Forget Claude Code, try Pi Agent instead…

[00:00:00]My name is David Andre and this is a complete course on PI agent. First, what even is PI? PI Agent, also known as PI.dev, is a very simple and customizable AI agent and it's the AI agent I've been using every single day, even more than cloth code and CEX. Also, it's one of the fastest growing repositories in all of GitHub, meaning soon enough, I think Pi will become the most popular AI agent in the world.

[00:00:25]Right now, we're witnessing the Pi revolution. A lot of the top people in AI and business have recently switched to PI, and I'm one of them. I've been using Pi every single day. I've talked to the founder, Mario Zakner, and I've taught over 250,000 people how to use Pi Agent, and I've compiled everything I know about Pi into a clear step-by-step course, which is what you're going to get in this video. So, first, let me show you how to install and set up Pi by going to pi.dev, which is the official site for PI agent. And here all you have to do is scroll down a little bit to see the oneliner installer command. I'm going to go with a curl command and simply click on copy. After you copy the command, open any terminal on your computer and simply paste it inside.

[00:01:06]This is going to install pi globally on your computer. If this is your first time setting up pi, it will take like 20 seconds to install it. Now, if you want to use pi effectively, you need to understand the difference between a product and a harness. Cloth code and codecs are more of a mass market products. They're highly opinionated, bloated, they're slow, they have tons of features, tons of safeguards, guard rails because they're made for tens of millions of people, the mass market VIP coder audience. Why, on the other hand, is a harness. It comes with just four tools. It's the most minimal agent out there. It has a very tiny system prompt, and the rest is up to you. And I think the homepage of pi.dev says it the best.

[00:01:46]You should adapt pi to your workflows, not the other way around. Now, why Pi?

[00:01:52]This is not the only agent out there.

[00:01:54]Why should we be using Pi over other agents? Well, first of all, it's the most minimal agent out there, making it easy to customize and change. Also, the system prompt is just 1,000 tokens, which is 10 to 15 times less than other agents. And by the way, those are tokens that you have to pay for every single time you use it. And unlike Codex or Cloth Code, Pi supports over 15 different providers with thousands of different AI models. So back to the terminal here to launch Pi all you have to do is type in two letters PI and hit enter and this will launch it. As you can see I'm already authenticated. If you are not type in /lo and this will open the menu for selecting your provider. Right? So you can use either a subscription such as the CHBD correct subscription or an API key. I'm going to go with that and I'm going to select open router. There it is. Hit enter. And next we need an API key. So let's switch back to the browser. Go to open router.ai here. Go to the top right and make sure you're logged in. Then go to the credit section and make sure to charge up some credits. You don't need to do $90. Just do $5 or $10. That'll be more than enough. Then go to the left and click on API keys. And inside of top right, you'll see this blue button, new key. Click on that. And this lets you create a new open router API key. I'm going to name it subscribe. If you're watching this and if you want me to make more videos on PI agent, make sure to subscribe. We are so close to 400,000 subscribers. So please go below the video and click the subscribe button.

[00:03:15]It's completely free and it's the easiest way to show appreciation for this type of content. Okay, so next I'm going to set a limit. I'm just going to do $30, something reasonable. And I'm going to click on create. Then I'm going to copy that. Keep your API keys private. Do not share them with anybody.

[00:03:29]I'm going to go to terminal and paste it in here. Hit enter. And as it says, saved API key for open router. So now we should have everything ready to send the first bronze. So say hi. And let's see if we can get a response. There it is.

[00:03:40]Hi David, what do you need? Amazing. So this is PI agent running locally on my MacBook powered by Opus for if you want to change the model obviously you can do /model to select any other model available on open router uh which basically they have all the models right so that's why you use it if you want to change the thinking effort as you can see I'm on extra high do shift tap this is one of the first keyboard shortcuts you need to learn shift tab says thinking off then if I do shift tab it's minimal low medium high and extra high usually I have it on extra And I do prefer to use fast even though it's double the cost of Opus 4.8. Opus 4.8 fast inside of Pi Agent is just incredible. You'll see what I mean later in the video. I've been building software for years and the back end is still the thing that slows everybody down. You can cook up a nice front end in an afternoon, but the moment your app needs real data, user accounts, embeddings, file storage, you find yourself stitching up together five services that barely work together. This is why Superbase exists. Superbase gives you a single Postgress instance with authentication, storage, PG vector all built in and it is production grade so it doesn't fall over once you put some real load on it. Now the real reason why buildings with superbase is so easy is their agent skills. You just give the skill to your agent and tell it to install Superbase and just like that cloth code or cursor can understand your schema, your RLS policies, your migrations, everything about your database. So when the agent writes SQL, it lands it on the first try, not on the fifth one. And unlike other databases, Superbase is fully open source. In fact, Superbase is betting on a world where agents write all of your code and they're laying the foundations for it.

[00:05:21]So if you're building anything with AI, you really should be using Superbase.

[00:05:25]Plus, you can get started completely for free. It's going to be the first link below the video. Thank you to Superbase for sponsoring this video. Now before we begin configuring our PI agent, you need to understand how the context engineering works inside of PI. So just like most agents, PI gets context from simple markdown files. And there are three main markdown files that PI looks at and these are the free ones. First is system.md. This will override the full system prompt. Be careful with this one.

