I recently read the book The Courage to Be Disliked by Ichiro Kishimi and Fumitake Koga. If you are unfamiliar, it is an overview of Adlerian Psychology, also known as Individual Psychology.

I’ll admit that I had never heard of Alfred Adler or the psychology he was a proponent of, but I am glad that I gave this book a read. Unlike many psychology or self-help books, this one is written in the form of a narrative dialogue between a student and a mentor, which makes it very easy to read.

How do you react when difficult circumstances arise?

Life isn’t always fair. It’s not easy. Difficult circumstances will arise for all of us from time to time. The question is how will you choose to respond during tough times?

It is tempting to give into our emotional response and allow that to dictate how we react. This, however, is not good. Emotions are fleeting and driven by hormones flooding your body. They are indifferent to reality outside your current circumstance. They have no perspective.

The Boring Path to Sales Success

Ask any top sales performer the secret to their success, and chances are, you won’t get a flashy answer. You won’t hear about a secret script or a viral campaign or some once-in-a-lifetime pitch that changed everything. What you’ll hear — if they’re being honest — is something much simpler, and far less exciting:

💡Sales Success Comes Down To Consistency, Discipline, And A Commitment To The Basics.

Python Decorators

Decorators are a way we can use higher order functions to modify other functions. Typically they are used to wrap a function with another function.

def hello(name="Ian"):
    def greeting(func):
        def wrapper(*args, **kwargs):
            print("A man is sitting at the bar, you go up and greet him.")

            if name == "Ian":
                print("My name is Ian, what's yours?")
            else:
                print(f"My name is {name}, what's yours?")

            print("The man glances your way momentarily, then moves to the other end of the bar.")
            result = func(*args, **kwargs)
            return result
        return wrapper
    return greeting

@hello("Alice")
def bar_talk():
    print("You start a conversation about the weather with the bartender instead.")

@hello()
def another_chat():
    print("You shrug your shoulders and ask the bartender about the local sports team.")


print("=== First Interaction ===")
bar_talk()

print("\n=== Second Interaction ===")
another_chat()

In the example above, you would get the following print out:

What is RAG?

If you’ve been trying to keep up with AI, there’s a good chance you’ve come across the term RAG. When I first learned heard the term, I wasn’t exactly sure what it meant form the context of the discussion.

Retrieval-Augmented Generation (RAG) is a technique that enhances the accuracy of large language models (LLMs) by giving them a wider context window and including external (from the LLM’s database) knowledge sources.