Think about the last time you picked a library. There's a good chance you didn't Google "best Node.js queue library." You asked ChatGPT, Claude or your editor's assistant, got three names, and tried the first one.

That moment, when an assistant chooses which three names to list, is now one of the most important distribution channels for developer tools. And most maintainers have never looked at it.

This post covers where those recommendations come from, how to measure yours with a ~40-line script, and the changes that actually move them.

Two kinds of answer, two sources of truth

When a developer asks for a recommendation, the assistant answers in one of two modes:

Mode When it happens Where the answer comes from

From memory Coding assistants, chats without web search, quick questions What the model learned in training, up to its knowledge cutoff

From search ChatGPT search, Perplexity, Gemini, Copilot, Claude with web search Live retrieval: search indexes (Bing, Google, their own), then synthesis

They…