Transcription
I've spent over 1,000 hours running my entire business with one AI tool, Cloud Code. And for me, it completely transformed what I can do with AI, but also what I can achieve in my business.
Most people are using AI for small wins. Writing stuff, getting answers, automating small tasks, solving one-off problems. That's helpful. But if you're doing just this, you're really missing the exponential AI transformation here, not even scratching its surface.
There is a completely different way of working with AI, and very few understand it because it's so new. It wasn't even there 6 months ago. In this video, I will break down the seven pillars that will unlock this transformation for you. It will shift your perspectives entirely. It's not about tips to save time here and there or to automate small tasks. This is a ground-shaking upgrade. Not just me saying that, but the members in my community on School, CCG, who have implemented this business operating system powered by AI. I will tell you more about this later. What I can promise now is that by the end of this video, you will see and use AI completely differently. Let me show you that.
Before I reveal to you the seven pillars of this AI big transformation, I need to explain to you this concept of AI operating system. The experience most people have with AI is the following. You chat with chatbots or AI like ChatGPT, Gemini, and all that stuff. You ask a question, get some answers, close tab, repeat. You have siloed chat sessions, siloed tasks you do with AI, ChatGPT, or any AI tools, and everything is kind of closed, right? It's tool by tool. You use ChatGPT for this, you use maybe Midjourney for that, you use another tool for something else, whatever. Everything is siloed, right? And disconnected each time. It feels like you're starting from scratch. Every conversation begins with zero context. You have to remind it about your business, your goals. You have to copy-paste resources. You have like, it's tedious and not effective at all. This is like having a different assistant every day who knows nothing about you, your project, what you're working on, and you need to remind it everything. That's boring.
What's different with an AI business OS is that fundamentally, this is an environment where your entire business operates. And that means, a bit like a computer operating system, it knows everything about what you're doing. You don't use Windows for specific tasks only. It's just that Windows is the layer through which everything happens. For an AI business OS, it's the same. It's the layer through which everything you do for your business, or even for your life and personal projects, happens. Leveraging knowledge, processes, automation, and so on. Everything inside one single system. That's super powerful. Everything is connected through the OS. So that's the same for an AI operating system. It's exactly the same concept, but for your business operations with this AI layer that makes it smart.
So, this is how it looks like an AI operating system. You have the strategic layer, basically, where your goals, your priorities, positioning, target customers, all these critical information about your business are well known. The strategic layer. Then you have the project management layer, where all active projects, their progress, status, dependencies, the next actions to do in a given project are sitting. You have the daily operations, where you have your planning, your task execution, productivity tracking, reuse, etc. You have a knowledge bank that has past learnings, frameworks, playbooks, templates, successful outputs. You've got, you know, knowledge you capitalize on.
In my case, I have a specific team for content creation because I use content to advertise what I do and teach other people what I do. You can have a content creation pipeline that is writing your content, taking into account your positioning, the targeting audience you want to craft content for. You have the content pipeline. My team has multiple agents in this pipeline for content creation. In your operating system, you can have also your process library, your workflows, your routines, your standard operating procedures. They are well known inside your operating system so that it can be used when it makes sense for specific tasks. You have also tools connections, of course, which mean your AI OS is connected with other tools you may use using APIs, webhooks, different technical manners, whatever. And finally, you have historical memory, which means the AI OS is logging everything you do so that it remembers what you do, the learnings from what you do, and all this is accessible to the AI and to yourself.
Okay, this is how you can modelize an AI operating system. Mine is running inside Cloud Code because for me, that's the best system for the moment on the market to run such an AI operating system, and this is what I teach inside my CCG community on School.
So, what it replaces, if you set it up properly, the AI OS will replace project management tools like Monday, Notion, and all that stuff. It will replace CRM functions. I have my CRM inside Cloud Code in my operating system. It will replace planning tools. I do daily planning, goal tracking inside Cloud Code OS with the right routines, the right systems, the right workflow, the right data. It will replace knowledge management tools that you're using like Notion, wikis, and so on. It will replace automation platforms. In my case, I'm not using any longer Make.com, Zapier, and Integromat, and all that stuff. I don't need that any longer. Every automation sits inside Cloud Code in my operating system. It will replace database tools like Airtable and so on. I'm not using Airtable anymore. I have everything inside Cloud Code. The databases are on Cloud Code, and potentially I can use Supabase or some other database provider if need be, if I need more advanced database features, but to be honest, I'm not using them. Everything sits in Cloud Code. Very simple database systems.
Presentation tools, forget about that. Now, I used to use external tools to create craft presentations. But for instance, the presentation you're watching here, it has been 100% produced inside Cloud Code. I just asked Cloud Code to craft the HTML presentation corresponding to the content I wanted to share with you, and that's it. I have a specific skill for that, by the way, small detail. And of course, what it replaces is the second brain. You don't need a second brain any longer. Cloud Code OS, or your AI operating system, will be your second brain.
And so, the key shift here is: you may still have a traditional use of AI, which means you go to the AI. Now, you will go to your AI operating system. This is your work environment.
Traditional AI use: Each conversation starts fresh, or you need to copy-paste or remind context to the AI.
AI Operating System: You have persistent context and memory in the AI operating system.
Traditional AI use: It's always a challenge to connect tools. So you have disconnected tools, even if they're making progress with connectors, webhooks, and stuff like this.
AI Operating System: Still, in an AI operating system, it's an integrated ecosystem. That means it's way easier to plug whatever tools you're working with, as long as there is an API.
Traditional AI use: You manage the AI.
