Top 10 Repos explained: Archify, Omarchi, OpenMAIC, and more transcript

You're going to get a gorgeous visual that will explain your project's code easily. You'll have an insane way of turning an old dead computer into a futuristic AI device. It is amazing by someone you know. You're going to get a stunning way to spy on the world. Is it a little creepy? Well, you're [clears throat] going to see some real life use cases for it. That's this week's top 10 GitHub repos. Links to everything below, including to my co-host LinkedIn if you want to connect with him there.

Time stamp so you get what you need. Let's get into it. Presented by Zapier, the AI automation company. Adam, the hottest repo of the week is called Archify. And what it does is it describes your system chat in a clickable diagram. Let me show you what it looks like. And I'm wondering what someone would use this for. >> Yeah, I mean, this is a great way. You know, we we we often will describe with words to AI what we want to build, but words don't really capture relationships and flow and directionality.

And so when engineers are typically building a new system, I've got a whiteboard over here. I draw it on the whiteboard first because that's a way better way to communicate. And I'll take a picture of that and I'll send it to AI. What this is is a tool that helps you create these system architecture diagrams with AI so you don't have to get the whiteboard out. You don't have to get dirty. And then you can edit them. You can watch as it changes and treat it as as like documentation and a spec for what you want to build.

And this looks like a tool that's like a little more than some of the the diagram tools we've seen so far that are just generated image. This one's actually interactive. You can click and drag. You can move things around and edit, too. >> I'm a visual person, too. Okay, I could totally understand how I >> AI is a visual person, too, Andrew. It's you. It's me. It's AI. It's everything. It wants pictures. It craves screenshots.

It craves graphs like this. I guarantee if you use something like this, your designs, your your systems, your software will come out much more accurate with a lot less work. >> Okay, I can see that. I can see how I would understand it better this way. Next is something just super cool. We got to show a video. It's called God's Eye View. It's a spy satellite console in your browser and it uses real data. I mean, there's a lot of this stuff that's already live on the internet like live planes, ships, satellite information, wildfires, public street cameras, but how do you get access to all of them?

How do you see it all? What this repo did is it said, "Okay, I understand that this stuff exists. I'm going to make it easy for you to to navigate." In fact, look, this this GIF here is a really good visualization of how it makes all of that data accessible. Really cool interface. I don't exactly know what the use case is. I've got this video here for people who are downloading this this file where you can see it. In fact, here, let me just do a quick hit play on this. feel like you're in a spy thriller movie, but the data underpinning it is actually real.

So, what [music] you're looking at is the real-time location of vessels, planes, satellites, and so much more. >> Showing the White House for some reason, it seems a little suspicious. But what what would I even use this for? >> You know, Andrew, I was just thinking that same question. The one thing that pops up for me is, you know, number one, like I'm sure you use FlightAware or one of these other tools to track like, oh, my my spouse is coming home.

I'm going to pick her up from the airport. I'm going to track it. I don't want to use the the crummy like app from the airline. And so, I use Flightare or something. But the second idea came into my head, I've shipped things internationally a lot before on these big, you know, shipping vessels and they don't have tracking. They'll be on the water for 4 weeks, but the boat is tracked. And so if you can figure out what boat it's on, and I've done this before, but it's hard to find, you know, one of these platforms that lets you in for free and say, "Oh, I know which boat." Oh, now I can track it.

I know it's it's almost to Panama. It's, you know, it's it's in the canal. It's moving through. Like, so I I think this is kind of interesting. There's a lot of like tracking needs that that we have. And I want status updates. I don't know about all the Yeah. the picture of the White House and the the camera views and I don't know. So, I don't know what all that's for, but I like the plane and and boat tracking. >> I I could see how I would use this.

I moved to Mexico. My wife wants to go to a new city here. I I asked Claude. I asked friends. It's not the same as just seeing street view, for example, and seeing what else is going on. All right, makes sense. Let's move on to the next one. I don't know how to pronounce this one. It's called open make, I think. But here's what it is. You know how when you want to learn a topic, in the past, you'd go to YouTube. Today, you're going into like chat GPT.

