Use search agents to map AI bot naming trends

A writer used a Claude swarm to gather thousands of bot names and compare patterns by gender, industry, and launch year.

Done with Claude· Advanced· Oct 2026

What they did
After spotting an AI bot name they thought was amusing, the writer asked a swarm of Claude agents to search the web for AI bot names. The agents ran 4,654 searches and built a catalog of examples. The writer then reviewed the names for patterns across gender, industry, and release year.
How it went
The review showed that human-style bot names are usually feminine, though that varies by industry. It also suggested that bots giving themselves names may be becoming less common, with far fewer in 2026 than in 2025. The writer also highlighted a few favorite names.
Tips
This works best if you define the categories you want tracked before the searches start. Ask for a source list and a simple table, then have the agent pause before any final write-up or publication step.

Try it yourself with Claude

I want to study [type of product or name] and spot naming patterns by [dimension 1], [dimension 2], and [dimension 3]. Use many parallel web searches to gather as many examples as possible, and for each one record the name, source, and the attributes I asked for. Then compare the results for trends and outliers. Before you finalize or share anything, stop and ask me to approve the data set and the conclusions. Finish with a table and a short plain-language summary of the main patterns and any limits in coverage.

Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.

Read the original on news.ycombinator.com ↗

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