AI Operating System: The AI systems manage your work and your workflows. You can delegate that to which you cannot do to GPT or Gemini.
Traditional AI use: AI does tasks, answers your questions.
AI Operating System: AI runs the operations using your SOPs, your knowledge bank, your past execution examples, your playbooks, and so on.
And so, traditional AI use is just a temporary helper that you need to retrain over and over again. Whereas with an AI operating system, you have a permanent infrastructure that compounds. Everything you do is analyzed, stored, leveraged for the next stuff you will do, and everything is connected and aligned with your goals, your strategy. So that's way more powerful.
So, you need here to have a mental model shift. Stop thinking "AI tools I will use for XYZ." Now, start thinking "operating system where my entire business is run." The AI operating system, it's the means for the big AI transformation that I will now show you, explain to you, and I will cover the seven pillars for this massive AI transformation. A new way of using AI with crazy results.
Pillar number one: Build it your way. So that's your AI operating system with your logic, your rules. What does that mean? Now, it's not AI that runs your systems. It's an AI that helps you build and design a system exactly as you envision them and as you want them to work. The tool adapts to your specific needs, right? It really matters because now it's architecture. It's not just operational. You don't need to adapt to these tools or to a specific app. Now, you can have a tool that fits your operational logic.
If I take an example, I have a specific way of managing my tasks, and I couldn't do it in an effective manner in traditional tools. So, inside my OS, I have a specific workflow and task structure and way of managing my tasks that fit my needs, my way of doing things. And of course, you learn by doing as well. And so that means you can correct and you can make the tool, the operating system, evolve as you use it because you're facing maybe friction, bottlenecks that you want to remove. And then the AI operating system is super flexible, and you have AI to help you evolve it according to your needs.
An analogy I can use to explain that is that most tools out there, and AI tools in particular, they're like renting an apartment, like you live within the constraints of this apartment. Whereas with an AI operating system built on Cloud Code, because once again, it's the best solution to do it till now on the market, an AI operating system is like having an architect who builds the house to your specifications, that may change, by the way, and then helps you live in it, which means work with the system, right?
And so here, I would like to highlight what I call the evolution principle, and that's a key insight, which means the power of this approach is that the system evolves based on actual use. Think about it. You're using a tool and you think, "I don't like this." Okay, let's change the way it works. Or, "I don't like the interaction." Oh, let's change the interaction. "Oh, it would be great to have this additional layer so I can do this automatically." Oh, no problem. Let's implement that. Okay, the tool evolves according to actual use. Which means it prevents you from over-engineering as well, since you know that you can make the tool. Okay, let's start V1 and let's add additional features because they are actually important based on my experience. Okay, so no more assumptions here. If you increase the complexity level, it's driven by real operational needs discovered through consistent daily execution. And that's critical. Like, this evolution principle is key. The system improves because you use it. Your use reveals what's needed, and what's needed gets built.
And if I take some examples, I built my system to organize projects, plan tasks, ensure alignment of my priorities in a way I actually enjoy working with daily. Okay, my Cloud Code is an evolution of me working with it and implementing what is useful for me. And so, over several months of use, I evolved my workflow for tasks, scheduling, prioritization, execution to better fit how I like to work and what I learn from using a system consistently. Okay, the system wasn't designed upfront and imposed on me. It emerged from use and adapted to serve me better.
I can illustrate that right away. For that's my business OS, and this is what we could do. Um, hey, I remember that, um, the last few weeks, we have upgraded the way we manage task planning. In very simple words, can you describe the evolution of the way we plan tasks and how we implemented that at the system level? Don't be technical. Just use words that anybody can understand. Just so I can see how the logic evolved and how we make this happen and change the system to apply this logic based on our experience of programming tasks inside the OS. Can you do that for me? Make it short. I'm presenting that on a video, so I want people really to see it. You can see it's exploring different stuff that we did, collecting data, gathering the report, and then that's it. Answer: There is a full report, and this is a summary story in a nutshell.
Chapter one: The old way. It was a simple to-do list. This week, someday, but I got some tasks that were skipped or that I lost. It wasn't perfect. So then there was a first fix in December. I added some real due dates to every task, basic, but hey, I felt that I needed it. So, okay, we implemented it. And then at the beginning of 2026, big upgrade. Now we have a smarter task management system with due date, strategic importance, priority level, time estimates, what product you belong to, what's blocking. And actually, today, I added some layer of intelligence as well, so that prioritization is a bit more automated. And so there was this shift from you managing a list to the system managing.
Okay, quick example. You can see here that the OS, the AI operating system, is self-aware. I mean, it can find how it's working and it can find what kind of modifications we made. I don't have to remember that stuff. It does it for me. Super powerful. So, that was a good example of "build it your way." Pillar number one.
Pillar number two: Build in goal guardrails. And the goal here is to stay on track without willpower. We'll talk about the strategic layer here. So, what is it? It's very simple. We have a strategic layer. I call it the AI growth engine. And that means every project, ID, task, random, whatever you do inside the AI operating system is evaluated through the lens of the strategic layer. And in this strategic layer, there are your goals. In my case, I have one obsessional big goal. That's my framework to plan and set goals. I have only one. Everything else is irrelevant. You have the way you plan to attain this goal. In my case, same. I have one unique vehicle, one unique path to attain this goal. In my case, that's my School community. And the one current principle bottleneck, because same here, I consider that at any stage in the business, there is one main bottleneck that you should remove, and if you remove it, it will drive the maximum impact. That's my way of planning, of having a strategy. Of course, you can adapt and have your own structure for your strategic layer.