[00:05:52]I would probably not touch it. If you want to change its default behavior, append system is better. This is appended at the end of the system prompt every single time you use PI. It's basically just like updating the system prompt without messing up any of the default things that Mario added. The third option is creating agents.mmd file either globally or inside of any folder you're working on with context specific to that project that folder. This is always added in that session. So mostly you're going to be changing number two and number three when you want to change how PI agent behaves on the context side. And one more thing that's very nice about PI is that it even reads your existing cloth.m MD files. So if you have a clot code setup with a project full of cloud MD files, PI will work there just fine right away. So as I mentioned, Pi comes with just four built-in tools. Read, write, edit, and bash. Very simple. Read allows you to read any file. Write allows you to create files. Edit allows you to edit or change files. And bash is the most powerful tool which allows PI agent to control the terminal. Everything else like web search, you need to add it yourself through extensions. Don't worry, I'm going to show you all of that step by step in a second. But first, you really need to internalize that these four tools is all you need. You don't need dozens of MCPS, hundreds of pre-built skills, endless amounts of plugins. You don't need that. And PI agent is the clear proof. And again, this approach is very powerful. For example, just with bash tool, Pi can basically do anything on your computer since it can use the terminal and it can open files, manage files, install packages, create folders, open applications, close applications, analyze your network, improve Wi-Fi speed, anything else that a professional developer could do if you had full access to your computer, PI agent can do. So, let me show you how to update the context inside of Pi by having it update itself, right? So, I can say find the global.py pi folder on my MacBook and it can find that and inside say like inside find the append system file.

[00:07:52]There it is. It found this append system and say okay add in a new sentence saying that you should always respond in English unless I talk to you in a different language then respond in that language. Any change you want to make just tell it to make it and it will make it right. As you can see I have some other stuff here. Always make your responses clear and concise. dates. I prefer this format. If you're American, you are incorrect. Day, month, year is the only correct format. Anyways, I have some other stuff. You know that I'm in Poland. Katita, no emojis. Short direct English. This is the new sentence that was just added. This is also a good one.

[00:08:26]David can't see tool/bash output. Always relay results in text. If you use cloth code, you know how annoying it is when it just says here's the results and it doesn't show you the results. So, that's why I added this. And yeah, anything that PI agents should know in any session, just add it into appendystem.mmd.

[00:08:44]Then if you're working on specific projects, just just say something like create agents.md for that project. And we'll create an agents.mmd file specific to that project, which is always going to get loaded if you're using pi in that project. And again, more on that later in the video. I'll show you some demos and I'll show you my existing workflow, which is way more advanced than using this terminal. In fact, let me give you a sneak peek because I'm using PI Agent inside of CMAX and I'm using it to do a lot of things at the same time. And I know this might seem overwhelming to some of you, especially if you don't have T-Max or CMAX installed. But trust me, this setup is very OP. You can easily launch new PI agents. You can have them control it. List out other PES inside of this CMAX workspace. And this really is how I use AI. Like 90% of my AI interactions happens right here inside of CMAX with PI agent. So later in the video, I'll show you my agentic engineering setup. But for now, I'm going to be using a simple terminal, which any of you have access to, and you can just do the steps I'm doing. Oh, and by the way, all of the prompts, skills, templates, extensions, everything I mentioned in this video are going to be available in the first link below video.

[00:09:50]So, click on that. It's completely free.

[00:09:52]Just fill out your email and I'm going to email you the full bundle of my Pi agent setup. Another thing you need to configure right away with Pi is web access. So since Pi is very minimal, it doesn't come with a web search tool. But setting this up is very very easy. So on the homepage again, this is pi.dev. Go to packages in the top and here just scroll down and type in pi web access.

[00:10:14]Hit enter. And there it is. This is the main package for PI web access. You can see that it gets over 90,000 downloads per month. And all we need to do is just copy this button and open the terminal and just run it. Or you can even tell PI to run it. check if I have boom now I know I already have it so it will say yes if you don't have it will say no and say like okay install it globally and it will just install that right what a lot of you don't realize is that you can use these agents to improve the agents right you don't need to do everything yourself in the terminal you don't need to try to understand every command once you have the agent installed use the agent to make it self-improve itself tell it install this package rewrite this prompt set up a new skill and it can do it. So, a lot of you are limiting the AI by your own limited prompts, by your own low-level prompts because you're not giving it ambitious enough of tasks.

[00:11:09]This is not 2024 anymore. The AI agents are super powerful. You, the human, are the limiting block. So, pay attention because I'm going to be showing you how to set up Pi in a way where it can 5x 10x your productivity easily. And I know that because it happened to me. So now that we have the web access configured, we can say browse the web and tell me about the new Elon Musk interview with Jamie Diamond. As you can see, it will use the web search which is by the way free. It uses Exa and it just searches it for free and it's very fast as well.

[00:11:38]Look how fast that was, right? So you you don't need to switch to Chad GPT to cla to Perplexity to do a web search.

