Every "AI" opponent in a board game — Tic-Tac-Toe, Connect 4, Checkers, Othello, Chess — tends to run the same idea: search the game tree, assume the opponent plays their best, and pick the move with the best guaranteed outcome. That idea is minimax, and alpha-beta pruning is what makes it fast enough to run in a browser tab with no backend.
I built an interactive version where you can step through minimax on a real board and toggle alpha-beta on to watch it skip work: play with it here. This post is the written companion.
Minimax in one function
Score a finished position from the AI's point of view: +1 if the AI wins, -1 if you win, 0 for a draw. Then walk the tree of possible futures. On the AI's turn it takes the max of its options; on your turn it assumes you take the min (the worst outcome for the AI). That alternation is the whole algorithm.
function minimax(node, isMax):