And the problem with YouTube is it's just consistent and static. The problem with chat GPT is yes, it's interactive, but it's all chat. What this does is it creates basically an online education like class for you with fake students with slides with an immersive experience. That's what it's about. Here's this uh it's a paid tweet here. I want to call that out, but he did a really good job of explaining what it is. And and here and you can see also what open make stands for.

It's open massive AI empowerment course. And if you go to the repo, they do actually have a sample here where you can see what it's like to learn. But all you have to do is say, "I want to learn about whatever." And it will create this classroom for you to learn. I see the value in this one. This one's really interesting. [clears throat] I mean, this is like all those skills we've seen previously where you could call a skill to say, "Teach me this topic." And it'll create a PDF, but far more interactive and in an interface.

Is that is that right? Am I understanding? >> Exactly. Exactly. All the things that you're used to. I'm going to not let it load right now and leave it to people to download this after we're done. >> By the way, if you are building, you should know about my sponsor, Zapier, which makes their SDK available to you. Here's why, uh, Adam, people would use this. And I say Zapier because everyone when you hear Zapier, you go, "Oh, I have all this image of what it used to be." No, there's so much more today. >> So, there are people who are listening to us right now who are building software for outsiders. um they're building software for their employees at a company that they're working for and what they want to do is take the software and make it make enable their users to connect it to the other tools that they use to their project management software to their email software etc.

But to build those connections is painful. So Zapier SDK makes it really easy. You just use Zapier SDK and then you say this is what I want my users to have access to. I want them to use my software with notion. and I want them to use my software with etc. over at this point it's almost uh 9,000 apps probably even more than that. It keeps growing. That's the value of this. Go tell them that you heard about them from me.

They were they were sponsoring this before they even knew what this was. All right. Zapier SDK. Let's talk about this. Go modern guidelines. Jetrains fix for agents that write 5-year-old Go. I've heard of Go. It's a language. But what is this? Yeah, Go is a programming language. It's a it's a back-end programming language. So, it runs on servers typically. Think of it as like similar to Python. Uh somewhere between Python and C or C++.

And and you know, a common frustration with things that change a lot with AI is my AI model was trained in November and now it's September. Well, wait. all the things that have developed, the new releases, the feature changes in the language, none of that is in the model. And so I'm getting stale recommendations. And so this and there's a lot of tools like this. You know, if you program in different languages or have a different topic, it wouldn't find one that's for you.

This will plug in to cloud code or codeex so that codeex is aware of, oh, here's the best package that was released three months ago. You got to use this one and here's how you have to use it. Here's the examples. The LLM doesn't know, but it could quickly learn. And this is the tool to make it quickly learn those things in an automatic way. >> All right. Can I say, by the way, I'm so proud of these graphs that I've been building.

It's It's working. I save all the stars every week and I'm able to build it. Okay. Next. Open Claude. Claude Codes workflow pointed at any model you want. This is a fork of Anthropics Claude code rewired to run on OpenAI, Gemini, Deepseek, or free model on your own laptop. It is not from anthropic and it's so own readme file says so in writing and we'll talk about the controversy with that. What do you think? What do I need to know? >> So this is open claude.

I'm familiar with open code and then obviously claude code you know cloud code is not an open you know the not open source but open code is open source. It's been around for I would say a long time now in in the AI era. like why would I use this instead of open code that's already open, it's already free, it's well supported, it has a big community around it. I'm trying to find like what is what is the reason why I would use this >> and >> and you and I spent some time before we got started trying to find that and we just couldn't find it. >> Yeah, >> I don't get it.

Um, you know, one thing I would point out, if if you're out there and you've been using open uh or sorry, cloud code, you're like, "Oh, I want to find a way to use this cheaper or free, go and try codeex actually, too, because I think of of all of these." Open code is a is a great open free uh, you know, platform. But Codeex can also use all these other models. Uh, it's open source, so you can fork it if you want and change it.