Important thing here is that you have a high-level strategic vision that is the only source of truth. Everything you do should be aligned and contributing to this. But it's more than just a reminder system about what is a priority for you and what is the big goal for you. It's actually a structural constraint built into how the system operates. Why? Because before you do anything, before you act, there is a checkpoint: Is it contributing to the strategic layer? To the one big obsessional goal? Does it match the one vehicle? Is it relevant to address the one current principle bottleneck? One question: Is it relevant to what I want to achieve? And once again, this checkpoint is structural, not optional. Anything I do inside my AI operating system is checked against this strategic layer. If it doesn't match the strategic layer, it's killed. I don't do it. I don't start it. Okay, that's why I call it P number two, building goal guardrails. And actually, that's the system which ensures that manages that. It's not you. It's not your own discipline. It's not you who needs to remember. The system will do it for you.
Example of this principle, of this pillar. Every day when I start working, I do a routine that is a daily planning. This is for instance, today when I'm recording this video, I did my daily roadmap. So that's my daily roadmap, and you can see, uh, there is my one thing: it's record this YouTube video. The critical context, I have some context. You can see I haven't been very disciplined. I've been warned because I skipped some daily discipline stuff and so on. It reminds me stuff, but I have this daily roadmap. Basically, the AI operating system is planning my day for me. And when it does this, it checks my strategic layer. It checks that what I will do and what I will focus on is coherent and aligned with my strategic goals. And I do that daily. Same, I have another process when I have some ideas or when I think about stuff I like to do, brain dump, which means if I have an idea, I will just open. I have a specific workflow for that inside my OS, my AI operating system. It's a specific pipeline. I just speak to my AI. It will check my brain dump and then it will process it. There are agents, there are some frameworks, and so on, whatever. But it will process it, and in this process, it will check: Is this idea or is this thought aligned with the big obsessional goal and with the strategic layer? How is it connected to it? How is it contributing to it? If it's not, it will alert me, "Hey, this stuff is useless." Or if it is, it will develop structure, format it in alignment with my big obsessional goal, with my unique vehicle, and with my bottleneck, with my strategic layer. Okay, once again, that's this lens that is used to process information, to analyze actions before execution.
Anyway, the big idea here is that you can maintain strategic alignment and coherence automatically inside the architecture of the system without any willpower and discipline on your side. That's just crazy. How many times have you used goal-setting systems or systems like Notion when you have fancy organization to be sure that you're on track and you're doing the right stuff at the right moment and you stay aligned with your commitments and your goals? And if you're like me, most of the time, you start using it and then after, it's draining to maintain. Here, there is no such thing. It's inside the AI system. The AI system does it for you, period.
And for creative minds, if you're like me, you have most likely conceptually creative minds, which means you naturally generate many ideas. You see many opportunities. So you were facing, most likely like me, a specific challenge, which is scattered execution across too many directions. Okay, that's a problem I've suffered from for a long period of time. Now I've solved this problem once and for all with this approach, thanks to AI. The strategic constraint architecture channels my creativity toward only what matters. That's key, without my willpower. Okay, so your conceptual intelligence is applied exclusively to business-relevant outputs that match your strategy. You stop wandering out of priorities. Not through your willpower. It's not your discipline here. It's just through the system design. It's there. No effort on your side. For me, and if you're a creative mind like me, it's just will change your life. It has changed mine.
Pillar number three: Focus without fighting. Here, it's all about protecting your attention without requiring any willpower on your side. How it works? Since every initiative passes through the strategic constraint architecture, the first, the previous pillar, your attention is automatically directed toward aligned work, stuff that matters, priorities. Ideas, if you have many, they are captured so that they are not lost, so you feel reassured, you haven't lost it. Then they are evaluated. They are not ignored. Evaluated by not by you, but by the system, and then they are deprioritized or parked for later so that you don't pursue impulsively. In this, there is a double effect. One, you're not fearing losing ideas that come up. That's step one. They are captured, evaluated, and a priority is assigned. And second, you're not scattering your attention and your effort automatically. Super powerful.
So, it's like having guardrails on a mountain road. You don't have to concentrate on not driving off the cliff. That's the role of the guardrail to end that. Your attention can go to driving well, work on stuff that matters here and now. And so, the key takeaway from this is that an AI operating system, well-designed, will protect your focus. And once again, not by your willpower, but by system design and AI, once again. So you don't have to constantly ask yourself, "Should I be doing this?" No, the system will answer this question for you, and then you just apply. Of course, you can challenge if you like, but literally, you don't have any energy to invest in this. The system will already do the job. Okay, it will answer the question structurally.
I feel from a psychology perspective, it's also critical. Why? Because it's easier to accept not doing something when a third party, acting as a mirror or third eye, makes the call. If you're an entrepreneur like I am, for most of us, the problem is that we have too many ideas. We see too many opportunities, and you know, there is always this feeling of missing out. Here, you have a system that will tell you from an external perspective, "Don't do it. It's not aligned with your priorities," and it guesses what, it will help you not doing it. The AI provides this external rationalization that avoids doubts and overthinking. That means now you're not doubting, "Oh, maybe I should do it, maybe not. I don't know." Overthinking about it. You don't do that any longer. So you're saving precious mental resources. Focus protection. It's really relieving, not frustrating. The decision isn't mine alone. It's validated structurally by the system. I'm not the only one to decide here. It's really helpful.
Example I can give you. I have at my system level, I have a sub-agent that I call the ruthless prioritizer that applies my brutal prioritization framework. I'm a bit of an extreme guy on this, really. I've built systems to brutally prioritize, that means kill as many tasks as possible on my task list so I can focus on the very few things that matter. Okay, it brutally kills non-prioritized ideas. That's one of the agents I have here. It's the ruthless prioritizer, brutal prioritization specialist, proactively identifies the one thing using four-dimension evaluation, etc. Okay, I have an agent at my system level dedicated only to this.