[00:11:44]You could just do all of that from the comfort of your PI agent. And here it is. It was on the 4th of June. Jimmy Davin interviewed SpaceX part of the IPO road show blah blah blah. Here's some more info about this topic. Clear formatting. Very nice. And just like that, Pi can now do web search. So if I do Ctrl + C to kill this session and if I launch Pi again, you can see that it comes with the Pi extension. And this is how you make it yours. You don't rely on Enthropic or OpenAI to give you hundreds of pre-made extensions, prompts, guidelines to keep you limited. You get P by Agent fresh, completely empty, and you configure it yourself. It might seem scary at the beginning, but as soon as you know how to create skills, prompt templates, install extensions, and again, I'm going to go into how to set these up in depth later in the video.

[00:12:32]But as soon as you do the first one, such as the Pi web access, you can realize how easy it is to improve your PI agent and keep configuring it and customizing it for your own needs, for your own use cases. So let's talk about how to make your PI agent 10 times better. Since PI is very minimal out of the box, you need to learn how to extend it, how to improve it. And this really is the secret to getting the most out of PI agent. Knowing how to keep improving it day by day. And there are four main ways to improve your PI agent. Each one is more powerful than the last. So this I would say is the must learn thing. If there's one thing from this video you're going to learn about Pi, it is knowing these four methods because this is what really is going to separate people who just install it and stop using it after two days. And people who get Pi and their Pi grows with them and becomes more and more powerful with each passing day. So pay close attention because these four methods you have to know them by heart. The first two are the simplest ones. First is agents.md classic, right?

[00:13:35]This is the always on context just adding anything that you want pi to remember every single message put it into agents.mmd file. The second thing is a bit more advanced and that is prompt templates. So this is not just simple prompts. This is more like slash commands. So if you know inside of cloud code you can have these pre-built commands that you can trigger with slash you know review slash push to get whatever you want to do. Same thing works inside of pi. any prompt that you find yourself repeating often, turn it into a prom template and it's triggerable with a slash command. The third way to improve your pi is skills.

[00:14:09]So just like typical agent skills, these get autoloaded when they're relevant. So if you have a skill about YouTube, anytime you begin talking about making the next YouTube video, Pi will load that skill. It will read the full contents of that skill and it will be in the context window. So this is similar to cloud skills, it works exactly the same. Now, the fourth way to improve your PI agent, which is the most powerful, is extensions. And these are real TypeScript code. So, they can do the most, but they're also the heaviest, the hardest to develop, right? So, changing your agents.mmd file, you can just say make your answers more concise, and you change it like that. Creating a prompt template also takes 30 seconds.

[00:14:45]Creating a new skill, that can be a bit longer, maybe one or two minutes.

[00:14:48]Creating a new extension, that's the hardest, right? So, usually use extensions from other people. I'm going to show you the best ones in a bit, but these are real TypeScript code. They can do a lot. They work as hooks. And these are basically when markdown changes aren't enough. And a great example is the PI web access extension we added earlier. Okay, so now let me show you how to create a new Chrome template. I already showed you earlier how to update the append.md file. So here you have pi.

[00:15:14]If you don't have it started, again, super easy to start. Just type in pi, two letters, and then you can ask it find the global.py PI folder in my MacBook and the slashprompts folder inside. So, as you can see, these are the prompt templates I have right now, but it's super super easy to create more prompt templates. So, I'm going to say, okay, now create a new prompt template that's going to be slash review and it's going to be about doing a deep review of the entire codebase.

[00:15:45]Something like that. You just explain what is the thing that you want the prompt template to insert and what is the shortcut. Right? So now the shortcut is slashreview. And by the way when you make any changes to your pi config if you want it to take effect immediately you need to do slash reload because right now let's let's try this right. If I wanted to type in /re right now it will not work. Slash review it doesn't work. It's not there. So we need to do slashreload. This will reload the entire Pi keybinds, extensions, skills, prompts, themes. Just it will reload your entire PI agent. And boom, just like that. If we do SL review, it works now. And as you can see, we have the SL review skill and we enter it. The whole prompt gets loaded. This is how easy it is to create these prompt templates. And again, I didn't do anything. I just told PI agent to create the new prompt template for me. And after doing /reload, it works. So, anytime you find yourself repeating the same prompt more than once a day, create a prompt template for it. It's going to save you so much time. Now, since I don't need this one, I'm going to say find the slash review prompt template and delete it. And by the way, all of my prompt templates, skills, extensions, my entire PI config is available in the new society. So, when you go to the classroom here, you can see PI agent on the right. Click on that and you can see my prompt templates, skills, agents, MD, append system MD, and extensions. So you can just take any of these here from the resources and add it to your Pi setup instantly. The link to new society will be below the video. Now my favorite prompt template by far is this one short.md. So anytime I do like, you know, let's say explain to me how transformer architecture works for LLMs, it's going to give a long answer, right?

[00:17:24]And even though I have it inside of my append.md, which you saw earlier, it always gives a long answer, right? This is just the nature of the new tokenizer from Enthropic. So I have this prompt template /short that I can just invoke and it says make your answer simpler and shorter. In the past I used to type this 20 30 40 times per day which adds up right wastes valuable minutes of your time and you need to be as optimized as possible in the age of AI. Every single minute is valuable. AI is advancing so fast that you cannot be typing the same prompts over and over. That's why prompt templates exist. So now I just have to do /short tab enter and it makes it simpler and shorter exactly like I wanted. So this one is by far my favorite prompt template. The next thing I want to show you is my skills. So I'm going to do / new to create a new instance of pi. And actually when you do a slash new it doesn't show the skills.

