Oh My OpenCode Review: Better than Claude Code?

Key Takeaways

What's up YouTube profest? I'm not going to relive uh the 2015 period. I'm just a bit happy that is Friday and I don't have to work for the weekend. But what we are doing today is I will be checking out all my open code because I checked out open code last week. Um why do I want to check out all my open code? Well, first off, it was cited as one of the reasons why Entrophic banned the use of Clo code subscriptions and other tools. And there could honestly not be a better promotion for my open code than this. I understand that Entro Traffic wants to promote their own um CLI coding tool, but to be honest um I would never waste my um my cloud code tokens on on open code as of now. So I would just think like um yeah that's a pretty stupid mistake on their part. And second off because on my last video which did quite well by the way um that and as you know my viewers have the most high IQ among um yeah among almost everyone. And the top comment was actually someone who said that oh my open code changed his or her life. And like honestly I can't even remember the last thing that changed my life. Maybe when I realized that playing League of Legends all day and really trying to become very good at the game isn't the best use of my time and that if I would spend the same amount of time studying computer science that I could actually get a degree. So I just quit playing League of Legends and started studying and now I have a CS degree. So um yeah, hopefully this is something like that. And if it's not, you will be simply blocked from my channel because you can promote the tools all you want. But if it's just not good, well, I don't tolerate any stupid claims on this channel. Anyways, back to the video. Um, today we're going to check out all my open codes. Um, and um, if you don't know what Open Code is, basically um, yeah, just check out my last video. But open code is getting quite popular like I said. But this is not open code. This is oh my open code. And [snorts] um as you can see it it claims to be the best agent harness around. It got like 18k stars and increasing every day. So it's definitely getting um more and more popular. Um it also looks my my first impression of it that was it was a bit too commercial. like if I see that that a fully productionized version and I have to join a weight wish list or a wait list like that's immediately maybe a bit of a bad impression for um for me also because the the read me is so long that I probably need an AI agent um to read all of that. um they have a if I have to summarize it what this basically is it's someone's um open code config with all the with all kinds of different sub agents and MCP servers and skills that he used in his own um config like um it's stated somewhere in the documentation where is it um someone he claims to have spent a lot of money on LLMs I I don't even know how you spend $24,000 on on LLMs, but he describes as basically like um a plugin. You install it and you're ready to go. So, um if you're not really into um like custom customization of your AI agents, um this is claimed to be a config that will just um work for you so that you don't have to um agonize over agent harness choices, but instead that he will do the research, he will make a config. Um he doesn't even know how to write TypeScript. Um, so it's also entirely AI generated, but that's the norm um, right now. And he compares it against with open code being Dian and all my open code being YUbuntu. I don't really follow this um, this disclaime. But maybe let's look a bit more at the documentation before we go into the actual installation and and giving you some examples. Um the main thing is um that will immediately become clear with this is that you get some he calls it teammates um but these are just some agents. Let me search because um it's very hard to ne navigate and you basically get a a couple of agents. Um you have cisphus the default agent which acts like the orchestrator for calling the other agents. Then you have an agent for for code review. Then you have an agent for actually um searching documentation and for codebased understanding. Then another one for um codebase exploration, a a front- end agent, someone who is good at writing documentation and someone who is good at analyzing images um and PDFs and the main agent CFUS or also some other agents I think can can spawn these new agents and they are claimed to work together as a team because by default open code only comes with a builder and a planning agent. Um, so by installing this, you basically get a bunch of of pre-made agents that he thinks are tuned very well. Um, some other things that are included are some MCPS. Let's see. Um, which ones are included? Um, a web search tool powered by X AI. I never heard about X AI. So it's not like like Google or or or yeah something well known. You also have some um a context 7 MCP for fetching documentation about libraries. This one is a very common one. And then you also have a crap app which can basically search for GitHub repos. Me myself, I'm not that big of a fan of MCPS because I think they often just pollute your codebase with a lot of functions you don't even um need. I'm much more a fan of implementing deliberate skills than just yeah than just pulling a lot of functions from TMCP in your context window. Um you also have um LC LSP but this is just features