Witmer says Jujutsu’s flexibility and safety changed his approach to version control.

Working with git has been great, especially in contrast to what came before. But despite years of development, it still has sharp edges and presents a steep learning curve. Jujutsu doesn’t fix that, exactly, but it sands off some rough edges and makes some different decisions that result in a much safer and far more flexible workflow.

What surprises me about jj excitement/adoption is that nobody claims it’s revolutionary or 10x better than git or anything like that. They just say it’s marginally better in many small ways that I guess add up to adoption-worthy. In this post, Nathan explains how jj has made him think differently about commits and intentionality, rebasing, conflict resolution, and more. He also followed this post up with a (perhaps more approachable) jj tips and tricks

Joran Dirk Greef: Tiger-style, yeah. And that’s sort of all the safety techniques. So assuming that we do still have bugs, we also have like 6,000 assertions that check the operation of TigerBeetle in production. If any one of them trips - it’s like 6,000 tripwires - then there’s probably maybe a CPU fault, or a memory fault, or a bug. And then we immediately shut down the whole database. You wanna operate safely, or not at all. And that way you get total quality control, and the system becomes safer and safer. You don’t have latent bugs. Yeah, so Zig really suited not only the performance, but also some of the safety decisions.

Chris Benson: I really love this line of thinking… Daniel and I focus very much on the show about kind of AI for good, and not everything being about making a profit in a business, but kind of how does it affect society. It’s a big theme in the show. And I run a nonprofit when I’m not working at Lockheed; it’s a pure public service nonprofit, and it’s turned to another full-time job that I don’t get paid for… When you think about how AI can do good in these ways, obviously taking into account the safety and privacy issues that are there… You mentioned climate change, you mentioned food insecurity, and suicide prevention, which kind of ties into the mental health theme… And as we have these AI agents, as we combine generative AI with some other tools, and there’s an agent for everything in the future… There’s some agents that can handle mini tasks, they are mini specialized, and everyone talks about that coming… You mentioned about kind of suicide prevention, and I think that’s a fantastic idea if you have that agent, that personal assistant that’s always there and can kind of take care of you. Beautiful idea. Also an education.

I have a daughter who just turned 12, and I’m trying really hard - and I know education is a big thing for you… How do we see our children today growing up in this world? How can AI help them with education? How can it make their world better? There’s the scary things like job loss that we always worry about, but there’s also these amazing potentials for good as well. What are your thoughts about AI and education, and where that goes into the future?

Amal Hussein: I get that. I’m watching a show right now on HBO called Avenue Five, and I feel like it’s another show that really – I mean, it’s basically about this driverless ship, with like a fake captain, and the fake captain is there to just appease the… It’s to give the passengers a sense of human psychology safety… But things go wrong on the ship, nobody knows how to fix it, nobody knows how to do anything, right? It’s like, “Oh, we’re just a civilization from the future, and we’ve just automated trips to space.” [laughs]

Jason Carter: Yeah. It’s interesting, because you have to think about it differently if you’re a platform provider of the technology. So if you’re Zoom, you control the entire experience, right? You have a dedicated mobile app development team, dedicated desktop team etc. If you’re a company like Vex, you can sort of provide components for people that, “Hey, if you use this on your application, then you will get a really great preview page, and the devices are going to work really well no matter what platform you’re on.” And that’s very challenging.

[34:24] I’m always trying to join our kind of internal demo from any device that I can, just to see, “Hey, how does it work on this?” I just got the folding Samsung smartphone, and I’ve been having a lot of fun playing with that… And that trips up the site quite a lot. People aren’t designing for that sort of a system.

So the way that I see that it could work is providing super-great tools, whether that’s SDKs that work on lots of different platforms, with just sort of like training wheels and safety built-in, where “Hey, if you want to get started and build a better application, just clone this open source repo that has examples of how it works.” You could just run that yourself, if you want; toss in an API key, and you’re off to the races. Or “Hey, here’s a really good audio picker. And we know that it’s cross-platform, we know that it works well… Just take that if all you need is an audio picker”, versus “Hey, here’s a video grid that works super-well across all sorts of systems.” And it’s kind of a moving target in the browser as well, because there are constant updates and changes to WebRTC, right? Safari did not support it for quite some time, until, if I recall correctly, Apple added FaceTime to the web. And then all of a sudden, they fixed up their WebRTC support so they could support their own product.

So long story short, it’s challenging, but I think the best way you can do it is make it so that it’s much simpler to provide those experiences, so that if someone is kind of using Vex as we hope they would, with our components, then they’ll have a good time, and hopefully, that spreads out to more and more applications.

Daniel Whitenack: Yeah, so I have a couple of follow-up questions on this, which is really interesting. One is I just want to maybe get your perspective, since you’re more plugged into this space and have interest in the area… I Know that it’s been talked about for quite a while that the sort of short or last mile kind of trips, like in a city, in a large city, you could have like air taxis, which are basically like humans in a big drone, and flying around the city. My understanding is any reasonable person would say, “Well, there needs to be computer systems within that, that would coordinate and manage the safety of all the routes.” If there’s a bunch of things flying around in the air, it gets very complicated in a crowded space. So maybe this gets us closer to that… Do you have any thoughts?

Doug Martin: And I was a huge JavaScript developer, up until (I think) about 2015. Then I started doing Golang. Then I moved on to Scala, and doing a lot of that. Then I wanted to come back to my roots, I guess, and started doing more JavaScript, and uplifting some of the old projects that I had – like, FastCSV was written in JavaScript initially. So I wanted to look at what the latest technologies were, and TypeScript was really starting to take off, and I had been doing typed languages a lot recently… And I fell in love with how much safety it provides you… It’s kind of like that warm blanket at night. You feel a little bit safer.

