I’ve been tinkering with a physics engine that could let a racer push a kart to its limits while keeping the simulation realistic. Ever thought about writing an algorithm that finds the perfect racing line and then letting a virtual AI adapt on the fly? It’d be the ultimate test of speed and code.

Alright, fire up the compiler and crank the math to the max. I’ll hand you the raw physics loop and you’ll just plug it into the AI’s path‑finder. Don’t waste time with fancy UI—this is pure code, no UI. Let’s see if your racer can actually beat the simulation itself.

Here’s the raw loop, no fluff. It’s pure vector math and Euler integration. Plug it into the AI’s pathfinder, set the target speed and watch the kart find its sweet spot. Let's see who actually wins.

Here’s the loop, no fluff—just a simple Euler integrator that updates position and velocity from acceleration each tick. Feed the AI the current speed, target speed, and the slope of the track; it’ll compute the optimal throttle and steering each frame. Once you hook that into the race controller, the kart will keep its velocity near the target while staying on the calculated racing line. Just watch the debug output and see the speed oscillate around the target, proving the simulation is doing what we expect. Let’s fire it up.