The Ultimate Guide to Building 10x Faster with Claude Code

Most people know what Claude Code is, but they have no idea how to actually use it to build faster. So, in this video, I'm breaking down the exact road map that will help anyone use Claude Code to build 10 times faster on both technical and non-technical tasks. The road map is six actionable steps that you can implement today that are inspired by the frameworks that I used while the COO of a $25 million tech startup, and what I've taught millions of other people like you on YouTube. So, part one is build the top of your T. You want to start doing more. While I was at my first job as a software engineer at J.P. Morgan, they would stress the importance of being a T-shaped developer. And what this means is you have breadth in a lot of areas, but depth in a single area. With AI, the same applies to every person. You need to become a T-shaped builder. So, that's breadth in every industry, which is the top of the T, and it's now 100 times easier with AI. And then you want depth in one specific area, that is the vertical part of the T, and that's where you're an expert. In this video, the first three steps we'll go through will help you establish the breadth at the top of your T, and then the last three will identify what archetype you fall into and how to build the depth needed to differentiate yourself. So, step one of building the top of your T is lock in your AI stack. The biggest issue with AI is feeling overwhelmed by the number of tools out there. And this leads to what I call the AI tool graveyard, where you have a bunch of tools you've tried, spent time on, and then you just abandoned it with little to show for it. So, in order for you to build faster, we need to identify our AI tool stack and stop questioning if these are the right tools to use. Make a decision, use it in your day-to-day, and then every three to four months re-evaluate. My general rule of thumb is I don't need to be first, second, or third to a new tool. I wait until it's so undeniable that I just have to use it. So, here's what we will use and what we won't use, because explicit do's and don'ts reduces scopes and helps you have laser-sharp focus. First, we're going to use the Claude desktop app. In my eyes, this is the simplest way to interact with Claude Code while giving it access to all of your local files. You just download the app, select the code tab, and then you select the project you're working on. If you are more comfortable using it directly in the terminal, that's entirely fine, too. But the second is we'll be using Claude skills, plugins, and MCP connections. At a high level, skills are repeatable workflows you can have Claude run for you. Plugins are bundles of skills and commands that you install. And MCP connections, like Claude, reach into external services like Gmail, calendar, Notion, whatever you're using. And the beauty of all three is they extend what Claude can do. And the general rule of thumb is we want Claude code to be our interface. We don't want to have to juggle between a bunch of different tools and logging into different web pages. One last thing that I consider as part of the stack, because it's one of the only universally agreed upon things in the AI ecosystem, is using plan mode. In Claude desktop, click next to the plus and select plan whenever you're working on anything robust. Then you could say, "Task, interview me to identify any gaps or issues in my plan before building." And I'll then go ahead and create an exact plan to help Claude build it quicker and make sure it's exactly what you want. This is universally agreed upon, so it will help you build faster. Now, the first step set the foundation, but the second step is where the fun begins. Step two, expand your domains of execution. Think of your output like a factory. Each step requires a specific skill, and every step that you can't complete yourself reduces your ability to get done. And before AI, learning every skill in your factory took years. So, you had to work with experts called sales people, lawyers, designers, engineers, marketers. But today, with AI, you can get a foundational understanding in minutes, and then most day-to-day tasks become doable on your own if you take the time to learn the basics. And suddenly, you'll stop needing permission and expand the list of things you can complete end to end. process of learning foundational skills in a new domain is what I call going zero to one. So, how can you go zero to one in different subjects? The truth is, with any new skill you're learning, seeing is believing. I can tell you all day that you can do this stuff, but until you actually do it yourself, you won't believe that you can actually do it. So, no matter what field you're in, these three mini projects will help you go zero to one quickly in domains that matter. The first micro project is build a calendar review automation. This is to get operational basics. This project will expand your knowledge into operational automations and give you confidence when building out systems from scratch. In this case, we're going to set something up that reviews your calendar, checks any email conversations with that person, and gives you an overview of the relationship so you can be prepared for the next call. To do this, first go to Claude desktop, hit plus, go to connectors, go to Gmail and Google Calendar, and then connect them. For your own understanding, connectors are Anthropic's branding for MCP integrations inside the Claude apps. It makes it super simple for you to make these connections. There's really no need to get boggled down in how it actually works. Then go to Claude and type this prompt in to create a skill called email brief. At this point, when you hit enter, you've created a custom Claude skill that does the same thing every single time. And suddenly, when you do this, you'll see how easy it is to set up operational automations and the realm of possibilities expands instantaneously. And the