of of open code. So the first thing you should know is my open code doesn't add any functionality or or features you couldn't do with open with open code. It's just a a really extensive setup or config for open code. But anyway, like enough rambling. Let's just go to the installation of this library of a documentation. Um where is it? Installation. I've this first time I've ever seen an installation manual for LLM agent because if you are too lazy to ever um um install my open code, you can just ask an LLM to install it for you or yeah like the agent itself and it it will just guide you through it. But um the installation is so easy that just just install it yourself. you have to install um this installation didn't work with MPX um broken but yeah that's a bit expected with AI coded tools that some things are broken but you need to install bun x which no not bun bunjs uh which is basically a a nodejs replacement which entrophic by the way um bought recently and yeah just install this um you can do it with with curl But of course um it's also available on brew but I have already installed this. And then you can just execute. So let's open my terminal. Then you can just execute um bunx. Oh my open code install. You'll see it will pull a bunch of of stuff. I really wouldn't recommend trying to link this right now because open a because Entrophic seems to be really hard on cranking down on this. So you might get um banned for this. But um if you don't have it, you will get the GLM 4.73 um some usage from that from open code which um is quite a good model. But I do have a chipd plus of our pro subscription. So I'm going to sign up for that. And also um you can integrate with Google Gemini. Um uh you can easily do this because um what was it called again? Anti-gravity. Google anti-gravity like this this ID of Google if you just um you can download it and and sign up with your Google account. But this basically also as you can see it has a free plan and by um just logging in with your Google account you can get access to Gemini tree pro with some of course some rate limits which aren't as good as if you would pay but I would definitely recommend um linking it. Um, according to the people on Twitter and X, um, Gemini is better at UI, but I don't really believe in these unfounded claims. But anyways, um, I will click next and then it's installed. So, um, let's quit this and let's basically see what it's about. So, let's go to a repo that I have. um watch fishing. If you don't know what watch fishing is, very interesting. Um but anyways, um to launch my open code, you just have to launch um open code. It always takes a while to spawn. And now you will see instead of the usual um builder and planner, you have uh Cisphus and planner sysphus. Why did they pick Seisphus? I don't know. I would have in my own personal config I would pick something cooler like I don't know like Goku or some other anime figure instead of Sophus because that's the weep that I am but you can also see that I have some that you have some new MCP servers installed um some formatterers like this is you can already see a bit like they installed a lot of stuff for you and for example I'm not going to write latte or or um with this So why is it even installed? You can also see um when you just type your commands that there are some new ones um available such as the Ralph loop which I will later show um some in it deep initialize hierarchical what what does this do again? So let's see if I can actually find what in it deep does. The thing what the thing is a bit docu writing documentation with an AI agent has gotten a bit too easy. So before people hate is writing documentation. So documentation was always very concise and you can find what you want. But now um yeah you you basically can't find anymore what you want unless you just put an AI agent on the get repo itself. put um in initialize hierarchical agents I don't know Ralph loop a refactor skill which will help you with refactoring um you can see the um web search MCPS um to initialize a new setting but that's normal um yeah and all these other things are uh included by default with um all my open codes also um like the the config is like um usual you go to config /open code and um you will see that we will now have a oh my open codes um JSON in which you can specify um the models you want um you can for example see that um by default these open code GLM models are installed but I don't want to use them I basically want to use my um GP5 5.2 codec. So, I'm just going to change that a bit. Um um GPT or should I spell it CEX. Will this work? Oh, wrong button. Um come on. Load the codec. Okay. Now the both both agents are using um GPT 5.2 codex. Another thing that I've yeah because I already had it installed and it's keeping installed. Um you can do some other settings here like um setting up how much iterations your um RA loops should run. If you don't know what a RA loop is, um I will make a video on it soon, but it's just a method to really autonomously put your agent in a loop um to build software so you can just make it run for 5 hours on an end without your um interaction. But anyways, let's maybe try to see how this would work in a normal um flow. I'm in an watch fishing library, [snorts] which is a fishing app for my Apple Watch that I'm developing. So, um, let's maybe think about what would be a good new feature. Let's say, okay, I know