5 posts carrying this tag.
We measured how coding agents search with grep on Home Assistant and Saleor: about 150 model runs and 13 million tokens. Grep finds the files, then buries them in noise, and it can't follow inheritance or code that never says the name. A bigger model doesn't fix it.
Grep finds 87% of the files a question needs, then buries them in noise. We put TypeSafe's Jev classifier behind grep on 5,075 candidate files from Saleor, Kubernetes, Istio, Argo CD, cert-manager and etcd. It found more of the right files than Opus 5.5 at about 1% of the cost.
At a conservative 1,000 tokens per source file, 10 million files is roughly 10 billion tokens. A 1 million token window holds 0.01% of that, and a 10 million token window holds 0.1%. Closing that by scaling needs something like a 10,000x increase rather than a 10x one, and quality per token moves against you while you try.
Sourcegraph built the most complete cross repository code search anyone has shipped, and it did so on an assumption that held for fifteen years: a human is asking. Humans supply the meaning the index leaves out. An agent cannot, and at 10 million files a 1 million token window holds 0.01% of the estate, so the gap is not one model generation away.
This argument was being compared to the Vim and Emacs wars in 2024, and then it returned everywhere inside six months. Something dragged it out of retirement, and it is not really about where files live. The variable that decides whether agents work is whether the question of what depends on this is answerable at all, and neither layout answers it.