reason is you no longer have to ask anyone to do this, and you realize how simple it is. The second micro project is launch a personal niche command setter. This is to get the basics of building a website. In 2026, there's absolutely no reason that you can't build your own website. And this project is important because you will see how effective AI is at building websites, and you'll understand that you can now build your own tools from scratch. And if you are technical, pay attention because there are some things here that I bet you haven't thought through. Type this prompt into Claude and then hit enter, and this will go and create a website and launch it for you. But there is something really important here that I want to call out. We're able to call the email brief skill and run that from our machine. We're essentially creating a command setter that can let us interact with Claude skills we've created without spending a ton of money on Claude API credits. This opens the door where you can create a command center where you can trigger these automations to run automatically for you. We'll get into this later in this video, but this is super powerful. Now, all of a sudden, you don't need anyone to help you make a simple website, and you can start thinking about making your own personal command center to help you with your day-to-day tasks. [music] Again, I will cover this later when we go through the niche and the archetype that you fall under. The third micro project is create branding guidelines. This is for basic branding and marketing. Now, no matter what you do, whether you're an employee or a business owner, branding is critical. [music] I personally would hate spending time on something and then have someone say, "That's not on brand." or "This doesn't follow our required guidelines." So, to help mitigate this so you can start building and getting things actually approved quicker, let's start thinking about it proactively. We're going to update the niche command center that we created in micro project number two by writing this prompt. This will then go ahead and create a branding page that you can reference in all future projects to make sure that whatever you're doing is on brand. What this will do will create a branding guidelines and update the claw.md file. And by establishing clear guidelines and updating the claw.md, you're going to constantly remind your Claude code system whatever your branding guidelines are so anything it produce follows these guidelines. Suddenly, you don't have to ask for branding and design help. Once you do these three micro projects, you are going to have a different swagger about what you can and can't do. And recently, I actually sent these to one of my buddies and he sends me this text. He said, "I guess this is my first true experience with it and it's really blowing me away. Seeing and doing is believing and until you do it yourself, you're just not going to believe that you're capable." Now, at this point, you've proven to yourself that you can do more than you thought. But, as you do more, you need to create an environment that continuously improves over time. That brings us to step number three, which is about building a self-improving system. In order for us to truly build faster, we need to set up a system that learns and doesn't make the same mistake twice. I like to visualize your system as a bucket. 99% of people using AI have a leak in the bottom of the bucket. They use it and context fills up, but over time the bucket slowly drains and they end up having to repeat themselves or AI continues to make the same mistakes. We need to fix that leak so the system learns automatically and self-improves over time. Now, I have a video on my channel where I dive deep on this, but here are the three most important features that you need. The first is you set up the project structure. You need to give every output you produce a home. We need to create a project that you can easily store data so that it can capture specific contextual information based on whatever you're working on. To do this, open Claude Code and make sure you're in the folder where you created the mini projects from step two, and then paste this prompt in. As part of that prompt, it will explain what each folder does and why it's needed, but in short, we have a raw folder that takes in any raw information that you want. This could be a call transcript or a YouTube transcript. This is the original source of truth. And then it creates a wiki, which is basically a table of contents, which tells AI what is in each raw file. A mental framework here is {slash} raw is holding the entire book, where {slash} wiki is the table of contents, so AI can quickly navigate. The second feature is bulk data ingestion. We want to fill this project with data that we've already done, so it can learn quicker. And so first, we're going to create a Claude skill that systematically adds new resources, so every new file gets handed properly. Here's a prompt for a skill called add new resource. This skill will bring any raw file into {slash} raw, then automatically process it into the wiki folder. And one question you may have is what resources do I add? Really anything specific to what you're working on. So this could be blog posts from people you trust, call transcripts from your manager, whatever. But you don't want to just stop at other people's materials. This is your system, so you have to make it you. To do this, what I do is I record myself constantly. Voice memos, end-of-day rambles about what I worked on, and this add new resource skill will take those rambles from you, your lived experience, and then ingest it into the system, so it can constantly improve. So that pulls in external data, your own data, but there's one other piece of data that you have to actually look at. Claude Code desktop stores all of your conversation history locally in a file. And what this means is that Claude Code can look your past conversations, identify ways to improve