[00:18:17]So I'm going to do ctrl c. This is a very important command you have to learn for the terminal. Ctrl c not command ctrl c. It kills the existing process.

[00:18:25]Okay. So no matter whether you're developer, whether you're non techchnical, you have to know Ctrl C.

[00:18:30]It's one of the most essential commands for the terminal. So I'm going to start pi from scratch. And the reason is because I want to see the set of skills, right? And you can see that I have a lot of skills over 50. I mean, you know, some people have way more, but these are the ones I actually use. I don't have random skills that I don't use. I would say probably 85% of these are from me.

[00:18:48]The remaining 15 are from other popular repositories. But let me actually walk you through some of them because this really is the bread and butter of pie.

[00:18:56]These skills is what saves me so much time every single day. I honestly couldn't live without them. So I'm going to say find the global.agent/skills um folder and open it in finder for me.

[00:19:09]And again you can tell pi to open apps for you. So instead of me searching around on my, you know, desktop taking minutes to find a folder, which this is crazy, you know, as I'm interviewing developers, and by the way, we're hiring. So if you want to work with us in Katavit and Poland, there's going to be a link below the video, see what roles we have open, and if you qualify for any of them, make sure to apply. But just seeing people still do stuff manually where they click around looking for folders, it's so amateur. Like you can literally use an AI agent like pi to tell it open this specific file inside of finder for me and it will do that right away. So that's what I did here with the agent file and that's what I did here again with the skills file. So here here you can see I have a lot of skills and most of them have been created in the last 30 days actually. So there are some that are older but uh yeah these skills is constantly what I create, constantly what I upgrade and again all of them are going to be available inside of the new society classroom right here in the PI agent module. So from these skills here are the ones that you should definitely have research prompt. Okay, this one's really good. So I'm going to jump into PI agent say read the research prompt skill and explain it. And since I know it's already going to be very long, I'm going to do slshort and I'm going to do option enter to pre-fire it, right? So you can presend the next message and it, you know, I predicted that it's going to be too long of an explanation. Actually, this one is pretty fine, but still the shorter one is better here. And basically, this makes py optimized for deep research program writing. So anytime there's something deeper that like you want to use maybe a chat GBD 5.5 pro extended or perplexity deep research or perplexity computer something just you know a deep research tool that runs for 10 15 minutes this will write the prompt for that. So maybe I can say what are the best meals to eat before working out for the best workout effectiveness. And then I'm going to say follow the skill to write a research prompt for this. And it's going to read the skill. Well, it already did read it earlier here. See, this is what it looks like when pi reads a skill. You see this purple skill and that's how you know it read the skill. So now it gave me this research prompt and I can just copy that into you know proper computer or chbd 5.5 pro extended and it's highly optimized prompt. I don't have to explain it every time. Right? So this is a beautiful example of a skill and again that's just one of the 50 plus different skills I have for pi and again all of that is available in the classroom of the new society. Okay so earlier you saw me send a prompt before the next one was finished. So this is called steering pi midrun and there are two ways to do this. You can press enter to steer PI agent right away after the tool call finishes. This is if something is going wrong. So if you see it going down the wrong path, you just say no, that's not the folder I'm talking about and you send enter and that's going to steer it right away. But if you want to cue a message to send after Pi finishes completely, then you do alt enter on Mac, it's option enter, and this will send a follow-up message after PI agent finishes responding. So this is great if you already know what's going to happen.

[00:22:15]You just do option enter and you type the next prompt. You do option enter again and you can send like two to three messages ahead of time and when Pi finishes the current task or the current response, it will automatically send the next message. Very clean. I use it all the time. Also, the slash compact feature inside of Pi is very good. Let me just show you because this is way better than the cloth code one. So here we've been talking for a while, right?

[00:22:36]You can do like slash compact. Boom. And it will compact the context. And look how fast it is. It will be like two to three seconds. There it is. literally two maybe three seconds inside of cloth code. This takes a minute. It's so slow. I never use it inside of cloth code. I hate it inside of cloth code. In fact, most agents have very very slow compaction. But that's not the case in pi. This slash compact is beautiful.

[00:23:02]It's elegant. It's fast and I use it all the time. So at the bottom you can see the percentage of your contacts window.

[00:23:07]So maybe I can send a message because after slash compact you just need to send. So we're at 2.5%. you know when you start reaching like 30 40 50% you definitely want to slash compact plus you can keep an eye on your costs. I'm using a very expensive model obviously at extra high reasoning effort. So the costs are going to be quite substantial, but no matter what you're using, each model is performing worse when it's like 90% of context compared to at like 5% or 15%. Right? So at the bottom, this is always available. Very useful bottom bar. Actually, let me quickly walk you through the bottom bar because it's very useful, right? So on the left you have information about the tokens. Then you have your current spend for this session. Then you have the percentage of the context window. Then it's auto, this is auto compaction. Then you have the model uh creator name. So that's enthropic. This is not the provider because I'm using open router. So model creator name. Then the model name. You can see that I'm using the fast version.

