The BEST & WORST Advice to Build 10x Faster with Claude

0:00 In this video, I'm going to break down the best and worst advice for using AI to build 10 times faster. Because the truth is, there have never been more people who are sharing horrible AI

0:08 advice that is completely backwards, and it is destroying how people use AI in their day-to-day. Now, if you don't know me, my name is Austin, and I'm not just a content creator. I was a lead engineer

0:17 at JP Morgan. I was a COO of a tech startup worth over $25 million, and I've helped hundreds of founders and operators dominate with AI in their specific industry. So, for each AI

0:26 strategy, I'll break it down in a tier list, then break down exactly what you should be doing differently instead, and the nuances that are only clear after you've spent hundreds of hours using

0:34 these tools. So, strategy number one, which is Dtier, is reduce your token spend by switching to free open-source models. This advice is well-intentioned, and I know from the comments that budget

0:44 is one of the biggest concerns for a lot of you, but let me explain why this is a problem. There are three ways you can actually pay for AI. With your money, with your time, and with the quality of

0:52 your work. Open source models may save you money, but you'll pay for it somewhere else, either in the time you burn or in a worse output. And this is exactly why I tell everyone, only use

1:01 free open source models when you have to. And since you're watching this video, you're likely one of two people. You're either someone using AI to build a business, or you're someone using AI

1:10 to help you at your full-time job. And neither of those is something to treat lightly. And I'm not saying to go crazy and burn through tokens. What I am saying is rewire how you think about AI

1:20 spend in the first place. If you need a car for work, you don't call your $500 car payment a waste of money. You need it, so you spend it. And your AI spend deserves that same logic. If hitting

1:29 token limits or chasing cheaper models is hurting your output, the fix isn't cutting a tool. It's rethinking the spend. And the reality of the situation is right now your tokens are subsidized

1:39 by VC money. The $100 you're spending today could cost $2,000 once these companies stop chasing market share and start chasing profit. So, what should you do instead? Well, no matter what,

1:49 make sure your system is token optimized so you get the most out of your budget. And if you're wondering how to do that, link below, I have a free walkthrough that uses my Claude plugin to help you

1:57 do exactly this. So, that's the first strategy. Getting to strategy number two, which is a tier. Turn repeatable workflows into skills. There's a foundational belief that I've talked

2:05 about a lot on this channel. When you're using AI, you want to own the intelligence, not rent it. And skills are one of the best ways to unlock that. If that sounds a little bit complicated,

2:13 let me explain. When you go back and forth with Claude, Chachi Pat, or whatever tool, you're teaching that system how you work. But there's a problem with this. Even if it nailed

2:21 exactly how you work, that teaching doesn't go anywhere. It lives in that one conversation on that specific platform. And that dynamic of being platform specific, that isn't owning

2:30 intelligent. That's a rental. And it puts you at the mercy at whatever the AI service provider decides to charge you next. This is where skills come in. It packages up your industry knowledge into

2:39 a file that you own. So, if you build on Claude, you could bring it into Codeex and it'll work the same way. Now, skills are super powerful and I won't dive into it too much in this video, but there are

2:47 some nuance when using this. You don't want to go around and collect every skill you find on the internet like you're collecting Pokémon. Instead, use taskdriven skill creation, which has

2:57 four steps. First, do the task. Then, tell AI to create a skill from that conversation. Then, run the skill and see if it works. And then, at the end, if it doesn't work correctly, correct

3:05 the output. And then, say based on this conversation, enhance the skill. And as you get into creating skills, you're likely going to add more and more direction to them. And that brings us to

3:14 the next piece of advice. Strategy number three, which is Ctier, is give AI as much context as possible. So to understand this, you need to understand what context is. Actually, this is the

3:24 extra information about you, your business, whatever that you give AI to help you produce a better output. This information is hyperritical, but people don't always understand the nuance. More

3:34 high quality context is good, but only up to a certain point. The example I like to use is think of the context you give AI like a fridge. AI opens the fridge, sees one high quality item and

3:44 knows exactly what to grab. You add a bit more, it's fine. But keep stuffing the fridge and eventually it's impossible to find anything in there. And then if something goes bad within

3:53 the fridge, the whole fridge can smell and it can impact everything else. So there's a rule of thumb that I go by. Relevant context helps. Outdated or conflicting context hurts. So, to audit

4:03 your own setup, you can use this prompt to review every contextual file you've got and flag anything that's gone stale. Now, if you're wondering what the actual best way to provide context is, that's

