In what areas can you see the difference between what’s good and what’s great?
The Large Language Models (LLMs) of generative AI treat all inputs equally – everything gets thrown into the model to create an aggregate composite. They are a great way to find the average or generic way to approach something, which is amazing since it allows anybody that isn’t a practitioner to access average output in that area.
But that means that you need to build areas of expertise where you are beyond the average or generic. And to do that requires taste, the ability to notice what makes things exceptional, because LLMs will treat exceptions as outliers.
So what do you notice that others don’t? What do you see instantly that you have to explain to others?
Another way to differentiate yourself from LLMs is personalization. While you can train a personal model, LLMs typically deliver output for a generic person. There’s an opportunity to deeply understand a specific person’s needs, and create something customized to serve them in the moment. One of my strengths as a coach is to deeply understand my clients; where an LLM might generate a laundry list of actions from the leadership literature, I will offer the exact insight they need to get them unstuck and moving forward.
Developing this ability to see what others don’t, and to connect with others to customize solutions for them, will be what differentiates us from the LLMs for now. Let’s practice what makes us unique as humans rather than duplicate what machines can already do better than us.