So I went through and started upgrading FastCSV, and what I quickly found is starting JavaScript first and then porting over - how many things that you just ignore that could break your code, or whatever… And then TypeScript’s like, “Nope, you shouldn’t be doing that.”

So that’s when I really started to fall in love with it and see the power of it. I mean, it’s not giving you as many checks as a fully-typed language would, but it makes JavaScript just a little bit better. So it was really that – coming back from typed languages to JavaScript.

And the other thing that TypeScript helped me do, when coming back to an old JavaScript project, you have to build up this huge mental – the full context of the project, to know how everything ties together and make sure you’re thinking about all the edge cases. And if you haven’t looked at a piece of code in a couple of years, especially JavaScript code, that’s hard. So you’re like “How is this called again?” and then you right-click, and find usages, and nothing pops up. And you’re like, “Oh, that’s because I did a dynamic lookup or something on it, and it’s not actually referenced anywhere.”

So TypeScript gives me the ability to come back and support projects, even though I’m not actively working on them day to day. So once I really embraced the power of that, I’m not looking back.

Ro Gupta: Totally. I’ve seen a few different ways of framing this. Some people frame it as – they use a dichotomy of AI versus rule-based, or something like that. I also more recently saw it, which I kind of like, as someone using sort of nature vs. nurture… Maybe let’s start with that. We were talking about priors before, and that’s where I’ve seen – actually, the nature vs. nurture dichotomy I saw because we’re connected… So one of the several academic institutions that we have pretty close ties with is NYU here in New York. NYU is known for Yann LeCun and his work, but also Gary Marcus… And in some ways, they’re sometimes friendly at odds with each other, and I’ve seen them even debate this concept of nature vs. nurture for AI… And I might be morphing it a little bit simplistically or off what they mean in their arguments, but when it comes to what we think about, and what Elon’s thinking about when he’s saying what he’s saying about Tesla’s eschewing of things like maps is “Can an AI get to where it needs to get purely on just learning, and essentially nothing else? Or is there a need for there to be a certain–” I think Gary Marcus uses the term “innanteness”. Again, I’m kind of morphing it for this conversation a little bit… But in our case, that might be analogous to the use of priors. So I think a lot of these debates boil down to that.

Actually, yeah, we kind of have a dog in the fight, sure; we are a mapping company, and that’s used for priors, but actually, for me, I’ve always felt like what is actually gonna solve the problem both now, but where can you future-proof yourself, including on the business side? It’s really important to future-proof yourself, so that if and when certain trends materialize, you can sort of seamlessly ride that wave, as opposed to completely flipping your technical approaches that you’ve taken. This SD/HD to MD is a perfect example of that. Right now, I don’t care who you ask - especially for really high levels of autonomy, and also where the driver is truly not in the loop, and also in complicated environments, no one is able to do that without priors, and no one thinks that will be possible from a safety case, from regulatory and societal acceptance rate case for several years at least, if not more than that. The but is what if that changes?

The thing is, we always have to be humble, because these things change in a very nonlinear way, and our lizard brains still really struggle with nonlinearity in predicting things, because we just don’t know where we are in those [unintelligible 00:35:38.08] So that’s why we always exercise humility there, and kind of think about what-if scenarios… And I think the what-if scenario of allowing this AI to be more nurture than nature, so just purely whatever you expose it to, it learns, and it just gets better, and it needs less and less of what it was hardwired with from the beginning, I think it would be a great thing. For us, it would actually allow us to focus on higher-level problems, where you’re switching from certain problems on the lower rungs of the hierarchy…

[36:17] Again, I don’t mean to plug our blog, but another post we referred to in this last post was this thing we call “The mapping hierarchy of needs.” It’s sort of a take on the Maslow thing. Over time, there’s higher-order problems that the data that we create still are really important for. It’s just that it’s stuff like user experience, or compute efficiency, or economics… Whereas the first-order problem that everyone’s really trying to get over the bar with is safety. So that’s where, as I said right now, everyone really wants to use good priors for that.

But in the steady state, you could totally envision maps being more used for things like comforts, and monetization, and things like that. If you think about aviation or other industries, there’s certain datasets that were much more critical for safety, but are really now much more for comfort. Say for example turbulence, or weather data. I’m old enough to remember when we did worry about poor-taste jokes about TWA, and stuff, about their safety.

Chris Benson: [35:59] I think you will, though. One of the things that was notable is that the state of California licensed testing for over 50 companies with an enormous number of autonomous vehicles… And they noted that they’d already driven over two million miles. When people hear “autonomous vehicles”, they’re often thinking about cars on the road, but what we’re really seeing here is a transformation, and they call it out in this report, that you’re seeing – I think we’re right on the cusp, now that California has done that, and you’re gonna see other states and other countries as well engaging in the same thing, as people recognize that these vehicles can be safely integrated into society, whether or the road, or in the air, or on the water, wherever we happen to be. And we’re gonna see that more and more.

I think this action by California demonstrates that we’re right at that tipping point as we’re recording this. We’re gonna see it everywhere. In the company that I work at, autonomy is a big part of it, as it is in many different industries… So I think you’re gonna see autonomy becoming fairly common over the next few years, whether it be on our nation’s roads, or those of other nations, or from the bottom of the ocean, to the surface, all the way to outer space. I think that it’s gonna become…