Tyler Cody

I develop systems-theoretic foundations for learning, intelligence, and consciousness, together with systems engineering and design methods for artificial intelligence. My current topical work includes space systems, scaling laws, and AI tokens (2025+). Previously, my applied research centered on cyber-physical systems with learning components (2018-2025).

Rather than treating these as unrelated application areas, I use them as testbeds for recurring questions about change and reuse, lifecycles, and iterated games.

I posit that abstract systems theory offers both an advantageous means of considering learning without explicit reference to solution methods and a way to stratify the assumptions underlying learning phenomena into appreciable levels of abstraction. The general systems nature of learning cannot be escaped; every solution method necessarily inherits it.

In order to improve your game, you must study the endgame before everything else, for whereas the endings can be studied and mastered by themselves, the middle and the opening must be studied in relation to the endgame.

Jose Raul Capablanca