the system, and suggest custom skills while servicing any information that's worth ingesting. So what you can say is {slash} add new resource, bring in my Claude conversation history, and process any learnings from it. Suggesting improvements, custom skills to create, or lessons learned that we can add to our system. This now creates a clear way for you to bring in data and bulk uploads it with the most valuable information, your actual conversation history. Feature number three is self-improvement loops. So, we set up the structure, we've ingested data, and now we need to make it so it continuously analyzes data and improves the system. To do this, we'll follow skill-driven loop creation. Essentially, anything that we make that we want to run automatically or in a loop has to be derived from an existing skill. The reason for this is before you automate anything, you need to make sure it actually works consistently, and skills are the best framework to do this. So, for a self-improving loop, we need to create a skill called improve system. To do this, write this prompt into Claude, which will create the skill for you. This skill itself will look at your past history, look at your conversation, and suggest improvements. I have a version of this in my plugin build partner.ai if you want to head start on setting this all up. Once you have that, you can go to Claude desktop, select routine, and then it creates a routine that calls the skill every Friday. And the beauty here is that if you update the skill, the routine itself that automatically triggers will update automatically. In the case of this routine, if you want to create a system that's fully automatic, you could do {slash} improve system auto approve every suggestion. Personally, what I like to do is manually review improvements to make sure that the system is self-correcting in the right direction. So, what I'll do is I'll say {slash} improve system create a file formatted for Obsidian that I can approve or deny changes. And Obsidian's just a way to view these files locally that's entirely free. So, this far we have covered a lot. We've established our AI tool stack. We've outlined three micro projects that can help you expand the top of your T so you can start doing more, and then we've laid the groundwork for a self-improving system. But, the reality is just having the top of the T in the AI world isn't enough. You have to have depth. And before we dive into the three-step process to know what to double down on, if this is your first video, welcome to the channel. But, if this is your second or more, here is our anti-slop agreement. The visuals, the testing, the me writing on this piece of paper, this is all for humans, not for AI scrapers. So, all that I ask from you is that you subscribe as part of this agreement to help this content reach more people so that I can keep making videos like this. Also, I do want to congratulate Tom Brooks 24 for winning our Claude Max giveaway. He's building an automation system for his construction business. Absolute legend. To enter the next giveaway, comment below with what you're building or a recent feature that you made. And yes, each video that you comment on gives you an extra entry to this giveaway. Part two is build your depth in a specific vertical. One of the biggest issues with how people think about AI is they always want to do more. More social media posts, more code written, more websites, more, more, more. But the reality is that's only one side of the equation and it's something that doesn't really interest me that much. What interests me is how AI can be used to improve the quality of the final product. And I'll go even a step further. I'm anti-automation. I'm pro-augmentation. Automation leads to shitty output. Augmentation leads to next-level output. And in a world where you can do infinite things with AI, there is really zero advantage of just cranking out more slop. The advantage is increasing quality while you increase quantity. A personal example of this, I spent five years posting 190 videos on YouTube, which got me to like 9,000 subscribers, right? I had the quantity. But then in the past six months, I shifted focus and I pivoted to quality. Recently, in a span of five days, I got more subscribers than I did in five years. In the world of AI, there is a surplus of quantity, but there will always be a shortage of quality. So, how do we double down on what we do best to 10x our output in a specific vertical. Step four is identify your vertical. The first thing you need to know in going deep is where to go deep. And there are two ways to do this, right? The first is by the archetype, what you identify as, and the second is by auditing, like what do you actually do? In terms of your archetype, there are three types of people that are winning in the AI era, and most successful people will land in one or a combination of two. The first is the builder. This is someone who ships products, automation tools. The second is the storyteller. This is content, narrative, brand distribution. And the third is the systems thinker. This is processes, workflows, ops, infrastructure. This is anything that turns one good run into a repeatable system. For me, I'm primarily focused on storytelling. For my business, this YouTube channel, and the content comes first for me. And yes, I do spend a ton of time building out systems and creating products for businesses I work with. But right now, I'm primarily focused on storytelling vertical. So, the natural question that you may have is which vertical are you? Well, to start, what are you currently doing the most? If you're a software engineer, you're likely a builder. If you're a marketer, a storyteller. If you're a project manager, a systems thinker. The trap that most people fall into is they focus on things that they wish they were, but they don't actually spend their time on it. Instead, if you're a software engineer, get really good at using AI for software engineering. Same for marketers, same