[00:24:00]And then the reasoning effort which again you can change that with shift tab easily cycle between them. So this is very useful status line. And obviously inside of pi you can change anything. So if you wanted to remove some of this maybe you don't want the context info or whatever you can just tell pi to update its theme and it can easily do that. So there's many different themes on pi. So you can ask it check global.py folder for any custom themes. There it is.py/ aent/ themes. So if you don't like this theme and you want it to be different, you want it to look maybe closer like cloth code, you can actually do that with one or two prompts telling PI agent to update itself. And again, I want you guys to realize we are so far in AI that you can literally tell these agents to self-improve themselves. Stop trying to figure out everything yourself. Stop trying to be the bottleneck. Tell the agent change the user interface to look more like code. Make it look less like terminal, more like JBD. Whatever you want, it can do it. Just communicate it clearly and don't give up after the first prompt. Now, this one is super important. Maybe I should have said it even earlier, but PI agent is always in YOLO mode. So, it will never ask you for permissions. And if you're a beginner, this can be very risky. But I would argue that it's just a skill issue because it can easily delete a folder.

[00:25:13]you can easily delete a file or install some packages that you don't want. But again, this is why you should use powerful models. So do not use pi with small models. Please avoid models that are cheap like Haiku Gemini Flash. Don't do it. Don't do it. There's a reason I'm using the latest version of cloth opus.

[00:25:29]Okay? When Cloth Mythos comes out, I'm going to instantly switch to that. When OpenI releases GPD 5.6, I'm going to switch to that. Use the most powerful model possible. Do not use small models and definitely do not use them inside of pi because it's in yolo mode and if you use a small model the chances of it messing up and doing some catastrophic mistake is much much higher than if you use the latest version of opus. So this is completely different approach than cloth code or codex. Both of these are very safe by default very restricted.

[00:25:59]They ask you to approve like every other tool call. It's very annoying and that's because these companies are trillion dollar companies. I mean both OpenAI and Enthropic are valued at $1 trillion and they cannot risk some agent going rogue and deleting companies data, right?

[00:26:15]Deleting a production database or whatever. So they heavily guard rail them. They heavily restrict them and that's good for beginners but it's not good for us people who are actually serious about AI. Now you have two options right with Pi. You either use the best model and continue without safety guardrails, which is what I'm doing, or you install a package to solve this, which is actually what I would recommend people to do. And there's a great one called PI permission system.

[00:26:39]So, let me show you once again. When you go to pi.dev, the default PI website at the top, you can click on packages. And you can see all of the popular packages, recent ones, whatever. So, just type in permission to find all of the packages around permissions. And there are a lot of solutions for this, right? You can click through them, learn about them, but the most popular one is this one. Pi permission system with 17,000 downloads per month. So, you can just click on that, read about it, or you can just copy the prompt right here. Pi install.

[00:27:09]Just copy that. Boom. And tell it to your PI agent. Check if we have this installed.

[00:27:15]Boom. Boom. Okay. So, I'm going to say do not install it because, you know, I don't mind it being in yellow mode.

[00:27:21]Personally, I like it. But if you do want to install it, if you, you know, maybe are newer to AI, you're not sure what these agents do, maybe you're on a company computer and you cannot risk by deleting some some info, uh, then definitely install this one. Uh, again, all of this is again the link to this package is going to be inside of the classroom here in M society. Can just click on that. It's going to take you directly to the specific package where all you need to do is just copy this and send it to your PI agent saying install this package. And just like that, it will install it for you. Now, so far we've been using PI inside of the default Mac OS terminal, which is fine, but it's nowhere near as powerful as using it inside of CMAX. So, let me show you that. By the way, if you don't know what CMAX is, I recently made a full video on that. So, if you want to check it out, make sure to watch it after this one. But CMAX is basically the terminal for AI agent management, for running multiple AI agents in parallel. In fact, let me show you how easy it is to spin up multiple agents, right? So, we have PI, we have cloud code, I can launch in Codex, and this is, by the way, real time. you know, I'm doing all of this in real time. And just like that, I launched four different agents in parallel in the same workspace in a nice 2x two grid, right? And uh this is Cmax.

[00:28:30]This is possible. And actually, we can ask Pi check what's running inside of this CMAX workspace and give all of these agents, all the other free agents, a simple task just for them to analyze something, not make any changes.

[00:28:45]This unlocks a world of possibilities because here you can see that pi I have two skills cmax and delegating to agents which you will get um in the new society repo. And there it is. It delegated to other agents. You can see it sent the prompt to other agents by itself. I'm not doing anything. This is pi working with these agents and telling them what to do. So by itself it analyzed the Cmax workspace because I have a skill for this Cmax and a skill for delegating to agents. It read both of these skills in like half a second. It was super fast.

[00:29:12]And then it basically send all of them a test prompt without me having to do anything. And again, this is really the future where you have one agent as a orchestrator. The other agents are doing the tasks. I'm going to go more in depth into this later in the video, but just know that if you want the most out of Pi, you should definitely use it inside of CMAX. It is the way it is how I use it every single day. And it just makes it so easy to launch different workspaces with command N. Or if you are in the same workspace, you just do command D to launch a new pane on the horizontal split. You type in pi. Or maybe you want to do a vertical split.

