How to Make OpenClaw 10x More Powerful

Open Claw is the most powerful AI tool ever created. But you might not feel

ever created. But you might not feel that way. For most people, it just feels

that way. For most people, it just feels like chat GPT inside Telegram. That's

because you're barely scratching the surface. In this video, I'm about to

surface. In this video, I'm about to show you the five most powerful techniques and workflows to turn Open Claw into your personal autonomous AI employee. All right, so the first one is

employee. All right, so the first one is sub agents. And most people have no idea

sub agents. And most people have no idea this is even a thing. You're likely

using a single agent for all sorts of tasks. But to make OpenClaw actually

tasks. But to make OpenClaw actually powerful, you need to create multiple sub aents, each one built for a specific task. For example, this is the exact

task. For example, this is the exact workflow I use. I have my main agent called Mono. She's my thinking partner,

called Mono. She's my thinking partner, my second brain. She helps me brainstorm ideas, make better decisions, but she rarely actually does anything herself.

Instead, I have multiple sub aents that Mono uses as our workers to do the actual work. For example, for coding

actual work. For example, for coding tasks, I have a sub agent called Samantha, and I'll show you how to create it in a second. She has her own model, context window, and memory, which helps not to overload my main agent. So,

when I need to build something, I just ask Mono about it, and she passes it straight to Samantha, who writes the actual code. Now, the cool part about it

actual code. Now, the cool part about it is it's actually very easy to create. In

the gateway, if we go to the agents tab, you can see that currently I only have one main agent. So, open up your Telegram or whatever app you're using to chat with OpenClaw and paste in this prompt. I'll also leave it in the

prompt. I'll also leave it in the description of this video. Create a new persistent agent named Samantha or however you want to call it and make her my dedicated coding assistant. Set GPT

5.3 codeex as her primary model and use Samantha for all coding related tasks.

Leave my main agent unchanged and tell me when Samantha is ready. And that's

it. Now go back to the gateway dashboard and refresh the page. And as you can see, we now have a new agent that Mono will use for all coding tasks. Now,

let's talk about skills. These are

basically new abilities you give to your agent, which literally makes it more powerful. When you just install OpenClaw

powerful. When you just install OpenClaw for the first time, you will be prompted to install some official skills. The one

that I highly recommend is Clawhub.

Clawhub is basically the app store for your agent, a marketplace where you can find, install, and update thousands of community-built skills. And this skill

community-built skills. And this skill gives your agent the ability to use that website and install skills for itself.

For example, one of my favorite skills is last 30 days. It teaches your agent to search through Reddit, X, YouTube, and the web from the last 30 days to get

you the latest news and viral trends on any topic you want. The beauty of it is you can just copy the link to the skill, paste it to your agent, and ask it to install it for you. Basically, the more

skills you install, the more powerful your agent becomes. For example, this one gives it the ability to search the web and this one to interact with GitHub. And if you don't find the skill

GitHub. And if you don't find the skill you need, you can just ask your agent to search for it or even build one itself.

But be careful when installing skills from Claw Hub. It's a community-driven marketplace, meaning anyone can publish a skill, and not everyone out there has good intentions. So, some skills might

good intentions. So, some skills might contain malicious code.

All right, so what makes OpenClaw different from chat bots is it can actually be proactive and autonomous.

You don't always have to prompt it in order for it to do something, but only if you set it up right. For example,

every morning at 8:00 a.m., my agent sends me a morning brief that contains the latest AI news, a few content ideas I can create, tasks I need to complete today based on my to-do list, and a few

tasks the agent can do for me. All of

that autonomously without me asking. To

set this up, copy this prompt from the description and modify it based on your needs. It basically says, "I want to set

needs. It basically says, "I want to set up a morning brief. Every morning at 8:00 a.m., send me a report that

8:00 a.m., send me a report that includes and then your list of everything you want your morning brief to contain." And if that doesn't impress

to contain." And if that doesn't impress you and you want to make it even more proactive, try out this prompt. Every

day, I want you to work on your own to iterate and improve. Surprise me daily at 9:00 a.m. with a new task or project you completed to improve my pre-existing

workflows. What it does is it makes your

workflows. What it does is it makes your agent improve every day and build new things for you based on all the information it knows about you. Now, the

most common problem people have is memory. It forgets a lot of things over

memory. It forgets a lot of things over time. And here's why that happens. As

time. And here's why that happens. As

you use OpenClaw, your context window slowly fills up. And to prevent it from being full and save you some money on tokens, OpenClaw automatically runs compaction, which summarizes older

conversations into a compact summary entry. The problem is after each

entry. The problem is after each compaction, your agent forgets about lots of things. To fix this, use this single prompt. What it does is right

single prompt. What it does is right before that compression happens, your agent saves the most important things from the context to a memory file. so

nothing gets lost. Now, there's a lot more going on with memory and how to make it even better. If you want me to create a separate video about it, let me know in the comments. But for now, I'd highly recommend reading this Reddit

post. It's a little bit technical, but

post. It's a little bit technical, but it clearly explains the actual problem with open claw memory and how to make it almost permanent.

Finally, the best way to improve your agent is to make it improve itself over time. We can create an infinite

time. We can create an infinite self-improving loop that makes your agent continuously learn and get better.

On Claw Hub, there's a skill called self-improving agent. What it does is it

self-improving agent. What it does is it creates a self-improving folder with a few simple files and folders that it uses to store hot memory, correction logs, and contextspecific patterns. So,

every time you correct it, it remembers that and avoids the same mistake in the future. Basically, the more you use it,

future. Basically, the more you use it, the more it learns what you want it to be, how to act, and how not to. But if

you don't want to install a community skill, you can get almost the same system with this single prompt. copy it

from the description and your agent will build the whole setup itself. Or you can just copy the link to this skill and ask your agent to build it for you, which avoids any chance of downloading malicious code. And if you want to learn

malicious code. And if you want to learn how to make OpenClaw 90% cheaper, check out this video right here. And I'll see you in the next one.