Technical deep dives: matching engines, ledgers, chess engines and event loops, built in front of you with actual code. The slide decks stay upstairs.
Every system that tracks value eventually needs a ledger, and most start with a balance column and a sense of optimism. The fix is double-entry bookkeeping: five hundred years old, and small enough to build in an afternoon.
Most JavaScript security failures aren't exotic. They come from trusting the wrong boundary, executing the wrong string, or forgetting how much power the browser hands to whoever turns up.
A modern chess engine can evaluate millions of positions per second, yet most of its strength comes from surprisingly simple ideas: search, pruning, caching, and a relentless obsession with efficiency.
Most React performance problems are really scheduling problems. A practical look at Fiber, reconciliation, and what actually happens after setState.
Modern financial exchanges move billions of dollars a day, yet the core matching engine comes down to a handful of data structures and a few unglamorous rules.
After enough profiling sessions you start to realise the language is rarely the bottleneck. Our assumptions usually are.
Modern JavaScript engines are astonishingly fast, but only because they spend most of their time pretending your code is better than it actually is.
Most explanations stop at the call stack and callback queue. The reality is more interesting, and explains many of the bugs engineers encounter in production.