Pillar number four: Go deep, not wide. Now you've got permission to sink into what matters. Focus protection. That means now you're focusing on fewer things, which means you have time, resources, energy to go deeper. Thanks to focus protection, pillar number three, you can go deeper on things that matter. So you sink further into initiatives instead of spreading thin across many. And that means you will get better at doing the stuff that matters. That's literally a recipe for success.
How it works? When you're not constantly evaluating, "Should I be doing this?" When you're not distracted by shiny new ideas because your focus is protected. When you're not scattered across competing priorities because you have a system that sets the right priorities and kills as many irrelevant stuff as possible, you can dig further into the work that matters and is aligned with the strategic layer. Develop more sophisticated thinking as well. And guess what? Produce higher quality outputs.
Example: I can work harder on fewer things with additional capabilities. That's a critical element here. Not only I'm focusing on the very few things that matter, I have energy, I have time, I have mind space to go deeper to these very few things. But in addition to that, I have AI as leverage as well to explore further and to execute faster and to go deeper because now AI can structure and challenge my thinking. I don't have to spend energy on structuring stuff. AI will do it for me. I have an AI that can connect other resources, can pull different resources from the system to focus on a specific or execute on a specific task or subject that matters. It can pull knowledge from project A, frameworks from project B. It can just compile all of this resources so that they are available in the system for a given task. It can do research refinement on my behalf. This is something that's well known from AI users. You ask AI to research about XYZ. It's not perfect, but that's one leverage to get information you don't have. So, it can do that as well. And more importantly, it can put relevant context that I might have forgotten because sometimes you did some work that gives some result that would be super useful for a new project, but you just forgot about it. Now, this system, the AI operating system, knows it's available, remembers it. Okay? So, it's not just about saving time or going faster. It's also about more capability applied to fewer, more important initiatives, which allow you to go, guess what, deeper, faster, and get better results. That's the consequence. Deeper work produces more sophisticated outputs.
But you know what? Sophistication going deeper creates also its own problems, and that's what the next pillar will address. Before I show you the next pillar, let me show you an example of "go deep, not wide" and illustrating some of these capabilities of the AI operating system, connecting resources, pulling relevant context, and so on. Let me show you that.
Hey, I'd like to work on a new attraction offer for my CCG community and ideally test two different acquisition channels and launch this new offer in these two acquisition channels. I'm not sure I should proceed and what kind of resources I can use, past experience, knowledge we have accumulated inside the systems to do this in an effective manner. Can you help me organize my thoughts and execute these projects?
So, it's doing what I asked. It will help me organize my new attraction offer project. It will explore resources, past knowledge, etc., in the system. And so, now it's doing its job. It's searching for a bunch of stuff related to offer, funnel, acquisition, launch keywords, and so on. Then it's checking past projects in my incubator where some projects sit. Look at this. It has found some resources. But let me also check future tasks and current priorities. So I understand where it fits strategically. So now it's checking both my strategy but also my current task list to see what kind of availability there is for that. And then summary: what already exists. I have some avatar research that is available to work on this attraction offer with different buyer profiles and refined avatars. I have some offer structures already existing. That's my current funnel and offer ladder. I have some value propositions that are well-framed. I have some offer messaging that is available somewhere in my system. I have a launch playbook. I have one launch that was okay that I did. I have a pipeline to attract customers, and so I have some gaps. But I mentioned that I want two acquisition channels, and based on my system, I can use ads, which is one acquisition channel that I can use, YouTube, which is another one. I can potentially use other channels, but they are not that effective for me, even if I have some resources I can use there.
Okay, then my recommendation: recommendation of the system. I should pick, if I want to test a new offer or an existing offer, I should pick what acquisition channel I should use, most likely ads and YouTube, which is on point with what I do, and the timeline as well, because I have already lots of tasks that have been prioritized and that are on the task list. So I may not have the bandwidth to do this. So the system already has everything related to my main offer, which is CCG, my community. But if I want a different attraction offer, like a lead magnet or special promotion, that would be new work. And now it's asking my attention. And of course, then I could go on. But here, in minutes, it has found all the necessary information available in the system to work on this new project. And guess what? And you can see the way I explain the product is really broad and specific and okay. If it was a real project, I would be more accurate, specific, I would give more inputs. Okay. But here, with basic information, I already pulled information from everywhere in the system that is relevant to executing this project. Compiled that, identified some gaps, reconciled that with my current tasks, my priorities, and then recommended actions or asked follow-up questions. Can you see how crazy it is?
So that means now I can focus on creating this new offer, go deeper. And guess what? Do we have some offer creation frameworks I could use for to create a new offer? And the answer is yes. I have three powerful frameworks. I have the "100 Million Offers" inside my own system. That's not the book. That's me processing the book and turning it into an eight-step process with sub-agents to work on every dimension of the offer. I have the Money Models framework. Once again, I crafted a video about this. It's not the book itself. It's me reading the book, turning this into process agents to do the job and apply the frameworks in the books. I have the attraction, because we are working on attraction offers. I have the five attraction offer types available there, ready for execution. I also have a skill to apply offer creation skills specifically for School communities. And so here, it's recommending a course of action. Okay. So yes, I have resources to craft offers. And I can do the same for anything. I can say, for this launch of this offer, what are the different steps I need to do to advertise the offer? Then it can lay out the steps, and then I can say, "Okay, what are the resources we have to execute the steps?" Then it can find the different frameworks and stuff that are available to do this. Okay, just to show you that leveraging this AI operating system helps you go faster, deeper, leveraging resources that you have available already, which mean most likely in your day, in your current business, you have procedures, SOPs, return of experience, playbooks, and so on, available. So you can put them in your AI operating system, and now they're available to execute future projects and tasks in a deeper, faster manner, and get better results. Most likely.