for operations, etc. These skills are what got you this far, and it's the lowest barrier of entry to get deep in that vertical. So, those are the types of archetypes in which to lean into, but if it's not yet obvious, let's look at the data. Go to Claude and type this prompt in. It will look at your conversation history and then identify which verticals you have naturally biased towards. [music] If you don't know where to start, start where your energy has naturally been drawn to. At this point, you know which archetype you lean towards, but why does this actually matter? Well, this builds on something I said in step one. Sometimes it's just as effective to know what you're not working on as it is to know what you are working on. So, once you've labeled yourself and identified where you want to focus, you know what you don't want to focus on, and that helps remove decision fatigue. Decision fatigue is the new cigarette. Remove decisions and you're going to start building faster. Now, at this point, you're ready for the next step. Step five your archetype-driven skill library. Based on your archetype, you are going to want to build out your skill library. And to do this, we're going to take a proof-based skill creation approach. Only build skills from work you've already done. And this makes sure that every skill you create is grounded in real work, not theoretical. And it also forces you to converge on the archetype you identified in step four. You can't build storyteller skills if you're never doing storyteller work. And so, by default, you're going to start focusing on what you're actually working on, not science projects someone told you would help change your life. And while you work on these skills, there are four different skill types to keep in mind. The first is utility skills. These are small reusable skills to do one thing very well. For example, draft email response could be a utility skill for drafting email responses. Second is verification skills. These are skills that check the quality of the final output. From Claude directly, verification had the most measurable impact on Claude's output quality internally. The third is data enrichment skills. These are skills that pull external data into our system. For example, I have a funnel digest skill that pulls traffic data from all of my websites. The fourth is orchestration skills. This is a skill that chains multiple steps together. For example, you could have a skill that says end of day review, which could run the {slash} funnel digest skill and the {slash} draft email response skills as part of an end of day checklist. So, you understand the four categories, but how can we start creating skills that are specific on what we're actually working on, in turn actually helping us build faster? First, audit your system to suggest new skills and fix existing skills. Use this prompt, which will map your skills into categories and give you an understanding of what you're already doing and suggest improvements plus new skills from your past conversation history. You have to know where you're at to know where you should go. And before you just go buck wild creating a ton of skills, every skill you make is overhead for your system. So, if you aren't using skills, just delete them. If you have overlapping skills, combine them. So, once you create these skills, it's time to refine them over time. In my eyes, generic skills are extremely worthless. And this is why I kind of roll my eyes when someone says that they're sharing hundreds of skills with you, or this whole folder with hundreds of skills. The value comes from the personalization of each skill. Austin Law, who runs growth at Anthropic, said it best about generic skills. It's good scaffolding, but you still need to spend the time to right-size the template to your stack, your edge cases, your workflow. So, what you need to do is use the skill, identify holes, and enhance it over time. Using a skill we actually created earlier in this video, whenever I run a skill and I find that the output wasn't exactly what I wanted, I'll write this in a Claude. This will take the skill that I just used, the back and forth to get a output that I wanted, and it will suggest ways to improve the skill to get a better final product the next time I use it. And a key here is that I try and reduce the time for every feedback cycle. If I use a skill and it's not perfect, update it right then and there. Don't wait cuz you're going to forget or your self-improving system isn't going to have all the context that you have at the current moment. Oof, I'm getting jazzed up about this, but this stuff is so important. Now, the third thing, after you've audited your existing skills and have refined them over time, you need to enhance skills so that they can verify the output. There are a number of ways to actually do this, but here are my favorite ways to verify outputs. You can update your Claude MD with explicit verification language. So, you can have it say, "Before returning any work, verify that it works and the task is complete. And if you can't verify the result, fix and rerun." The second is that you want to connect any external services your skill use. For example, if it deploys an app, connect wherever it's deployed so it can verify a successful connection. Here is a prompt that you can see for which MCP servers would be valuable for verifying any of the existing skills that you use in your setup. Think of this like saying, "Hey, here are my skills. What are ways that I can improve my system to empower them to verify the output they produce." And the last for non-technical stuff, I use buildpartner.ai to verify my outputs against experts. For example, if I want Gary V to review my content strategy, I call /bp expert advice to review the response. So, in this step, for the skill library, we've identified how you can determine what skills to work on, how you can actually improve those skills, and then ways that you can help the skills verify the