[00:29:45]You do command shift D. You launch another PI. Or if you don't want to even do that, you can say, I closed the other three agents. Make sure to launch three more PI agents inside of this CMAX workspace. You just tell it to PI to launch more agents in there, right? It can look at the state of the CMAX. It can launch new paints. It can do vertical splits, horizontal splits.

[00:30:07]There it is. It just launched these by itself. and it launched these PI agents by itself. So, CMAX is really amazing.

[00:30:14]It also allows you to like zoom in, zoom out different terminals. It allows you to resize them nicely. Um, yeah, it really is the the ultimate terminal. So, if you are still using the default Mac OS terminal, I mean, it's fine. You know, I'm not going to hate on it because I've used it for years as well.

[00:30:30]It's fine, but it's nowhere near as powerful as CMAX. This has been built for running multiple AI agents in parallel. So, I would highly recommend you use it. And again, it's completely free, just like Pi is completely free.

[00:30:41]So, both are open source, both are free.

[00:30:43]There's no reason not to use them. Like, you literally have no excuses. The only excuse is sitting down and setting this up. So, actually do it. If you're watching this video, when you finish, watch it all over and set it up. Don't just be a watcher. Most people are just watchers. They go through life. They don't implement anything. They never change. They have the same habits. Don't be one of them. Be a doer. Implement everything I'm showing you. All of this is free. It's easy to implement. It's so easy. Like I'm showing you all the steps. You just have to do it. Sure, it might be intimidating for the first time, but you have no excuses. In this video, I show you everything. It's the ultimate PI agent course. So, if you really are serious about AI and you want to be on the cutting edge, stop being a washer and start being a doer. Now, as you might have noticed, PI agent has no sub agents, and that's by design. So, instead of using sub agents, Mario, the creator of Pi, recommends spawning multiple PI instances in parallel, just like you can see here I did with T-Max.

[00:31:36]And you can use either T-Max or CMAX easily. Like these are tools that are very easy to use. And this is the workflow I've been using daily. It's simpler, it's more transparent, and you're actually fully in control, which cannot be said if you're using cloud code and the cloud code sub aents, which half the time you don't even know what the sub aents is doing or why it's doing that. Also, the PI plus codeex combo is very OP. So using PI agent with Codex is really incredible for development especially. So I would actually say that this is one of the best PI workflows out there currently using PI as the orchestrator and the CEX as the you know coder as the one as the one doing the task like the actor. So Codex CLI managed by PI amazing for coding and development and this works especially well inside of CMAX because PI can spawn and manage other agents by itself. It can read the CMAX panes. It can kill them. It can restart them. It can pull them and check them every 5 10 seconds.

[00:32:33]Yes, doing this inside of CMAX is the way to go. And by the way, you get the best of both, right? So you get a PI agent that's your personal agent with all the context that you know, you know how to talk it to. It's easy to talk to.

[00:32:44]You can use any model. If you prefer cloud models, you can use that. And you're fully in control. And that agent is driving Codex, which is right now the most powerful coding harness. Plus, you can save cost because instead of Codex, you can use the CHBD subscription, which you're already paying for. And instead of PI, if you're using the open router API key, you don't burn as many tokens as if you're only using PI or running two to three PI agents in parallel. So PI plus codeex definitely the way to go.

[00:33:09]In fact, let me just show it to you. So I'm going to say kill the other three CX panes. Now launch four new ones in 2x two grid next to you and in each launch CEX-OL.

[00:33:25]So this will launch Codex CLI inside of YOLO mode and again we can just chat with Pi and it's going to manage these um Codex agents easily.

[00:33:34]All right. So it's launching them. Okay.

[00:33:35]It's not really the grid is not really fixed but it launched the agents. Fix the grid.

[00:33:41]It does not look good. And I'm going to hit enter without option enter to steer it right away. And you can actually do a screenshot as well. This is something I didn't show you. You can easily do CtrlV to attach screenshots. Here I'm going to do escape to interrupt it. So anytime Pi is chatting you can just do escape at any time to interrupt it and it will stop generating tokens. And if you want to paste in a screenshot it is CtrlV, not command V. Here is what it looked like and it will read the contents of that screenshot. We'll see okay this was messed up. It's not the nice grid that we wanted and it will figure out how to fix it. Okay. So now I think it's on the right track.

[00:34:21]There it is. Exactly like I wanted. So we have the Pi on the left and a 2x2 grid of CEXes on the right. And look how amazing this is. Like anytime this launches, it just never gets old. Pi launching these agents and managing them. It's it's amazing. So now I'm going to say, okay, now give each of them to build a simple single HTML app.