Pillar number five: Complex ideas, because we focus, so we can go deeper, so we reach a level of sophistication that is higher, but yet simple execution. That's Pillar number five. We got sophistication without the struggle, basically. Because the problem is when you go deeper and you develop sophisticated ideas, more sophisticated ideas. Why? Because you have AI handling structure, memories, organization, discipline, all that stuff. It frees up mental capacity to go deeper and work on more sophisticated execution and ideas. So when you're doing this, you encounter friction. Okay, it's really easy when you're working on complex stuff or advanced stuff or deeper stuff. It's really easy to overthink, to have analysis paralysis, and this level of complexity may slow down your implementation. That's a risk. The barriers between a good idea and executed reality are bigger, right? And so, the classical reaction to this complexity-related issue is that most people stay shallow. They avoid sophistication to maintain speed, or they go deep, but they get stuck, and they don't execute. Okay, that's the classical problem that may arise if you start going deeper on subjects and on work you do.
That's where we have an AI operating system that will bring the five friction removal mechanisms. Let me show you that. It's all about removing friction here, and that's what an AI operating system will do. That's why Cloud Code does for me and for the members in my community who join the Cloud OS program.
First friction removal mechanism: Resource assembly. The system pulls past resources to feed new execution. It knows your current projects and priorities. It knows past outputs and learnings. It knows available resources in the framework. You know, historical insights from previous work. Once again, it's not magical. It's that the AI operating system is built that way with the right mechanism, the right processes behind the scene that allows that. So that means when you start something new, relevant resources are assembled automatically without you making the effort, and sometimes from sources you might not remember you have. Just this. It's super powerful. It's really related to knowledge management, but it's done by the AI system for you. Think about it. Think about what you're doing with your AI tool, ChatGPT, Gemini, or even AI Notion in Notion. This kind of classical AI tools, you never got that. Everything is siloed, or everything is limited. Here, you're removing silos. Here, you give access to the AI to all your resources, and the AI system, the AI operating system, will use that with purpose and in a smart manner so that you can access these resources when you need them without making the effort of remembering where they are or even that they exist.
Second friction removal mechanism: Alignment validation. You can see here, it's really related to the second pillar we saw. Before significant effort begins, the strategic layer confirms alignment. Okay, always this lens to confirm that what you will do is aligned with what you plan to achieve your goals, right? It prevents the friction of discovering mid-project that you're off track. Okay, I mean, the goal of productivity, like the main principle of productivity, if you think about it, is to kill as many stuff as you can before even starting them. That's the game. So here, you have this done automatically. It removes friction. It removes also the pain of thinking, "Is it really valuable what I'm doing here?" Yes, it is. The system has confirmed.
Third friction removal mechanism: Execution support. Now you have operational routines that support your implementation directly inside your AI operating system. For instance, you have project management structure. Okay. You have daily planning workflows that check the task list, that prioritize the task list, that kill tasks that are not relevant according to your goals or according to what you've started the day before, the week before. You have productivity assessment cycles. You have progress tracking automatically at the task level and at the project level. All these are routines or systems mechanisms that are already implemented in the AI operating system, and they are run for you without any effort. That means you don't have to spend time, energy, and effort to build the "how to execute" infrastructure. It's already there. It's supporting your consistent, effective execution with all these processes, workflows, routines, automation. Sometimes it removes friction. Really, it's "I want to do this. Why are the resources available?" Resource assembly. It will pull the resources. "Is it really worth doing?" Yes, you have this lens that automatically checks if it's aligned with your big goals. Okay, done. Then, "Okay, now I need to do it. How do I do this?" Hey, you have all these processes that do it for you, that show you how to do it, and support how you do it.
Then, the fourth friction removal mechanism is build capability. And here, it's AI's inherent capabilities that will help you to structure projects, to create ad-hoc tools. Okay, so many times for execution, I need some tools. I need some, I don't know, I need some verification scripts, or I need to connect with an external tool. No problem. I mean, the AI will help me to just write the right script, create the right API connection, or create the right prompt to do whatever. You can create ad-hoc tools. AI will help you design workflows, systems. It will help you connect with external tools when needed. These are inherent code or AI capabilities that you can leverage. But now, it's well-structured inside your AI operating system, and you are sure that whatever you build is aligned with the pursuit of the goal. When you have a vision for how to execute something, because let's face it, most of the time when we want to do something, we pretty much know how to do it, the step-by-step process, or the way that makes sense to achieve it. But now we need sometimes to build systems or infrastructure or knowledge to help us execute that. Okay. And so that's where building capability of AI is super helpful because now you can brain dump what you think you should do and how you think you should do it. You can, of course, ask AI to check if in any past project or any available resources we have some experience about that that you can leverage that and reuse this. And then if you need specific stuff to be built to execute, hey, you just ask AI, it will do it for you fast, right? That's building capabilities of AI, super powerful.