And the interface and the CLI is far better than than cloud code. So try some of the other tools like rather than this is maybe my recommendation to GitLab is is maybe try some of the other tools like I don't know if we need another opensource version of cloud code we've got some of those uh you know may maybe try and support one that's already out there or I would love if someone could come back and say no open cloud is better in this one very specific way cuz sometimes some of these tools they're very opinionated about one thing and they solve a problem that nobody else does.

Uh, I wasn't able to figure out what that was from from reading about it, but >> I'm going to send this to the uh the GitLab the GitLob people, GitLob people, and see if they can fill me fill me in on this. By the way, legality of this is unsettled. The repo says it itself. OpenCloud's own license file states in writing, "This project does not have anthropics authorization to distribute their proprietary source. Users and contributors should evaluate their own legal position." I I I'm surprised they would even use the name Claude considering what happened to Claude.

That doesn't go well. It's >> so we'll see what happens here. >> Scientific agent skills. This is a set of over 160 skills that turn your AI assistant into a working scientist. Just drop this instruction pack and it teaches an everyday AI assistant real lab work query and genomics database, run the chemistry calculation, draft the paper, etc. instead of being walked through every step of the way. You [snorts] like this one and usually hate when their their skills on the top 10 list for the week.

Why are you not hating on this one? >> You know, I I hate generic skills. Here's how you'll write better. Here's how you'll I don't know what, but this is not a set of generic skills. This most of these are wildly specific to hit hit this here. Hit the Encats Arax. I have no idea what that is, but I'm sure one scientist out there is like, "Oh, I know exactly what ENCAT's Arax is, and here's why I use it, and here's what I have." and now they have a skill that's going to help them do their work and they're maybe not as AI savvy as everybody else and so they can have this that's just going to make whatever their weird specific niche science thing was that's going to get easier as a result of going into these skills.

This is not a package where a scientist would go in and use allund how many of 163 skills. People are going to go in they're going to find the one or two things that are perfect customuilt for them and they're going to go. So I love I love that. I love the depth there. All right, that's the number six hot repo of the week. Number seven trending is called Mini Mind. Build your own language model for about the price of coffee.

The Eli 5 is the complete free recipe for training any tiny language model from absolute scratch. Pre-training, fine-tuning, Laura DPO with every algorithm written in plain. How do I pronounce this? Type >> pietorch. >> Pytorch pi. Anytime you see python or pi py, it's p i like the pie you eat. >> [snorts] >> So you can read what is actually happening. You like this one. Why? What is it? >> I love it, man. I mean, small language models are coming.

They're not here yet, but by, you know, this time next year, definitely two years from now, every person, every business is going to have a bunch of custom trained small language models to write your email subject lines or your email or what, whatever the thing is that you're doing, you should have a custom model that's working for you. And in order to get to that world, we're going to need a lot of tools just like this one to help average people train models.

Right now, that's pretty hard to do. The tools are hard to understand and the big labs are capable of it, but very few people are building easy to understand tools like this that can run on regular hardware. So, I absolutely support this one. I love it. I'm definitely going to go and try it this week. >> Needle is a small language model, right? That we covered. >> Needle is a small language. Yeah. Yeah. But but that one was like a pre-built model.

So you could think I could build a bunch of custom needles by using Mini Mind. >> Got it. Okay. All right. By the way, the founder of Needles saw that he was on. He's going to come on and explain to me how to use Needle and give me all kinds of use cases. >> So cool. >> Coming up number eight. I know this one really well. Open SEO. Here's what it is. I think this title is it needs a little explanation. The $129 a month SEO tool rebuilt as a pay as a pay per.

So the $129 reference is actually even understated. It's a reference to how much you pay for Semrush and Hrefs when you need software to help you with your SEO. So what this guy Ben decided to do was he said, "I think we can open source this and make it free. What you do need though, Adam, is a data source, something to tell you what's connecting to what what's on the internet. That data source costs pennies." And so he goes, "Look, I'll give the software for free.