4:12 where strategy 4 comes in, which is S tier. Build an LLM knowledge base your AI can actually use. This is one of my favorite pieces of advice on this entire list because it genuinely changed the

4:22 trajectory of my career. An LLM knowledge base is a way to structure contextual files on your computer to better teach AI about your job or your business. Going back to the fridge

4:31 metaphor, what we're building here is an industrial refrigerator room. This allows you to add more context and it's still easy for AI to find it. The easiest way to understand this is to

4:40 just show you mine. So, I call it my internal OS. And inside it, I have two folders, my raw and wiki. / raw is where every unprocessed piece of information sits. So, for example, this could be the

4:51 exact article I liked about writing marketing copy. And then in the /wiki folder, it takes the material and then pulls out the key learnings. It's essentially creating a table of contents

5:00 for everything that's sitting in the / raw folder. Then when I ask the knowledgebased a question, it'll check the wiki first and when it needs more information, it knows exactly which raw

5:08 file to look for. You're essentially building a map for AI so it can find and access highquality contextual information for whatever you're working on. Now, I have a deep dive video about

5:17 this if you want to go further or if you want me to help you set this up for your business. There's a link below to work with me. Either way, once AI understands more about your work, you'll start

5:24 seeing more things you can build, which makes the next mistake especially tempting, which is F tier. But before we get to that, everything we're talking about is about building faster. But what

5:32 if you're ready to take the next step and start getting paying customers, which brings us to today's video sponsor, which I'm super excited about. If you've ever wanted to turn

5:39 something you've built into a real business, the idea usually isn't the hard part. It's really everything around it. That's taking payments, getting to know customers, and knowing what's

5:48 actually working. This is what handles, which I've been really impressed with. So, you guys know that I've been working with buildp partner.ai, my claude plugin that helps

5:55 people build faster with LOAD. And now officially powers the payments for it. And yes, previously I did have a payment processor, but why did I move? The reason is that isn't just a way

6:04 to process payments. It's everything that's built on top of the payment layer. Now, there are three features that I love. The first is that you can run your business from inside Claude

6:12 code. So, has a CLI and an MCP that you can connect directly to Claude. So you can just ask it in plain English to make a payment link, pull your stats, or launch an ad. This is actually how I set

6:22 up all of Build Partners payment tiers without ever leaving claw code on screen. This is literally the prompt that I wrote. I want you to create all of my current products in And it

6:30 just did it. The second feature is the flexible checkout. So customers get 100 plus payment methods without any additional setup. Plus, they have a buy now pay later. So a customer can pay

6:40 over time while you get paid entirely upfront. The third is that it can help you with ads. This is something that I'm personally excited to get my hands dirty with because I'm not an ad expert. I

6:50 primarily do organic content like this. And I bet a lot of you watching aren't ads experts either, but the reality is ads are one of the best ways to get traffic to your product. And has

7:00 made it super easy to get them set up and running. And because their ad platform is tied to real payment data, you can see which ad actually made a sale, not just which one got the clicks.

7:09 So whether you're starting something new or already have a business, sign up for using the link below in the description. Now, no matter what tool you use for payments, you have to be

7:18 strategic with what you build, which brings us to the next piece of advice, which is Fier Strategy 5, Fier. If you can build it, you should build it. So AI has made it possible to build almost

7:29 anything. But should you? So sure, you could rebuild the software you're paying 10 bucks a month for, but how long will that actually take you? And will it hold up through every edge case? And are you

7:38 going to do the maintenance when it needs a patch every 6 months? This makes it obvious. The answer is no. And I've watched so many people learn the basics of vibe coding or see how powerful

7:48 something like claw code really is and then suddenly they want to build absolutely everything. So here's my question for you. Do you actually need to build what you want to build or are

7:55 you just excited that you can build it? And I've personally fallen for this, right? I once decided to rebuild our CRM myself. About 10 hours later, I just never used it. it didn't hit feature

8:04 parity and I just decided to go with Google Sheets. And I've watched business owners do this time and time again. They rebuild an entire project management tool over a single missing feature only

8:14 to realize that they were misusing the original one and they wasted all of that time. Building on this, I recently read a book called 10x is easier than 2x. And the core idea is that 10xing is actually

8:24 easier than 2xing because it kills the decision fatigue of debating whether to do something at all. So before you build anything, ask yourself, is this a 10x move or is it a 2x move? And then this

8:34 will make it extremely clear that when you want to rebuild a software that you already have or it just is missing one single feature, you just won't do it because that's a 2x move. And if you're

8:43 watching this channel, we're 10xers. We're not 2xers. Save the 2xers for other channels. Now, you will eventually decide to build something. And that brings us to the next piece of advice.