And then, finally, integration assurance. That's the last friction removal mechanism, which means basically, new work you're working on will integrate with your existing AI business operating system, right? That means the results you got, the work you do, the assets you're building, or you're using to achieve results can be stored, put at the right place in the AI business operating system so that it can be reused. Okay, you can create knowledge banks, you can create process and SOPs libraries, you can create routine frameworks, you can create automation, of course, you can create a tool ecosystem. You can capitalize on every single stuff you do inside the AI business operating system. And once again, it's by design, and all this removes the friction of execution. Now, there is nothing that exists in isolation. Everything is connected. Every work you do is capitalized on. Every work you do can use resources that you've accumulated from past work, from past knowledge, from past experience. And so the result is that now you execute sophisticated ideas at speed and at ease. And now deeper work doesn't mean slower work. You have removed frictions with all these five mechanisms I've shown you.
So, it's kind of like the difference between hiking through unmarked wilderness, you have to cut branches and it's painful, versus following a well-maintained trail. Okay? Both can reach the same destination, but not with the same effort. One involves constant friction. The other lets you just focus on the journey itself and enjoy it. And you will see when you work with such a supportive system, you enjoy working. You're not drained by, you know, stuff you have to pay attention to and that are really eating your energy. No, now you can enjoy going deeper and be more sophisticated and execute faster as well because you have a supportive system that changed everything. Because let's face it, doing work is good, but if you enjoy what you're doing, if you feel like you have this feeling of, "Hey, I'm achieving stuff that matters," and I'm actually going deeper than what I expected, and it's faster than what I expect, and "Oh, I have this new, I don't know, sometimes intrusion or I can explore it's validated against my strategic layer and now I can implement right away." It feels way simpler. It's super, it gives you so much energy. That's crazy.
Pillar number six: Nothing you learn gets lost. Every insight is captured and reusable. So, what it is? Everything you do, action, feedback, realization, findings, results, return of experience can be analyzed, captured, and learned from. AI serves as leverage for capture and compounding, and that's critical. And so, how it works? The system captures behavioral patterns, how you work, like the way it works for you. Captures knowledge artifacts, insights, frameworks, standard operating procedures, skills, learnings, playbooks, and so on. It creates faster feedback loops because now it can identify what succeeded, what didn't, and explain why. And it creates realization moments, discoveries you made while doing stuff, actually. Okay, it's by design inside the system, inside the AI business operating system. This captured intelligence becomes accessible material for future projects with no friction.
And here, I would like to highlight the compound effect. Okay, because you can see that all these pillars we have covered so far, they are connected, right? Each pillar amplifies the next. Like pillar number four allows you to go deeper. Pillar number five removes friction in execution. Pillar number six, this one, capitalizes on past learnings. And so here, the past learnings help you go even deeper. There is a loop here, and deeper work generates more learnings, and more learnings compound further as additional resources for the next execution, right? And so this is the big equation here: Knowledge plus experience plus action equals compound intelligence. And let's face it, we all know that we should do this, right? But the problem is the friction of capturing information, structuring it in the proper manner, and then exploiting it in the right manner. Guess what? AI operating system will do it automatically. The whole cycle, the capture of the information is done by default.
Everything I do inside my business OS is captured. Like, for instance, if I show you this, this is my content team. Uh, this is actually the video I'm currently recording. You can see it has logged. We have worked on hook complex, and it has logged it. Okay, yesterday at 12:30, I created, I worked on the hook. Okay, it's tracking everything I do. It's recapturing information. Each time I make progress on the project, it's capturing it. Okay, so it capitalizes on everything I do. And this data aggregation allows me to do analysis, which means I use them to feed my roadmap routine. I also do productivity assessment that I do daily. So daily, I do a plan, I do productivity tracking, productivity analysis, and I track everything I do. That's why I can do productivity assessment as well. I do that daily. So I'm accumulating data, analyzing data daily. But it's not me doing this. It's my system. Doesn't take me any resources here for me. No energy, no time. It's done in minutes while I'm doing something else. It's tracking automatically. It's analyzing automatically daily. And guess what? I'm doing the same weekly, leveraging what I recorded and analyzed daily. And then I do it monthly. Okay, weekly synthesis, synthesis aggregated into monthly insights. And then I do it quarterly. And then I can do it yearly. Okay, at each frequency, there is data that is tracked, logged, stored, analyzed, insight extracted, and that feeds the next assessment for the next frequency, like the daily assessment feeds the weekly assessment, that feeds the monthly assessment, that feeds the quarterly. It's all automated. I have nothing to do here.
And so that means it reveals in a very granular manner, without my discipline, without my effort, without my energy, it reveals achievements, wins, failures as well, lessons learned, behavioral patterns, tactical and strategic drift. And here, this is the key insight from this pillar. All of this is systematized. The AI follows processes to perform analysis without effort from you or me. And that's a game-changer. Data is captured and processed automatically. I think we all know that we should track what we do, but it's painful, that's why we don't do it. We all know that we should have regular assessment of what we are doing, if it's aligned with the goals, and what's the next step, and is the next step aligned with the goals, and what are the capabilities we have to do next. But it requires to track data, to collect them. It's painful. We have so many other stuff to do. That's when an AI operating system is super useful. Why? Because it does it for you.
I have a routine where I do some Cloud Code usage evaluation. And so to this date, I've spent more than 1,000 hours, but I wasn't tracking time on a regular basis the entire period. So that means I've spent more time than this. But hey, that's not the point. I'll spend at least 1,000 hours with Cloud Code OS, my operating system. And yeah, this is the operation log entries. More than 2,000 operations during this period. Project files, more than two, I mean, so many project files created here. The daily roadmap generated, because this is a routine I've implemented not so long ago. But hey, almost 60 daily roadmaps generated. I may have skipped some, but hey, whatever. I'm tracking everything. Not me. The system. Daily assessment completed as well. The key deliverables built. Okay, so that's one of the other processes in my OS. It's just tracking everything I do, and it's evaluating my use of the system. It takes 2 minutes of my time to just trigger that, and then it's done automatically. Okay, just to show you. So the system is tracking everything for me automatically.