[00:34:39]Each of them should be different app and tell them to launch it on different local host ports. So you can just chat with Pi in plain English. Again, again, this these ones could be completely zoomed out because you're not really chatting with them. And what's nice about CMAX is that the zooming in is custom for each pane, right? So if you want some of them to be like very large font size, maybe the PI agent that you're talking with, you can zoom it in while the other ones are very small and uh not really interactable, but also easy to look at what they're doing, right? So now Pi is pulling them. You can see it's doing like sleep 25 to check on it in 25 seconds. And your job is basically to communicate your grand goal to pi and it's going to send it to codexis which themselves can do /go goal to work forever until that goal has been achieved. Right? So really the amount of abstractions the amount of loops you can run here is only limited by your imagination. But this is my favorite workflow basically using pi. Usually I have like two codexes not four because usually two is enough. But I'm only talking to the Pi and it's managing the COX instances and it doesn't burn as many tokens because all it has to do is do sleep and then read the contents of those codexes. But 90% of the tokens or more is generated by the COX CLI which I'm running on GBD 5.5 medium fast or if it's something more difficult I do high or extra high but medium is usually enough and definitely use fast mode inside of Codex. In fact, I would say that the CH GBT $100 subscription is probably the highest value $100 you can spend in all of AI. So if you don't have that, you're definitely missing out. But yeah, Codex right now is the best at difficult coding. And there it is. Yes, open all four as new Brave browser tabs.

[00:36:21]So again, Pi can control a computer and it can do stuff, right? So there it is.

[00:36:25]We have one, two. So all of these are the same right now.

[00:36:30]So I'm going to tell it screenshot and confront it.

[00:36:34]All of these are the same right now.

[00:36:36]Make sure to fix this. Read what the codexes are doing. Okay. So what happened is they wrote the same index.html.

[00:36:43]So now PI agent is going to correct them and you can see that it send the prompt to all four of them so that they create this in a separate subfolder because they kind of overload the files, right?

[00:36:54]And the main idea I want to drill into your head here is that how much longer would it take you to read the outputs of these codexes and try to understand what each of these codex agents is doing. If it outputs like 2,000 tokens, sure you can say make your answer simpler and shorter, but it still would take you a lot of time to read the full output and to understand whether it's on the right track, whether it did what you wanted to do. But instead, if you have a PI agent monitoring the output of the CEX agent, it can read those tokens way faster. I mean, an LLM can read maybe 100 times faster than humans. So all you need to do is tell Pi what you're trying to achieve. What is the end outcome, the desired end goal, and will manage the codeex to get there. This is especially OP if you're debugging a VPS. Let's say you have Hermes agent on a VPS, you also have a Codex CLI there to kind of manage it, right? So if you want to update your open claw or your Hermes agent to latest version, you ideally have a Codex CLI on the same VPS. But instead of talking to the codeex which you have to figure out what's the status of the VPS, why did the Hermes gateway crash? Why is open claw disconnecting WhatsApp, you instead run pi. The pi opens a new cmax pane. It sshes into the VPS, launches codexi on the VPS and it talks to it and anything it outputs it will know it instantly. So this is really the way having your main orchestrator, your main agent that responds in a concise and clear way, has the main context, knows your preferences, knows your preferred style of conversation, manage other agents that are very powerful developer optimized agents. This is the way. So trust me, implement this as soon as possible. You're going to implement it sooner or later. So either you do it now or you do it in 2027, it's entirely up to you whether you want to be on the cutting edge and get an unfair advantage or if you want to be behind everybody.

[00:38:39]That's your choice. So now this should be solved. If we reload these, we should have a different app in each. So we have the timer, we have the calculator, to-do list, and uh what is this? Stopwatch, right? So very simple apps obviously, but the main idea is that each of these codexes build a different app and it cost me zero in open router cost because was just managing, right? So it only spent a few tokens reading the outputs of them. But most of the code, I mean all of the code and most of the tokens would have written with Codex CLI which is powered by my JVD pro subscription which I'm paying for anyway. Now perhaps the most advanced concept inside of PI agent is the sessions. I'm going to try to explain it as clearly as possible.

[00:39:18]Every session is a tree. So it's not a linear you know step-by-step assistant chat like in cloth code. It's instead more of a tree like this. You can maybe compare it to Git work trees if you understand that. But basically anytime you make any change it branches off right. So maybe the easiest way is to demonstrate it. So if we jump back into pi and I do escape you can do escape twice. So if you do escape once it interrupts the message. If you do escape twice you can go to any previous point in the conversation history. So maybe if you scroll up to my last user message here I can hit enter and do no summary.

[00:39:53]And I can change my prompt here. You know, I can say uh um why are they all showing the to-do app answer in short, right? So, I'm saying a different message from that point in history and it's going to investigate that and I'm going to interrupt it because I don't care about the response. What I care about is the tree has been created. So, if I do escape double, we can see that we still have both versions, right? We serve the original message which was me sending the screenshot and pointing out the issue and we have the new message which I just sent right now. It kind of branched off. So instead of having a linear single chat history, it branched off into two. And now we can continue in each of them. And if we if we change the message any of them, it would branch off again. So this is the most advanced message history. It's a bit harder to understand than the linear one you have in JBT or cloud code, but it's the most advanced one. It's the most customizable one and you can go back any point and just branch off. Now, if you want to manually split a branch into its own session file, you can run slashfork. So, this is a command inside of pi that will split the branch. Let me show you. Let's jump back into CMAX here. So, we can do /fork and it will create a new fork from the previous user message. So, we can select which message maybe you know here before we did the build. So, instead of simple HTML gap, we can say a game, right? Right? So we could say now give each codex agent a different web app game to build. Right? And this is a completely different fork and it's forked to a new session. So it's not just the same session in the tree. It's completely new sessions. So if you do slash resume you can see your previous sessions. This is the chat history. So for people who are coming from cloud code chb the codex app and you want to see your previous chats or threads sessions is the equivalent in PI agent.

