The Truth Behind AI Context Windows: Why Bigger Doesn't Mean Better

Despite vendor claims of 200k to 2M token context windows, practical performance degrades significantly after ~100k tokens—a critical gap for AI coding agents that consume tokens rapidly. This limitation directly impacts development workflows, as models enter a 'dumb zone' where attention and recall drop sharply, regardless of advertised capacity. Rather than waiting for larger windows, the effective solution is deliberate context management through written artifacts and strategic handoffs between sessions.