Muscle Building Myths Debunked!

Описание: Timestamps:

00:00 - Intro
01:26 - Training Variables
01:45 - What Makes Advice Bad
02:04 - Oversimplification
04:49 - Talking in Absolutes
08:05 - Personal Bias
11:47 - What Good Advice Looks Like
13:21 - Not Avoiding Complexity
15:53 - Practical Example
18:51 - Outro

Video Summary:

Training Variables
Before we even talk about advice, we need to know what matters. I outline the key training variables—intensity, volume, frequency, exercise selection, recovery, and more—that form the foundation of smart hypertrophy training. These are the levers we adjust to make progress.

What Makes Advice Bad
Bad advice usually fails in one of three ways: it oversimplifies complex systems, it presents extreme or absolute views, or it projects personal experiences as universal truths. Each of these can leave you stuck, confused, or chasing things that don’t work for you.

Oversimplification
Advice like “just progressive overload” or “just eat more” sounds simple and catchy—but without context or explanation, it teaches you nothing. These one-liners give you an outcome, not a process, leaving you guessing when things stop working.

Talking in Absolutes
Statements like “you must do squats” or “one set is all you need” can sound confident, but they shut down flexibility and critical thinking. Good training evolves. You need to understand how variables interact—not lock yourself into someone else’s rigid system.

Personal Bias
“My delts grow from just rows” or “chin-ups are all you need for back” might be true for that person—but genetics, structure, and recovery vary wildly. Copy-pasting someone else’s experience rarely works unless you understand the ‘why’ behind it.

What Good Advice Looks Like
Good advice is built on logic, supported by evidence, and teaches you how to think—not what to blindly follow. It helps you understand context and adapt based on your goals, recovery, and feedback.

Not Avoiding Complexity
Growth isn’t always simple. The goal isn’t to reduce everything to a soundbite—it’s to build clarity over time, even if that means understanding more layers. Simplicity can be deceptive when the system you’re working with is complex.