People can sign up for for the data source for pennies or they could pay me 10 bucks a month and I'll host this software for them and get them to data included which is peanuts. The beauty of this is not just the money. We keep talking about how open-source and GitHub gets you free versions of all these tools. The beauty of this is the customization. Adam, I saw people create CRM that connect into open SEO. So if they're asking for backlinks, the CRM keeps track of it. beautiful dashboards for people who are not into SEO to keep track of how their stuff is performing in search engines.

And so yes, Semrush and Ahrefs have a big advantage in the fact that they have built their software over the years, but for many people it's too bloated and more importantly, you can customize it. That's what Ben built here. We have a whole show on that. It's fantastic. People love it. [snorts] >> I mean, I'm really excited. I'm I'm so excited about this that I'm signing up for it while you're talking. [laughter] It's I mean I we use all those other tools.

They're really expensive. They're really slow. I want to add another seat. And they say, "Well, that's another $1,000 a month or some crazy thing." So, I'm so excited. I I think if this can deliver what what it's promising, I'm I'm over the moon. I'm I'm going to sign up today and and find out more. >> In fact, a lot of people did. After I interviewed Ben and did the video, he sent me an email. He goes, "Andrew, we got so many customers because of this.

Actually, so many users." He didn't say that anyone necessarily paid him, but he doesn't seem to care. I don't know how his business is going to survive when he's charging only $10 a month for hosting. Um, but all right, this is a start and people >> maybe if you know hook him up with us, we might be able to help him find a better business model for it cuz clearly there's a lot of opportunity in this space >> and a lot of love.

All right, I'll make the introduction to Gateway X, the venture studio in St. Louis. Okay, I have been so wrong about this in so many ways and I'm so obsessed with this. One way that I was wrong is I called it omachi like a lot of people on YouTube. DHH calls it omachi. It's like oma, what is it called? Omacasa where you go into a Japanese restaurant and they give you the thing that they think you want. Right? That's where the name comes from.

What this is is Linux that you can run on an old laptop and the AI agent is part of the experience and an AI agent that's not just Siri, but it's more than that, Adam. And this is what's exciting me about it. People are saying, "I don't like how my operating system lives or works. I don't want to have to accept it." >> With Mac, I have to accept it. Or maybe I find some tool that I could add that will jank up the system and make the make it do the thing I want.

Here, I could just tell my AI rewrite the freaking operating system and give me what I want. And that kind of customization, that kind of built-in AI is really interesting and it's really powerful. And more than that, now I think what you're also getting is DHH's taste. And yes, it is kind of ACA. He's, for example, added a video editor onto this and a video shorts editor into this. Even though he even though he says, "Look, I want this to be like a Formula 1 car." You know, he's a racer.

Um, [snorts] and I I like how they will shave ounces off of their car. And he goes, "I keep trying to shave ounces off of the code." He still is willing to put some software on there that that he thinks you need and want, and yes, you can remove it if you want it. Really beautifully done. People have taken old laptops, started to use this. Suddenly, Linux is really hot because of this. Um, and uh, our boy Alex Finn who's excited about everything is super excited.

Let's just say I got to hit play on this. Alex always like the the the thing that just came out is always going to change the world. >> The entire internet is going nuts talking about this brand new agentic operating system named Omachi. And for good reason. It is the only AI native operating system I've ever used. And it has made it basically impossible for me to go back to Mac OS or Windows. until until Mac OS comes out with a new laptop next week and he gets excited about that.

You need to switch to Omachi immediately. I don't know if I share his his definitive enthusiasm, but I'm excited about it. What do you think about this? >> Yeah, you know, I Mac often gets in the way of my AI agent. I'm trying to build something and I'm dealing with security and it won't let me install this and now I've got to go and do a bunch of things. Having an operating system that's intentionally meant to be used and even changed by agents is a pretty compelling pretty compelling promise. >> All right, next final one for the week and then we're going to go into user submissions, viewer submissions.

