Leveling Up with Eric Siu

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Everyone's talking about loops as the next big thing in AI. The founder of Claude Code says he doesn't prompt anymore—he builds loops. The founder of OpenClaude agrees. But what does that actually mean, and more importantly, how does it make you more money?

In this video, I break down what loops really are and how they apply to your business:

⬛ Why prompting coding agents is becoming the old way of working

⬛ The 5 parts of every business loop: trigger, signal, action, eval gate, stop condition

⬛ How to apply loops to sales, content, recruiting, and operations

⬛ Reviving stale and lost deals automatically

⬛ Why broken loops in Slack and Telegram are where work goes to die

⬛ How compounding loops put you ahead of 99% of businesses

This isn't theory. If you build tighter loops around revenue, content, recruiting, and ops, you'll be ahead of nearly every business out there—because almost nobody is thinking about this yet.

Chapter

00:00 Why Loops Are The Future

00:41 The Receipts: What The Founders Say

02:00 What A Loop Actually Is

04:00 Five Tips For Running Agents Autonomously

05:00 The Loop Is The Expensive Part

06:00 Business Examples: Stale Deals & Speed To Lead

07:30 The Five Parts Of Every Business Loop

09:00 Broken Loops In Slack & Telegram

10:30 Applying Loops To Recruiting & Ops

11:30 How To Run A Loop Audit

13:30 Why Loops Compound

How to Connect

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Fable 5 and Mythos 5 are here — and this is huge for revenue.

In this video, I don't just break down the announcement. I show you exactly how to turn these new Claude models into money-making machines for your business. Whether you're a founder, operator, or running a services business, these use cases will put you ahead of the competition starting today.

These aren't theories. CEOs and engineers are already using these models today to compress months of work into days and recover six figures on single deals. If you spend just one day exploring this, you could be miles ahead of everyone else.

Chapter

00:00 Fable 5 & Mythos 5 Are Out

00:13 The Mythos Class Model Explained

00:57 Autonomous Revenue Ops Engine

02:30 Visual Intelligence Competitor Analysis

03:09 Enterprise Security As A New Revenue Vertical

04:17 Build A Unified Intelligence Bot

05:01 Autonomous Research To Strategy Pipeline

06:08 Automated Implementation Accelerator

07:08 Why You Should Explore This Now

How to Connect

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Most companies are approaching AI the wrong way. They buy subscriptions, run a few experiments, and wonder why nothing changes. In this video, I break down the exact systems we're using to help teams become AI-native, from skill repositories and internal AI training programs to operational standards that increase speed, alignment, and execution.

I also share why the future belongs to "pods of one" and how organizations can create a culture where employees continuously level up instead of waiting for permission or training.

Chapters

(00:00) Why Most Companies Still Suck at AI

(00:13) Building an Internal Skills Repository

(01:44) Using Leaderboards and AI Gamification

(02:17) The Rise of the Pod of One

(03:39) How AI Apprenticeships Create Leverage

(04:43) Command by Negation Explained

(05:44) Why High Agency Teams Win

(06:25) Creating an AI-Native Culture

(06:43) Final Thoughts

Everyone is chasing AI software, but the biggest opportunity may actually be services. In this video, Eric explains why top investors are betting on services-as-software, how AI is reshaping agency and consulting business models, and why the future belongs to companies that sell outcomes instead of labor. He breaks down managed growth loops, AI-powered operating systems, and the new organizational structures that will separate winners from everyone else.

If you're building an agency, consulting firm, service business, or AI startup, this video will change how you think about growth, valuation, and the next decade of opportunity.

Chapters

(00:00) Why Services Beat SaaS

(01:13) The $1 Software vs $6 Services Opportunity

(02:52) Why Managed Growth Loops Matter

(04:49) Agents, Loops, and Human Judgment

(06:43) How Single Brain Powers AI Service Businesses

(07:22) The Services-as-Software Manifesto

(08:41) The New AI-Native Org Chart

(10:13) Building Outcome-Based Offers

(11:13) Final Thoughts

Most businesses are still using AI the wrong way. They are stuck using ChatGPT like a search engine while the companies moving fastest are building end to end workflows, autonomous agents, and closed loop systems that compound over time.

In this video, I break down the four levels of AI adoption in business, why most teams fail with implementation, and how to actually build systems that increase revenue instead of creating more busy work. I also walk through real examples of how we use Hermes, OpenClaw, Slack, and specialized agents inside our company to handle strategy, analytics, ad creatives, workflows, and decision making.

If you want to understand how AI will actually change the way businesses operate over the next 12 months, this is the framework you need to see.

Chapters:

(00:00) Why Most Businesses Use AI Wrong

(00:22) The 4 Levels of AI Adoption

(01:03) Open Loops vs End to End Workflows

(02:31) The Power of Closed Loop Systems

(03:52) Why AI Adoption Is Failing in Companies

(05:30) Why Every Business Needs One Brain

(06:50) The Future Org Chart of AI Teams

(07:52) Real Examples of AI Agents at Work

(09:14) Build in 22 Minutes, Not 22 Weeks

(09:53) How I Use Hermes Inside Slack

(11:43) Creating Compounding Growth Loops

(12:48) Why Nobody Talks About This Yet