one, um, another cool thing, but this is just from my open code that I can just call an editor to create my prompt. Um, I want the fish I can catch to depend on the actual um, weather. So I think Apple offers some libraries for that type. I want you to figure out how this works and how to implement it. So let's put on the planner and um see what actually happens. You can see this put in an analyze mode um and it will you will see very soon that it will start spawning a lot of agents like we have this um explore agent that we are doing. Um you see it's it's it is delegating to a lot of um sub agents like a um like a librarian task and explore tasks. These are all kinds of different sub aents. um you will see if some background tasks complete because these are running um in parallel and I really believe like um if you're not completely new to AI coding agents but um in an intermediate stage and you're just learning about sub agents and skills and stuff. This really shows you um what is possible by creating your own open code config. However, I've been using my open code for a few days now. But as you can see, it does a bit too much in my opinion. It spawns too much agents um too much tool calls and you'll see like all these agents are um in itself using uh using using tokens. So basically in only um what is it like 3 minutes I've already used 100 um K tokens and it's it's not even done like this this librarian agent which um if you will look at the um um if if you will look at the documentation what this actually does um it's used for multi-reo analysis is it used to say right here like don't use an expensive model for that and um they even set up a free model by default because if you set this up with Opus 4.5 you will just be um yeah you will just be broke in a in only a few hours. So I guess like oh my open code changing my life is kind of true because you can really like blow yourself up. this just keeps working is going very ind depth probably reading all the available documentation um that's available. Okay, it's it's done. I actually fell asleep because it it it took so long. Let me maybe see how much tokens we've already wasted. Um so here 26,000 um tokens. this librarian task. Um 51,000 tokens. Um and as you can see what it actually did. Um like it it cloned a lot of um repos, but you can't see that anymore. But you can see here it also set some envir which I personally didn't give it permission to. But um it probably cloned it to some folder for which it had some permission. So, it's clones some sample repos and then this one also 18,000. So, if you're looking for something fast that you can control, this is not it. But to be honest, just coming up with this um simple plan like code can do this 100 times better and it doesn't start clinging all kinds of kit repos and stuff. It just searches online and does it in in a few uh few minutes. I'm not going to implement this feature right here, but maybe let's also look at the how good it is at implementing things or what it does right then by just um let's make a cookie clicker. If you know Cookie Clicker, very fun. Um, Cookie Clicker open code. Like back back in the days when I was um still a a student at university and you had um you had exams like this. This was it, man. Just um clicking cookies all day while you were studying. And after a while, you can set up your own automatic cookie clicker and you can just watch it. It's it's much more addicting than than it looks. So, um let's see if um Cphus can make a basic cookie clicker. Um um I'm just going to I'm not going to plan for it because this will go on for for 20 minutes. So, we'll just ask um can you implement a cookie clicker in um let's say with NodeJS? Um no, let's just make it very simple with HTML plus JavaScript plus CSS functionality. Very basic. Just click on cookie and number increases. And of course also someone said in my last video, yes indeed you can cycle through the different variants of your model. Um but I don't waste want to waste any more um tokens with open code because it uses um enough um because here we are probably also going to see the UI agent and we can indeed see that um front end is being delegated to the UIUX agent. So um yeah there's a specific one with a specific prompt for designing good UIs can of course um inspect um what it's what it's doing he is responsible for creating the buttons and I think one of the main strengths of of my open code is that it shows you indeed what is possible like this is um if your workflow involves a lot of UI work it's very smart to make a separate agent to that with a separate context window and um take up context of the the the main agent. Okay, he implemented some basic tasks. So let's see what the um orchestrator agent is going to doing. Um for some reason he says like that we need to simplify the cookie clicker. But once again, you see um it's it's very inclined to um delegate tasks which causes the um yeah the the token cost to explode. Um so if you're very um you want to be very spare with your tokens, open code or my open code, you you shouldn't use this. Let's see um what it implemented. um an index on HTML a very basic script like I think um it's removed almost anything that the second agent call removes almost everything that the first uh one added but anyways let's see um if it actually works well inde a a very very basic cookie clicker but indeed um it works and indeed I didn't