alt Hacker NewsGPT-5.2 has a 400,000 token context window. Claude Opus 4.5 is just 200,000 tokens. To my surprise this doesn't seem to limit their ability to work with much larger codebases - the coding agent harnesses have got really good at grepping for just the code that they need to have in-context, similar to how a human engineer can make changes to a million lines of code without having to hold it all in their head at once.
That explains the coherence, but I'm curious about the mechanics of the retrieval. Is it AST-based to map dependencies or are you just using vector search? I assume you still have to filter pretty aggressively to keep the token costs viable for a commercial tool.