Pillar number seven: Outsource your mental load. Organization is handled by the system, not by your mind. It is cleared from that. You subcontract. This is the exchange. You subcontract to AI the organization, how things are structured and arranged, the tracking, what's in progress, spanning, complete, the memory, what we've done, what we've learned, what we've captured before, what are the playbooks, the knowledge, and so on. That accumulates all that is subcontracted to the AI operating system. And so that frees up space in your mind for important stuff because now your mind is no longer occupied with remembering where things are, tracking what needs attention, organizing information structures, or maintaining mental models of projects status. You don't, your mind doesn't have to do this any longer. So now you have space to do more valuable stuff.
And here, there are two concepts I'd like to highlight. First one is the emergence effect. That's a key insight. Resources and ideas you'd forgotten about with the system are captured by the system, and so they will resurface automatically when relevant. It's relieving. You don't.
Have to remember the system will emerge automatically, surface automatically the relevant resources you need to use for whatever you want to achieve. Why? Because the system holds your history and when this data, historical data becomes relevant to current work, it emerged without you having to remember it exists. It's really like having a librarian who knows your entire collection and automatically bring relevant books to your desk. When you start a new research project, including books you forgotten you own. That's super powerful.
So emergence effect and I've seen it over and over again. Here, I, the way I present it to you may sound a bit theoretical, but when you use an AI business operating system, you, you'd be amazed sometimes some stuff that emerge or surfaced. Like project, like so many times there were some resources, assets, or projects I had started and totally forgotten about, but super useful for new stuff I'm trying to to start now. And this, the the system just like pull this information, make it available, and then we can like work deeper, faster.
The other concept I'd like to uh highlight here is the capture, validate, execute loop. That's the core process here. Okay, this is something I've done so many times. You can capture your brain dump. Okay, you can brain dump into your system. So many times I have, you know, if so that emerge in my brain and it's, it's connect, I mean, super fast, it's connecting to many stuff. And if I try to structure it, it just cut the the flow. It, it just restrict my sync. But if I can just open a, here I'm, I'm doing a whisper flow to discuss from with my eyes. So if I'm in front of my computer, I just open whisper flow and just talk like randomly. I don't, not trying to stream anything. It's a brain dump and so it's captured by the system. And I have a process specifically in my business OS that collect this, which means I can speak to it directly, or I can just record a Loom and then I put a transcript there. So that means the brain dump is captured by the system.
Then the system will analyze it against my goals, my priority. Remember this strategic layer, goal alignment automatically. So it will, it will just check that automatically without me doing it. So that two things: it can validate if it's relevant to pursue or develop, and if it is, it can structure it and rearrange it so that it match my priorities and my goals. And it can also enrich it with some stuff we already did or some information or element that are in my strategic layer that are resonating with this new idea or the stuff that I want to achieve. Okay, or this brand by gate. The system then, when it's validated against the strategic layer, I can find the relevant existing knowledge to enrich it or to connect it with some stuff, projects we, we have started or projects we did in the, or not we have stored somewhere, or playbooks, or whatever. So you can enrich the brain dump, connect it with additional resources, and then the next phase of the loop is execution. If it's aligned, match with relevant existing knowledge, which is optional, but hey, that's good. Then it can be implemented fast with companioning intelligence, which means we can reuse stuff we've learned in the past, capture validated resources, and then executed. That's the loop.
And so now that way, ideas don't get lost. And at the same time, you don't get distracted either. Okay, ideas, they enter in the structure loop, this process. And once again, since it's a loop that is run automatically by the system, it frees up some mental load, mental resources. And now, really, each time I have an idea, I capture it directly in my business OS, or sometimes with Loom if I'm on the go, and I put the transcript in the right, and I the right process, and the right pipeline inside the business, and I just forget about it. It's there. It's available. I can leverage it, or I can execute it if need be. And it can resurface in my daily routines, weekly routines. The system knows, it captures, validates, resources, prepares for execution. It knows. And when I need it, it resurfaces through my routines. Can resurface in the daily routines or in various execution workflows during my daily planning, productivity assessment, weekly review, knowledge capture. All happens through the system. It's all like, it's already set up. I have no effort to do. It's already there. Okay. And I just participating. I'm just feeding the system with my work and my, so unstructured one. And then the system holds the structure, takes care of organizing stuff, takes care of making available this knowledge, ideas, project work for future execution or ongoing execution. Okay? I don't think about where did I put that. Hey, I remember I worked on something. Where is it? Oh, I need to to find it in my Google Drive or my. No, I don't do this any longer. I just say, hey, I need to work on this. I'll find the right resources for that. We'll pull the right resources in that. Or if I have prepared work, hey, I remembered I gave you some sort about this and find it. Yeah. Oh, yeah. S capture this is available. This is the analysis of it, and this is how you can execute it. That's freeing [snorts] you from the friction of remembering, structuring, organizing. You don't have to pay attention to that any longer. And that's a new experience of achieving things. That's what I mean by transformational. You can see we are far from asking questions to ChatGPT or asking ChatGPT to write whatever. That's another world. That's another level. That's the one I'd like to open the door to for you.