output. Before we get to the last step. At this point, we've established the top of the T. We're able to tackle tasks in different verticals, and we've also gone deep and started creating custom skills that are proof-based with verification baked into them. Now, we need to create our own interface that helps streamline everything we do, which is step six, your niche command center. In step two of this video, we briefly created a niche command center, which was a local website with one button that runs a skill. That was a proof of concept just to showcase the power. In this step, we enhance it for the vertical you spend the most time on. Now, if you're wondering why this is so powerful, there are four key reasons. The first is that you're creating a fully customized workspace. Every section, every button, every feature you build is designed around your workflow. This is the opposite of how you normally use software that helps you in your day-to-day. So, if you're using a other tool, you're bending your workflow to make it work within that ecosystem. In this case, you're actually creating a tool that bends to fit you and your exact needs. For me, this meant creating a YouTube dashboard with every single feature that I need, and I don't have to go to external services. Instead, it's all-in-one. I've shaped it to my exact business and the exact needs that I have. The other benefit of a niche command center is it uses Claude membership instead of your API credits. Most AI tools that you create cost a ton of money to run because they hit the API on every request. And as somebody who's built tools for thousands of users, this change of using your account instead of API usage can really save you a ton of money. The third is that you can dynamically create prompts based on dashboard data. So, here's what it looks like in practice. So, on my niche command center, I have a copy prompt button. I click that, and I'll get an exact prompt with the context from the dashboard loaded. So, I can maneuver this dashboard and change the data on it to generate an optimized prompt that I can then bring into Claude code directly to run. I copy it, I paste it in Claude, I hit run, and it streamlines everything I do. The key here is I'm making it to help me work faster. I don't care about anyone else. And this alone can 10x your output. The more you dive into your vertical, the better you're going to start getting in it because this niche command center is going to unlock your productivity. The fourth is that you can trigger Claude to run in the background on a single button click. So, the dashboard can become the orchestration layer that you can then manage to trigger these agents. When I use this, I visualize being in like a Star Trek command center, and you're clicking buttons to trigger these Claude agents to spawn for you. And the fifth benefit of this is it can save money on unnecessary SaaS products. In my example, there are tools out there that I was paying for to visualize thumbnails in the context of YouTube. Instead of paying for it, I just built that feature into my niche command center, [music] and now I'm saving money. There are probably a bunch of different tools out there that you're using that you're paying for that you could probably just recreate. Now, for this video to expand on this niche command center, I'm going to give you a structure to help you build this all out. In step two, we built the shell, but now we want to build the features. Type this into Claude, which will create a list of all of your skills, plus an input field where you can type and build [music] a custom prompt. Once you have this run, and here you can see it running on my system, it'll create two buttons. One that you can click and it'll grab the prompt that you can then bring into Claude code, and the other will trigger Claude in the background, which you can then watch the output stream on your screen. This is like seeing the Claude code agents running that you just triggered. Now, these are foundational tools that I use for clients that I work with, my own internal operating system, and this establishes the foundation that you can build on top of. So, let's say you're building this out and you wanted to have something that pulls your Google calendar. You could just say, "Add a tab to the page that is synced with my Google calendar and show me my upcoming meetings." You'd hit enter, and then it'll build for you or ask for any information that you need to provide. And because it's all running locally, you don't have to worry about any of the technical challenges like deploying an app. And depending on the vertical that you're diving deep on, on screen I show each of the archetypes and different niche command centers that may inspire [music] you. So, if you're a storyteller, a builder, a system thinker, so use these as a source of inspiration to drive whatever you're working on. And as you're building out this niche command center, a question that you may have is, "I can just do this quicker manually myself than adding it to this center." Sure, maybe, but this is where you want to lose the battle but win the war. If a task normally takes you 30 seconds and it takes maybe 60 seconds to add it to the dashboard so that it's there forever. If you get 1% better every day, it'll be crazy how much better this command center will be for you. I can't stress how impactful my command center has been for for business as we start to take off. At this point, you know exactly what it means to be a T-shaped builder, and you know how to build 10 times quicker. The theme is get good at many things first by going zero to one. Then get great at one archetype, and that archetype should be the one you already are, not the one that you wish you were. And if you like this video, you'll love this video where I dive deep on cloud skills. Everything I cover there builds on what we just covered in this video, and if you pair the two, you will build 10 times faster. I'll see you in the next one. Peace.