@kenwheeler: the funny thing about this is that you could name an agent JanitorAgent and its still largely as capable as some PM age…

X AI KOLs Following News

Summary

The article discusses how AI agents can be named arbitrarily, such as JanitorAgent, and still be as capable as other agents like PM agents given the same base model, highlighting anthropomorphism as organizational rather than functional.

the funny thing about this is that you could name an agent JanitorAgent and its still largely as capable as some PM agent, given the same base model. I look at the anthropomorphism as more organizational than functional.
Original Article
View Cached Full Text

Cached at: 09/14/26, 11:28 AM

the funny thing about this is that you could name an agent JanitorAgent and its still largely as capable as some PM agent, given the same base model.

I look at the anthropomorphism as more organizational than functional.

Codez (@0xCodez): SpaceXAI engineer (ex-Cursor):

“99% of people still use GrokBot like Google and only 1% are building teams of self-learning agents

i’m running 10-20 Grok cloud agents in a loop. I have a Chief of Staff, a PM agent and 15+ worker agents“

in a 20-minute workshop, a SpaceXAI

Similar Articles

AI agents recreate the “rockstar developer” problem, just faster

Reddit r/AI_Agents

The post compares AI agents to 'rockstar developers' who create clever but unmaintainable code, pointing out that agents lack memory of their own actions. It recommends using visible conventions like AGENTS.md, ADRs, and tests to keep agent-generated code understandable by the team.

@SuJinyan6: https://x.com/SuJinyan6/status/2073955240349770069

X AI KOLs Timeline

This blog post by SuJinyan6 examines the evolution of AI agents from simple LLM+tool use to context engineering and long-running harnesses, citing Anthropic's recent work and discussing how agent capability is now a system-level property involving multiple components.