Now I'd like to share with you a meta layer. I call it meta layer with two very key concepts, which is delegated discipline and zero willpower consistency. Okay, because there is a universal human problem. Basically, we know what routines would help us. We know what we should do. We know that we should do daily planning. We, we know that we should do regular review and reflection. We know that we should do systematic capture of learnings, experiences, and so on. We know that we should consistently track our progress. We know that. But the problem is that maintaining these routines require discipline and willpower. And these are resources that deplete and fail very quickly. You cannot rely on your discipline and willpower. Actually, I cannot. I know I cannot. Maybe you are stronger than me on that. Anyway, the breakthrough insight is that now it's AI that can hold the discipline. You don't have to be disciplined. You don't have to have any willpower any longer for this stuff. The few disciplines I have and the few willpower I have, I can dedicate it to critical activities I like to do, by the way. And so now the AI operating system maintains the daily roadmap creation, the productivity assessment, the knowledge capture, the progress tracking, the pattern analysis. These happen regardless my motivation level on any given day. And you know what? I run, I run analysis across the information that is tracked by the system, my daily operation, my productivity assessment, all that. And it, it found out that there is no correlation between my productivity and my motivation. Whatever my motivation level, my productivity level is the same. Doesn't change. Why? Because I don't need to be motivated. I just ask, hey, do the day. I just ask, hey, do the productivity assessment. I just, I just say, hey, okay, we did a great work, like capture it, and it does no effort from me. So that's why I called delegated discipline. The discipline to maintain valuable routines is delegated to the AI operating system. This is the system that is disciplined. It's not me. I just harvest the benefits.
And the second concept, which is zero willpower consistency. Consistency that doesn't require my willpower. That's the best one, right? And now it's the system that is consistent, not me. I'm just participating, and my participation is really, really small. I mean, small when it comes to triggering this uh routines and and all that. Okay, my participation is big in the sense that now I'm working on very valuable stuff with the help of the system, and the system captures the results of my work. But you know, I don't need willpower to stay organized, disciplined, track stuff. No, everything is delegated to the AI system. Okay, the consistency is structural, not personal. And why this matters? Because without AI, you know that you should track daily progress, but you don't do it. Uh, you do it for a week, and then you stop. Uh, you have no data that accumulates, no patterns that emerge, no improvement that happens. You, you've just killed the loops because consistency is so hard, requires so much discipline. When you have an AI operating system, the system tracks daily progress, data accumulates automatically, patterns emerge from automated analysis, and improvement becomes inevitable, systematic. And so that's the big insight here. Capturing and processing of data is gold. But without an AI operating system, it's tedious. It's hard. It's always skipped at some point. But with an AI operating system, it happens. And you benefit from the gold without a TIGUM.
So what an AI operating system actually delivers? Simple. You may assume that AI does tasks you don't want to do. Lots of people understand the value of AI that way, but actually, it's not this. AI helps me build systems as I envision them. You know, classical AI advantage or AI benefits is AI saves me time. No, AI protects my focus and funnels execution. That's way better. What people ask you most of the time is that AI automates, automates repetitive work. So many times I've heard people saying, "Hey, you should do AI. It automates repetitive work." No. AI enables depth and sophistication without the friction. It's not wider. It's deeper and better. Now, AI is a productivity tool. Really? No. It's more than that. AI compounds my knowledge and intelligence over time, speeding up the improvement loop, feedback loop. That's way more powerful. People assume AI handles operations. No, AI holds discipline so you don't have to. AI holds consistency so you don't have to. AI adds capability. That's not just this. AI simplifies externally. Why? And internal sophistication. A good illustration of that is that I've just killed like 90% of my subscriptions and external tools. Now that I'm using an AI operating system, that means I have simplified my operations dramatically. But in the daily work I do, I can go deeper and be more sophisticated, be more complex with the tasks and the things I achieve. But it feels simple because I have the support of my AI operating system. And that's, that's the transformation that I want for you.
And so the transformation equation is this one. Build it your way. That's system design. Building gold guardrails. That's alignment by design for everything that you do. That's focus. Number three, focus without fighting. That's execution funneling. Plus, go deep, not wide. That's quality amplification. Plus, complex ideas, yes, but simple execution. That's friction removal. Plus, nothing you learn gets lost. That's knowledge compounding mechanism. Plus, outsource your mental load. That's cognitive offloading. Plus, number eight, delegated discipline. That means zero willpower consistency equals exponential execution capacity. This is qualitatively very different from AI automates some tasks and answers questions and saves me some time. You can see the difference. The transformation equation is game-changing. And the only thing that you need to achieve that is a well-built AI operating system inside Cloud Code, because that's the best solution to do such a crazy good system on the market for the moment.
So now the question isn't, what do I do with the time AI saves me? The question is, what can I achieve when AI handles the discipline, the memory, and the friction for me? The answer to this question is, you're not saving time, you're gaining capacity. Capacity to go deeper, stay aligned, execute faster, and compound everything you learn by doing without the struggle that usually comes with it. So if this transformation resonates with you, because by the way, that's the new way of working with AI, and it's brand new, and very few people know about it, very few people understand that and experience that on the database. I, the luck to do it, and members inside my community too. So if you want to learn more about building and using an AI operating system inside Cloud Code, because this is the tool we're using for your business or personal projects as well, it works. This is exactly what we talk about inside my school community, CCG. What you'll find there is some resources and knowledge that I share about code, about custom GPTs as well, and about AI business operating systems. And there is also my Code OS program. That's a premium program. And in this program, I share my entire AI business operating system that you can copy-paste right away for turnkey implementation, benefiting from ongoing upgrades that I made to it, because this is the one I use and I improve on a daily basis. And you get also implementation support as well. And the only thing you need to get access to that is to go on my CCG community. That's here. And I'm happy to see you in there, or I see you in the next video. Cheers.