It's Google's forecasting model. It's called Times FM and it's the new version that they just came out. What is it and why do we even care? >> Yeah, there's there's a lot of what's called time series data in the world. you know, you you've got say your SEO stuff we were just looking at. Well, how many clicks did you get? How many impressions per month, per week, and as you look at all of these, you know, even the temperature?

Well, how do you predict what the temperature is going to be next? Right? If I'm watching it this morning, well, there's a lot of modeling software out there and you could hire an engineer. This aims to make it very easy to take any time series numerical data and project out into the future what it might be next. Right? Right? If you gave this the last week's worth of temperature data, you see how it goes up during the day and down at night.

This model would do whatever machine learning type stuff has to be done. You don't have to learn how to do it. It will take all of that and it will project out. You say, "Oh, you want another week's worth? Great. It'll give you another week's worth of of estimated temperature data." We use this, we actually use this exact package internally uh to help project statistics for you know one of our e-commerce brands to project what signups will be for a course that we offer and and you know it's just better than than the basic math we were doing before which was how many have we gotten, how much time and then here's how many we expect in the next amount of time.

So it's like a little bit better better estimations. You know, if if you're just doing basic averages right now, this is going to get you probably 40% more accurate. [snorts] >> And this is from Google research. It is not someone who's stealing Google's name. >> All right. Next, first stars. Adam, we've had people who will email me afterwards and say, "You featured me. I now have 30 stars, 40 stars. It is amazing on GitHub." People who are brand new to this are submitting what they've done often for the first time.

I want to show some of it. I won't be able to get to all of it. We'll save it all for we'll save the rest for next week, but let me show a few here. This one is called Hindsight. It's a coding agent that reviews its own session. Um, what do you think of this or what is this? >> I think it's really cool. Uh, if you haven't seen it, there's built into Cloud Code a slash command called I think it's insight or insights that also will do something like this.

And I think there's a lot of how do you how do you stop making the same mistakes, right? And and how do you as you start new coding sessions, how do you learn from your past mistakes and encode those changes so that you don't make them again? And it's not just your mistakes, it's the agents mistakes, too. So something like this is there to help you just improve, improve, improve. That way, you're not burning tokens. You get to a better result faster. >> By the way, one thing that I've learned from you is take the these repos and give it to my agent and say based on how I work or based on my skills that I've created, what can I do?

It gave me I have a feedback loop that at the end of working with my agent, I will then go through a feedback loop so that I can improve it. And I said, "How would I use this and what he's done here to improve my approach?" And it gave me six tips based on what he did. And one of them is when something breaks three times, don't fix it. Go upstream and see what caused the issue and fix that. I like that. And I'm going to I'm going to find ways to integrate this into my feedback loop.

Next is something called model deck. See how much your AI subscriptions you have actually left. This is pretty. I'm going to show a screenshot and then we can move on because you can tell immediately what this is. It shows you how much of your agents um usage you still have left on your subscription. Really sweet. Like it a lot. Next, Cortex Suite AI memory system and codebase analyzer. The memory system and codebase analyzer built to make long agent sessions more reliable with an integration for people already using Graphify.

What is it or what do you know about it? >> Yeah, I it's it's like one of those memory systems that says, well, I can look at everything that's there and I'm going to give access to the agent. the the design of your system so that the agent can make smarter choices and that this will also last between agent sessions so the agent doesn't constantly have to rediscover oh where was that file where was that function where you know what's the structure of the database this kind of keeps all of that in one uh tool layer >> two stars I am the second when you see this viewer go and see how many stars by the time this comes up okay next is RTA smiti brain he explained the name of it and what it comes from.

Here it is. The name isn't an acronym. It's a cosmic order. Truth in in the rig vita smeari is memory. Okay. Project memory. So a new session doesn't start from scratch. Local first evidence-aware project memory for AI coding agents. It keeps an evidencebacked view of a project's current reli uh reality so the next session doesn't have to reconstruct it. And uh I think that explains it really well. I'm going to leave it there.