specify anything at all so it actually um followed the task quite well. Another thing I maybe want to show you is just um let's just do something else. Let's remove this cookie clicker and instead let's do a try to make a flappy bird. Um let's go into it with open code. And what I basically I'm I'm really into Ralph loops lately, but for some reason um the RA loop of open code I I just don't know how um exactly this works. And I think some of these features that are included with open or my open code are are just uh simply uh yeah five coded and and very broken because like it says like um right here Ralph, come on. Where is it? Ralph. Ralph Ralph Ralph loop supports all programming languages and you should just call it with Ralph loop build a rest API and normally it has some access to some files a a product file uh a file to um track progress. So I would assume if you make a custom command like I have for the regular open code that it will actually start by creating these files. But know what what this actually does is like um for example if I say um build flappy bird um you can see the prompts right here. Um you will work on the tasks continually. um you are a self-re referential development loop but there is nothing in this prompt about these BRD files and these and these tasks um and and and this task file that's normally included. So I don't even know this this isn't really doing anything Ralph related. it maybe just puts it in in an infinite um in an infinite loop while wasting a lot of tokens. So I will just say like um a lot of these features are um actually basically very broken in this in in all my open code. So you can't trust anything that's included. And yeah, after using all my open code for a few days, I just personally I think it's it's very much a a waste of tokens. Um, [laughter] and it's it's definitely not for me. I also cloned like um the repo of of all my open codes. Um, because right here, where is it again? And you can really um see what all these um what all these agents basically um well what the prompt actually is. So for example for um you can see the what was it again called the Cisphus agent you see like um the prompt is just like insanely large and I probably can't find it right now but it's so hard prompted to call all these separate sub aents which causes it to really burn through a lot of tokens and yeah, you can inspect the prompt um of of all the agents right here. And in my opinion, like AI agents work best if you make a workflow or if you make a set of agents that are specifically aimed at at your workflow. For example, when I'm working on some Terraform deployment code, I don't need all these MCP servers to, for example, um, control my browser and have some scales to make my UI look better and have a bunch of of of these, um, of these agents that are aimed at front end or searching up documentation when I just want to um, build some some some Terraform code. So I will just make some skills and an agent prompt um that is specific to my workflow and by just um having this very extensive maybe if it was a bit more minimalistic but there's just so much included with all my open code and it just takes up your entire context window which makes your LMS perform worse and also burns through a lot of tokens. Like one of the most important skills that you need to learn as an AI engineer is really optimizing your your context window and keeping it as clean as possible. But you can see these um first of these these prompts are um pretty um insane of um my open code of these agents and they are very much hardcoded with the um actual tools that are included with open my open code which are a lot. Also AI agents are pretty much a bit of a black box. So, do you even want to make it even more of a black box by just not even knowing um the the the prompts of the agents that you are uh using? I think by manually creating these agents and manually writing your scales, you get more insight in how your development setup actually works. Maybe also for me personally, but I just like uh creating my own own agents. I'm interested in learning how to write a RA loop from scratch, learning how I can best write prompts for my setup, how I can write scales, how I can write slash commands, and by just using this my open code plugin, you don't learn anything from that. So, to be honest, I wouldn't really recommend it in your daily um workflows. It can be if if you're very new to agents, I would not install it because it will just overwhelm you. If you um want if if you're a bit advanced, you also don't want to use this because you want to create a development setup and agent specifically for you. And if you're maybe a bit in between and you want to see what's possible and you have an OpenAI subscription, so never link your API key, do this. But if you have an OpenAI subscription like I do and you want to explore a bit what is possible, maybe get some inspiration about some agents. For example, this front-end agent can be very useful and you might want to adapt it in your workflow. Well, Dentis is actually pretty interesting, but um anyways, I didn't regret regret checking it out, but I'm going to uninstall it as soon as possible and probably never look um back at it. Um so, anyways, I hope you enjoyed the video. Why? Maybe leave a comment down below if you like open code or my open code, why you specifically like this. And I hope I see you in the next