8:52 Strategy six, which is a tier. Plan before you build. This is building on the last point, but everyone in the AI world wants to go go. But the best people actually move slow to move fast.

9:03 So the first question you should always ask is, should I build this? But when the answer is yes, it becomes, how should I build this? And that's where plan mode is so powerful. In Clawude,

9:11 just type /pl and it drops you straight into plan mode. Or you could just say, interview me to create a plan on how to build whatever you're trying to build. But with this, there are a couple of

9:20 nuances worth thinking about. The first is that you have to scrutinize the plan. Everyone falls into this trap, but if you're going to just nod along, you might as well not be in plan mode. The

9:29 whole point of planning is to use your brain, so you have to think. The second is that don't over plan. My favorite quote on building fast comes from Brian Armstrong, the CEO of Coinbase, and he

9:40 says, "Action produces information." So yes, you should plan, but don't plan so much that you never actually build anything. As I've built automations and products, I've noticed that you will

9:49 never think of everything during the planning phase. Some requirements really only surface once you're actually testing and using the thing that you want to build. So plan, but don't over

9:58 plan and bias towards action. That's how you get the information. And once you start planning and building, you're going to get the building bug. And at that point, you're going to want to

10:07 follow this next piece of advice. Strategy seven, which is F tier, automate everything. Now, this one is different from the build everything trap. It's not about if you should

10:16 automate something, it's about how you should automate something. Automating your whole life sounds sexy on paper, but it skips four steps that you need to hit first before you do anything with

10:26 automation. And this actually is inspired by Elon Musk. Say what you want about the guy, but he runs a five-step process before automating anything. The first step is question every

10:35 requirement. Why do this? Why do I care in the first place? Make requirements less dumb and never assume a rule is correct just because a smart person made it. Step two is delete any part of the

10:46 process that you can. You want to be ruthless about removing things. And if you're not occasionally adding things back, you're probably not deleting enough. This is something I started

10:54 doing more and more in my business where if I'm not sure if information is needed, I just delete it. And then if somebody complains, we'll figure it out later. And I have yet to have anybody

11:03 complain when we delete processes. So that's step two. Now step three is simplify and optimize. Improve what's left after deletion. Elon Musk warns that the most common error of a smart

11:13 engineer or operator is optimizing something that shouldn't exist. Step four is accelerate cycle time. Before you automate anything, can you just speed up whatever you're doing before

11:22 actually automating it? This is the process of automating versus augmenting. Can you augment it enough so that there's no longer friction in actually completing the task? And then step five,

11:31 automation, which always comes last. Automating a broken process just produces garbage at scale. And the first four steps make sure that that doesn't happen. And now before we get to the

11:41 last three strategies, one of which includes my favorite, you guys know the drill. This is our anti-slop agreement. Everything here was built by humans and for humans. So, as part of this

11:50 agreement, subscribe to this content so that I can keep making it and it can reach more and more people. We're at 90K subs and I have a goal of getting to 100K subs in the next month. So, I

11:59 appreciate everybody who subscribes. And as a thank you, I give away a Claude Max subscription every video. And this video's winner is Chase Ferrari2291, who is building a tool to promote

12:09 personal brands. To enter this video's Clawude Max giveaway, comment the worst AI advice you've ever personally been given or the best advice you've gotten. I will accept sarcastic answers as well.

12:19 Let's have some fun in the comments. Now, once you found something that's worth automating, if you split work across agents, that can be extremely helpful, but it only works if it

12:27 actually separates, which brings us to strategy 8, which is Btier. Use multiple agents to build faster. This is genuinely strong advice, but there's one nuance you have to get right. The more

12:37 agents you're running, the more context switching you have to do. Each time you jump from one task to another, you lose time remembering where you were. And we've all experienced this, right? You

12:47 jump between tasks and you feel like you never got anything actually done. Now, I'm not saying you should wait there for 5 minutes while AI works on something, twiddling your fingers. But you should

12:56 be strategic about how you use agents. Here are three strategies that have actually worked for me in terms of paralyzing tasks. The first is say launch sub aents in your prompt. If you

