Context is the bottleneck for coding agents now

There's a misunderstanding here broadly. Context could be infinite, but the real bottleneck is understanding intent late in a multi-step operation. A human can effectively discard or disregard prior information as the narrow window of focus moves to a new task, LLMs seem incredibly bad at this.

Having more context, but leaving open an inability to effectively focus on the latest task is the real problem.

Asking, not arguing, but: why can't they? You can give an agent access to its own context and ask it to lobotomize itself like Eternal Sunshine. I just did that with a log ingestion agent (broad search to get the lay of the land, which eats a huge chunk of the context window, then narrow searches for weird stuff it spots, then go back and zap the big log search). I assume this is a normal approach, since someone else suggested it to me.

This is also the idea behind sub-agents. Claude Code answers questions about things like "where is the code that does X" by firing up a separate LLM running in a fresh context, posing it the question and having it answer back when it finds the answer. https://simonwillison.net/2025/Jun/2/claude-trace/