It's got seven stars including one for me. Let's go to the next one. you. This is great. YouTube subscriptions ingest. This is my first GitHub submission. I'm new to the AI space. I learned GitHub a couple of weeks ago and spent about four weeks immersed in tutorials before building this to solve my own struggle with managing YouTube subscriptions. It uses Andre Karpathy's LLM wiki framework. Raw data in uh raw data into a local staging folder processed into structured markdown with a prompt asking whether you want local search to cut the token overhead.

Basically, it allows you to study uh YouTube videos quickly and um and [snorts] use them and use the data from them in in an organized markdown, right? >> Yeah, I love that. >> Oh, look at this. Wait, I got to read this. The first inest did 11,500 videos from 41 channels in 10 minutes. Okay, next. Reimagine it. Uh redesign skill that reads your file instead of inventing a vibe. You looked at this. What can you tell me um about what it >> I mean go scroll down to see some pictures.

First of all, I love the aesthetic that that this brings and anytime you can get an aesthetic into your coding agent that's different than the default, you're going to start to see outputs that are uniquely you and that are special. So, I love that. Uh th this though is about how do you create a design system in a way that the agent's going to understand. So, you get to sit here, you get to fiddle, you get to play with a bunch of different traits of how do I want it to look?

And then once you have that, you save your HTML file that encodes all of that styling. And now the agent can just copy and paste those styles into whatever you say, I want a button over here. Great. It'll copy and paste that style. It'll copy and paste the header. So, it kind of is speaking the language that the agent wants to speak versus you describing, I want a purple box that's floating, that looks really pretty, blah, blah, blah, but that's not really detailed enough to give the agent what it needs.

So, I I love this. I'm going to try it. Like I said, I love the aesthetic, too. So, uh I even just enjoyed scrolling around. Like, I'm I'm one of those weird people, Andrew, that's got like art books hanging around. Like, this is a book of logos and stuff. Like, I just I love to scroll through this to get inspiration. So, I highly recommend >> I do, too. I want more of that, more inspiration because then it gives me ideas and I say to my agent, now copy this and make it feed it into my system and help me adjust it.

Okay. Uh I think we're going to end with this one. It's called Radiant. Multiple AI agents in one shared conversation. It's a native Mac app where several agents share one conversation and consult each other midtask backed by a server you can reach from your phone, signs in with subscriptions. I love that. Instead of API keys, and runs local models with no key at all. Um, it's got two stars, so it's very early. Actually, I thought I gave it a third.

There we go. I will say this, this could really use a few screenshots to help us see how this works. Hopefully, by the time that you see this viewer, it will be up there. If you are new, you should know some of these people did not have their repos online, did not have it on GitHub public until we went back and forth by email and then they said, "Okay, screw it, Andrew. I'm going to show it." And then things started to to to go. >> Andrew, we should put together a little guide.

We've looked at so many of these. we should put together a guide for people of here's how you should lay out your readme, here's what your screenshot should show. You know, we've looked at so many and some are awesome, but they're hard to understand. So, I' I'd actually like to help people describe these things better. So, when people submit them to you, it's like, "Oh, this is cool." And we maybe even help them grow with that as well. >> I would like that.

It It would make my job a lot easier. Sometimes when someone sends me one of these repos, it takes me It takes me like half an hour to get I get sucked in trying to understand it and trying to figure it out. And I think if they did a better job with the readme, it would help. Okay. Again, this is so brand new. We're talking about two stars. And three stars now. So, I don't mean to be critical. I just mean to be helpful.

I'm glad that it's there. If you've been watching and you haven't subscribed, please subscribe. It's a good way to show us. If there's one of these that has been helpful for you, let us know in the comments. If there's a different type of show that you would like, let us know in the comments, too, because you've seen me. I'm now doing these uh roundups, so you can get a few different repos around a specific topic, but I'm fishing for topics.

So, say all that in the comments. You've got my email address. And um Oh, now that this is over, I've got another set of 10 that you really need to see. There's a link for you right here. We'll see you there.