Most of my readers know how keen I am on discussing NLP Modeling — both on this blog and offline.
Stever Robbins is a sharp cookie in NLP circles. In this post, he riffs on NLP Modeling and weaves a few juicy historical details into his narrative. Pay particular attention to his mention of the 4-tuple, a variable created by Bandler and Grinder to track sensory modalities brought in and out of awareness. Very, very few NLP beginners know of the 4-tuple and only the most serious students will sit through the hairy presentation of the concept.
On distinctions and operations:
In Math, distinctions called “numbers” include 4, 5, and 9. Our operators include something called “addition.” The rules of math say when you combine 4 and 5 using addition, you get 9.
In NLP, we have distinctions called “4-tuples” with a specific set of internal/external sight, sound, small, taste, etc. We have an operators, “set anchor” and “fire archor.” Given two different 4-tuples, we can anchor both. When we combine them using the operator “fire off anchors,” we get a new 4-tuple with elements of the original two.
Notice how Bandler and Grinder worked on creating a specific code with which to track what’s happening in awareness and communication. Little attention is given to this code in trainings nowadays but you’ll find it worth your while to sink your teeth into it and figure it all out. You’ll find all of this in the seminal books of NLP (Structure of Magic I and II, Patterns I and II).
On modelers:
The paradox is that those who love building models rarely enjoy applying them once the model seems to work. And those who like application are rarely good at building them.
That’s why so few NLP trainers are well-integrated and multi-faceted. One of these few is Tony Robbins.
Although I disagree with Stever here. If you adhere strictly to the NLP Modeling distinction (also discussed here), the modeler MUST by presupposition apply the model naturally in his or her behavior.
Read through Stever’s post. Great little nuggets on modeling that will hook nicely into what we’ve been discussing here.
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