13:05 have tasks that could be split into independent pieces, for example, I might say launch five sub aents to research across YouTube, Google, Reddit, Twitter, and my internal OS that paralyzes the

13:14 research instead of running it sequentially, which makes it roughly five times faster. The [music] second is partition deep work and surface work. If something's genuinely important and

13:23 takes all your focus, just do that one thing at a time. But if it's all small tasks that just need to get done, that's the perfect candidate for running four or five threads at once. My personal

13:33 move here is just spinning up four or five separate chats in clawed code, one per task, and archiving each one once I'm complete with that specific task. The third is give each agent a unique

13:43 task so that you can avoid overlap. The best way to think about this is how I run build partner.ai. I've got one agent working on admin features, another on the landing page, and another on our

13:51 one-on-one coaching feature. Each owns a distinct part of the product, so I'm not worried about them crossing swords. Now, zooming out, those are specific pieces of advice, but this is a general trap

14:01 that most people fall into. This is the trap of more. And this doesn't just stop at agents. For example, tools. More tools isn't automatically better either. Which brings us to strategy 9, which is

14:11 Dtier. Experiment with new AI tools. So, this is a weird one, but I hate this piece of advice for a couple of reasons. The first is that a new tool drops every single day. The moment you allow

14:21 yourself to start trying them, you now have to decide which ones are worth your time and which are worth skipping. And this is just stressful and it introduces unnecessary decision fatigue. The second

14:31 is if you do start trying new tools, you end up constantly switching between tools and every switch means reconfiguring and relearning something you already know how to use. Now,

14:40 personally, I have one AI workspace, which is Claude. Then I have two or three other tools that solve a very specific use case or problem I have. So, here are two foundational rules that

14:49 help most people that I talk to. The first is look for tools that solve specific problems. Don't window shop just for the sake of it. The second is that you don't need to be first to try a

14:58 tool. You're on this channel, so you're naturally in the AI ecosystem. If a tool is actually worth it, it'll keep popping up and you'll be able to use it. Don't worry. If you take a look at my channel,

15:08 I intentionally don't try and be the first person to talk about tools because I actually practice what I'm preaching here. I don't care to be first. I don't care to be second. I do care to adopt

15:17 it. And once I feel it's needed, I will make a video about it. Now, whatever tool you choose, making sure that something actually works and isn't broken is super critical to getting

15:26 highquality outputs from AI. Which brings us to strategy 10, which is S tier, give AI away to check its own work. This is something that the creator of Claude Code said will 2 to 3x the

15:35 quality of your outputs. And it is so powerful that Claude's most recent models now do this by default. So, what does this actually mean? And if the model does it by default, do you still

15:43 have to care about this? Well, first, what does it actually mean? If AI can proactively catch issues in what it created and then fix them before you ever see it, it's like they never

15:51 happened. But there is a limitation to this though. Default verification is still somewhat generic. AI doesn't know what correct looks like for your specific task. So to minimize needing to

16:00 go back and forth, you still have to strategically build the verification element yourself. And here's how I personally do this. For more technical tasks, I'll say, "Tell me how you'll

16:09 verify the output as part of the plan." Now, I've already talked about how powerful plan mode is, but by explicitly building in a verification plan, you'll be more confident that AI actually knows

16:18 what the target finished product is. Then, for non-technical tasks, I define the output structure I want ahead of time. For example, I have a script outline skill, and as part of that, it

16:28 verifies the final structure before I ever see it. Both of these, at a high level, will get AI verifying its own work. But what I personally like even more is having AI tell me how I can

16:37 verify the output. After any big change, I'll say, "How can I manually verify this?" And it hands me a personal verification plan. The reality is that most people still verify outputs by

16:46 hand, and they should, but they neglect to have AI help them with this actual step in the verification process. So, you want to think about how you can use AI to make your life easier in your

16:56 manual verification. So, let's run through the board. D through F tier. That's chasing free models, drowning in context, building things you don't need to, and chasing every new tool that

17:05 drops. This is all terrible advice. The top tiers, that's turning repeatable works into skills, planning before you build, running agents strategically, building a knowledge base AI can use,

17:15 and having AI check its own work. Just by doubling down on the winners and avoiding the bad advice will transform your productivity. Now, one A tier piece of advice was about building LLM

17:24 knowledge bases. So, if you want to learn how to do that, go watch this video. If you like this, I guarantee you'll love that. So, I'll see you over there. Peace.