[00:41:40]Now session files are port portable JSONL. So you can c them slash share them, write tool against them. You can do a lot with them. So if you have a session that you want to share with somebody on your team, you can just do slash share and send them a link. So here is what that would look like. Slash share. Boom.

[00:41:57]Uh team not found matrix. Okay. So I'm getting some error. So I'm going to have pi debug that. Copy. Paste that in. I'm getting this error anytime I do the slashshare inside of pi and do slash share.

[00:42:14]Investigate why that is. Browse the web about what is the proper solution and tell me how we can fix it. Do not make any changes yet. And this is the exact process you should follow when you run into unexpected errors because so far everything has been smooth in this video which is good. you know, I'm making a nice tutorial for you, but it doesn't give you the skill set of how to fix it in case something is different. Maybe you have a different operating system, you have a different computer, you have a different version of Mac OS, whatever.

[00:42:42]Maybe you misinstalled it and you have two conflicting Pi installations. If something goes wrong, provide it a screenshot. Tell it what's going wrong.

[00:42:50]Tell it to do the web search. Hopefully, you already set up the Pi web access extension and tell it, "Okay, explain what is going wrong and how we can fix it. Do not make any changes yet. It will do the web search. It will analyze it here. It did the web search super quickly. And investigation complete. No changes made. What share is blah blah blah contains. Okay. So my setting contains matrix but there is no matrix theme installed.

[00:43:14]So we can probably remove the matrix theme. Yes. Go with removing the matrix theme. Do not do anything else. This is how you debug. You tell pi this is what went wrong. You give it a screenshot.

[00:43:29]You tell it to do web search and um it will fix it. It will research the stuff and will tell you how to fix it. So now if we do share it should work. Now we we can we we have to do slash reload.

[00:43:40]Remember anytime you do something you have to do slash reload. Uh so I'm going to say read the status of the four codeex agents in this CMAX workspace so that there is something in the chat history and then I can do the slash share. Okay, there it is. It gave me a response. So I'm going to do slash share and it's creating a gist that'll be easy to share with the rest of my team. So we get two options. We get a share URL and a gist. So I can click on this. It'll open. Actually it opened here. It's kind of funny. Uh it opened inside of Cmax because CMAX has a built-in browser by the way. That's another reason you should download it. But this is what it looks like. You basically get a link where you can share the entire session.

[00:44:14]On the left you have the chat history.

[00:44:15]And on the right you have the the outputs, right? The prompts from you as well as the PI assistant. So anytime you want to share a conversation with your team, it's literally just one command away slash share and that's it. That's how easy it is to share your pi history, chat history for a specific session with somebody else so they can see how you came to that conclusion. They can see how you prompted or whatever. So this is very OP command. Make sure to use slash share. On the topic of sessions and sharing, you also need to understand the slashres command. This is how you can jump back into any previous conversation or session you had with Pi. So none of that is lost. Let me show you. It's actually very easy. So when we go into Cmax here, let's say your Cmax crashed, you had to restart your computer or whatever, right? And you have to start pi again. It starts fresh, starts a new session. So the way you would go to a previous session is just do /resume and this will show you all of the previous sessions. This one you can see 9 minutes ago here. This one is four minutes ago.

[00:45:13]So you can just go into here and this one is a fork. So you can nicely see it's a fork of that and in fact if we do a new one say like hey and then we kill it and we start by and do slash resume we should see that as a separate session. So there's the hey session which is now literally seconds ago and this is one 9 minutes ago and that's how you can see different sessions and you can just hit enter and boom there you are in the next session say let's resume our work or whatever right so anytime you want to continue in a previous chat this is how you do that another controversial design decision in PI agent compared to other agents is that it's antiMCP it's again MCP servers you can see that we've went through this entire video without mentioning MCPS once And that's because the PI approach is completely different. Instead of connecting MCBs directly, it serves them as CLI tools. So anything you want to do with PI, it can do it as a CLI command line interface. So if you really need to call an MCB server for some reason, you wrap it as a CLI tool and suddenly PI can control it just like it can do any other terminal command. So there's this thing called MCP border which exposes MCP calls as CLI commands and then PI can just run them through the bash which is one of the four tools it has. There's also PI MCP adapter community extension.

[00:46:26]It skips the MCP bloat and there's one small proxy uh for MCP servers and it loads all of the tools directly. So if you really need MCP, these are two solutions, but usually it's just better to use direct terminal commands CLI tools which PI can natively execute without any issues. So that's it. This has been the ultimate PI agent course and again all of the resources from this video will be in the new society classroom right here inside of the PI agent module. All the extensions, agents, MD file, skills, prom templates, everything I mentioned, you can find it right here and just take it, copy it and implement it right away. The link to new society will be below the