implementation

It’s clear to many that we’re already stepping into the age of wisdom work. Every CEO Dan Shipper points to the rise of the allocation economy, where the advent of AI means everyone will become a manager: “You won’t be judged on how much you know, but instead on how well you can allocate and manage the resources to get work done.” Being a great man

Connection: Vulnerability, impartiality, empathy, and wonder

The majority of us have been taught that connection is earned through achievement. We believe that once we become successful, smart, or generous enough, we’ll be worthy of connection.

But people don’t want you to be perfect. They want to be connected to you.

Discernment goes beyond what is true in the stacks of data. It is the ability to see things clearly and zero in on what matters.

What most people don’t realize is that your relationship with yourself sets the tone for everything else. If you don’t trust yourself, you won’t trust your team. If you shut down your own desires, you’ll feel resentful of

evidence suggests that piling on more data often hurts decision quality:

1. Too much choice stalls action. In the famous "jam study," shoppers presented with 24 flavors bought jam 3 percent of the time, while those offered just six flavors purchased 30 percent of the time—a 10-fold jump.


2. Information overload erodes well-being. Two-thirds of

#4—Prompting is a finicky art, but a worthy investment While it would be great if the three techniques I’ve shared so far immediately transform your prompts, there's a decent chance they will fall flat for your use case. My guess is that they will even become irrelevant as models become smarter and more cost-effective over time. My point in sharing

#3—Be methodical about the examples you provide The staple of any few-shot prompt is its examples. I had strict screening criteria for the examples that were added to my contrarian, punchy, tweet Spiral. The only tweets that were allowed were those that: did not exceed the single-tweet word count (i.e., were not a thread or long post) had over 100,

#2—Show-based telling > tell-based telling Showing your LLM examples of what it is you’re trying to create is the principle of showing vs. telling—a key tenet of storytelling the world over (and something Geroge Lucas certainly understood). But I’ve found that showing is also an excellent way to approach any telling that you need to do. In accor

#1—Less is often more when it comes to instructions For whatever reason, the presence of certain words can skew LLMs into unexpected behaviors. Additional instructions will often go ignored until you remove the offending words or instructions. Recent research shows that a less-is-more approach seems to work for LLMs on a pretty profound level. For

Overcoming few-shot friction There is one problem I’ve noticed with example-based prompting: Most creators and businesses aren’t using it. I think this is because you have to overcome three major inconveniences before you start to take advantage of few-shot prompting on a consistent basis: Upfront effort: A few-shot prompt is only as good as the ex