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Balancing AI
A reflection on learning, friction, and choosing which parts of the work we want to keep for ourselves.
#thinking #learning #ai -
Why I Taught Software Testing with Cars
What is a teacher actually doing when they reach for an analogy?
#communication #learning #thinking -
Learning Terrain Model pt. 5 – Slow Feedback, Complex Domain
The rules aren't stable and real iterations are almost impossibly rare. How do you build judgment when some of them only come once?
#frameworks #learning -
Learning Terrain Model pt. 4 – Fast Feedback, Complex Domain
Iterations are cheap, but the rules aren't stable. How do you extract real signal when the domain keeps moving under you?
#frameworks #learning -
Learning Terrain Model pt. 3 – Slow Feedback, Complicated Domain
The patterns are real and the rules exist. How do you build mastery when chances to practice them are rare and expensive?
#frameworks #learning -
Learning Terrain Model pt. 2 – Fast Feedback, Complicated Domain
The rules are real and every iteration is cheap. How do you make sure the repetitions are actually building something?
#frameworks #learning -
The Learning Terrain Model
Not all learning is the same kind of problem. The approach that works in one environment can actively slow you down in another.
#frameworks #learning -
What If Easy Answers Are the Problem?
Easy answers tend to kill curiosity. Unless you use new information to ask better questions, the journey might end the moment you find the answer.
#curiosity #learning #thinking -
Tacit Knowledge in the World of AI
As AI handles more of the analytical work, what happens to the knowledge that resists being articulated?
#ai #learning #thinking