Why Developers Are Naming Their LLMs (And What It Says About Our Relationship With AI)

Why Developers Are Naming Their LLMs (And What It Says About Our Relationship With AI)

Jun 06, 2026 ai tools developer culture llm usage startup productivity vibe coding ai workflow

Let's be honest — most of us have caught ourselves talking to AI like it's a colleague. Now, it seems, we're giving them names too.

A recent Hacker News thread sparked an unexpected conversation: if you could name your own LLM, what would you call it? The top response? "The Intern." Brilliant, useful, requires constant supervision. Cheaper than hiring. Young, eager, full of potential — but definitely not ready to fly solo.

It's funny because it hits close to home.

The reality is that naming AI has become a quiet cultural phenomenon among developers and startups. Some assign gender-neutral names to avoid bias. Others give their models quirky names that reflect their personality quirks. A developer might call their debugging assistant "Clara" because she's always asking clarifying questions. Another might name their code generator "Atlas" because it literally holds up their entire workflow.

But here's what gets interesting: the names we choose reveal how we actually perceive these tools.

"The Intern" framing suggests a tool that needs hand-holding — powerful but not autonomous. "The Colleague" suggests partnership. "The Consultant" suggests expertise on tap, billed by the token. Each framing changes how we interact with the system, how we set expectations, and how we handle failure.

This matters more than it might seem.

When you name something, you humanize it. You create a relationship. And right now, the developer community is actively negotiating what kind of relationship they want with AI. Are these tools junior teammates? Powerful oracles? tireless workhorses? The naming tells the story.

At NameOcean, we've seen this play out in how teams organize their AI stack. Teams that treat their coding assistants as "junior developers" often build better oversight workflows. Teams that treat them as "experts" sometimes skip critical review steps — and pay for it in bugs.

Maybe the real insight from that HN thread isn't the joke. It's that we're all still figuring out the right frame for AI. The names we assign aren't just nicknames — they're mental models. And getting the model right might matter as much as getting the model itself right.

So, what would you name your LLM? The answer might tell you more than you expected.

Read in other languages: